political and economic effects essay

The relationship between economics and politics

Readers question: Why cannot politics and economics be seen in isolation?

Economics is concerned with studying and influencing the economy. Politics is the theory and practice of influencing people through the exercise of power, e.g. governments, elections and political parties.

In theory, economics could be non-political. An ideal economist should ignore any political bias or prejudice to give neutral, unbiased information and recommendations on how to improve the economic performance of a country. Elected politicians could then weigh up this economic information and decide.

In practice there is a strong relationship between economics and politics because the performance of the economy is one of the key political battlegrounds. Many economic issues are inherently political because they lend themselves to different opinions.

Political ideology influencing economic thought

Many economic issues are seen through the eyes of political beliefs. For example, some people are instinctively more suspicious of government intervention. Therefore, they prefer economic policies which seek to reduce government interference in the economy. For example,  supply side economics , which concentrates on deregulation, privatisation and tax cuts.

On the other hand, economists may have a preference for promoting greater equality in society and be more willing to encourage government intervention to pursue that end.

If you set different economists to report on the desirability of income tax cuts for the rich, their policy proposals are likely to reflect their political preferences. You can always find some evidence to support the benefits of tax cuts, you can always find some evidence to support the benefits of higher tax.

Some economists may be scrupulously neutral and not have any political leanings (though I haven’t met too many). They may produce a paper that perhaps challenges their previous views. Despite their preferences, they may find there is no case for rail privatisation, or perhaps they find tax cuts do actually increase economic welfare.

However, for a politician, they can use those economists and economic research which backs their political view. Mrs Thatcher and Ronald Reagan were great champions of supply side economists like Milton Friedman, Keith Joseph, and  Friedrich Hayek. When Reagan was attempting to ‘roll back the frontiers of the state’ – there was no shortage of economists who were able to provide a theoretical justification for the political experiment. There were just as many economists suggesting this was not a good idea, but economists can be promoted by their political sponsors. In the US, the Paul Ryan budget proposals were welcomed by many Republicans because they promised tax cuts for better off, cutting welfare benefits and balancing the budget. (1)  A popular selection of policies for Republicans.

Economic thought independent of politics

On the other hand, economists who stick to data and avoid cherry picking favourable statistics may well come up with conclusions and recommendations that don’t necessarily fit it with pre-conceived political issues.

Many economists may be generally supportive of the EU and European co-operation, but the evidence from the Euro single currency is that it caused many economic problems of low growth, deflation and trade imbalances.

Economics needs political support

If you study economics, you can make quite a convincing case for a Pigovian tax – a tax which makes people pay the full social cost of the good, and not just the private cost. This principle of making the polluter pay provides a case for Carbon Tax , congestion charges, alcohol tax, and tobacco tax e.t.c.

However, whether these policies get implemented depends on whether there is political support for them.

For example, a congestion charge was proposed for Manchester, but it was very heavily defeated in a referendum. A new tax is rarely popular. As an economist, I would like to see more congestion charging because it makes economic sense. But, what can make ‘sense’ to an economist can be politically unpopular.

The political appeal of austerity

Another interesting example is the political appeal of austerity . After the credit crunch, there was a strong economic case for expansionary fiscal policy to fill in the gap of aggregate demand. Politically, it can be hard to push a policy which results in more government debt. There may be an economic logic to Keynesian demand management in a recession – but a politician appealing to the need to ‘tighten belts’ and ‘get on top of debt’ can be easier slogans to sell the general public, rather than slightly more obtuse ‘multiplier theories of Keynes’

Who runs the economy – Politicians or economists?

Another interesting case is the relationship between fiscal policy (set by government) and monetary policy (largely set by independent Central Banks)

In the UK and US (and Europe) fiscal policy has been relatively tight, given the state of the economy. As a consequence, it has fallen to Central Banks to pursue an expansionary monetary policy to offset the deficiencies of fiscal policy. If politicians pursue tight fiscal policy, Central Bankers have to adapt Monetary policy.

See: problem of politics and economics

Micro economics – free of politics?

There are some areas of economics we could argue are free of politics – basic supply and demand and concepts like the theory of the firm are not laden with political ideology. But, even in micro-economics, you could argue that politics can’t help seeping in. If you take an issue like privatisation – there is a clear political issue. Who should control key industries – private enterprise or the government?

Another issue with economics is that some criticise the subject for prioritising economic growth and maximisation of monetary welfare. Some argue that the aim of society is not to maximise GDP – but to maximise happiness, the environment and being satisfied with what we have. Therefore, a politician from an environmental background may disagree with the whole premise behind macro-economics. It is not just about the best way to promote economic growth. But, whether we should be aiming for economic growth in the first place. That is a political issue too.

• Problem of politics and economics
• Microeconomics and macroeconomics
• Framing political and economic messages
• Media bias in the UK

26 thoughts on “The relationship between economics and politics”

Pleasure in reading while learning something. Very nice and helpful indeed!

What come first in political, politics or economics?????

Well structured. In the years 2010-2012 there was a ‘eurozone’ crisis. How is the situation todate?

still missing the thesis’s

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The Social, Political, and Economic Effects of the Affordable Care Act: Introduction to the Issue

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The Patient Protection and Affordable Care Act, commonly referred to as the ACA and signed into law on March 23, 2010, was the most significant reform of the American health-care system since the passage of Medicare and Medicaid a half century earlier. As former President Barack Obama noted in his personal assessment, the law was intended to “improve the accessibility, affordability, and quality of health care” (Obama 2016 ). In service of these goals, the “affordable care” portion of the measure sought to expand coverage to the uninsured through Medicaid expansion and the creation of insurance marketplaces with sliding-scale premium subsidies, cost-sharing subsidies, and rate restrictions, as well as the requirement that dependents be permitted to remain on parental insurance plans up to age twenty-six. The “patient protection” portion included new regulations aimed at increasing access and improving insurance coverage, such as guaranteed issue, a prohibition on preexisting condition exclusions, no annual or lifetime caps on expenditures for covered services, coverage of essential health benefits, and free preventive care, among others. This portion also included provisions implementing pilot and demonstration projects aimed at exploring new payment and care models such as accountable care organizations or bundled payments, and new care coordination models for dual Medicare-Medicaid eligibles and other populations. Last were a number of additional provisions—such as increased funding for community health centers and incentives for states to continue rebalancing their Medicaid long-term care spending toward home- and community-based services—also intended to improve the availability of health care and its alignment with need (for summaries of ACA provisions, see American Public Health Association 2012 ; Kaiser Family Foundation 2013 ).

Viewed narrowly, a primary focus of the law was to extend health insurance to the approximately forty-nine million non-elderly individuals who were uninsured in 2010 (DeNavas-Walt, Proctor, and Smith 2012 ). Although determining exactly how much of the ensuing increase in insurance coverage can be attributed directly to various elements of the law is challenging for reasons we discuss, simple estimates derived from extending the preexisting trend in uninsured rates suggest that more than eighteen million non-elderly adults gained insurance, amounting to a 46 percent reduction in the number of non-elderly adults without insurance (Blumberg, Garrett, and Holahan 2016 ). In promising to extend health insurance to most of the uninsured, the ACA had the potential to offset the toll that low incomes and financial uncertainty take on the large share of poor and uninsured citizens. In a neoliberal era, it also promised to achieve some measure of redistribution, with benefits funded largely by the affluent through new taxes on high earners and new fees on health-care stakeholders.

Although the number of non-elderly adults gaining insurance potentially due to the ACA is a relatively small fraction of the total population, virtually the entire population was affected to some extent by its provisions, including substantial regulatory components that changed important rules on the ground for private insurance and the existing public insurance programs. However, although these regulatory effects were broad and important, they were in many ways more difficult for individuals to recognize. The ACA used multiple levers of change, many of which were quite hidden to the ordinary observer, which may help explain why such a significant reform had in many cases modest behavioral effects, especially on individuals, as discussed in this introduction and in many of the articles in this issue.

Although nominally focused on changing various components of the health-care system, the ACA has touched on a broad variety of social institutions and societal relationships. Connections between states and the federal government, between governments and health-care providers, between governments and individuals, and between individuals and firms all were altered by the ACA. Taken together, the elements of the ACA had the potential to spur major societal changes beyond extension of health insurance coverage. Indeed, the law’s passage was followed by continuous challenges in Congress, in the courts, and in the states, due in part to the far-reaching nature of the law. In addition to spurring considerable political discourse and action, these challenges affected the ACA’s implementation and may have changed its impacts. Six years after the law passed, elections ushering in unified Republican control of government at the national level and Republican control of government in many states potentially shifted the environment surrounding the law and its implementation as well.

The health reform has prompted a great deal of research among social scientists exploring its origins and effects. However, much of what researchers, policymakers, and the general public might want to know about the Affordable Care Act is difficult to learn. The ACA was sweeping in its reach, touching many aspects of the health-care system specifically and American society more broadly, and its passage coincided with the early years of recovery from a profound economic shock, the Great Recession. In addition, important but not fully understood long-term changes in health care and labor markets were occurring before the ACA and may have been affected by it in ways that are difficult to disentangle. Consequently, identifying specific effects of the ACA from those of other factors likely to affect outcomes of interest is challenging. Research designs that involve comparing outcomes before and after some aspect of the ACA took effect are fraught with the difficulty inherent in pulling apart competing causal factors, any or all of which may be operating. The coincidence of the ACA’s passage with the start of an economic recovery makes focusing on deviations from existing trends less convincing than such an analysis might be in calmer economic circumstances. In many cases, both opponents and supporters of the ACA can point to results from such analyses that support their views.

These difficulties imply that more credible research assessing the ACA has largely taken one of two forms: descriptive assessments coupled with an explicit recognition of their descriptive nature and research focusing on aspects of the ACA that offer the possibility of usable exogenous variation. As a result, research on some aspects of the ACA has been considerable but on other aspects minimal. The extension of parental coverage to young adults, which affected those age twenty-six and younger but not those older than that; competition in markets for individual insurance across the country, which had differential levels of preexisting market depth; and especially the expansion of Medicaid coverage, which was made optional to states by the Supreme Court’s decision in the 2012 case National Federation of Independent Business v. Sebelius have received more attention. 1 In addition, substantial literatures on the effects of the ACA on health-care delivery reform (for a review, see Blumenthal, Abrams, and Nuzum 2015 ) and on health outcomes have emerged. However, other components—often the less visible ones—have received less consideration because of both the difficulties in finding credible research designs and the data limitations; in addition, work on the economic, political, and sociological effects of many components of the ACA is scanty. The outbreak of the COVID-19 pandemic in 2020 heightens the importance of many of these questions.

This issue of RSF begins to fill these gaps with a series of articles from social scientists assessing these broader effects of the health reform. In this introduction, we situate these articles by reviewing the relevant literature on the ACA’s economic, political, and social effects. We examine extant discussion of the implications of the ACA’s design for private insurance markets and the major public insurance programs as well as the effects of the law on noninsurance components (such as the health-care workforce, providers, and so on). We examine the responses of states to the many decisions the ACA required of them regarding insurance exchanges, Medicaid expansion, and navigator support. We then turn to effects of the ACA on individuals, both nonpolitical effects (health insurance coverage and access, financial security, labor-market effects, and effects on family structure), and political effects (changing patterns of political behavior and attitudes). We confine our review to topics relevant for the examination of the broad social, economic, and political effects that the articles included in this issue examine; we do not review the voluminous literatures on health-care delivery reform and health outcomes, including literature on changes in the treatment of various health conditions (such as substance use disorder, cancer, obesity, or many others) affected by expanded access to coverage for such treatment, nor do we review health reform case studies of individual states. Our review reveals that despite the great volume of research the ACA has inspired thus far, many additional areas are in need of examination. In the hope of fostering a continued research agenda among social scientists, we conclude by highlighting areas where more work is needed.

• HOW THE ACA HAS CHANGED THE HEALTH-CARE LANDSCAPE

We begin our review by discussing various ways in which the ACA’s provisions have changed the health-care landscape in the United States, how implementation has proceeded, how the ACA’s design elements affect private insurance, what the implications are of the ACA’s noninsurance and public insurance components, and how the states have responded to the ACA’s provisions. After providing this context on the health and policy impacts, we turn to the extant work on the economic, social, and political effects of the ACA.

The Course of ACA Implementation

The Affordable Care Act is an extraordinarily complex law with thousands of provisions, not to mention a politically contested one subject to unrelenting attacks by partisan opponents. The status of high-profile provisions garners much media attention and scholarly consideration (for example, Blumenthal, Abrams, and Nuzum 2015 ), whereas far from the public glare a great deal of quieter activity is under way, many provisions going into effect and others falling by the wayside. Helen Levy, Andrew Ying, and Nicholas Bagley (this issue, 2020 ) go beyond existing overviews of high-profile provisions to analyze the implementation status of approximately two hundred “key” provisions as identified in prior research. They discuss each of the ACA’s titles in turn, providing a helpful overview of the law, and delineate five categories of reasons some provisions were invalidated, repealed, or abandoned, including “legal challenges,” “born to fail,” “interest group pressure,” “failure to thrive,” and “executive branch sabotage.” The authors discuss examples of key provisions that fall into each category and provide a brief narrative about salient events surrounding each one. Overall, however, their analysis indicates that a majority of the law has been implemented. Subsequent articles in the issue—and the rest of our literature review—in turn examine the social, economic, and political effects of many of the provisions that have been at least partly implemented.

Implications of ACA Design Elements and Subsequent Design Choices: The ACA and Insurance Markets

Before the ACA was enacted, private insurance could be obtained either through a group, such as an employer, or in the nongroup market. By far the largest share of private coverage was employment based: according to data from the 2010 Current Population Survey, in 2009 only 9 percent of the individuals younger than sixty-five who had private insurance at some point during the year had directly purchased insurance only (see U.S. Census Bureau 2010 , table HI01). The private nongroup market suffered from a number of problems, including lack of access to insurance for individuals with preexisting health conditions, high administrative costs, limited choices, and continued exposure to health expenditure risk, with caps on coverage or exclusions of coverage for certain conditions being common features of privately purchased plans. Employer-sponsored insurance (ESI) markets by many measures functioned better, although some plans also had annual or lifetime limits on coverage so that enrollees were exposed to the risk of catastrophic health expenditures, some imposed waiting periods on coverage for preexisting conditions for new employees, and small-group plans in some states had higher premiums attributable to required medical underwriting. Nevertheless, ESI represented the largest source of insurance for the under sixty-five population, nearly 73 percent in that age group who had insurance at some point in 2009 having employment-based coverage (see U.S. Census Bureau 2010 , table HI01). The ACA was therefore intended to address the problems of private insurance markets but not reduce the extent of ESI coverage.

The most visible aspect of the ACA’s impact on insurance markets was the establishment of health insurance exchanges (also called Marketplaces) in which individuals could shop for individual or family policies. Importantly, these policies must be offered to anyone, with pricing variation permitted only on the basis of geography (market rating area, typically metropolitan statistical areas [MSAs] plus the remainder of the state not included in an MSA), family composition, age (the ratio of premiums for the oldest to the youngest enrollees not to exceed three to one), and tobacco use. Plans offered must fit into one of five tiers within which all plans must be actuarially equivalent: one catastrophic high-deductible tier generally available only to younger individuals, and four “metal levels”—bronze, silver, gold, and platinum—that correspond to increasingly generous coverage. Within tier, plans compete primarily on price (premium plus cost-sharing requirements) and the network of providers included in the plan. Regulations also apply to both employer-sponsored and Marketplace plans, including a minimum ratio of benefits to premiums (different levels for large-group and small-group or individual plans), standards for “essential health benefits” that must be covered, an annual out-of-pocket expenditure limit, and a ban on annual or lifetime coverage limits. Tax credits to reduce the cost of the premium and reduced cost sharing on a sliding-scale basis are available in the individual market to families with incomes below 400 percent of the federal poverty level (FPL). In addition, if offered, dependent coverage must be made available to unmarried adult children younger than twenty-six.

To ensure that employer-sponsored coverage was not reduced, firms with more than fifty workers were required to offer “affordable” coverage meeting minimum value standards to full-time employees or pay a penalty, although the implementation of the penalty was delayed until 2015; small firms (fewer than fifty workers) were given the opportunity to purchase a health plan to offer through the Small Business Health Options Program (SHOP). Small firms could also drop coverage and allow their workers to enter the individual Marketplaces. Group or individual plans in existence when the law was passed were grandfathered—that is, did not have to meet all the requirements of the law until the insurer or employer made a significant change in coverage or pricing.

These regulations, and the rulemaking that accompanied them, were fundamental changes for private insurance markets, beginning with the clear increase in information available to potential consumers of individual plans. The “metal” tiers and standards for coverage made comparing plans more straightforward, though the extent of the networks of providers available in each plan was a key remaining variable, and one that has generated questions about the trade-offs inherent in “narrow network” plans between lower premiums and ease of access to health care. Both Leemore Dafny and colleagues ( 2017 ) and Daniel Polsky, Zuleyha Cidav, and Ashley Swanson (2016) show a clear association between the narrowness of the network and the premium, estimating a 6 to 9 percent reduction in premium with a narrowing of the network, and a larger reduction if both physician and hospital networks are reduced. Aditi Sen and colleagues (2017) find that individuals who are Hispanic or low income constitute a disproportionate share of enrollees in plans with networks that include fewer than a quarter of the physicians in a local area. However, further research is needed on whether narrow network plans have resulted in any health-care access or health implications or function primarily as an effective check on health-care prices. Another concern was that consumers would be unlikely to shop around in subsequent open enrollment periods, particularly given low rates of plan switching in Medicare Part D (Sanger-Katz 2014 ). Although some evidence indicates that a fair number do change plans on the ACA exchanges (Pearson, Carpenter, and Sloan 2016 ), to date little research has been undertaken on such plan switching and its effects.

Perhaps because so many of our day-to-day activities are conducted online, it may not be immediately apparent what a structural change Section 3021 of Subtitle C (“Health Information Technology Enrollment Standards and Protocols”) represented in its call for “Electronic matching against existing Federal and State data, including vital records, employment history, enrollment systems, tax records, and other data determined appropriate by the Secretary to serve as evidence of eligibility and in lieu of paper-based documentation.” The requirement for online enrollment capability meant that various electronic records systems, both private and public (state and federal) needed to be able to exchange information that could then be used in an eligibility determination for Medicaid or premium subsidies. This was such an immense undertaking that roll-out of the online enrollment system for the exchanges was, as is well known, less than smooth. Moreover, evidence suggests that problems have persisted in states experiencing particularly difficult roll-outs (Scheuer and Smetters 2018 ). The establishment of this capability, however, represents a significant change in ease of access to Medicaid—as of January 2019, according to a Kaiser Family Foundation survey of states, for the first time individuals can apply for Medicaid online in all states and can receive eligibility determinations within twenty-four hours in forty-six states (Brooks, Roygardner, and Artiga 2019 ). In addition, it represents an opportunity for states to streamline eligibility determination for a wider variety of programs (Dorn, Minton, and Huber 2014 ).

The ACA envisioned certain roles for states in insurance regulation, the federal government taking on some of the regulatory roles that states had formerly held, such as establishing the benefits that qualifying insurance plans would have to provide or mandating employer offering of insurance, but the states being given the opportunity to establish their own state-level marketplaces. However, the roles as envisioned were not necessarily the same as the roles that occurred, many states choosing not to design their exchanges and instead adopting the federal one. Nevertheless, individual insurance markets continued to have considerable variation at the state level. One decision left to states was market definition, in particular, the geographic area that would be considered a single market. Michael Dickstein and colleagues ( 2015 ) find that counties that are smaller or more rural have more insurers and lower premiums when they are “bundled” with larger counties, although more heterogeneous regions (in terms of proportion urban versus rural) have fewer insurers and higher premiums, suggesting a trade-off for states between bundling smaller counties with larger ones and keeping more dissimilar counties separate.

Once the markets are defined, the decision about whether to enter the market is up to insurers. Researchers have noted two countervailing effects of additional entry into insurance markets. First is the typical effect of price competition arising through additional entry, which would tend to push down prices to consumers. However, because of bargaining between insurers and providers, the entry of additional insurers into a market is not guaranteed to lower prices to consumers because individual insurers have less bargaining power vis-à-vis providers when insurers are more numerous (see, for example, Moriya, Vogt, and Gaynor 2010 ; Ho and Lee 2017 ). Researchers have studied the impact of competition on consumer prices in the ACA’s individual insurance market. Focusing on arguably exogenous sources of variation in the number of insurers, they have found that the entry of an additional insurer has generally resulted in a reduction in prices to consumers of between 4 and 5 percent (Dafny, Gruber, and Ody 2015 ; Abraham et al. 2017 ; Lissenden 2017 ).

Particularly given that markets with more insurers have been shown to offer lower prices to consumers, a concern persistently expressed by observers of the ACA has been exit of insurers from the individual markets. In a series of issue briefs, analysts at the Kaiser Family Foundation have tracked the performance of insurers in the individual market since the passage of the ACA (see, for example, Cox, Levitt, and Claxton 2017 ; Fehr, Cox, and Levitt 2018a , 2018b ). Examining medical loss ratios (the share of premiums paid out in claims) in the individual insurance market, they find that medical loss ratios rose to unprofitable levels in the first two years of the ACA marketplaces but began to decline thereafter, suggesting that after an initial period of inadequate information about the individuals purchasing insurance that led insurers to set their prices in the market too low for the level of risk, insurers in the market have begun to gain information that allows them to set prices more accurately. Nevertheless, many of the markets have been characterized by instability and uncertainty about the level and nature of enrollment. Mark Hall (this issue, 2020 ) assesses the sources of instability in individual insurance markets using documentary research and case studies from ten states. He focuses particularly on the roles of actuarial uncertainty (which arises because insurers must account for unknown responses to known changes in market rules) and political uncertainty (which arises because insurers do not know whether and how regulations might change) in insurer pricing and entry decisions. Based on interview evidence, he concludes that actuarial uncertainty is not inherently destabilizing, although political uncertainty is; he points to regulatory flexibility on the part of the states and the subsidy structure as ensuring the resilience of the individual insurance markets in the face of political uncertainty. Jean Abraham (this issue, 2020 ) also studies instability in the individual markets, classifying local markets as more or less volatile based on changes over time in insurer participation and premiums and more or less vulnerable based on insurer participation and premiums in 2019. She finds that by her measure nearly a third of local markets experienced high volatility in the segment of the market offering subsidized plans, a slightly smaller share experiencing high volatility in the unsubsidized portion. She classifies markets as vulnerable if they have below-median insurer participation and a premium level above the median premium, and finds that vulnerable local markets are more likely to be rural, to have less healthy populations, and to be in states that have not expanded Medicaid.

It is not surprising that the individual insurance markets are affected by the states’ decisions on whether to expand Medicaid, given that Medicaid expansion removes more risky low-income individuals from the private risk pools. As a result, individual market premiums are expected to be lower, on average, in states that expanded Medicaid. Aditi Sen and Thomas DeLeire (2018) find this to be the case, comparing premiums for plans on both sides of a state border where one state expanded Medicaid and the other did not. Similarly, Lizhong Peng ( 2017 ) finds that premiums fell in Pennsylvania and Indiana when Medicaid expansion occurred.

Researchers have also assessed whether either the hope of the ACA’s designers that employer-sponsored insurance coverage would continue as a mainstay of the insurance coverage structure, or the concern of the ACA’s opponents that ESI coverage would fall significantly, have occurred. Overall, employer-sponsored insurance seems to have largely remained stable: Abraham, Anne Royalty, and Coleman Drake ( 2016 ), Frederic Blavin and colleagues ( 2016 ), and Adele Shartzer, Blavin, and John Holahan ( 2017 ) all find little change in ESI offerings or take-up post-ACA. One area that has elicited some concern is the small employer market, innovations such as the SHOP marketplace never becoming operational (Curran 2017 ). Focusing on small employers, Sabrina Corlette and colleagues ( 2017 ) use qualitative data from six states to describe changes in the small-group ESI market, noting that though rates improved for some small groups, employers with younger, healthier employees saw rising premiums, which has led some small employers to pursue lower priced but less complete coverage or other options. However, in comparing the small-group market with the individual market, Abraham, Royalty, and Drake (2019) note that on average, small-group markets appear to be functioning better than individual markets, offering more plan types and lower premiums. Overall, how people have fared in the small-group and individual insurance markets as a result of the ACA would seem to be important areas for further research.

Implications of the Noninsurance and Public Insurance Components of the ACA

Although much of the scholarly work on the Affordable Care Act has thus far centered on the private insurance components of the law, such as the exchanges and new regulations, the law contained multiple provisions for Medicaid and Medicare as well as noninsurance provisions affecting many aspects of health care. A number of these provisions affect health-care delivery and, ultimately, health outcomes; and a robust and growing health services research literature examines those outcomes. However, we have found relatively little scholarly analysis thus far of the social, political, and economic effects that these many provisions might exert on individuals and institutions. Hence we highlight hypotheses that observers have put forth about their likely effects and describe analytical findings where they exist.

By increasing health insurance coverage, the ACA was projected to increase the demand for health care, putting pressure on providers and provider participation. For example, Stephen Parente and colleagues ( 2017 ) estimate that demand for physicians, licensed practical nurses, and medical aides will increase more than 10 percent between 2014 and 2021 relative to a no-ACA baseline, and demand for other occupations—such as technician, registered nurse, and home health aide—will grow at somewhat lower rates. Their model predicts differential wage increases across provider types, with greater wage increases among health-care occupations requiring more education and training, such as physicians and registered nurses. Upward pressure on wages could also counteract other ACA provisions meant to control rising health-care costs.

The ACA includes additional measures intended to meet the increased demand for providers created by expanded health insurance coverage. The law permanently authorized and increased funding for the National Health Service Corps (NHSC) program, which provides scholarships and loan repayment to primary care providers who work in underserved areas. However, despite some increases in field strength—the total number of clinicians in the program—the number of open NHSC positions is higher than the number of NHSC providers (Heisler 2018 ). The ACA also increased Medicaid payments to primary care providers to Medicare levels for two years, 2013 and 2014. However, studies have found no apparent effect on physician participation in Medicaid, perhaps because the bump was temporary (Decker 2018 ; Neprash et al. 2018 ).

According to at least one survey, efforts to increase the size of the health-care workforce or to encourage physician participation in Medicaid could improve enrollee satisfaction. A 2014–2015 survey of Medicaid recipients found more patient satisfaction and greater access in states with higher physician participation per capita in Medicaid (Barnett, Clark, and Sommers 2018 ). Inequalities persist, however: racial and ethnic minorities report less satisfaction and access than white recipients. Ongoing economic, political, and sociological questions remain about whether the size of the health-care workforce and distribution across health occupations and geographic locales will meet patient needs in the future and how to reduce disparities in access across income, race-ethnicity, and other demographic categories.

Although the impacts on the health-care workforce have not yet been fully assessed, several studies have examined the impact of the ACA on hospitals and community health centers. By expanding Medicaid, the ACA has reduced the amount of uncompensated care that hospitals provide (Blavin 2016 ; Dranove, Garthwaite, and Ody 2016 ), particularly among hospitals serving a disproportionate share of low-income patients (Camilleri 2018 ). Although some substitution of Medicaid expansion funding for existing state or local safety net hospital funding was likely (see Duggan, Gupta, and Jackson 2019 for evidence on this substitution for California), the evidence to date indicates that hospitals, particularly those serving poorer populations, have benefited financially from the ACA. Richard Lindrooth and colleagues ( 2018 ) find that Medicaid expansion under the ACA is associated with better financial health for hospitals and lower likelihood of closure, particularly in rural areas. This could be good financial news for safety net hospitals if as a result they have greater capacity to treat more private insurance patients (at higher reimbursement rates), but alternatively could represent a financial threat if non–safety net hospitals attract healthier Medicaid patients and sicker ones remain at safety net hospitals.

Another ACA provision doubled federal funding for community health centers (CHCs), which provide care to twenty-six million Americans (Rosenbaum 2017 ). Researchers report that this increase in funding, together with Medicaid expansion, has significantly increased patient volume and reduced the shares of uninsured patients at CHCs (Han, Luo, and Ku 2017 ). Congress extended the original five-year grant for CHCs several times, but future funding remains uncertain (Lewis et al. 2019 ). Cuts in CHC funding would disproportionately affect access for low-income individuals and rural residents (on the latter, see Cole et al. 2018 ).

The ACA includes demonstration projects aimed at better coordination of care for those dually eligible for Medicaid and Medicare. However, enrollment in these demonstration projects remains below projections (Grabowski et al. 2017 ), and advocates have voiced concern that the dual eligible demonstration projects do not do enough to address racial and ethnic health disparities (Sharma 2014 ). The ACA also provides new options for creating medical home models of coordinated care. Questions remain as to whether the medical home concept reduces racial-ethnic disparities in access for health services (National Academies of Sciences, Engineering, and Medicine 2015 ) or brings parity to mental health services (Sahasranaman 2017 ).

One difficulty the patient-centered medical home model faces is that its principles of comprehensive care that includes disease prevention and management of chronic conditions may be challenging for small physician practices to implement due to the financial and other resources required. Radhika Gore and colleagues (this issue, 2020 ) study the implementation of two particular population-health strategies espoused in the ACA—electronic health records and community health workers—in the context of efforts to implement hypertension control strategies among small practices serving South Asian immigrant communities in New York City. Using a method of semi-structured interviews and on-site observation of clinic workflow before and after implementation, they find that although some aspects of the strategies strengthened care provision and patient engagement, others proved challenging to implement or were not perceived as helpful by providers; they outline some of the challenges faced in making these ACA population-health strategies successful in the context of small providers and culturally distinct communities.

Beyond demonstration projects for dual eligibles and other populations, a notable feature of the ACA was an effort to make institutional investments in demonstration projects more generally to better ensure their translation into policy, such as creating a new Center for Medicare and Medicaid Innovation (CMMI), increasing the budget for demonstration projects and allowing them to be non-budget-neutral, exempting some elements from judicial and administrative review, and increasing the authority of the secretary of the Department of Health and Human Services to expand Medicare and Medicaid demonstration projects without congressional approval. Philip Rocco and Andrew Kelly (this issue, 2020) examine fourteen demonstration models CMMI pursued between 2012 and 2018. Despite the increased budgets and authority, they find that only two new payment and delivery models have been certified for expansion. The actuarial certification process, they conclude, requires measurements of quality and attributions of savings that are difficult to meet, particularly for complex demonstration projects involving many types of stakeholders. Barriers to innovation therefore remain, even with increased discretion and resources.

The ACA contained many provisions affecting Medicare. A substantial health services research literature examines the effects of delivery system and payment reforms such as programs to reduce unnecessary hospital readmissions, develop accountable care organizations, introduce bundled payments and other value-based rather than volume-based reimbursement, and so on, which we do not examine here. Other provisions were intended to improve Medicare benefits by expanding preventive services, providing an annual wellness visit, and closing the prescription drug coverage gap known as the “donut hole” (reducing cost sharing in the coverage gap from 100 percent before the ACA to 25 percent in 2019 for brand name medications and in 2020 for generic drugs). Research indicates unequal patterns in utilizing these new benefits. For example, only a small share of Medicare beneficiaries received an annual wellness visit in the provision’s first four years, increasing from 7.5 percent in 2011 to 15.6 percent in 2014, whites, women, urban residents, non-dual eligibles, and those from higher-income areas being more likely to do so (Ganguli, Souza, and McWilliams 2017 ). The ACA also introduced changes to private Medicare Advantage (MA) plans, which enroll a large proportion of Medicare recipients. MA plans are subject to the medical loss ratio provision, limiting the amount they can spend on administrative costs, profits, and other non-health-care aspects to 15 percent of their Medicare payments. The ACA also sought to reduce payments to MA plans, which were higher than traditional Medicare payments, 14 percent higher per capita in 2009 (ASPE 2014 ), in part by reducing the per-enrollee “rebate” an MA plan received when its bid was below the benchmark rate in the county, based on traditional Medicare spending in the county. Senior citizens exerted pressure on Congress to avoid such cuts (Kelly 2015 ), a kind of protective constituency policy feedback, although MA plan payment rates did fall, on average, to be equivalent to traditional Medicare, and MA enrollment grew significantly (Guterman, Skopec, and Zuckerman 2018 ).

The ACA also contained a large number of provisions addressing public health, including the creation of a public health council and a $15 billion public health fund, “the first time that a comprehensive public health strategy, with dedicated funding, was articulated in federal law” (Chait and Glied 2018 , 508). Other provisions aimed at prevention, oral health, immunizations, laboratory capacity, minority health, diabetes, childhood obesity, women’s health, tobacco cessation, and so on (for a summary, see Chait and Glied 2018 ). Although some work on the effects of these initiatives on health outcomes has started to emerge, to the best of our knowledge none on the political, social, or economic effects has, perhaps because the impact of the ACA on such effects would be difficult to disentangle from myriad other social factors.

The ACA included multiple streams of financing that were intended not only to support new spending obligations such as Medicaid expansion and health insurance subsidies, but also to change both health-care and health insurance incentive structures and to magnify the law’s redistributive effects. Some financing sources were imposed on health-care stakeholders, such as new annual fees on pharmaceutical manufacturers and health insurers as well as taxes on medical devices and indoor tanning services. More relevant for possible social, political, or economic effects were tax changes for individuals, ranging from lower limits on flexible spending accounts for medical expenses and an increased threshold for itemized deduction of unreimbursed medical expenses, to changes with clearly redistributive implications, such as increased capital gains and Medicare payroll taxes for high earners and the so-called Cadillac tax.

Among the financing streams, the Cadillac tax was the subject of the most hypothesizing and analysis. A 40 percent excise tax on employer-sponsored health benefits that exceed certain thresholds, the Cadillac tax was intended not only to raise revenue but also to partly offset the tax exclusion for employer-sponsored insurance and to discourage employers from offering health plans that are so comprehensive that they encourage overuse. The thresholds, $10,800 for individuals and $29,100 for families, were indexed to the Consumer Price Index, which tends to increase at a lower rate than health-care costs, meaning that the tax would apply to more plans each year. Because of this and other controversies around the tax, its implementation was delayed several times. Thus scholarly analysis could not assess the effects of the Cadillac tax, but instead focused on estimating which workers would be affected by the tax when it came into effect (Claxton and Levitt 2015 ; Herring and Lentz 2011–2012 ; Lowry 2015 ). Mark Warshawsky and Michael Leahy ( 2018 ) estimate, for example, that 12 percent of workers would be affected at the outset, the highest concentrations among those who tend to have more generous benefit packages: union members, workers in education occupations, and workers in the top quartile and top decile of earnings. Workers in the Northeast and West would be more likely to be subject to the tax than those in the South or Midwest because of regional variations in health-care costs. Sherry Glied and Adam Striar ( 2016 ) speculate that the tax would ultimately be more progressive than first thought because it would most affect workers with health savings accounts. The tax may have induced employers and workers to move toward plans with greater cost-sharing or narrower provider networks, and it could have increased financial risk for the demographic categories most likely to be affected. That the Cadillac tax would fall on the health plans of more highly resourced and organized individuals resulted in political pressure to prevent or blunt its implementation. Congress finally repealed the tax altogether (along with the ACA’s taxes on the health insurance and medical device industries) in a budget bill passed in December 2019 and signed by President Donald J. Trump (Keith 2019 ).

Finally, by extending health insurance to the previously uninsured with funds extracted from higher-income households, the ACA will have effects on American patterns of inequality. Scholarly work on the social, political, and economic effects of the law’s distributional consequences has just begun. Before most ACA provisions were implemented, Henry Aaron and Gary Burtless ( 2014 ) predicted that money incomes would increase slightly for the bottom quintile and fall slightly for other income groups, though none of the changes were large and most changes were concentrated in the bottom two deciles. Kevin Griffith, Leigh Evans, and Jacob Bor ( 2017 ) find that the ACA decreased socioeconomic disparities in insurance coverage, the gap in the insurance rate between those with incomes above $75,000 and below $25,000 shrinking over time. The decreases were larger in Medicaid expansion states, where the gap fell from 31 percentage points to 17 percentage points, than in non-expansion states, where the gap decreased from 36 percentage points to 28 percentage points. As the ACA extended health insurance access to adults in ways unrelated to their relationships with employers, spouses, and children, disparities were also decreased across sociodemographic groups, men, black and Latino adults, and adults with less education gaining insurance at greater rates and narrowing preexisting gaps by gender, race and ethnicity, and education (Gutierrez 2018 ). Naomi Zewde and Christopher Wimer ( 2019 ) use the ACA’s Medicaid expansion to estimate that Medicaid coverage reduced the nation’s poverty rate by about 1 percent, the effect concentrated in the non-elderly adult population that was the focus of the expansion.

Political and Policy Responses to ACA Provisions in the States

One of the defining characteristics of the Affordable Care Act was the large role assigned to states. Although the law created a national framework for extending health insurance to more Americans and for addressing practices in the private insurance market that reduced access, states were charged with important implementation and policy responsibilities. These included deciding whether to create an insurance exchange, implementing new insurance regulations, and determining whether to participate in various initiatives and demonstration projects aimed at health education, healthy living, health-care delivery, payment structures, and so on (Weil and Scheppach 2010 ). The Supreme Court’s decision rendering Medicaid expansion optional further heightened the importance of state decision making. Proponents of state control have traditionally lauded the possibilities for innovation and for tailoring policy to local conditions that such subnational policy responsibility affords. But states vary in their levels of expertise, previous policy experience, administrative capacity, and fiscal strength, not to mention political climates and partisan control of government. Delegating important aspects of the ACA to the states ensured substantial uncertainty and variation in the law’s operation on the ground.

A number of scholars have examined the drivers of state choices in implementing the Affordable Care Act, including their decisions regarding health insurance exchanges (Jones, Bradley and Oberlander 2014 ; Rigby and Haselswerdt 2013 ; Shor 2018 ) and expanding Medicaid (Barrilleaux and Rainey 2014 ; Jacobs and Callaghan 2013 ; Shor 2018 ). Most find that party control of state legislatures and governorships is a dominant factor in explaining state policy choice, Democratic-led states implementing the ACA more enthusiastically. Some also find that state administrative capacity and previous policy experience, such as previous expansions of Medicaid, were also related to ACA implementation (Rigby and Haselswerdt 2013 ; Jacobs and Callaghan 2013 ; Haeder and Weimer 2015 ). Evidence on the influence of interest groups is mixed. On the one hand, the greater presence of business and professional lobbying groups is associated with less state progress on Medicaid expansion (Callaghan and Jacobs 2016 ). On the other, the greater presence of pro-expansion interests was influential in one study—public interest groups (Callaghan and Jacobs 2016 )—but not another—safety net providers (Grogan and Park 2017 ). Public opinion has an independent effect on policy choices in some analyses (Rigby and Haselswerdt 2013 ; Grogan and Park 2017 ), but only an indirect effect, through elected officials, in others (Shor 2018 ). Also, race matters. In the degree to which public opinion is associated with Medicaid expansion decisions, the opinions of white state residents matter, not those of nonwhites (Grogan and Park 2017 ). That ACA implementation occurs at a time of heightened political polarization complicates the usual pathways by which policies diffuse from one state to another (Volden 2017 ). Finally, and in some ways most normatively concerning, actual health insurance need in the state does not seem to matter for politicians’ decision making (Jacobs and Callaghan 2013 ; Barrilleaux and Rainey 2014 ).

Most of these studies use state-year as the unit of analysis, although Boris Shor ( 2018 ) is able to use the state legislative district due to methodological advances that permit the estimation of public opinion and legislator ideology at that level of disaggregation. Unlike some of the individual-level studies, which use causal designs, most state studies are based on observational data.

One early decision states faced was whether to implement their own health insurance exchange or use the federal one. A state-level exchange could be attractive to conservatives as a market-model solution meant to foster competition and drive down health insurance prices, as was extolled during the Massa-chusetts reform under Republican Governor Mitt Romney and in various Republican health reform plans over the years (Jacobs and Skoc-pol 2010 ). Also, a state-level exchange would heighten state control and ward off the “partial preemption” of the federal exchange (Rigby and Haselswerdt 2013 ). On the other hand, running a state exchange could be viewed as embracing the progressive ACA reform championed by President Barack Obama, a Democrat. Also, the federal rules on exchanges and minimum standards meant that the exchanges were a form of “one-tailed devolution” (Conlan and Posner 2011 ), in that it was easier for states to proceed in a liberal direction than in a conservative one (Rigby and Haselswerdt 2013 ). Republican state lawmakers were caught in a dilemma: state-level exchanges appealed to partisans who sought to minimize federal intervention, but also represented entrenchment of a law they opposed and might complicate legal challenges to the ACA (Jones, Bradley, and Oberlander 2014 ).

In examining early steps that states could take in setting up exchanges, Elizabeth Rigby and Jake Haselswerdt (2013) find more activity in states with more supportive public opinion and with either Democratic governors or a high share of Democrats in the state legislature. Simon Haeder and David Weimer (2015) find greater state cooperation in setting up exchanges in states with unified Democratic legislatures and less cooperation in those with a Republican governor or a Republican elected insurance commissioner. Shor ( 2018 ) examines state legislator roll-call votes on several ACA outcomes. He too finds that state exchanges were opposed more by conservative and Republican state legislators, legislator ideology having a stronger effect than legislator partisanship; district public opinion did not have an effect independent of the legislator characteristics. Thus analyses of both state-level decisions and individual legislator roll-call voting indicate that conservatives and Republicans were less likely to support state-level exchanges than liberals and Democrats were, despite the possible attractiveness of such exchanges to conservatives.

Another decision states had to make was whether to expand Medicaid after the Supreme Court effectively made expansion optional. An examination of early decisions regarding Medicaid expansion in 2012 and 2013 (such as issuing gubernatorial or legislative statements supporting expansion, applying for federal planning grants, or streamlining Medicaid application processes) found that party control is an important though not perfect determinant (some Republican-led states moved toward expansion). States were also more likely to have taken steps toward expansion if they had previously expanded Medicaid or if they had more administrative capacity (as measured by insurance oversight, policies against Medicaid fraud, and existing high-risk pools for the medically needy). However, states with greater need—those with lower average per capita income—were less likely to have done so (Jacobs and Callaghan 2013 ).

Lawrence Jacobs and Timothy Callaghan (2013) examined bivariate patterns only. Rigby ( 2012 ) analyzed state resistance to the ACA in 2010 and 2011, as measured by a three-item index adding whether the state had filed a lawsuit challenging the ACA, had passed legislation in opposition, or had forgone federal planning grants, finding that GOP control of government (governor, attorney general, or insurance commissioner) was the most important factor, accounting for half of the total variation in outcomes. Also important was state public opinion. State capacity (for example having a less professionalized legislature) was more modestly associated with resistance, as was the degree of change the ACA represented from current policy, such as the magnitude of Medicaid enrollment or the net costs to state budgets the ACA would bring (Rigby 2012 ).

Similarly, an analysis of governors’ decisions to support Medicaid expansion found that gubernatorial partisanship and legislative party control were the most important factors; public opinion did not exert an independent effect, nor did need—support for Medicaid expansion declined with the share of state uninsured population (Barrilleaux and Rainey 2014 ). In yet another analysis of Medicaid expansion decisions in 2012 and 2013, supportive public opinion is associated with expansion, but only whites’ opinions are statistically significant, not nonwhites’ opinions (Grogan and Park 2017 ). As in his analysis of insurance exchanges, Shor ( 2018 ) finds that state legislators’ roll-call votes on Medicaid expansion are associated more with legislator ideology than legislator party, public opinion again working through those pathways rather than exerting an independent effect on legislators’ voting.

Several researchers have assessed the role of organized groups in state choices on Medicaid expansion. Colleen Grogan and Sunggeu Park (2017) find no statistically significant role for safety net interest group influence (measured by the number of community health centers and the number of patients served per capita) on state Medicaid expansion decisions. However, Callaghan and Jacobs ( 2016 ) do find a significant effect: states with Democratic control of government and more public interest and nonprofit lobbyists per capita had taken more steps toward Medicaid expansion, but those with a stronger professional and business lobbyist presence had taken fewer. State affluence, past policy choices, and administrative capacity did not exert independent effects.

Another policy choice was funding navigators, assisters, and certified application counselors to assist consumers in comparing plans on the health insurance exchanges, applying for subsidies, and enrolling (Goodell 2013 ). Such navigators are typically members of advocacy groups or social service organizations. Variation in state funding of navigator programs is wide; those states that established marketplaces had more funding available given the nature of federal funding sources. States could elect to use their own money as well. During the first open enrollment period, California and Maryland spent as much on navigators as all states with federally run marketplaces combined (Goodell 2013 ). State variation in advertising and navigator budgets per capita of the uninsured population remained pronounced in the ACA’s sixth open enrollment period in late 2018 (Corlette and Schwab 2018 ).

Some states erected barriers to navigators, such as stringent licensing and training requirements. In many cases, insurance agents and brokers lobbied for these regulations, viewing navigators as “government-funded competition” (Kusnetz 2013 ). In some states, local health departments have engaged in the outreach that navigators might otherwise play, as in Houston, where the city’s Department of Health and Human Services headed a collaborative effort aimed at increasing health insurance enrollment even in the absence of Medicaid expansion (Runnels et al. 2016 ; Williams et al. 2016 ). Nonetheless, significant state variation in outreach remains, and evidence of navigator effectiveness suggests that this variation—and sharp reductions in navigator funding for federal marketplaces under the Trump administration—could be particularly harmful to vulnerable populations. In the early years of ACA implementation, African Americans and Latinos were more likely than white consumers to seek navigator assistance (Enroll America 2014 ; Mosqueira, Hua, and Sommers 2015 ); navigators also proved particularly helpful for those seeking insurance who had low incomes, low levels of health literacy, complex family situations, or limited English proficiency (Pollitz, Tolbert, and Diaz 2018 ). Overall, those receiving in-person navigator assistance were about twice as likely to enroll as those who tried to access insurance without help (Enroll America 2014 ).

The ACA includes many initiatives and demonstration projects in which states could participate. State choices to participate have not been analyzed in many instances. One exception is the article by Lisa Beauregard and Edward Miller (this issue, 2020 ), which examines state adoption of the ACA’s home and community-based services (HCBS) initiatives from 2011 to 2015, using both cross-sectional and longitudinal models. Many individuals in need of long-term supports and services prefer to receive care at home rather than in a nursing home. Although the number of individuals receiving Medicaid HCBS has increased over time, the initiatives in the ACA were meant to accelerate the shift to noninstitutional care and to address cross-state variation in long-term services and supports rebalancing. The authors find that HCBS initiative adoption was more common among more liberal states, those that had previously adopted HCBS policies, and those with neighboring states that had adopted; in the cross-sectional model, states that had expanded Medicaid under the ACA were also more likely to adopt the ACA’s HCBS policies. Thus several of the factors associated with Medicaid expansion, as mentioned, were important in explaining HCBS expansion as well: ideology, existing policy, and policy diffusion. Going against expectations, HCBS initiative adoption was also more common in states with less bureaucratic capacity (fewer state employees per capita) and more nursing home beds per elder. It could be that states with less capacity saw the HCBS initiatives as a way to bolster hiring in an understaffed area, and that states with more nursing facility beds had more incentive to increase HCBS options.

Given the importance and structure of the ACA, legal scholars and political scientists have examined the implications of the ACA for the operation of American federalism. For example, Abbe Gluck and Nicole Huberfeld (2018) argue that the ACA is valuable for illustrating how federalism operates contemporarily in the United States. They conclude that the ACA illustrates the “conceptual confusion” inherent in American federalism: is “healthcare federalism”—including the structural elements by which the federal and state governments divide responsibility—meant to produce “particular policy outcomes” regarding cost, access, or quality, or is it meant to “service structural aims regardless of policy ends,” for example “reserving power to states.” Frank Thompson, Michael Gusmano, and Shugo Shinohara ( 2018 ) use the ACA as a case of “executive federalism,” showing how some Republican governors abetted Trump administration efforts to undercut the insurance exchanges and Medicaid expansions through waivers, funding decisions, executive orders, and administrative roles, and how a few resisted ACA retrenchment. Some researchers express concern that enhanced state control and flexibility under the Trump administration is used less for innovation than for retrenchment and “intergovernmental blame shifting” (Jones 2017 ).

Many studies examine state choices to engage in various components of the ACA, but scholars are just beginning to examine the next phase in the ACA’s political effects: feedback effects arising from earlier state choices. In this issue, Richard Fording and Dana Patton ( 2020 ) examine one feedback that has emerged in the negative direction: how the expansion of Medicaid to new populations incentivized the adoption of work requirements in some states. Such requirements emerged first in expansion states led by Republican governors, who sought to assuage Republican voters’ objections to expansion by imposing additional terms and conditionality on Medicaid eligibility. The policy then diffused to newly expanding states, which incorporated work requirements from the outset of expansion, and even to non-expansion states, which imposed them in their existing Medicaid programs, rendering those programs even more restrictive than they had been before the ACA. In this way, the ACA provides an important example not just of positive policy feedbacks (policy entrenchment in many liberal states), but also of negative feedbacks of various forms in more conservative states (policy modification, policy reinvention, and policy regression).

• EFFECTS OF THE ACA ON INSURANCE COVERAGE, ACCESS TO HEALTH CARE, AND HEALTH

Unsurprisingly, dozens of studies estimate the impact of the Affordable Care Act on health insurance coverage, the vast majority focusing on the Medicaid expansion due to its importance in targeting the uninsured (just over half of the uninsured had incomes less than the new Medicaid eligibility income cutoff in 2011) and the opportunity for causal inference afforded by the Supreme Court’s decision to make the Medicaid expansion optional to the states. Research has also been substantial on the extension of parental coverage to young adult dependents that began in 2010, researchers comparing young adults eligible for the dependent coverage with those who were somewhat older and therefore ineligible. The most empirically convincing estimates indicate that insurance rates for young adults increased by about 3.5 percentage points (Slusky 2017 ). Given the general increase in insurance coverage following the implementation of the main components of the ACA, the literature has focused on determining the contribution of the ACA to the rise in coverage and estimating the contribution of the Medicaid expansion and the ACA’s other elements.

All studies focusing solely on the Medicaid expansion and examining insurance coverage find that Medicaid expansion resulted in sizable and statistically significant reductions in uninsured rates (for a review and comprehensive list, see Antonisse et al. 2018 ), virtually all of these studies relying on comparing outcomes between states that did and did not take the Medicaid expansion. Two take the analysis further, examining the Medicaid expansion in the broader context of the ACA as a whole. Charles Courtemanche and colleagues ( 2017 ) distinguish between substate areas with high and low rates of insurance prior to the ACA, noting that the ACA’s provisions will have more impact in areas where more individuals lack insurance coverage. Using this third dimension of variation in impact, along with the variation over time and across states, they find that in areas with average levels of uninsurance prior to the ACA, the uninsured rate fell by 5.9 percentage points in states with a Medicaid expansion and by 2.8 percentage points in states that did not expand, suggesting that the Medicaid expansion explains just over half of the overall fall in uninsurance on average, the contribution for certain subsets of the population being considerably larger. Molly Frean, Jonathan Gruber, and Benjamin Sommers ( 2017 ) estimate the premium subsidy for which a family would be eligible (which varies depending on the area of residence and family structure) and the Medicaid eligibility of the family under both pre-ACA and post-ACA Medicaid rules. Decomposing the change in coverage, they find that approximately 60 percent of the decline in uninsurance explained by their model can be attributed to expansion in Medicaid eligibility and 40 percent to the premium subsidies. A study that focuses on the impact of the premium subsidy policies (Hinde 2017 ) finds a statistically significant 5.4 percentage point increase in private non–group insurance coverage for individuals with incomes just above the 138 percent of the federal poverty limit cutoff in Medicaid expansion states and a statistically insignificant 2.3 percentage point increase in private non–group coverage for individuals with incomes just above 100 percent of FPL in non-expansion states.

Given the increase in health insurance coverage, demand for health care is likely to rise as the price falls. However, to the extent that supply of health care may respond more slowly, health-care use may not increase as quickly. Moreover, the causal linkages between health insurance, health-care use, and health are not obvious: individuals with health insurance tend to use more care and are healthier, but disentangling the causal effect of the insurance itself from other characteristics of insured individuals is difficult. Consequently, research examining the effects of the expansions of health insurance availability that occurred with the ACA on health care and health has been considerable. Researchers have examined a variety of health-care access and use measures, some of which may plausibly be affected quickly by an increase in insurance coverage; others may take more time for any effect to be seen. One of the goals of the ACA was to improve the appropriateness of care used, thus researchers have been particularly interested in examining whether appropriate preventive care such as blood pressure screening increased and use of the emergency department (where the uninsured are more likely to go to obtain care) fell.

Concomitant with the expansion in insurance coverage, measures such as whether someone needed care but could not afford it have been found to be lower in many studies (for a survey of Medicaid expansion studies, see Antonisse et al. 2018 ; for a survey of studies of the dependent coverage expansion, see Breslau et al. 2018 ). Other use measures have a less obvious relationship with insurance coverage given the possibility of supply side constraints, but studies examining use of primary and preventive care have generally found evidence of increases. For example, using the common state difference-in-differences approach, Laura Wherry and Sarah Miller (2016), Miller and Wherry ( 2017 ), Kosali Simon, Aparna Soni, and John Cawley ( 2017 ), and Ausmita Ghosh, Simon, and Benjamin Sommers ( 2019 ) find that at least some measures of preventive care use increased in a statistically significant way due to the Medicaid expansions. Courtemanche and colleagues (2018) find that both the Medicaid expansions and the impact of the ACA in previously high uninsured areas increased use of preventive care. Thomas Selden, Brady Lipton, and Sandra Decker (2017) strike a cautionary note, however, finding that for adults with incomes between 100 and 138 percent of the federal poverty level increases were similar in having a usual source of care and primary care visits, but adults in expansion states reported facing greater difficulty accessing physician care than those in non-expansion states, although those in expansion states saw larger reductions in out-of-pocket spending.

Some evidence indicates that use of acute care increased as a result of the Medicaid expansion, although estimates of such effects are more variable. For example, Wherry and Miller ( 2016 ) find that Medicaid expansions were associated with increased overnight hospital stays but no change in emergency department use in the first year of the expansion; results are somewhat different when they add additional data (Miller and Wherry 2017 ). Estimates of impacts on emergency department use vary, some researchers finding no change in overall emergency department use (Pines et al. 2016 ) and others finding an increase (Nikpay et al. 2016 ). Research on the dependent coverage mandate suggests that it led to a slight decrease in emergency department visits (see Akosa Antwi et al. 2015 ). Overall, hospital admissions seem to have remained largely unchanged, though the payer mix shifted toward Medicaid and away from uninsured admissions (Pickens et al. 2018 ). Focusing on substance abuse-related admissions, Angélica Meinhofer and Allison Witman ( 2018 ) find that opioid admissions to specialty treatment facilities increased in expansion states, especially those with comprehensive medication-assisted treatment coverage under Medicaid. Joanna Maclean and Brendan Saloner ( 2019 ) find some evidence of increases in prescriptions and specialty admissions for substance use disorder, but stronger evidence of a shift in payer away from uncompensated care and state and local government payments and toward Medicaid and private insurance.

Although having insurance may lead to moral hazard effects, research thus far has not found the ACA Medicaid expansion to have increased risky behavior such as smoking (Simon, Soni, and Cawley 2017 ; Courtemanche et al. 2018 ; Cotti, Nesson, and Tefft 2019 ). Instead, Chad Cotti, Erik Nesson, and Nathan Tefft (2019) find that Medicaid expansions were associated with reduced cigarette consumption and increased smoking cessation product use among the Medicaid-eligible population. However, Silvia Barbaresco, Courtemanche, and Yanling Qi ( 2015 ) find evidence of an increase in risky drinking following the dependent coverage provision.

Although insurance coverage and many measures of access to care have clearly improved under the insurance provisions of the ACA, the health impacts are as yet not clear. Researchers have found results ranging from an improvement in self-assessed health due to the Medicaid expansion (Simon, Soni, and Cawley 2017 ), to no effect on self-assessed health (Courtemanche et al. 2018 ), to reduced reporting of being in excellent or very good health in the first year after the expansion (Miller and Wherry 2017 ). Because changes in self-assessed health are subjective, they may reflect reductions in stress from greater financial security due to insurance or new information learned from new contacts with health-care professionals as well as changes in physical health, so it is perhaps not surprising that the results for self-assessed health vary. In addition, health impacts of insurance coverage may arise over the longer term. For example, Wherry and Miller ( 2016 ) find increased rates of diagnosing chronic conditions, and Benjamin Sommers and colleagues (2017) find evidence of increased treatment for chronic conditions, both of which might be expected to have longer-term impacts on health.

• ECONOMIC EFFECTS OF THE ACA: FINANCIAL AND LABOR-MARKET IMPACTS

Although improving the health of the population is an underlying goal of the Affordable Care Act’s provisions to move toward universal health insurance coverage, another goal of insurance coverage is to protect against the financial consequences of poor health. Health insurance is in many ways unique among types of insurance and, from the perspective of protecting against financial consequences, society’s interest in ensuring access to health insurance may be greater than for other insurance types, because though the risks of a bad health shock can be reduced by behavioral changes, they cannot be eliminated. Moreover, publicly subsidized health insurance plays a key role in the safety net supporting low-income Americans. As a result, household financial security is an important area where the ACA may have had economic impacts, and research in this area is considerable.

Much of the research examining changes in access to care has also examined whether provisions of the ACA affected reported difficulty in paying medical bills, inability to afford care, or magnitude of out-of-pocket payments. Researchers have found evidence for reductions in such measures with Medicaid expansion (see, for example, Miller and Wherry 2017 ; for a review, see Antonisse et al. 2018 ). Researchers have also found a reduction in such measures correlated with the ACA insurance expansion more broadly (see, for example, McKenna et al. 2018 ). Most of the extant studies examining the effects of the ACA on financial security have examined the Medicaid expansion; other ACA impacts, such as changes in rating rules, cost-sharing subsidies, and an increase in patient cost-sharing, may have had an effect as well, but are less studied.

More generally, research has shown that the ACA, and in particular the Medicaid expansion, has improved the financial circumstances of low-income families. Exploiting the fact that some California counties expanded Medicaid earlier than 2014, Heidi Allen and colleagues ( 2017 ) examine the use of payday loans—short-term, unsecured loans characterized by high annual interest rates and more commonly used by low-income families. The authors find an 11 percent reduction in the number of loans taken out each month in the early expanding counties relative to others. They also find reductions in the expansion counties in the number of unique borrowers each month and the amount of payday loan debt. Kyle Caswell and Timothy Waidmann ( 2019 ) use credit bureau data to compare individuals in expansion and non-expansion counties and across counties with more previously uninsured individuals relative to fewer, and find that the expansion improved consumer financial health on a number of dimensions, including credit scores, balances past due as a percent of total debt, probability of new medical collections, and probability of experiencing a new derogatory balance of any type. Luojia Hu and colleagues ( 2018 ) use a panel of consumer credit data and a synthetic control approach to deal with the issue of inconsistent pre-trends across expansion and non-expansion states. They also find evidence of improved financial well-being: the Medicaid expansion reduced the number of unpaid bills and the amount of debt sent to collection among individuals living in zip codes with a high share of previously uninsured low-income individuals. Kenneth Brevoort, Daniel Grodzicki, and Martin Hackmann ( 2017 ) examine medical debt more specifically as well as measure the indirect benefits to households of improved credit profiles. They find that the Medicaid expansion reduced the incidence of new medical debt, reduced the probability of becoming newly delinquent on a debt, and improved credit scores. These improvements, they show, translate into better credit outcomes, using novel data on credit offers to show that after the expansion individuals in adopting states received more offers of credit and at substantially better terms than individuals in non-adopting states. Their results indicate that the effects are larger for individuals with subprime credit scores. Because low-income individuals are more likely to have subprime credit scores, these results point to an improvement in financial security among low-income families as a result of the Medicaid expansion. Similarly, Dahlia Remler, Sanders Korenman, and Rosemary Hyson (2017) show the importance of Medicaid and insurance subsidies in reducing health-inclusive poverty, which they define as the poverty rate when accounting for health needs. They find that the ACA’s insurance provisions had a particularly strong impact on health-inclusive poverty among groups such as two-parent families and nondisabled childless adults.

Given the long-standing connection between employment and health insurance, a law such as the ACA may have consequences for the labor market, different provisions having possibly different and even contrasting effects, making overall impacts difficult to disentangle. In addition, the context of an economic recovery and improving labor market adds an additional layer of complexity, limiting the use of variation over time and making provisions that applied equally more difficult to study. The provisions that are most likely to result in labor-market effects, and thus which have received the most attention from researchers, include the dependent coverage mandate, the Medicaid expansion and exchange subsidies, and the employer mandate.

By offering insurance to young adults through their parents, the dependent coverage mandate would be predicted to reduce the incentive to work in jobs offering health insurance and to increase the incentive to work in jobs that do not offer health insurance or in self-employment. In addition, the income effect arising from newly available health insurance at low or no additional cost may reduce labor supply; it may also have differential effects on school enrollment, increasing the probability of enrollment in school for dependents who might have been reluctant to enroll in school if it meant not working or taking a part-time job without health insurance, or reducing the probability of enrollment in school for the group of dependents who previously would have been covered only while a student. Finally, wages among the newly eligible may rise if they take jobs that offer higher wages and fewer benefits such as health insurance, or if employers with large numbers of workers newly eligible for dependent coverage shift their wage-benefit packages accordingly. As Bradley Heim, Ithai Lurie, and Kosali Simon ( 2018b ) note, however, young adults may be less responsive to incentives arising from health insurance perhaps because of general good health or myopia, indicating that any effects of the dependent coverage mandate may be small.

Indeed, the results from the literature studying the dependent insurance mandate indicate small effects or no effects. Using similar approaches to those discussed earlier, Yaa Akosa Antwi, Asako Moriya, and Simon ( 2013 ) find some evidence of reduced work hours. David Slusky ( 2017 ), however, points out that these estimates are likely an overestimate due to differential trends for the treatment and control age groups used; he finds no evidence of changes in labor supply. Following Slusky’s suggested refinements but using new data, Gregory Colman and Dhaval Dave ( 2018 ) find some evidence that newly eligible dependents spent less time working and more time searching for work. However, James Bailey and Anna Chorniy ( 2016 ) find little evidence of increased job mobility among young adults. Finally, Heim, Lurie, and Simon ( 2018b ) use tax data to examine employment, self-employment, wages, and enrollment in education. They find effects that are in the theoretically predicted directions but quite small and only for a subsample of young adults whose parents have an employment-based retirement plan (a proxy for having employer-sponsored insurance). Overall, it appears that the dependent insurance mandate has had no substantial effect on labor-market behavior.

The Medicaid expansion and subsidies for insurance purchased through the exchanges have a variety of theoretical impacts on the supply side of the labor market. Most straightforward is the incentive for individuals to reduce labor supply, either to get below the subsidy eligibility level (or to qualify for a more generous subsidy) or because of an income effect of the additional resources provided by Medicaid or insurance subsidies (Congressional Budget Office 2014 ). This incentive implies reductions in employment and hours and thus increases in (voluntary) part-time work. However, individuals such as parents who previously were eligible for Medicaid if their income was very low have an incentive to increase their labor supply because they can now earn more and still have insurance. In addition, individuals in states that do not accept the Medicaid expansion also have an incentive to increase their labor supply to qualify for exchange subsidies that only apply to individuals earning more than the poverty line. In addition, the availability of health insurance through a source not tied to employment makes it easier for workers to change jobs or become self-employed.

Although theoretical predictions indicate a variety of possible labor supply effects, empirical work to date has found little evidence of statistically or economically significant labor supply effects of the Medicaid expansion. Using standard state difference-in-differences methods, multiple studies find no evidence of changes in labor-force participation, employment, usual hours worked, propensity for full-time versus part-time work, or wages as a result of the Medicaid expansion (Gooptu et al. 2016 ; Kaestner et al. 2017 ; Frisvold and Jung 2018 ; Leung and Mas 2018 ). This lack of a result is also found when using somewhat higher-income individuals as a control group (Gooptu et al. 2016 ), when examining outcomes for individuals observed for two years (Gooptu et al. 2016 ; Leung and Mas 2018 ), when focusing just on childless adults in states with no previous coverage for such adults (Leung and Mas 2018 ), and when using a synthetic control method to better account for the possibility of differential trends across expansion and non-expansion states (Kaestner et al. 2017 ). Similarly, researchers have found no change in the probability of retirement or part-time work among workers ages fifty through sixty-four beginning in 2014 in Medicaid expansion states relative to non-expansion states (Levy, Buchmueller, and Nikpay 2018 ). In addition, the Medicaid expansion does not appear to have affected exits of workers from unemployment, suggesting no detectable impact on job search behavior among the unemployed (Buchmueller, Levy, and Valetta 2019 ).

The only indication of labor supply effects comes from two working papers that focus on substate geographies. Mark Duggan, Gopi Goda, and Emilie Jackson ( 2019 ) find no aggregate effect on labor-force participation but an increase in participation and employment in Public Use Microdata Areas (PUMAs) with a higher pre-ACA uninsured rate among the Medicaid-eligible population and a reduction in labor-force participation in areas with a higher pre-ACA uninsured rate among the subsidy-eligible population. However, they find no effect on part-time employment, self-employment, or hours worked conditional on employment. Lizhong Peng, Xiaohui Guo, and Chad Meyerhoefer (2018) find evidence of a transitory decline in employment in border counties in expansion states relative to neighboring counties in non-expansion states, although they find no impact on wages. However, the data they are using correspond to the location of the job rather than the location of the potentially eligible individual, so it is not clear to what extent they are measuring a labor supply effect. In another study focusing on substate geographies, Lucie Schmidt, Lara Shore-Sheppard, and Tara Watson (2019b) find no evidence of labor supply effects for nonparents or married parents for any outcome (labor-force participation, employment, hours, or earnings) and at most a small increase in labor supply among single parents, comparing individuals in expansion PUMAs with those in PUMAs in bordering non-expansion states. The vast majority of the evidence thus suggests no economically or statistically significant effect of the Medicaid expansion on labor supply.

Finally, although the Medicaid expansion and the availability of subsidized insurance through the exchanges raises the possibility of increased job flexibility, research to date has not found evidence of increases in job changing or self-employment. Kavan Kucko, Kevin Rinz, and Benjamin Solow ( 2018 ) examine the universe of individual tax returns and find an increase in reported income just above the poverty level among taxpayers with self-employment income in states that did not take the Medicaid expansion. However, by matching the tax returns to survey data, they show that there were no differences in actual labor market outcomes, indicating an increase in reported income in response to the tax incentive but no real change in labor-market behavior.

The employer mandate, which requires firms with more than fifty workers to offer affordable coverage or pay a penalty, could have several possible impacts on labor demand, including incentives for firms to reduce their size below the cutoff if they are close to that level, to use fewer full-time workers but increase their hours, to increase use of temporary or contract workers, and to increase use of part-time (less than thirty hours per week) rather than full-time full workers. Firms forced to begin offering coverage have an incentive to reduce wages to compensate, although the minimum wage limits changes on this margin. However, 95.7 percent of firms with fifty or more employees offered health insurance in 2013 according to data from the Agency for Healthcare Research and Quality, indicating that any impacts of the employer mandate on labor demand are likely to be small.

The evidence to date on the employer mandate, much of which is primarily descriptive rather than demonstrating causal effects, largely bears this prediction out. Moriya, Selden, and Simon ( 2016 ) compare trends adjusted for economic conditions for different firm sizes and find little evidence of differential change in part-time employment by firm size. Using similar methods, Bowen Garrett, Robert Kaestner, and Anuj Gangopadhyaya ( 2017 ) find no difference between trends in actual labor-market outcomes and those predicted based on economic conditions and demographics for employment or usual hours per week, but do find an increase in voluntary part-time employment, particularly among women, and a decline in involuntary part-time employment. To obtain estimates that are more plausibly causal, William Even and David Macpherson ( 2019 ) try to incorporate differences between occupations more and less likely to be affected by the employer mandate. They find that among less-educated workers, involuntary part-time employment fell more slowly after 2014 in occupations with higher shares of workers likely to be affected by the employer mandate (working in firms with more than one hundred workers, not offered health insurance, and working thirty or more hours per week), which suggests that the employer mandate contributed to higher levels of involuntary part-time work, although it is not definitive given that trends across occupations may have differed in the absence of the ACA. They find no evidence of a change in voluntary part-time work.

Finally, the requirement that insurance policies must cover preexisting conditions and cannot charge higher premiums for them has important theoretical implications for job mobility because it allows an individual to change jobs or to take a job not offering health insurance even if a family member has such a condition. Little research thus far has focused on job mobility changes as a result of the preexisting condition limitation, but Pinka Chatterji, Peter Brandon, and Sara Markowitz ( 2016 ) find that the elimination of preexisting condition exclusions led to an increase in voluntary job changes among parents of a child with a chronic condition.

Overall, the evidence to date on labor-market impacts of the ACA suggests that they have been limited, even in areas such as labor supply and job flexibility where theoretical arguments suggest effects. Further work, particularly that which investigates possible sources of heterogeneity in outcomes across individuals and places, is needed before full conclusions can be drawn, however. In addition, although short-term effects of the ACA on labor-market outcomes may be smaller than long-term ones, as the time since the ACA’s passage lengthens, researchers will face additional challenges in attempting to disentangle ACA effects from the effects of other changes in the economy.

• SOCIAL EFFECTS OF THE ACA: FAMILY STRUCTURE

The extensiveness of the ACA and the importance of health insurance to individual and family well-being suggests that in addition to the direct impacts on coverage, health, and the labor market discussed earlier, its passage may have affected more indirect social outcomes, including marital and fertility decisions. Prior to the ACA, marriage was an important way for individuals to gain access to insurance if their employer did not sponsor it or they did not have a job but their prospective spouse’s employer did. The incentive offered by the possibility of insurance coverage thus may have induced couples in a relationship to marry or to marry earlier than they would have otherwise. Various provisions of the ACA changed this incentive, however. In particular, the young adult dependent coverage mandate provides young adults an additional source for health insurance coverage outside of marriage, reducing the incentive to marry. The provisions of the premium tax subsidy, like other tax subsidy programs, may have more complex effects on marriage incentives, penalizing marriage in some cases and rewarding it in others, depending on the income and employment circumstances of the potential partners. The requirement that preexisting conditions be covered also has implications for marriage (and divorce) since an individual no longer faces constraints on moving between insurance plans. In addition, as Joelle Abramowitz ( 2016 ) points out, indirect impacts on marriage may operate through other channels (for example, if young adults increased their school enrollment in response to the new coverage, their marriage propensity could be affected indirectly). Finally, the Medicaid expansion included a provision eliminating asset tests. In that case, when a spouse is diagnosed with an expensive medical condition couples do not need to divorce to preserve assets for the healthy spouse while obtaining Medicaid coverage for the unhealthy spouse (“medical divorce”).

In addition to marriage, the ACA’s provisions may have impacts on other aspects of family structure, such as fertility. These impacts are theoretically ambiguous given that having health insurance reduces the cost of any medical care, including the cost of childbearing, which would be predicted to increase fertility, but having insurance also lowers the price of contraception, thus reducing fertility. In addition, the ACA included a provision requiring insurers to cover contraception, which would be expected to reduce fertility further.

Despite the variety of possible impacts on family structure, relatively little research on family structure outcomes has been undertaken. In the area of marriage and divorce, the research thus far suggests that marital status decisions are affected by the policy. Abramowitz ( 2016 ) examines the impact of the dependent coverage mandate using a typical age-based difference-in-difference strategy, finding reductions in the likelihood of marriage and increases in the probability of divorce following the implementation of the mandate. Matthew Hampton and Otto Lenhart ( 2019 ) use longitudinal data to estimate the impact of coverage of preexisting conditions, finding that the probability of being married declines for men with preexisting conditions after 2014 relative to men without such conditions, a finding that is robust to a variety of specification checks, including a placebo test using alternate time periods not including a policy change. Finally, Slusky and Donna Ginther ( 2017 ) use state difference-in-differences to examine the impact of the Medicaid expansion on “medical divorce” and find that the Medicaid expansion decreased the prevalence of divorce among those ages fifty through sixty-four with a college degree.

As is true of research on marital status, research on fertility effects of the ACA has focused on the impact of the young adult dependent coverage mandate. Both Abramowitz ( 2018 ) and Heim, Lurie, and Simon ( 2018a ) take advantage of the age variation in the mandate, Abramowitz using data from the American Community Survey and the National Survey of Family Growth and Heim, Lurie, and Simon using tax records. Both studies find that the dependent coverage mandate modestly reduced childbearing, Abramowitz also showing evidence of a reduction in abortion rates and an increase in the use of long-term contraceptives. Because such little research has been published to date on fertility impacts of the ACA, this would seem to be an important area for future research, particularly given that previous work on Medicaid expansions and fertility has found equivocal effects of income-based expansions on birth rates but more consistent impacts of expansions to contraceptive access (for a review, see Buchmueller, Ham, and Shore-Sheppard 2016 ).

• SOCIAL EFFECTS OF THE ACA: IMPACTS ON VULNERABLE POPULATIONS

Because rates of uninsurance were higher in vulnerable populations before the ACA, many but not all such populations were intended to be helped by the policy. Evidence from Medicaid expansions in particular but also the ACA overall indicates that when subpopulations of low-income, low-education, or racial or ethnic minorities are studied, coverage gains are substantial (for a review, see Antonisse et al. 2018 , 3). In addition, health outcomes tend to have improved for those groups (see, for example, Sommers et al. 2015 ; Antonisse et al. 2018 ). One key group excluded from the intended effects of the policy, however, was immigrants who were either undocumented or had been in the United States fewer than five years. Researchers have pointed out the likely importance of additional funding for community health centers that was included in the ACA in providing care for this group (see Ortega, Rodriguez, and Vargas Bustamante 2015 ). However, relatively little work evaluating the impact of this part of the ACA has been done.

Similarly, the ACA, and particularly the Medicaid expansion, represents a potentially important new source of health-care funding for a group that has historically had low rates of insurance—the criminal justice–involved population (Boutwell and Freedman 2014 ). This population faces health challenges including rates of infectious disease, chronic illness, and trauma that are higher than in the general population (Rich, Wakeman, and Dickman 2011 ). A lack of health insurance among the formerly incarcerated therefore suggests that many of these issues have gone unaddressed. However, little is known about the impact of the ACA on this population, an important omission that Carrie Fry, Thomas McGuire, and Richard Frank (this issue, 2020 ) address in their article. Comparing arrest data from six urban county jails, they show that Medicaid expansion is associated with small decreases in rates of recidivism in two of the three county pairs examined. The declines are of similar magnitude across gender and racial-ethnic subgroups.

Another way the ACA may affect vulnerable populations is its interaction with other parts of the safety net. This area has received more attention, particularly in regard to programs for the disabled—Supplemental Security Income (SSI), a means-tested program requiring that family income and resources be below a cutoff in addition to the individual being determined to have a disability, and Social Security Disability Insurance (SSDI), a social insurance program for disabled individuals with significant work history that pays benefits based on an individual’s past earnings. Both SSI and SSDI provide beneficiaries with health insurance as well as cash benefits, SSI recipients being eligible for Medicaid and SSDI recipients receiving Medicare. The health insurance benefit is likely to be particularly important for the disabled, who are likely to have high levels of health-care needs and low levels of access to employment-based health insurance. Jae Kennedy and Elizabeth Blodgett ( 2012 ) note that several provisions of the ACA have the potential to affect disability program participation both by allowing disabled workers to remain privately insured (the elimination of preexisting condition exclusions, the elimination of lifetime caps on insurance payments, and the parental coverage mandate) and by granting public coverage through Medicaid even without a formal disability assessment. The possibility of health insurance not tied to disability program participation thus provides an incentive to reduce disability program participation. However, incentives are also in place to increase disability program participation. Because the disability determination process is time consuming, and SSDI recipients face an additional waiting period before they can receive Medicare, disabled workers may be reluctant to leave their jobs and health insurance to claim disability benefits because it could mean a long period without health coverage. The Medicaid expansion of the ACA might therefore encourage disability program participation among such individuals. In addition, the Medicaid expansion might encourage disability program participation if potentially eligible individuals become aware of their disability program eligibility in the process of applying for Medicaid.

Several groups of researchers have examined the question of the net effect of the Medicaid expansion on disability program participation and applications. Chatterji and Yue Li ( 2017 ) examine SSI participation in three states and Washington, D.C., that expanded Medicaid before 2014 under an optional provision of the ACA or a federal waiver. Notably, all of the expansions they study were built on previous state-run programs that had limits on benefits or the number of enrollees rather than being entirely new opportunities. Using synthetic control methods, they find a marginally statistically significant reduction in SSI receipt in only one state, Connecticut. Aparna Soni and colleagues (2017) also find a reduction in SSI recipients when they examine expansions that occurred in 2014 and 2015 using a simple difference-in-differences approach, although no effect of the expansion is evident when SSI participation is measured as a fraction of the population (Schmidt, Shore-Sheppard, and Watson 2019a ).

Because exit from disability programs is relatively low, disability program participation is affected by previous policies as well as new policies, suggesting that the stock of program participants may change more slowly than changes in policies would suggest. Moreover, the lag between application and enrollment may be substantial, raising the question of when the level of disability program participation might realistically be expected to reflect changes in public insurance policy. By contrast, applications to disability programs are likely to reflect policy changes more immediately. Two studies have examined research on SSI and SSDI applications using administrative data from the Social Security Administration. Priyanka Anand and colleagues ( 2019 ) run a difference-in-difference model using only PUMAs that match well on preexpansion characteristics with at least one other PUMA, finding that SSI applications were slightly higher in PUMAs in states that expanded in the first quarter of 2014 than in non-expansion PUMAs between one and five quarters after the expansion. However, as Schmidt, Shore-Sheppard, and Watson ( 2019a ) note, because Anand and colleagues pool all expansion and non-expansion PUMAs in their matched sample rather than comparing specific matched PUMAs, there is some evidence of dissimilar preexpansion trends in the two groups, raising the possibility that their results partially reflect differential trends across groups. Their estimates for SSDI applications are similarly inconclusive.

Schmidt, Shore-Sheppard, and Watson ( 2019a ) use annual applications for SSI and SSDI, but observed at the county level. To control for the likelihood of differential trends in disability program applications across expansion and non-expansion states, they compare application rates in state border counties that expanded Medicaid with those in counties in non-expansion states just across the border, showing that border counties are more similar to the county just across the border than to those with differential expansion status located elsewhere. They find no significant effects of the Medicaid expansion on applications or awards to either SSI or SSDI. Overall, the research in this area indicates that any impact of the new availability of public insurance on disability program applications or caseloads is negligible.

One concern about a research design examining Medicaid expansion that compares geographically proximate areas across state lines would be the possibility that individuals who would be eligible for Medicaid if they lived in an expansion state would move across state lines in order to obtain public insurance. Lucas Goodman ( 2017 ) investigates migration in response to the ACA Medicaid expansion and finds no evidence that migration out of non-expansion states to expansion states increased relative to migration in the reverse direction. His results are precise enough that he can rule out effects on migration rates that would produce Medicaid enrollment changes detectable in the data.

Finally, using a similar comparison of outcomes in expansion to non-expansion border counties, Schmidt, Shore-Sheppard, and Watson (2019b) examine participation in two additional safety net programs, the Supplemental Nutrition Assistance Program (SNAP) and the Earned Income Tax Credit (EITC). As means-tested programs, EITC and SNAP may be affected by the Medicaid expansion if individuals change their labor supply in response—either reducing it to qualify for Medicaid, which might increase participation in other programs, or increasing it because for individuals such as parents the Medicaid expansion offers more generous means testing than previous Medicaid eligibility limits. Even if labor supply does not change, eligibility for Medicaid or the process of enrolling in it may provide information about eligibility for other means-tested programs or make the process of enrolling in other programs relatively easier. Schmidt, Shore-Sheppard, and Watson (2019b) use county-level administrative data and PUMA-level data from the American Community Survey and find evidence of small increases in SNAP and EITC receipt. They find no evidence of labor supply changes, however, suggesting that information about program eligibility or enrollment is the primary mechanism behind the increases.

• POLITICAL EFFECTS OF THE ACA: IMPACTS ON INDIVIDUAL-LEVEL POLITICAL BEHAVIOR AND ATTITUDES

The largest expansion of social policy in the United States in a generation, the Affordable Care Act could potentially have profound effects on the political behavior and attitudes of ordinary Americans—those who may benefit from the law’s provisions, those who pay for the new benefits, those who embrace the law’s expansion of health insurance access, and those who resent or oppose it. As noted, several scholars have examined whether state decisions on the ACA were associated with public opinion, with mixed results. A much larger literature has explored whether the ACA and its implementation has had feedback effects shaping subsequent attitudes and behaviors. That is, scholars have examined political activity and preferences among the public not as an input into policymakers’ decisions but rather as an outcome of the law. Indeed, although much of the existing policy feedbacks literature examines policy initiatives of the past, such as Social Security, the GI Bill, and Aid to Families with Dependent Children (for an overview, see Campbell 2012 ), the ACA enables both the study of feedback effects as they emerge in real time and enhanced causal inference, due to the quasi-experimental roll-out of various provisions. That the ACA was the subject of a well-publicized and enduring political debate during its creation, enactment, and implementation would seem to heighten the possibilities for feedback effects as well (Sances and Clinton 2019b ).

Thus far, much scholarship has used the optional Medicaid expansion to estimate causal models of political behavior. Most analyses have found positive effects: increased voter turnout in states that expanded Medicaid. For example, Haselswerdt ( 2017 ) finds that aggregate voter turnout in House races declined less in 2014 (a midterm year) than in 2012 (a presidential election year) in states that had expanded Medicaid. An accompanying analysis using individual-level survey data shows that the positive turnout effect is evident among both Democrats and Republicans, the latter suggesting a backlash effect, given surveys indicating that most Republicans opposed the ACA. Joshua Clinton and Michael Sances (2018) compare counties sharing a border between expansion and non-expansion states, focusing on citizens between eighteen and sixty-four and below 138 percent of the federal poverty limit. Examining midterm and presidential elections before and after Medicaid expansion, they find that both voter registration and turnout increased in expansion counties, particularly those with a high share of citizens who are newly eligible for Medicaid. Unlike Haselswerdt, they find the participation effect concentrated in Democratic-leaning rather than Republican-leaning counties, evidence of a positive effect among recipients but not an anti-ACA backlash effect.

In this issue, Charles Courtemanche, James Marton, and Aaron Yelowitz ( 2020 ) estimate the impact of the ACA on voter registration and turnout, focusing not just on the Medicaid expansion but also on provisions intended to increase insurance coverage overall. Using the Current Population Survey’s November Supplement between 2006 and 2016 and capitalizing on variation across time, state Medicaid expansion status, and within-state pre-ACA uninsurance rates, they find that the ACA had small and statistically insignificant effects on registration and turnout. These results are in contrast to the positive Medicaid effects reported in analyses of aggregate data at the county level (Clinton and Sances 2018 ) and the congressional district level (Haselswerdt 2017 ), but are consistent with estimates of Medicaid effects on turnout outside of the ACA (Michener 2017 ).

In contrast to some of the findings for Medicaid expansion, the dependent care provision, by which individuals under age twenty-six can stay on their parents’ health insurance, does not have an effect on the political participation of these youth (Chattopadhyay 2017 ). The lack of an effect could be due to a variety of reasons: the dependent care benefit may not be visible as government activity because it depends on parents’ having private health insurance; it may be difficult to identify others benefiting from the ACA in this way, complicating potential mobilization by advocacy groups; the benefit targets youth, who are a low-participation group to begin with, and confers a short-term rather than lifetime benefit. The failure to find a positive participatory effect of the dependent care provision supports the view of other scholars who argue that the ability of policies to produce positive feedbacks may be contingent and fragile, particularly policies with designs as complicated, contested, and submerged as those of the ACA (Patashnik and Zelizer 2013 ; Galvin and Thurston 2017 ; Jacobs and Weaver 2015 ). We also do not know whether the dependent care provision changed the political behavior of parents, a possible question for future research.

Scholars have also begun to assess the mechanisms that may link ACA benefits to increased political participation, though much of this work remains speculative. A leading possibility is that gaining health insurance has a positive effect on individuals’ politically relevant resources. As discussed, the Medicaid expansion improved the financial stability of low-income families. Such stability may enhance recipients’ ability to engage in the “luxury good” of political participation (Rosenstone and Hansen 1993 ). Another resource effect of ACA-provided health insurance coverage could be improved mental or physical health, as research outside the ACA suggests. Better physical health is associated with greater political participation (Burden et al. 2017 ; Pacheco and Fletcher 2015 ; Gollust and Rahn 2015 ). Poor health could have an attention-interest effect—drawing focus from political matters to personal ones—or have a cognitive effect that inhibits political participation (Pacheco and Fletcher 2015 ; Blais 2000 ). As noted, effects of the ACA on health may not yet have emerged, although diagnosis and treatment of chronic conditions have risen under the ACA (Wherry and Miller 2016 ; Sommers et al. 2017 ).

A second mechanism linking health insurance and political participation is political engagement, including political interest, knowledge, and efficacy (Verba, Schlozman, and Brady 1995 ). Being newly insured because of the ACA could enhance recipients’ awareness of the stakes of public policy, linking their self-interest to government policy and enhancing their interest in government action, a form of “conscious mobilization” (Clinton and Sances 2018 ). Gaining insurance could have a positive “interpretive effect” (Pierson 1993 ), the government conferring a benefit and recognizing the recipient as a worthy citizen. Newly insured citizens might feel gratitude toward the government (De La O 2013 ) or become civically and politically engaged because of a “reciprocity” effect (Mettler 2005 ). Endorsement by politicians could dampen stigmatizing effects (Clinton and Sances 2018 ).

Third, the ACA could enhance political participation through a mobilization effect—either a positive effect on recipients or a participation-enhancing backlash among program opponents. One mobilization effect for recipients may simply have been mechanical: the 1993 National Voter Registration Act requires social assistance agencies, including the health exchanges, to provide voter registration services, which may explain increased turnout in Medicaid expansion states (Clinton and Sances 2018 ). Many navigator organizations assisting citizens in signing up for health insurance facilitated voter registration as well (Hagan 2016 ). Another possibility is group mobilization—that advocacy groups are actively organizing ACA recipients as pressure groups to defend the legislation—although we did not identify any scholarly accounts of such activity.

Fourth, policy threat could be a mechanism linking the ACA and political participation. Journalistic accounts describe protests defending the ACA from Republican repeal efforts after the 2016 election resulted in unified Republican control of the presidency and Congress (see, for example, Stein 2017 ). Scholarly accounts of anti-Trump and anti-Republican grassroots organizing are emerging (Gose and Skocpol 2019 ; Meyer and Tarrow 2018 ), protecting the ACA from repeal playing a significant role in this mobilization (see also Nadash et al. 2018 ). The ACA is an important case for analyzing the effect of policy threat on participation: previous analyses of policy threat and political participation find differing effects for means-tested versus universal programs: threats to cut Social Security and Medicare in the 1980s and 1990s elicited surges of senior citizen letter-writing to Congress (Campbell 2003 ); in contrast, cuts to Tennessee’s Medicaid program in 2005 resulted in greater turnout declines in counties with the largest disenrollment (Haselswerdt and Michener 2019 ). Thus more work is needed to assess the effects of policy threat for social policies of various designs and target populations, including the ACA and its many components.

One additional contribution the scholarship on policy feedbacks and the ACA has made is showing how the effects of public policy on behavior may vary by partisanship. Take-up of health insurance under the ACA varies by party identification: Republicans have been shown to oppose the ACA even when they might personally benefit (Kliff 2016 ); indeed, Amy Lerman, Meredith Sadin, and Samuel Trachtman ( 2017 ) find in their recent field experiment that Republicans in need of insurance are more likely to sign up if shown a private interface (healthsherpa.com) rather than the government interface (HealthCare.gov). The effect of party extends to political behavior as well. The ACA appears to elicit a backlash or “thermostatic” effect in which those who are opposed to the reform for ideological reasons or who perceive that they will not benefit or may have to pay for the reform react with increased political participation (Haselswerdt 2017 ; McCabe 2016 ).

The advent of the ACA also triggered a great deal of work examining effects on the political attitudes and preferences of recipients and other members of the public. Speculation circulated that support for the ACA, which hovered below 50 percent as the law was being debated, would rise once implementation began and people gained insurance through its provisions (Jacobs and Mettler 2011 ). However, previous scholarship looking for attitudinal changes after reforms of welfare and Medicare failed to detect them (Soss and Schram 2007 ; Morgan and Campbell 2011 ). Further, both political and design reasons to believe that the ACA also would not generate policy feedback effects have merit: the law was debated and implemented in a highly partisan environment, suggesting that partisanship might dominate personal experience as a driver of attitudes (Patashnik and Zelizer 2013 ). The law’s complicated, often hidden design elements might also undercut possibilities for attitudinal change (Chattopadhyay 2018 , 2019 ).

Early in the ACA’s trajectory—as the legislation was being debated and before anyone actually benefited from its provisions—partisan and racial considerations dominated the public’s attitudes toward the reform. Pooled cross-sectional surveys in 2009 and 2010 showed that party identification was more important in shaping support or opposition toward health reform than were demographic factors such as being older, higher income, or African American (Kriner and Reeves 2014 ). An analysis of individual-level change from a 2008–2010 panel survey found that during the debate over the law, opinions were more likely to change toward opposition than toward support for reform, and that Republicans were more likely to switch to opposition than Democrats were, the effect being more muted among Republicans concerned about health-care costs, presaging later findings that material stakes affected ACA attitudes (Henderson and Hillygus 2011 ). Scholars also detected motivated reasoning among partisans in the absence of actual experience as well as an effect of elite rhetoric: as elite rhetoric about the law stabilized, variance in attitudes diminished (Kriner and Reeves 2014 ). The power of partisanship and symbolic attitudes such as little trust in government remained powerful even after implementation began. For example, panel data from 2010 through 2014 showed that Republicans and those with less trust in government were more likely to say the ACA was increasing their tax burden, regardless of their experience with the law (Jacobs and Mettler 2016 , 2018 ).

Racial attitudes were also found to be highly correlated with support for the ACA (Henderson and Hillygus 2011 ). That the reform was debated and passed under the first black president made a difference; the relationship between racial attitudes and health reform attitudes was not apparent during the Clinton reform effort of 1993 and 1994, but materialized after it was clear Obama would be the Democratic nominee for the 2008 presidential election (Tesler 2012 ).

After implementation began, the question became whether actual experience—such as gaining insurance—might shape attitudes beyond party identification, racial attitudes, and elite rhetoric. Although in the past scholars have found that political attitudes often do not correspond to individuals’ apparent material interests, health insurance potentially has the characteristics that can trigger self-interested considerations: gaining insurance is a tangible, large, and visible policy event (Citrin and Green 1991 ). Evidence of increased support among those benefiting from the legislation has begun to emerge. As the ACA was implemented, fewer survey respondents said the law had no effect on health-care access (Jacobs and Mettler 2016). Both pooled cross-sectional data and panel data from the early years of ACA implementation also show that the gap between Republicans and Democrats in favorability toward the law was smaller among those who gained insurance through an ACA marketplace than those with employer-based insurance (McCabe 2016 ). These findings echo those of Daniel Hopkins and Kalind Parish ( 2019 ), who pool Kaiser Family Foundation surveys from 2010 through 2017 and find that Medicaid expansion made lower income Americans more favorable toward the ACA, the effects being stronger among nonwhite and Democratic respondents (and absent among higher-income respondents, who are more likely to have insurance from other sources, suggesting a self-interest mechanism at work). Similarly, those with personal or family experience with the ACA (such as using subsidies, gaining insurance, or getting prescription drug help as a senior citizen) are more likely to say the law has had a favorable impact on health access (Jacobs and Mettler 2018). Yet more evidence of personal experience affecting attitudes comes from an analysis of those using the exchanges to buy insurance, which found that they were much more positive toward the ACA after implementation commenced than those who remained uninsured (Hobbs and Hopkins 2019 ; see also Hosek 2016 ). The same study found that those in their early sixties whose insurance premiums were newly capped by the ACA became more favorable toward the law after implementation (Hobbs and Hopkins 2019 ; see also Nadash et al. 2018 ). However, the effect of personal experience varies across individuals in quite specific ways. William Hobbs and Daniel Hopkins (2019) also find that those purchasing insurance on the exchanges who experienced local premium spikes became less favorable toward the ACA.

Those with other forms of government health insurance are more supportive of the ACA as well (Jacobs and Mettler 2018; Lerman and McCabe 2017 ). Lerman and Katherine McCabe use a causal design—comparing those immediately above and below the Medicare eligibility threshold at age sixty-five—and find that getting Medicare increases both support for Medicare spending and support for the ACA. The effects of personal experience were stronger for Republicans, showing that personal experience and self-interest can offset some of the effects of partisanship.

That said, the effect of partisanship is so strong that Republicans in need of health insurance are less likely than Democrats to sign up under the ACA (Lerman, Sadin, and Trachtenberg 2017; Sances and Clinton 2019a ). The gap is larger in non-expansion states; in Medicaid expansion states there is no partisan difference in Medicaid uptake, suggesting that elite cues and partisanship are not just filters but actual bars to addressing a tangible need (Sances and Clinton 2019a ).

Another factor that might influence attitudes toward the ACA is news coverage and television advertising, although the existing work examining these relationships is correlational rather than causal. During the first two weeks of open enrollment in October 2013, news coverage of the ACA was more negative in states using federal marketplaces than those using state marketplaces (Gollust et al. 2014 ). Individuals in locales with a higher volume of insurance advertising and more local news coverage of the ACA in Fall 2013 were more likely to say that they were well informed about the law and more favorable toward it, although the effect was stronger for Democrats than Republicans (Fowler et al. 2017 ). After Marketplaces opened for business, a greater volume of television ads opposing the ACA was associated with lower Marketplace participation (Gollust et al. 2018 ). Looking at the effects of different types of health insurance and health-related political advertising on Marketplace participation, Paul Shafer and colleagues (this issue, 2020 ) use a county fixed-effects model to control for underlying differences across counties. They find that when more health-insurance-related ads sponsored by states are aired, enrollment increases, as it does, somewhat surprisingly, when more pro-Republican political ads that mention health care are aired (although this result is driven by a few locales where off-year gubernatorial contests or early federal primary elections were held). Other types of ads, including federal ads not dealing with Medicare, private ads, and pro-Democrat health-care-related political ads, do not show statistically significant correlations with enrollment, suggesting that both the volume and source of advertising matters for Marketplace participation, and that private-source advertising lacks the positive effect of state-sponsored advertising.

Yet other scholars examine the effects of elite rhetoric on public opinion. As noted, as elite rhetoric stabilized during the 2009 and 2010 health reform debate, public opinion became less volatile (Kriner and Reeves 2014 ). A comparison of word choice in senators’ press releases and in open-ended survey questions of the public during the debate reveals that elite framing did not appear to change public opinion but did influence the words and arguments members of the public used in explaining their ACA attitudes, the public adopting both Republican and Democratic rhetoric as debate ensued (Hopkins 2018 ). Last is the question of whether elite action, as opposed to rhetoric, can influence public opinion. One study of policy diffusion found that pro-ACA gubernatorial announcements in one state increased public support for the ACA in nearby states, a pattern the authors term “policy spillover” (Pacheco and Maltby 2017 ).

Julianna Pacheco, Haselswerdt, and Jamila Michener (this issue, 2020 ) provide another example of state policy choice and partisanship influencing public opinion (see also Pacheco and Maltby 2019 ). The authors estimate support for the ACA at the state level by quarter between 2009 and 2016, and find that differences between Republicans and Democrats in ACA attitudes are greatest in states in which Democratic governors established state-run health insurance exchanges. In the few states where Republican governors did the same, polarization in support by party identification is less, though the evidence is less clear. They conclude that attitudinal polarization is greater where state ACA policy choices are “aligned”—that is, where Democratic governors implemented the law—and more modest in the presence of greater “misalignment”—elite decision making that cuts across partisanship.

Finally, attitudes toward existing policies may become more positive in the face of political threat. Sances and Clinton (2019b) pool a large number of surveys from 2009 through 2017 and find that approval of the ACA is 1.3 percentage points higher in Medicaid expansion states than in non-expansion states, though this effect is apparent only after the 2016 election, when unified Republican control of the federal government made the threat of repeal more credible. The largest increase in approval was among lower-education non-senior adults, the expansion’s target population. They also find that support for repealing the ACA is 2 points lower in Medicaid expansion states than in non-expansion states, beginning immediately after ACA implementation commenced and corresponding to the well-established asymmetry of gains and losses (Kahnemann and Tversky 1979 ).

• CONCLUSION: QUESTIONS NEEDING FURTHER RESEARCH

The largest expansion of social policy in more than a generation, the Affordable Care Act has garnered a great deal of attention from scholars, as both this review and the articles in this issue attest. However, much work remains to be done in exploring its economic, political, and social effects. Some of this work will become more feasible as more data become available; more will emerge as longer-term effects come to fruition. We also hope to see more work based on qualitative methodologies such as ethnographic fieldwork and interviews added to the results reviewed here, which have largely been based on administrative data, survey data, and field experiments.

As we searched for extant social science research on the ACA, we identified a number of areas where interesting questions appear to be unaddressed thus far. Having noted some apparent lacunae at various points, we pose additional questions here in the hope of inspiring continuing research. Many of these questions arise because of uncertainty in the policy environment or differences between the ACA as written and as implemented, although others would have arisen even had the ACA been more broadly welcomed across the political and social spectrum.

We have noted throughout that much of the research about the ACA’s effects on individuals and families—whether on economic and financial outcomes or on political behaviors or attitudes—has examined the effects of the Medicaid expansion. Although a crucial part of the law and a component lending itself to quasi-experimental analyses, the Medicaid expansion was not the only provision affecting individuals’ financial security. Research is still needed on the effects of other components of the ACA that affect the cost and availability of health insurance, such as cost-sharing subsidies or the rating rules.

Some of the questions arising from the uncertain federal policy environment concern state responses: how are states responding to federal decisions such as approval of work requirements and other previously denied Medicaid waivers, the elimination of cost-sharing reduction payments to insurers, approval of association health plans and short-term insurance plans with narrower benefits, and how are these state decisions affecting individual well-being? Given the repeated unsuccessful attempts to repeal the law entirely and journalistic accounts of rising public support for it, more work is needed on the development of such support. To what extent are constituencies being mobilized to defend the ACA, and by whom? To what extent are new advocacy groups forming or existing groups redeploying resources or adopting new strategies to combat challenges to the law? How does the COVID-19 pandemic alter politics around ACA support or retrenchment? Other questions surrounding the uncertain policy environment concern individual outcomes: what are the effects on enrollment and other individual outcomes of changes such as reduced federal funding for advertising and for navigators or shortened enrollment periods? Last are questions about how the portions of the ACA focused on reducing health-care expenditures have been affected by policy uncertainty; for example, how has the policy environment affected what can be learned from accountable care organizations and other demonstration projects?

Some of the unaddressed questions are largely unrelated to issues of policy uncertainty but arise because of the far-reaching nature of the ACA or the structure of its provisions. One important question that has received less attention from researchers than we were expecting is how the ACA has affected measures of inequality, including income, earnings, or wealth. The ACA’s insurance provisions are implicitly redistributive, but little is known about the distributional consequences of various provisions of the ACA. We also know little about how much freedom of choice low-income people have among insurance plans and health-care providers and what the implications are for their health-care access, financial security, and feelings toward the reform and government, given that low premiums have generally been attached to narrow networks of providers. In addition, as time goes on, it will become possible to assess the downstream effects of change in one health insurance arena on another. For example, if private insurance premiums fall where Medicaid expands, will there be increased budgetary pressure on Medicaid given that the shift implies adverse risk selection into Medicaid? Another area with surprisingly little research is the effect of the ACA on employment, safety net participation, and other outcomes for various vulnerable populations, including immigrants and families with mixed immigration status, early retirees, and the unemployed. Other questions are largely unexamined: What are the economic, social, and political effects of the various public health interventions contained in the ACA, a question made particularly pertinent by the COVID-19 pandemic? To what extent and how has the implementation of the ACA affected nongovernmental providers of social services?

Although we describe the results from some research on employer behavior, many questions about how firms have responded to the ACA remain unaddressed: To what extent have firms and nonprofits altered their business models, patterns of lobbying, and enterprise investment decisions in light of the ACA? How have small employers been affected by the changes in the small-group insurance market? How have large employers changed their practices in response to regulations in the ACA? Also largely uninvestigated is the nature of the interaction between the ACA and another statute affecting employee benefits, the Employee Retirement Income Security Act of 1974 (ERISA). Because self-insured employer plans fall under ERISA’s jurisdiction, they are not subject to state insurance regulation, but the ACA exempted ERISA plans from some of its requirements, leaving regulatory boundaries unclear. As Gluck, Allison Hoffman, and Peter Jacobson ( 2017 ) point out, unclear boundaries between ERISA’s jurisdiction and the portions of the ACA devolving regulatory authority to the states raises difficulties for states in using their regulatory authority to implement state-specific health reforms. Gluck, Hoffman, and Jacobson give as an example Gobeille v. Liberty Mutual Insurance Co. , in which the Supreme Court ruled that ERISA preempted Vermont’s ability to require ERISA plans to participate in an all-payer claims database. 2 Another issue raised by ERISA-ACA interactions is the ACA’s exemption of self-insured ERISA plans from needing to cover “essential health benefits” as required of fully insured small-group (fewer than fifty employees) plans, an exemption that Corlette and colleagues ( 2017 ) note in their description of changes in small-group markets in six states has led some small employers to move toward self-insured plans.

The excellent articles in this issue expand our social scientific knowledge of the economic, social, and political effects of the Affordable Care Act. Just as earlier important social policy reforms have done, we fully expect the ACA to prompt new research for years to come.

↵ 1. National Federation of Independent Business v. Sebelius, 567 US 519 (2012).

↵ 2. Gobeille v. Liberty Mutual Insurance Co., 577 U.S. __ (2016).

• © 2020 Russell Sage Foundation. Campbell, Andrea Louise, and Lara Shore-Sheppard. 2020. “The Social, Political, and Economic Effects of the Affordable Care Act: Introduction to the Issue.” RSF: The Russell Sage Foundation Journal of the Social Sciences 6(2): 1–40. DOI: 10.7758/RSF.2020.6.2.01. Direct correspondence to: Andrea Louise Campbell at acampbel{at}mit.edu , Department of Political Science, Massachusetts Institute of Technology, 77 Massachusetts Ave., E53-489, Cambridge, MA 02139; and Lara Shore-Sheppard at lshore{at}williams.edu , Department of Economics, Williams College, 24 Hopkins Hall Drive, Williamstown, MA 01267.

Open Access Policy: RSF: The Russell Sage Foundation Journal of the Social Sciences is an open access journal. This article is published under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

• Aaron , Henry , and
• Gary Burtless
• Abraham , Jean Marie
• Abraham , Jean M .,
• Coleman Drake ,
• Jeffrey S . McCullough , and
• Kosali Simon
• Abraham , Jean ,
• Anne B . Royalty , and
• Coleman Drake
• Abraham , Jean
• Abramowitz , Joelle
• Akosa Antwi , Yaa ,
• Asako S . Moriya , and
• Asako S . Moriya ,
• Kosali Simon , and
• Benjamin D . Sommers
• Allen , Heidi ,
• Ashley Swanson ,
• Jialan Wang , and
• American Public Health Association
• Anand , Priyanka ,
• Jody Schimmel Hyde ,
• Maggie Colby , and
• Paul O’Leary
• Antonisse , Larisa ,
• Rachel Garfield ,
• Robin Rudowitz , and
• Samantha Artiga
• Assistant Secretary for Planning and Evaluation (ASPE)
• Bailey , James , and
• Anna Chorniy
• Barbaresco , Silvia ,
• Charles J . Courtemanche , and
• Barnett , Michael L .,
• Kathryn L . Clark , and
• Barrilleaux , Charles , and
• Carlisle Rainey
• Beauregard , Lisa Kalimon , and
• Edward Alan Miller
• Blais , André
• Blavin , Fredric
• Blavin , Fredric ,
• Adele Shartzer ,
• Sharon K . Long , and
• John Holahan
• Blumberg , Linda J .,
• Bowen Garrett , and
• Blumenthal , David ,
• Melinda Abrams , and
• Rachel Nuzum
• Boutwell , Amy E ., and
• Jonathan Freedman
• Breslau , Joshua ,
• Bradley D . Stein ,
• Shoshanna Shelton , and
• Brevoort , Kenneth ,
• Daniel Grodzicki , and
• Martin B . Hackmann
• Brooks , Tricia ,
• Lauren Roygardner , and
• Buchmueller , Thomas ,
• John C . Ham , and
• Lara D . Shore-Sheppard
• Buchmueller , Thomas C .,
• Helen Levy , and
• Robert G . Valetta
• Burden , Barry C .,
• Jason M . Fletcher ,
• Pamela Herd ,
• Donald P . Moynihan , and
• Bradley M . Jones
• Callaghan , Timothy , and
• Lawrence R . Jacobs
• Camilleri , Susan
• Campbell , Andrea Louise
• Caswell , Kyle J ., and
• Timothy A . Waidmann
• Chait , Nadia , and
• Sherry Glied
• Chatterji , Pinka ,
• Peter Brandon , and
• Sara Markowitz
• Chatterji , Pinka , and
• Chattopadhyay , Jacqueline
• Citrin , Jack , and
• Donald P . Green
• Claxton , Gary , and
• Larry Levitt
• Clinton , Joshua D ., and
• Michael W . Sances
• Cole , Megan B .,
• Brad Wright ,
• Ira B . Wilson ,
• Omar Galarraga , and
• Amal N . Trivedi
• Colman , Gregory , and
• Dhaval Dave
• Congressional Budget Office
• Conlan , Timothy , and
• Paul Posner
• Corlette , Sabrina ,
• Jack Hoadley ,
• Kevin Lucia , and
• Dania Palanker
• Corlette , Sabrina , and
• Rachel Schwab
• Cotti , Chad ,
• Erik Nesson , and
• Nathan Tefft
• Courtemanche , Charles ,
• James Marton ,
• Benjamin Ukert ,
• Aaron Yelowitz , and
• Daniela Zapata
• Courtemanche , Charles
• James Marton , and
• Aaron Yelowitz
• Cox , Cynthia ,
• Larry Levitt , and
• Gary Claxton
• Curran , Emily
• Dafny , Leemore ,
• Jonathan Gruber , and
• Christopher Ody
• Dafny , Leemore S .,
• Igal Hendel ,
• Victoria Marone , and
• De La O , Ana L
• Decker , Sandra L.
• DeNavas-Walt , Carmen ,
• Bernadette D . Proctor , and
• Jessica C . Smith
• Dickstein , Michael J .,
• Mark Duggan ,
• Joe Orsini , and
• Pietro Tebaldi
• Dorn , Stan ,
• Sarah Minton , and
• Erika Huber
• Dranove , David ,
• Craig Garthwaite , and
• Duggan , Mark ,
• Gopi Shah Goda , and
• Emilie Jackson
• Atul Gupta , and
• Enroll America
• Even , William E. , and
• David A . Macpherson
• Fehr , Rachel ,
• Cynthia Cox , and
• Fehr , Rachel
• Fording , Richard C ., and
• Dana Patton
• Fowler , Erika Franklin ,
• Jeff Niederdeppe ,
• Colleen L . Barry , and
• Sarah E . Gollust
• Frean , Molly ,
• Frisvold , David E ., and
• Younsoo Jung
• Fry , Carrie E .,
• Thomas G . McGuire , and
• Richard G . Frank
• Galvin , Daniel J ., and
• Chloe N . Thurston
• Ganguli , Ishani ,
• Jeffrey Souza , and
• J. Michael McWilliams
• Garrett , Bowen ,
• Robert Kaestner , and
• Anuj Gangopadhyaya
• Ghosh , Ausmita ,
• Glied , Sherry , and
• Adam Striar
• Gluck , Abbe R .,
• Allison K . Hoffman , and
• Peter D . Jacobson
• Gluck , Abbe R. , and
• Nicole Huberfeld
• Gollust , Sarah E .,
• Colleen L . Barry ,
• Laura Baum , and
• Erika Franklin Fowler
• Gollust , Sarah E ., and
• Wendy M . Rahn
• Andrew Wilcock ,
• Erika Franklin Fowler ,
• Pinar Karaca-Mandic
• Goodell , Sarah
• Goodman , Lucas
• Gooptu , Angshuman ,
• Kosali I . Simon , and
• Gore , Radhika ,
• Ritu Dhar ,
• Sadia Mohaimin ,
• Priscilla M . Lopez ,
• Anna A . Divney ,
• Jennifer M . Zanowiak ,
• Lorna E . Thorpe , and
• Nadia Islam
• Gose , Leah , and
• Theda Skocpol
• Grabowski , David C .,
• Nina R . Joyce ,
• Griffith , Kevin ,
• Leigh Evans , and
• Grogan , Colleen M ., and
• Sunggeun Ethan Park
• Guterman , Stuart ,
• Laura Skopec , and
• Stephen Zuckerman
• Gutierrez , Carmen M
• Haeder , Simon F ., and
• David L . Weimer
• Hagan , Elizabeth
• Hall , Mark A
• Hampton , J. Matthew , and
• Otto Lenhart
• Han , Xinxin ,
• Qian Luo , and
• Leighton Ku
• Haselswerdt , Jake
• Haselswerdt , Jake , and
• Jamila Michener
• Heim , Bradley ,
• Ithai Lurie , and
• Heim , Bradley
• Heisler , Elayne J
• Henderson , Michael , and
• D. Sunshine Hillygus
• Herring , Bradley , and
• Lisa Korin Lentz
• Hinde , Jesse M
• Ho , Kate , and
• Robin S . Lee
• Hobbs , William R ., and
• Daniel J . Hopkins
• Hopkins , Daniel J
• Hopkins , Daniel J ., and
• Kalind Parish
• Hosek , Adrienne
• Hu , Luojia ,
• Robert Kaestner ,
• Bhashkar Mazumder ,
• Sarah Miller , and
• Ashley Wong
• Jacobs , Alan M ., and
• R. Kent Weaver
• Jacobs , Lawrence R ., and
• Timothy Callaghan
• Suzanne Mettler
• Jacobs , Lawrence R
• Jacobs , Lawrence R. , and
• Jones , David K
• Jones , David K .,
• Katharine W. V . Bradley , and
• Jonathan Oberlander
• Kaestner , Robert ,
• Bowen Garrett ,
• Jiajia Chen ,
• Anuj Gangopadhyaya , and
• Caitlyn Fleming
• Kahneman , Daniel , and
• Amos Tversky
• Kaiser Family Foundation
• Keith , Katie
• Kelly , Andrew S
• Kennedy , Jae , and
• Elizabeth Blodgett
• Kliff , Sarah
• Kriner , Douglas L ., and
• Andrew Reeves
• Kucko , Kavan ,
• Kevin Rinz , and
• Benjamin Solow
• Kusnetz , Nicholas
• Lerman , Amy E ., and
• Katherine T . McCabe
• Lerman , Amy E .,
• Meredith L . Sadin , and
• Samuel Trachtman
• Leung , Pauline , and
• Alexandre Mas
• Levy , Helen ,
• Thomas Buchmueller , and
• Sayeh Nikpay
• Andrew Ying , and
• Nicholas Bagley
• Lewis , Corinne ,
• Akeiisa Coleman ,
• Melinda K . Abrams , and
• Michelle M . Doty
• Lindrooth , Richard C .,
• Marcelo C . Perraillon ,
• Rose Y . Hardy , and
• Gregory J . Tung
• Lissenden , Brett
• Lowry , Sean
• Maclean , Johanna Catherine , and
• Brendan Saloner
• McCabe , Katherine T
• McKenna , Ryan M .,
• Brent A . Langellier ,
• Héctor E . Alcalá ,
• Dylan H . Roby ,
• David T . Grande , and
• Alexander N . Ortega
• Meinhofer , Angélica , and
• Allison E . Witman
• Mettler , Suzanne
• Meyer , David S ., and
• Sidney Tarrow
• Michener , Jamila
• Miller , Sarah , and
• Laura R . Wherry
• Morgan , Kimberly J ., and
• Andrea Louise Campbell
• Moriya , Asako S .,
• Thomas M . Selden , and
• Kosali I . Simon
• William B . Vogt , and
• Martin Gaynor
• Mosqueira , Adrian Garcia ,
• Lynn M . Hua , and
• Nadash , Pamela ,
• Edward Alan Miller ,
• David K . Jones ,
• Michael K . Gusmano , and
• Sara Rosenbaum
• National Academies of Sciences, Engineering, and Medicine
• Neprash , Hannah T .,
• Anna Zink ,
• Joshua Gray , and
• Katherine Hempstead
• Nikpay , Sayeh ,
• Thomas Buchmueller ,
• Simone R . Singh
• Obama , Barack
• Ortega , Alexander N .,
• Hector P . Rodriguez , and
• Arturo Vargas Bustamante
• Pacheco , Julianna , and
• Jason Fletcher
• Pacheco , Julianna ,
• Jake Haselswerdt , and
• Elizabeth Maltby
• Pacheco , Julianna
• Parente , Stephen T .,
• Roger Feldman ,
• Joanne Spetz ,
• Bryan Dowd , and
• Emily Egan Baggett
• Patashnik , Eric M ., and
• Julian E . Zelizer
• Pearson , Caroline F .,
• Elizabeth Carpenter , and
• Chris Sloan
• Peng , Lizhong
• Peng , Lizhong ,
• Xiaohui Guo , and
• Chad D . Meyerhoefer
• Pickens , Gary ,
• Zeynal Karaca ,
• Eli Cutler , ,
• Michael Dworsky ,
• Christine Eibner ,
• Brian Moore ,
• Teresa Gibson ,
• Sharat Iyer , and
• Herbert S . Wong
• Pierson , Paul
• Pines , Jesse M .,
• Mark Zocchi ,
• Ali Moghtaderi ,
• Bernard Black ,
• Steven A . Farmer ,
• Greg Hufstetler ,
• Kevin Klauer , and
• Randy Pilgrim
• Pollitz , Karen ,
• Jennifer Tolbert , and
• Polsky , Daniel ,
• Zuleyha Cidav , and
• Ashley Swanson
• Remler , Dahlia K .,
• Sanders D . Korenman , and
• Rosemary T . Hyson
• Rich , Josiah D .,
• Sarah E . Wakeman , and
• Samuel L . Dickman
• Rigby , Elizabeth
• Rigby , Elizabeth , and
• Jake Haselswerdt
• Rocco , Philip , and
• Andrew S . Kelly
• Rosenbaum , Sara
• Rosenstone , Steven J ., and
• John Mark Hansen
• Runnels , Laura ,
• Kate Heyer ,
• Courtney Armstrong ,
• Malcolm V . Williams , and
• Laurie T . Martin
• Sahasranaman , Vanita
• Sances , Michael W ., and
• Joshua D . Clinton
• Sances , Michael W
• Sanger-Katz , Margot
• Scheuer , Florian , and
• Kent Smetters
• Schmidt , Lucie ,
• Lara D . Shore-Sheppard , and
• Tara Watson
• Schmidt , Lucie
• Selden , Thomas M .,
• Brady J . Lipton , and
• Sandra L . Decker
• Sen , Aditi P .,
• Lena M . Chen ,
• Donald F . Cox , and
• Arnold Epstein
• Sen , Aditi P ., and
• Thomas DeLeire
• Shafer , Paul R .,
• David M . Anderson ,
• Seciah M . Aquino ,
• Laura M . Baum ,
• Erika Franklin Fowler , and
• Sharma , Leena
• Shartzer , Adele ,
• Fredric Blavin , and
• Shor , Boris
• Simon , Kosali ,
• Aparna Soni , and
• John Cawley
• Slusky , David J. G
• Slusky , David J. G. , and
• Donna Ginther
• Sommers , Benjamin D .,
• Munira Z . Gunja ,
• Kenneth Finegold , and
• Thomas Musco
• Bethany Maylone ,
• Robert J . Blendon ,
• E. John Orav , and
• Arnold M . Epstein
• Soni , Aparna ,
• Marguerite E . Burns ,
• Laura Dague , and
• Soss , Joe , and
• Sanford F . Schram
• Stein , Jeff L
• Tesler , Michael
• Thompson , Frank J .,
• Shugo Shinohara
• U.S. Census Bureau
• Verba , Sidney ,
• Kay Lehman Schlozman , and
• Henry E . Brady
• Volden , Craig
• Warshawsky , Mark J ., and
• Michael Leahy
• Weil , Alan , and
• Raymond Scheppach
• Wherry , Laura R ., and
• Sarah Miller
• Williams , Malcolm V .,
• Laurie T . Martin ,
• Nazleen Bharmal ,
• Julia Joh Elligers ,
• Laura Runnels ,
• Kate Heyer , and
• Christian Lopez
• Zewde , Naomi , and
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In contrast to many earlier crises, the onset of the pandemic was met with a large, decisive economic policy response that was generally successful in mitigating its worst human costs in the short run. However, the emergency response also created new risks—such as dramatically increased levels of private and public debt in the world economy—that may threaten an equitable recovery from the crisis if they are not addressed decisively.

Worsening inequality within and across countries

The economic impacts of the pandemic were especially severe in emerging economies where income losses caused by the pandemic revealed and worsened some preexisting economic fragilities. As the pandemic unfolded in 2020, it became clear that many households and firms were ill-prepared to withstand an income shock of that scale and duration. Studies based on precrisis data suggest, for example, that more than 50 percent of households in emerging and advanced economies were not able to sustain basic consumption for more than three months in the event of income losses . 2 Similarly, the average business could cover fewer than 55 days of expenses with cash reserves . 3  Many households and firms in emerging economies were already burdened with unsustainable debt levels prior to the crisis and struggled to service this debt once the pandemic and associated public health measures led to a sharp decline in income and business revenue.

The crisis had a dramatic impact on global poverty and inequality. Global poverty increased for the first time in a generation, and disproportionate income losses among disadvantaged populations led to a dramatic rise in inequality within and across countries. According to survey data, in 2020 temporary unemployment was higher in 70 percent of all countries for workers who had completed only a primary education. 4   Income losses were also larger among youth, women, the self-employed, and casual workers with lower levels of formal education . 5   Women, in particular, were affected by income and employment losses because they were likelier to be employed in sectors more affected by lockdown and social distancing measures . 6

Similar patterns emerge among businesses. Smaller firms, informal businesses, and enterprises with limited access to formal credit were hit more severely by income losses stemming from the pandemic. Larger firms entered the crisis with the ability to cover expenses for up to 65 days, compared with 59 days for medium-size firms and 53 and 50 days for small and microenterprises, respectively. Moreover, micro-, small, and medium enterprises are overrepresented in the sectors most severely affected by the crisis, such as accommodation and food services, retail, and personal services.

The short-term government responses to the crisis

The short-term government responses to the pandemic were extraordinarily swift and encompassing. Governments embraced many policy tools that were either entirely unprecedented or had never been used on this scale in emerging economies. Examples are large direct income support measures, debt moratoria, and asset purchase programs by central banks. These programs varied widely in size and scope (figure 1.1), in part because many low-income countries were struggling to mobilize resources given limited access to credit markets and high precrisis levels of government debt. As a result, the size of the fiscal response to the crisis as a share of the gross domestic product (GDP) was almost uniformly large in high-income countries and uniformly small or nonexistent in low-income countries. In middle-income countries, the fiscal response varied substantially, reflecting marked differences in the ability and willingness of governments to spend on support programs.

Figure 1.1 Fiscal response to the COVID-19 crisis, selected countries, by income group

Similarly, the combination of policies chosen to confront the short-term impacts differed significantly across countries, depending on the availability of resources and the specific nature of risks the countries faced (figure 1.2). In addition to direct income support programs, governments and central banks made unprecedented use of policies intended to provide temporary debt relief, including debt moratoria for households and businesses. Although these programs mitigated the short-term liquidity problems faced by households and businesses, they also had the unintended consequence of obscuring the true financial condition of borrowers, thereby creating a new problem: lack of transparency about the true extent of credit risk in the economy.

Figure 1.2 Fiscal, monetary, and financial sector policy responses to the COVID-19 crisis, by country income group 

The large crisis response, while necessary and effective in mitigating the worst impacts of the crisis, led to a global increase in government debt that gave rise to renewed concerns about debt sustainability and added to the widening disparity between emerging and advanced economies. In 2020, 51 countries—including 44 emerging economies—experienced a downgrade in their government debt risk rating (that is, the assessment of a country’s creditworthiness) . 7

Emerging threats to an equitable recovery

Although households and businesses have been most directly affected by income losses stemming from the pandemic, the resulting financial risks have repercussions for the wider economy through mutually reinforcing channels that connect the financial health of households, firms, financial institutions, and governments (figure 1.3). Because of this interconnection, elevated financial risk in one sector can spill over and destabilize the economy as a whole. For example, if households and firms are under financial stress, the financial sector faces a higher risk of loan defaults and is less able to provide credit. Similarly, if the financial position of the public sector deteriorates (for example, as a result of higher government debt and lower tax revenue), the ability of the public sector to support the rest of the economy is weakened.

Figure 1.3 Conceptual framework: Interconnected balance sheet risks

This relationship is, however, not predetermined. Well-designed fiscal, monetary, and financial sector policies can counteract and reduce these intertwined risks and can help transform the links between sectors of the economy from a vicious doom loop into a virtuous cycle.

One example of policies that can make a critical difference are those targeting the links between the financial health of households, businesses, and the financial sector. In response to the first lockdowns and mobility restrictions, for example, many governments supported households and businesses using cash transfers and financial policy tools such as debt moratoria. These programs provided much-needed support to households and small businesses and helped avert a wave of insolvencies that could have threatened the stability of the financial sector.

Similarly, governments, central banks, and regulators used various policy tools to assist financial institutions and prevent risks from spilling over from the financial sector to other parts of the economy. Central banks lowered interest rates and eased liquidity conditions, making it easier for commercial banks and nonbank financial institutions such as microfinance lenders to refinance themselves, thereby allowing them to continue to supply credit to households and businesses.

The crisis response will also need to include policies that address the risks arising from high levels of government debt to ensure that governments preserve their ability to effectively support the recovery.   This is an important policy priority because high levels of government debt reduce the government’s ability to invest in social safety nets that can counteract the impact of the crisis on poverty and inequality and provide support to households and firms in the event of setbacks during the recovery. 

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What Is Political Economy?

Understanding political economy.

• History and Development

Political Economy in Academia

• Modern Applications

The Bottom Line

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Political Economy Definition, History, and Applications

Political economy is an interdisciplinary branch of the social sciences. It focuses on the interrelationships of individuals, governments, and public policy.

Political economists study how economic theories such as capitalism , socialism , and communism work in the real world. Any economic theory is a means of directing the distribution of a finite amount of resources in a way that benefits the greatest number of individuals.

These ideas can be studied both theoretically and as they are actually used. Public policy that is created and implemented derive from these economic theories. Political economists study both the underlying roots of these policies and their results.

Key Takeaways

• The field of political economy involves the study of how economic theories such as capitalism or communism play out in the real world.
• As political parties come to and leave power, economic policy often changes due to the ideology and goals of the party in power.
• Those who study political economy seek to understand how history, culture, and customs impact an economic system, and vice versa.
• Global political economy studies how political forces shape global economic interactions.
• The rise of globalism and global trade means that political economy of one country can impact both the economy and the politics of others.

Investopedia / Zoe Hansen

Political economy is a branch of social science that studies the relationship that forms between a nation's population and its government when public policy is enacted. It is, therefore, the result of the interaction between politics and the economy and is the basis of the social science discipline.

Those who research the political economy are called political economists. Their study generally involves the examination through a sociological, political, and economic lens of how public policy, the political situation, and political institutions impact a country's economic standing and future.

In a wider sense, political economy was once the common term used for the field we now call economics . Adam Smith, John Stuart Mill, and Jean-Jacques Rousseau all used the term to describe their theories. The shorter term "economy" was substituted in the early 20th century with the development of more rigorous statistical methods for analyzing economic factors.

Types of Political Economy

There are several notable types of political economies:

• Socialism: This type of political economy promotes the idea that the production and distribution of goods and wealth are maintained and regulated by society, rather than a particular group of people. The rationale behind this is that whatever is produced by society is done so because of those who participate, regardless of status, wealth , or position. Socialism aims to bridge the gap between rich and poor, eliminating the ability of individuals or groups to control the majority of power and wealth.
• Capitalism: This theory advocates profit as a motive for advancement and the ability of free markets to regulate and drive the economy on their own. The idea behind capitalism is that private individuals and entities are driven by their own interests—they control production and distribution, set prices, and create supply and demand .
• Communism: Individuals often confuse communism with socialism, but there is a distinct difference between these two theories. Communism was a theory developed by Karl Marx , who felt that capitalism was limited and created a big divide between rich and poor. He believed in shared resources, including property. Unlike socialism, however, under communism production and distribution are overseen by the government.

Political economy may draw upon sociology, economics, and political science to define how government, an economic system, and politics influence each other.

History and Development of Political Economy

The roots of political economy as we know it today go back to the 18th century. Scholars during the period studied how wealth was distributed and administered between people. Some of the earlier works that examined this phenomenon include those by Adam Smith and John Stuart Mill .

Antoine de Montchrestien

But the term is probably best ascribed to the French writer and economist, Antoine de Montchrestien. He wrote a book called "Traité de l'économie politique" in 1615, in which he examined the need for production and wealth to be distributed on an entirely larger scale—not in the household as Aristotle suggested. The book also analyzed how economics and politics are interrelated.

Smith was a Scottish philosopher, economist, and writer who is commonly referred to as the father of economics and of the political economy. He wrote about the function of a self-regulating free market in his first book, which was called "The Theory of Moral Sentiments." His most famous work, "An Inquiry into the Nature and Causes of the Wealth of Nations" (or " The Wealth of Nations ," for short) helped shape classical economic theory. It was considered the foundation for the field of study by future economists.

John Stuart Mill

The Englishman Mill combined economics with philosophy. He believed in utilitarianism —that actions that lead to people's goodwill are right and that those that lead to suffering are wrong. In essence, he believed that economic theory and philosophy were needed, along with social awareness in politics, to make better decisions for the good of the people. Some of his work, including "Principles of Political Economy, Utilitarianism," and "A System of Logic" made him one of the most important figures in politics and economics.

Importance of Political Economy

Political economy studies both how the economy affects politics and how politics affect the economy . As political parties come to and leave power, economic policy often changes in a country in accordance with the ideology and goals of the party in power.

Political changes can impact many areas of the economy, which can in turn impact elections and government policies. These areas include:

• Monetary and fiscal policy
• Food security
• Global trade
• Labor supply, demand, and crises
• Gross domestic product (GDP)
• Financial inequality
• Disaster management
• Environmental stability

As the economies of more countries become interconnected through globalism and international trade, the politics of one country can have a strong impact on the economy of another. Understanding the relationship between political power and economic decisions in one country can help other countries predict how their own economies will be impacted.

Understanding political economy can also help a country's economy become more resilient. If the government leaders in power at any given moment are forward-thinking, they can try to put laws and policies in place that create the greatest possibility for economic stability and growth, regardless of changing political power.

Political economy is still a widely used term that describes any government policy that has an economic impact.

Political economy has become an academic discipline of its own. Many major institutions offer the study as part of their political science, economics, and sociology departments.

Political economists conduct research to determine how public policy influences behavior, productivity, and trade. This work helps them establish how money and power are distributed between people and different groups. They may study specific fields such as law, bureaucratic politics, legislative behavior, the intersection of government and business, and regulation.

The study may be approached in any of three ways:

• Interdisciplinary studies: The interdisciplinary approach draws on sociology, economics, and political science to define how government institutions, an economic system, and a political environment affect and influence each other.
• New political economy: This approach studies actions and beliefs, and seeks to make explicit assumptions that lead to political debates about societal preferences. The new political economy combines the ideals of classical political economists and newer analytical advances in economics and politics.
• International political economy: Also called global political economy, which is slightly different, this approach analyzes the link between economics and international relations. It draws from many academic areas including political science, economics, sociology, cultural studies, and history. The international political economy concerns how political forces like states, individuals, and institutions affect global economic interactions.

Modern Applications of Political Economy

Modern applications of the political economy involve the study of later philosophers and economists, such as Karl Marx.

As mentioned above, Marx became disenchanted with capitalism as a whole. He believed that individuals suffered under regimented social classes, where one or more individuals controlled the greater proportion of wealth.

Under communist theories, this would be eradicated, allowing everyone to live equally while the economy functions based on the ability and needs of each participant. Under communist regimes, resources are controlled and distributed by the government.

Socialism vs. Communism

Many people confuse socialism and communism. It's true there are some similarities—notably, that both stress bridging the gap between rich and poor, and that society should relegate equilibrium among all citizens.

But there are inherent differences between the two. While resources in a communist society are owned and controlled by the government, individuals in a socialist society hold property. People can still purchase goods and services under socialism, while those who live in a communist society are provided with their basic necessities by the government.

What Does Political Economy Mean?

The term "political economy" refers to a branch of social sciences that focuses on relationships between individuals, governments, and public policy. It is also used to describe the policies set by governments that affect their nations' economies.

What Is the Primary Concern of Political Economy?

The main concerns of political economy are the relationship between governments and individuals, and how public policy affects society. These are determined through the study of sociology, politics, and economics.

What Are the Characteristics of Political Economy?

Some of the characteristics or themes of a political economy include the distribution of wealth, how goods and services are produced, who owns property and other resources, who profits from production, supply and demand, and how public policy and government interaction impact society.

Who Coined the Term "Political Economy"?

Adam Smith is generally considered the father of economics and of the political economy. But the term is generally ascribed to French economist Antoine de Montchrestien, who wrote the book "Traité de l'économie politique," which translates to the treaty of the political economy.

Political economy is a branch of the social sciences that studies the relationships between individuals, governments, and public policy. It examines how the realm of politics impacts the economy and how the economy impacts politics.

As political parties change, a country's economic policy often changes as well, based on the ideology and goals of the party in power. This can impact areas of the economy such as monetary and fiscal policy, food security, labor crises, rising inequality, GDP, and disaster management. These changes in the economy can in turn prompt new political laws, policies, or election outcomes.

The rise of globalism and international trade means that the politics of one country can have a strong impact on the economy of another. Understanding political economy can help countries become more resilient in the face of global economic changes.

Oxford Bibliographies. " Political Economy ."

Paganelli, Maria Pia. "Adam Smith and the Origins of Political Economy,"  Social Philosophy and Policy , vol. 37, no. 1, 2020, pp. 159–169.

International Relations and Security Network. " A Discourse on Political Economy ."

John Mill. "Principles of Political Economy." Longmans, Green, and Company, 1848.

Shleifer, Andrei, and Robert W. Vishny. "The Politics of Market Socialism,"  Journal of Economic Perspectives , vol. 8, no. 2, 1994, pp. 165-176.

International Monetary Fund. " What Is Capitalism? "

The University of North Carolina at Chapel Hill. " Communism: Karl Marx to Joseph Stalin ."

Adam Smith Institute. " The Wealth of Nations ."

Nicholas Capaldi. "John Stuart Mill: A Biography." Cambridge University Press, 2004.

Joseph Garnier. "Notes et Petits Traités Faisant Suite aux Eléments de L'economie Politique." Garnier frères, 1858.

Internet Encyclopedia of Philosophy. " Adam Smith (1723—1790) ."

International Monetary Fund. " The Political Economy of Economic Policy ."

Harvard University. " Political Economy ."

Stanford Business. " Political Economics ."

The College of New Jersey. " Interdisciplinary Concentration in International Political Economy ."

Oxford Research Encyclopedia. " International Political Economy: Overview and Conceptualization ."

Hampton Roads Naval Museum. " Socialism, Fascism, Capitalism, and Communism Chart ."

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AP World History: Modern Sample Long Essay Question

In the period 1850 to 2001, new technologies emerged that had significant social, political, and economic effects. Develop an argument that evaluates the extent to which changes in the spread of ideas/information before and after World War I impacted societies.

Step 1: Analyze the Prompt

As you choose which question you will answer, begin thinking about what your thesis will entail and how your essay will demonstrate a complex understanding. The notes of a sample high- scoring writer are below. Note that the writer plans to develop a complex argument by addressing not only changes, as required by the prompt, but also continuities in societies before and after World War I.

Thesis : changes: faster spread of ideas made news, politics, and war more immersive and fast-paced; continuity: cross-cultural interactions transform all cultures (complex understanding, historical skill)

Step 2: Plan Your Response

• Context : Gutenberg → 2nd industrial revolution (steamship, train, telegraph) → digital revolution (radio, TV, Internet)
• Thesis : changes: faster spread of ideas made news, politics, and war more immersive and fast-paced; continuity: cross-cultural interactions transform all cultures ( complex understanding, historical skill )
• Evidence : War of 1812 versus WWII, Vietnam, Gulf War
• Evidence : American Revolution versus Cold War
• Evidence : language: Arab traders & Swahili, and modern business & English
• ¶ conclusion: impacts of tech on society have become more pervasive, though tendency towards cross-cultural influence has persisted

Step 3: Action! Write Your Response & Step 4: Proofread

Sample high-scoring response.

A key change between these eras of communication is how the speed of ideas’ dissemination impacts their force of impact and makes news more pervasive in civilians’ lives. In the distant past, the slow rate of communication caused reactions that were often months, or even years, after the initial communication. For instance, the final battle of the War of 1812 was fought after the signing of the war’s peace treaty because news had not yet traveled by ship across the Atlantic Ocean. In contrast, the peace treaties of WWII were celebrated in cities around the world mere minutes after news of their signing was shared by telegram and radio signals. The quick spread of images and video from the Vietnam conflict helped intensify Americans’ resistance to the war. In recent decades, 24-hour live coverage of conflicts, as in CNN’s being the first to provide constant coverage of a war during the Gulf War, allowed policy- makers and civilians to respond instantly to developments. As news became quicker, so its impact became more significant and more immediate.

Another change is that the quick and pervasive spread of ideas has made political conflicts more ideological and propaganda-based, further drawing societies into global disputes. Political rebellions of the eighteenth century, such as the American and French Revolutions, were based on Enlightenment ideals such as equality and representative government; they made use of propaganda in the form of printed political cartoons, tracts, and engravings to spread their ideals among the populace. However, the news communication made possible by radio and television after World War II helped propel the ideological conflict between the communist Soviet Union and the democratic United States into a worldwide phenomenon that intensely impacted both nations’ citizens. Technology was able to so effectively spread this war of ideas that the two major superpowers never engaged in direct battle themselves; still, citizens were drawn into a culture of propaganda that demonized the other side, made bomb shelters and bomb drills a part of daily life due to fear of nuclear warfare, and saw governments pour millions of dollars into the space race. Technology thus made it possible for conflicts to become all-immersive, even if they were based on ideas rather than physical confrontations.

Despite changes in communication, constants about its impacts remain. Cross- cultural communications still transform societies as they borrow and adapt ideas from others. For instance, from the eighth century onward, Arab traders who traveled throughout West Africa and along the eastern and northern coasts not only enriched communities economically but also spread Islam. Further, the necessity for communication among traders led to the rise of Swahili, a language that combined Arabic and African words and is still the lingua franca in much of East Africa today. Similarly, in modern times, as Britain and then the United States dominated world trade, English became a kind of worldwide lingua franca of modern business. Just as Arab traders spread their religion, American culture also diffused to other societies: almost every nation in modern times, for instance, built American-style fast food restaurants. Mirroring the trends related to the spread of news and politics, cultural diffusions in recent decades occurred at a faster rate and to a more pervasive extent than in the past. Whereas primarily traders would have adopted Swahili as it developed over generations, today English is taught in grade schools throughout the world.

Cultures that interact always influence each other. In the past century, how- ideas travel at a faster pace. As they have in ever, technology has made the impact of this spread of ideas more pervasive and significant as news and political the past, societies will continue to transform as they encounter ideas from other cultures, but with this increased intensity of communication, the impacts of ideas will continue to escalate.

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The impact of economic, social, and political globalization and democracy on life expectancy in low-income countries: are sustainable development goals contradictory?

• Published: 18 January 2021
• Volume 23 , pages 13508–13525, ( 2021 )

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• Arif Eser Guzel   ORCID: orcid.org/0000-0001-5072-9527 1 ,
• Unal Arslan 1 &
• Ali Acaravci 1  

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The 17 Sustainable Development Goals announced by the United Nations are important guides for the development processes of developing countries. However, achieving all of these goals is only possible if the goals are consistent with each other. It has been observed in the literature that possible contradictions between these goals are ignored. Therefore, the main purpose of this study is to investigate whether two sustainable development goals (SDGs) of the UN are contradictory or supporting each other in low-income countries. These SDGs are “Good Health and Well-Being” (SDG3) and “Partnerships for the Goals” (SDG17). For this purpose, the role of globalization and democracy in life expectancy is empirically investigated in 16 low-income countries over the period 1970–2017. While globalization has been used as an indicator of the partnership between countries, democracy has been used as an indicator of accountability and cooperation between governments and societies. According to estimations of the continuous-updated fully modified (CUP-FM) and bias-adjusted ordinary least squares (BA-OLS), globalization and its subcomponents such as economic, social, and political globalization affect life expectancy positively. Democracy also increases life expectancy in those countries. The GDP per capita is also used as a control variable. Our results show that a higher level of per capita income is positively associated with higher levels of life expectancy. In conclusion, no contradiction was found between SDG3 and SDG17 in those countries. Achieving a healthier society requires economic, social, and political integration between governments and societies.

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1 Introduction

The main problem of economics is to increase economic development and social welfare. Increasing the social welfare level is a complex process that depends on economic and non-economic factors. Achieving economic development or increasing the level of welfare depends on achieving and sustaining the main objectives in political, economic, and social areas. Today, development is no longer a process that can be realized through policies implemented by governments alone. It requires cooperation between governments and societies. While cooperation between different countries requires globalization in the economic, social, and political fields, democracy is the way to ensure cooperation between governments and societies.

Health is one of the most important indicators of social welfare. Besides being one of the indicators of development, it is one of the determinants of human capital formation which is necessary for economic development. Individuals living in developed countries live a healthier life compared to those living in less developed countries. While the differences between the levels of development of countries determine the health conditions, at the same time, improvement of public health paves the way for economic development. Healthy people have higher opportunities to earn a higher income than unhealthy people. Individuals with higher incomes can benefit from better nutrition and access to health services. Therefore, economic development and improvement of health conditions represent a two-way process. In this context, the determination of the variables that will enable the achievement of the goal of a healthier society is especially important in explaining the economic differences between developing countries and developed countries. Because of its importance, health-related goals have an important place both among the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs) announced by the United Nations.

The world leaders with the support of international funding organizations announced the Millennium Declaration in September 2000 at the United Nations Headquarters in New York. They committed their nations to a new international partnership to achieve some development targets having with the final deadline of 2015. The Millennium Development Goals (MDGs) consist of 8 goals, 21 targets, and 60 related indicators covering a wide spectrum of development areas such as “End Poverty and Hunger (MDG 1),” “Universal Education (MDG 2),” “Gender Equality (MDG 3),” “Child Health (MDG 4),” “Maternal Health (MDG 5),” “Combat HIV/AIDS (MDG 6),” “Environmental Sustainability (MDG 7),” and “Global Partnership (MDG 8).” As we see, three of the goals are directly associated with the health status of the people. In the deadline of 2015, according to “Health in 2015: From MDGs to SDGs” report of the World Health Organization (WHO), there are improvements in health-related targets such as child health, maternal health, and combat with HIV/AIDS. Globally, HIV, tuberculosis, and malaria targets have been met. Also, the child mortality rate was reduced by 53% and maternal mortality by 43% (WHO 2016 ). On a global view, although health-related problems are largely resolved, the situation is not as good for low-income countries. As shown in Fig.  1 , significant differences exist between developing countries and developed countries in achieving health-related goals.

Source Halisçelik and Soytas (2015)

World Bank Income Groups’ MDGs Index Values in 2015.

According to MDGs, indexes in the context of health status show that the goals desired in terms of health are not attained in low-income countries compared to other income groups. After the deadline of MDGs, the United Nations has announced 17 SDGs, and “Good Health and Well-Being” takes its place as the third goal. Since achieving these goals requires the cooperation of countries and societies, “Partnership for the Goals” is determined as the seventeenth SDG. According to the United Nations ( 2019 ), the main indicators of global partnerships are trade, foreign direct investments, remittances, financial integration technology transfers, data monitoring and accountability, internet usage, and political integration among countries. In our study, while globalization is used as a proxy indicator of global cooperation, democracy is an indicator of cooperation between societies and governments. Democracy also refers to accountability levels of governments.

Globalization can simply be defined as the process of international integration which has economic, social, and political dimensions (Dreher 2006 ). Many countries have adapted to this process and have enjoyed the welfare effects of globalization by implementing necessary economic and institutional transformation. However, some countries still suffer from poor adaption to global markets. According to the KOF Globalization Index published by the Swiss Economic Institute ( 2020 ), low-income countries have the lowest globalization level compared to other income groups. They also suffer from bad health conditions such as low life expectancy, communicable diseases, and high mortality rates according to MDG indexes given above. At this point, the literature is divided into two parts. The first one blames globalization and argues that poverty and as a result of this, low life expectancy derives from the inequality created by globalization itself (Buss 2002 ). The second group mostly focuses on the benefits of free trade, capital mobility, and technology transfers (Rao and Vadlamannati 2011 ). The low-income countries also suffer from low institutional quality in the context of democracy and political rights. According to Freedom House’s list of electoral democracies, the countries without electoral democracy are mostly the low-income countries in the Middle East, North Africa, Sub-Saharan Africa, and Southeast Asia (Freedom House 2019 ).

The main question of our study is to determine whether the problem of low life expectancy in low-income countries is due to the low levels of globalization and weak political institutions in these countries. To answer this question, the role of economic, social, and political globalization and democracy in life expectancy in those countries is empirically investigated. This study provides several contributions to previous literature. First, we provide a new perspective in the context of sustainable development goals. Previous studies mostly focused on how to achieve SDGs, while possible conflicts between the goals were mostly ignored especially in the context of health. Such conflicts between sustainable development goals in the literature have mostly focused on the impact of economic growth and globalization on the sustainable environment (Ulucak and Bilgili 2018 ; Zafar et al. 2019a ). Those studies are mostly addressed the relationship between SDG7, SDG8, SDG13, and SDG17 (Zafar et al. 2019b ). To the best of our knowledge, it is the first study that investigates the relationship between SDG3 and SDG17. It is also important to examine this relationship in low-income countries since they still suffer from low levels of life expectancy, less adaptation to globalization, and poor democratic institutions compared to other income groups. Previous works mostly provide global evidence, while only a few studies focus on less developed countries. Achieving these 17 goals put forward by the United Nations at the same time is possible only if these goals do not conflict with each other. Second, empirical works in previous literature consist of traditional estimation methods called first-generation tests. In the analysis of panel data, the estimators considering cross-sectional dependence are called the second-generation estimators. Cross-sectional dependency simply refers to the situation when the shock that occurs in one country affects other countries as well. The source of this problem encountered in panel data analysis is the economic, financial, and political integration among countries (Menyah et al. 2014 ). The ignorance of cross-sectional dependence results in biased and inconsistent estimates and wrong inferences (De Hoyos and Sarafidis 2006 ; Chudik and Pesaran 2013 ). Low-income countries are mostly African countries where there is a rising trend in terms of integration to global markets and institutions (Beck et al. 2011 ). Using estimation techniques that consider cross-sectional dependence in those countries prevents misleading results. As the literature is divided into two parts about the effects of globalization on human well-being, fresh evidence via robust estimation methods is required in order to provide proper policy implications. To fill this gap, our work provides second-generation estimations.

2 Literature review

To improve the health conditions of a country, the welfare of the poor should be improved as well. Poverty is detrimental to access to health services. Therefore, the positive impact of globalization on health first emerged with its positive effects on economic growth (Labonté et al. 2009 : 10). The effects of globalization on growth were mostly driven by free trade, international specialization, technology transfers, knowledge spillovers, and competitive markets. It also offers broader opportunities for entrepreneurs and paves the way for innovation (Grossman and Helpman 2015 : 101). As expected, poverty rates significantly reduced in the last two decades because of the integration of developing economies to global markets (Harrison 2006 ). When trade liberalization and income increases are considered together, people's access to treatments and medications can be easier and life expectancy may be prolonged. However, we should consider other possibilities in the context of spreading communicable diseases. As Deaton ( 2004 ) mentioned before, access to cheap and easy travel can increase the rate of spread of communicable diseases. Migration is also another fact to take into account. Particularly rising sexual tourism and migrant sex workers increase the spread of sexually transmitted diseases such as HIV/AIDS. But today there are improved treatment methods to solve these problems. Even HIV-infected people can survive with antiretroviral therapy, and it also reduces sexual transmission of the infection (Dollar 2001 ; Cohen et al. 2011 ). Due to the high cost of advanced drugs as in the case of antiretroviral therapy, it should be accepted that people in low-income countries will have trouble accessing the drugs (Buss 2002 ). There are approaches known as the unequal exchange that globalization increases inequality among countries and that developed countries are more profitable from the globalization process (Love, 1980 ). It may also increase domestic income inequality. There are a few studies that came with the conclusion that globalization rises inequality (Dreher and Gaston 2008 ; Ha 2012 ), but Bergh and Nilsson ( 2010 ) suggested a different perspective. Due to extensive R&D investments and scientific activities, developed countries can find new treatment methods and supply advanced drugs. The only way to access that knowledge and these drugs are trade and integration between developed and underdeveloped countries. Globalization can play an important role in improving the health conditions of low-income countries to the extent that it can provide these linkages. One should also notice that wider markets and higher returns are important factors that motivate entrepreneurs. Buss ( 2002 ) claimed that the intellectual property rights of advanced drugs belong to private firms in developed countries, and because of the strong protection of property rights, less developed countries have trouble accessing them. However, rising global human rights became an important step to advance public health issues against economic concerns in the trade of pharmaceutical products.

The human rights approach focuses on how globalization affected disadvantaged people worldwide (Chapman 2009 ). It is an important instrument in the suppression of the inequality created by economic globalization. Because of the pressure on the government about human rights, disadvantaged people are becoming able to meet their basic human needs. The role of political globalization on this point is forcing governments to adopt global institutions. It increases the number of international organizations in which a country is a member. This makes governments more accountable in the global area and forcing them to pay attention to protect human rights. Gelleny and McCoy ( 2001 ) also claimed that integration among countries leads to political stability. Therefore, governments' tendency to violate human rights in order to maintain their power becomes lesser. Moreover, as social dimensions of globalization expand and communication opportunities among people in different countries increase, the possibility of human rights violations being discovered by other people increases (Dreher et al. 2012 ). Governments that know the international sanctions required by these violations have to be more cautious against human rights violations. Social globalization also provides cultural integration among the world’s people, and it changes lifestyles and consumption patterns worldwide. The consequences of this change can have positive and negative effects. First, increased urban population and sedentary lifestyles may enhance prepared food consumption and reduce daily movements which result in rising obesity and diabetes (Hu 2011 ). Second, although rapidly increasing consumption options and diversity are known as welfare indicators, they also can cause stress which is known as an important determinant of many diseases both psychological and physical (Cutler et al. 2006 ). Third, due to knowledge spillovers and communication technology, people can learn about healthy nutrition and protection from communicable diseases. Thus, unhealthy but traditional consumption patterns and lifestyles may change. These days we experience the coronavirus epidemic and we see once again the importance of globalization. Countries are aware of infectious diseases in different parts of the world in a very short time and can take measures to stop the spread of the virus. The changes created by social and political globalization play a major role in this emergence. Social globalization enables people in very remote areas of the world to communicate with each other, while political globalization forces governments to be transparent about infectious diseases.

With economic globalization, increased economic activity may lead to urbanization. One may think about unhealthy conditions of an urban area such as environmental degradation, air and water pollution, higher crime rates, and stress which reduce life expectancy. However, according to Kabir ( 2008 ), people living in an urban area can benefit from improved medical care, easy access to pharmacy, and to the hospitals that use higher technology. They can also get a better education and can enjoy better socioeconomic conditions.

Democracy can be considered as another determinant of life expectancy. In order to solve the health problems of the poor, people should draw the attention of the government. Sen ( 1999 ) claimed that the instrumental role of democracy in solving problems is enabling people to express and support their claims. Thus, the attention of politicians can be attracted to the problems of the poor. Politicians who have never tasted poverty do not have the urge to take action against the problems of the poor at the right time. Another linkage can be established through accountability (Besley and Kudamatsu 2006 ). In democracies, governments have an obligation to account to citizens for what purposes the resources were used. Thus, resources can be allocated to solve important public issues such as quality of life, communicable diseases, and mortality.

Compared to theoretical discussions, previous literature provides a lack of empirical evidence. Barlow and Vissandjee ( 1999 ) examined the determinants of life expectancy with cross-sectional data available in 1990 for 77 developed and developing countries. According to regression results, per capita income, literacy rate, and lower fertility are important determinants of life expectancy while living in a tropical area decreasing it. Another finding in this study shows that health expenditures in those countries failed to increase life expectancy. Following this study, Or ( 2000 ) analyzed the determinants of health outcomes in 21 industrialized OECD countries covering the period 1970–1992. This study presents gender-specific estimates separately for men and women. Fixed effects estimation results reveal a significant negative relationship between public health expenditure and women's premature death. The relationship also occurs for men, while GDP per capita dropped from the regression model due to high collinearity. Furthermore, GDP per capita and the proportion of white-collar workers reduce premature death for both men and women, while alcohol consumption increases it.

Franco et al. ( 2004 ) analyzed the impact of democracy on health utilizing political rights data of 170 countries. Empirical results show that people living in democracies enjoy better health conditions such as longer life expectancy, better maternal health, and lower child mortality. Following this, Besley and Kudamatsu ( 2006 ) investigated the nexus between democracy and health outcomes utilizing panel data from the 1960s to the 2000s. In their study, they used life expectancy at birth and child mortality variables for 146 countries as indicators of health outcomes. According to results, democracy has a positive and significant effect on life expectancy at birth and it also reduces child mortality. Safaei ( 2006 ) also investigated the impact of democracy on life expectancy and adult and child mortality rates with the data of 32 autocratic, 13 incoherent, and 72 democratic countries. According to the OLS estimation results, improving democratic institutions increases life expectancy and reduces child and adult mortality rates. Another finding of the study is that socioeconomic factors such as income, education, and access to health care services are important determinants of health status.

Owen and Wu ( 2007 ) found a positive relationship between trade openness and health outcomes using a panel of 219 countries. Health outcome measures of this study are infant mortality and life expectancy. Trade openness is one of the most important dimensions of globalization.

Kabir ( 2008 ) analyzed the determinants of life expectancy in 91 developing countries. Empirical results obtained are the opposite of the expected. According to results, per capita income, literacy rate, per capita health expenditure, and urbanization have no significant impact on life expectancy. On the other hand, the number of physicians has a positive and significant impact on life expectancy, while malnutrition reduces it. As a dummy variable, living in Sub-Saharan Africa is another factor that reduces life expectancy due to communicable diseases like HIV, malaria, etc.

Bergh and Nilsson ( 2010 ) used a panel of 92 countries in the period 1970–2005 to investigate the relationship between globalization and life expectancy. They used social, political, and economic globalization data separately, and the results show a significant positive effect of economic globalization on life expectancy at birth. But no significant relationship was found between social globalization, political globalization, and life expectancy. They also used average years of education, urban population, the number of physicians, and nutrition as control variables and the effect of economic globalization was still positive and significant.

Welander et al. ( 2015 ) examined the effects of globalization and democracy on child health in their panel data analysis for 70 developing countries covering the period 1970–2009. According to the results, globalization significantly reduces child mortality. In addition, democracy improves child health and it also increases the beneficial effects of globalization on child health. Following this study, Tausch ( 2015 ) analyzed the role of globalization in life expectancy in 99 countries. The results of OLS estimates show that globalization leads to inequality, and therefore, it reduces health performance in terms of life expectancy and infant mortality. These results are contradictory to positive views on the role of globalization in public health. However, in 19 of 99 countries, globalization increases public health performance. Ali and Audi ( 2016 ) also analyzed the role of globalization in life expectancy in Pakistan. According to ARDL estimation results, life expectancy is positively associated with higher levels of globalization. Another study on the Pakistan case proposed by Alam et al. ( 2016 ) concluded that foreign direct investment and trade openness which are important indicators of economic globalization affects life expectancy positively.

Patterson and Veenstra ( 2016 ) concluded that electoral democracies provide better health conditions compared to other countries. Their analysis includes annual data from 168 countries covering the period 1960–2010. Empirical results show democracy has a significant positive impact on life expectancy and it reduces infant mortality.

In their recent study, Shahbaz et al. ( 2019 ) investigated the impact of globalization, financial development, and economic growth on life expectancy. The authors used nonlinear time series analysis methods utilizing the data of 16 Sub-Saharan African countries over the period 1970–2012. Their results show that globalization, financial development, and economic growth affect life expectancy positively in 14 of 16 Sub-Saharan African countries.

The previous literature provides a lack of evidence in the context of globalization, democracy, and life expectancy relationship. There are also methodological weaknesses in previous empirical studies. First, it can be observed that previous studies are mostly based on traditional estimation methods. Second, the panel data analyses are based on the first-generation estimators that assume cross-sectional independence. This assumption is hard to satisfy due to integration among countries. In addition, ignoring the cross-sectional dependence results in inconsistent estimations. Particularly in empirical work in the context of globalization which refers to economic, political, and cultural integration among countries, considering the cross-sectional dependence becomes more important. Therefore, in order to make a methodological contribution to previous literature, we used second-generation panel time series methods considering cross-sectional dependence.

3 Methodology and data

According to the United Nations, achieving sustainable development goals requires global cooperation and partnership. Therefore, “partnerships for goals” has taken its place as the 17th sustainable development target. However, it was emphasized that some sub-goals should be realized in order to reach this goal. These include improving international resource mobility, helping developing countries to attain debt sustainability, promoting the transfer of information and technology between developed and developing countries, an open and rule-based free trade system, encouraging public–private and civil society partnerships, increasing transparency and accountability, and high quality and reliable data (United Nations 2019 ). In our empirical work, economic, social, and political globalization and democracy variables were used as proxies of the subcomponents of SDG17. In addition, the life expectancy at birth variable that mostly used in related literature as a proxy of health status and well-being, it is used in our study as a proxy of SDG3. In this study, we investigated the role of globalization and democracy in life expectancy in 16 low-income countries. Footnote 1 Following Barlow and Vissandjee ( 1999 ) and ( 2000 ), GDP per capita is used as a control variable in order to mitigate omitted variable bias. Our dataset is covering the period 1970–2017. Following the related literature, we present our model as follows:

where lex is life expectancy at birth which refers to the average number of years a newborn is expected to live. Life expectancy at birth data is provided by World Bank ( 2019 ) World Development Indicators. Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. The dataset is consisting of a weighted average of collected data from several co-founders. In Eq.  1 , X refers to the KOF Globalization Index developed by Dreher ( 2006 ). This index has been used in previous literature as a proxy of SDG17 (Saint Akadiri et al. 2020 ). The current version of the data published by the Swiss Economic Institute is revised by Gygli et al. ( 2019 ). The globalization variables are between 0–100, and 100 refers to the highest globalization level. In our analysis, we used subcomponents of globalization index such as economic (EC), social (SOS), and political (POL) globalization in addition to overall globalization (GLB). Due to high collinearity, the effects of different types of globalization are analyzed separately. Models 1, 2, 3, and 4 represent the estimations with overall, economic, social, and political globalization indexes, respectively. The democracy variable ( dem ) is provided from the Polity IV project dataset (Marshall and Jaggers 2002 ). While the increases in this indicator represent a more democratic regime, the decreases represent a more autocratic regime. Finally, gdp is real GDP per capita (constant 2010 $) and it is provided from World Bank World Development Indicators. All variables transformed to the logarithmic form except democracy due to negative values. In the estimation of the model, the panel data analysis methods are used.

3.1 Cross-sectional dependence

Traditional panel data methods are based on the assumption that no cross-sectional dependence exists among cross section units. However, this assumption is hard to satisfy due to rising economic, social, and political integration between countries. The estimations do not take this process into account may cause inconsistent results. Such results may also lead to incorrect inferences (Chudik and Pesaran, 2013 ). The existence of cross-sectional dependence in variables and the error term is obtained from the model analyzed with Pesaran ( 2004 ) \({\text{CD}}_{{{\text{LM}}}}\) and Pesaran et al. ( 2008 ) bias-adjusted LM test. These techniques are robust whether N > T and T > N. Therefore, \({CD}_{LM}\) and bias-adjusted LM ( \({LM}_{adj})\) tests are found to be appropriate and their test statistics can be calculated as follows:

Equation  2 shows the calculation of Pesaran ( 2004 ) \({CD}_{LM},\) and Eq.  3 is Pesaran et al. ( 2008 ) bias-adjusted LM test statistic. \({V}_{Tij}\) , \({\mu }_{Tij}\) , and \({\widehat{\rho }}_{ij},\) respectively, represent variance, mean, and the correlation between cross section units. The null and alternative hypothesis for both test statistics; \({H}_{0}\) : No cross-sectional dependence exist; \({H}_{1}\) : Cross-sectional dependence exist.

In the selection of stationarity tests and long-run estimators, the existence of cross-sectional dependence will be decisive. If the null of no cross-sectional dependence is rejected, second-generation methods that assume cross-sectional dependence should be used in order to provide unbiased and consistent estimation results.

3.2 Slope homogeneity

Pesaran and Yamagata ( 2008 ) proposed a method to examine slope heterogeneity in panel data analysis based on the Swamy ( 1970 )’s random coefficient model.

The calculation of the test statistic of Swamy’s model is given in Eq.  4 .

In Eq.  4 , \({\stackrel{\sim }{\beta }}_{i}\) and \({\overbrace{\beta }}_{WFE},\) respectively, indicate the parameters obtained from pooled OLS and weighted fixed effects estimation, while \({M}_{T}\) is the identity matrix. The test statistic obtained from Swamy’s model is improved by Pesaran et al. ( 2008 ) as follows:

where \(\stackrel{\sim }{S}\) is the Swamy test statistic and k is a number of explanatory variables. \({\stackrel{\sim }{\Delta }}_{adj}\) is a bias-adjusted version of \(\stackrel{\sim }{\Delta }\) . \({\stackrel{\sim }{Z}}_{it}\) =k and \(Var\left({\stackrel{\sim }{Z}}_{it}\right)=2k(T-k-1)/T+1\) . The null and alternative hypothesis for both test statistics is given below.

The rejection of the null hypothesis shows that slope coefficients of Eq. 1 are heterogeneous. In the selection of panel data estimation methods, the results of those preliminary analysis are taken into account.

3.3 Unit root test

Pesaran ( 2006 ) suggested a factor modeling approach to solve the cross-sectional dependency problem. This approach is simply based on adding cross-sectional averages to the models as proxies of unobserved common factors. The Cross-sectionally Augmented Dickey–Fuller (CADF) unit root test developed by Pesaran ( 2007 ) is based on that factor modelling approach. This method is an augmented form of Augmented Dickey–Fuller (ADF) regression with lagged cross-sectional average and its first difference to deal with cross-sectional dependence (Baltagi, 2008 : 249). This method considers the cross-sectional dependence and can be used, while N > T and T > N. The CADF regression is:

\({\stackrel{-}{y}}_{t}\) is the average of all N observations. To prevent serial correlation, the regression must be augmented with lagged first differences of both \({y}_{it}\) and \({\stackrel{-}{y}}_{t}\) as follows:

After the calculation of CADF statistics for each cross section ( \({CADF}_{i}\) ), Pesaran ( 2007 ) calculates the CIPS statistic as average of CADF statistics.

If the calculated CIPS statistic exceeds the critical value, it means that the unit root hypothesis is rejected. After the preliminary analysis of unit root, the existence of a long-run relationship between the variables in our model will be investigated via Westerlund and Edgerton ( 2007 ) cointegration test. After this, the long-run coefficients will be estimated using the continuous-updated fully modified (CUP-FM) estimator developed by Bai and Kao ( 2006 ) and Bias-adjusted OLS estimator developed by Westerlund ( 2007 ).

3.4 Cointegration test and long-run relationship

In this study, the cointegration relationship was investigated by Westerlund and Edgerton ( 2007 ) LM bootstrap test. This method considers cross-sectional dependence and provides robust results in small samples (Westerlund and Edgerton, 2007 ). This method is based on the following equation

where \({n}_{ij}\) is an independent and identically distributed process with zero mean and var( \({n}_{ij})\) = \({{\sigma }_{i}}^{2}\) . Westerlund and Edgerton ( 2007 ) suggested following LM test in order to test the null of cointegration

where \({S}_{it}\) is partial sum process of the fully modified estimate of \({z}_{it}\) and \({\widehat{w}}_{i}^{-2}\) is the estimated long-run variance of \({u}_{it}\) conditional on \(\Delta {x}_{it}^{^{\prime}}\) . If the calculated LM statistic is below the critical value, the null of cointegration will be accepted. The critical values will be provided using the bootstrap method in order to prevent cross-sectional dependence.

In the estimation of long-run coefficients, the CUP-FM estimator was used and this method is based on the following regression

where \({\widehat{\lambda }}_{i}^{^{\prime}}\) refers to the estimated factor loadings and \(\hat{y}_{{i,t}}^{ + } = y_{{i,t}} - \left( {\lambda _{i} ^{\prime } \hat{\Omega }_{{F \in i}} + \hat{\Omega }_{{\mu \in i}} } \right)\hat{\Omega }_{{ \in i}}^{{ - 1}} {{\Delta }}x_{{i,t}}\) indicates the transformation of the dependent variable for endogeneity correction. According to Bai and Kao ( 2006 ), CUP-FM estimator is robust under cross-sectional dependence. However, the assumption that the number of common factors (k) is known cannot be satisfied in practice (Westerlund, 2007 ). Therefore, Westerlund ( 2007 ) suggested a bias-adjusted estimator (BA-OLS) following the methodology of Bai and Kao ( 2006 ) except in the context of determining the number of common factors. The author suggested the estimation of k using an information criterion as

where \(IC\left(k\right)\) is the information criterion. In this study, we determined the number of common factors via the Bayesian information criterion (BIC) as follows.

In the equation above, V(k) is the estimated variance of \({\widehat{u}}_{it}\) based on k factors. By minimizing the BIC, we obtain \(\widehat{k}\) . Westerlund ( 2007 ) showed that the estimation of k provides better results compared to CUP-FM estimator assuming k is known. Both of the estimators require cointegrated variables in the long run.

3.5 Empirical results and discussion

The results of Pesaran ( 2004 ) \({CD}_{LM}\) and Pesaran et al. ( 2008 ) bias-adjusted LM tests are given in Table 1 .

The results given in Table 1 show that the null of no cross-sectional dependence is rejected at 1% according to both \({CD}_{LM}\) and \({LM}_{adj}\) test statistics in all variables. In addition, in the error terms obtained from models 1, 2, 3, and 4 the null of no cross-sectional dependence is rejected at 1%. These results show that the methods to be used in the analysis of the stationarity of the variables and the determination of the long-run relationship should consider the cross-sectional dependence.

The results of homogeneity tests developed by Pesaran and Yamagata ( 2008 ) are given in Table 2 . According to the results, the null of homogeneity is accepted at %1 in all models. Therefore, estimators assume parameter homogeneity are used in our analysis.

After the preliminary analysis of cross-sectional dependence, the CADF unit root test developed by Pesaran ( 2007 ) is found to be appropriate for our model because of its robustness under cross-sectional dependence. The results of the CADF unit root test are given in Table 3 .

In the analysis of unit root, constant and trend terms are both considered at level, while only constant term is added at first difference. Maximum lag level is determined as 3, while optimum lag level is determined by F joint test from general to particular. According to results, the null of unit root is accepted for all variables, while calculated CIPS statistics of first-differenced variables exceed 1% critical value. All variables have a unit root, and their first differences are stationary ( \({I}_{1})\) . Therefore, in order to determine the existence of a long-run relationship, we applied Westerlund and Edgerton ( 2007 ) panel cointegration test. This method considers cross-sectional dependence and can be used, while the series are integrated in the same order. The results are shown in Table 4 .

Constant and trend are both considered in the analysis of cointegration, and critical values are obtained from 5000 bootstrap replications. The results show that the null of cointegration is accepted for all models. There is a long-run relationship between life expectancy, globalization, democracy, and GDP per capita. After determining the cointegration relationship, we estimated long-run coefficients utilizing CUP-FM and BA-OLS estimators proposed by Bai and Kao ( 2006 ) and Westerlund ( 2007 ), respectively.

The long-run estimation results given in Table 5 show that overall, economic, social, and political globalization are positively associated with life expectancy at 1% significance level according to both CUP-FM and BA-OLS estimators. The results show that a 1% increase in globalization index increases life expectancy %0.014 and %0.015 according to CUP-FM and BA-OLS estimators, respectively. The impact of economic, social and political globalization indexes is 0.013%, 0.011%, and 0.015% according to CUP-FM estimation results while 0.014%, 0.012%, and 0.017% according to both estimators, respectively.

Our results confirms the findings of Owen and Wu ( 2007 ), Ali and Audi ( 2016 ), and Shahbaz et al. ( 2019 ) who found a positive relationship between globalization and life expectancy. Our empirical work also supports the evidence of Bergh and Nilsson ( 2010 ) in terms of positive effect of economic globalization on life expectancy. While the authors found no significant impact of social and political globalization on life expectancy, our results show that life expectancy is positively associated with both social and political globalization. The results we found contradict Tausch ( 2015 )’s evidences in 80 of 99 countries. However, according to his results, in 19 of 99 countries, globalization affects health positively. When these countries are examined, it is seen that 14 of them are countries in the low and lower-middle income groups. In this sense, it can be said that the evidence we found for low-income countries is in line with the author's evidence. As Dreher ( 2006 ) mentioned, despite its possible inequality effects, the net effect of globalization on development is mostly positive and our empirical work supports that idea. The effect of democracy on life expectancy is also positive and significant at 1% which confirms the findings of Franco et al. ( 2004 ) and Besley and Kudamatsu ( 2006 ). In electoral democracies, people living in poverty and suffering from health problems can easily attract the attention of policymakers compared to autocracies. This leads to the reallocation of resources to solve the primary problems of the society. In the context of sustainable development goals, our results show that there is no conflict between SDG3 (good health and well-being) and SDG17 (partnerships for the goals). The improvement of the health conditions of the poor countries depends on global partnership and economic, social, and political integration among countries. In addition, democracy is an important tool in achieving the goal of a healthy society, as it fosters accountability, transparency, and partnership between governments and the societies they rule. As stated in the introduction section, low-income countries show low performance in terms of health-related sustainable development goals, and their connections with global markets are weak compared to other countries. At the same time, democratic institutions are not developed. Our work supports the idea that in order to achieve SDG3, global partnership and democracy are required.

The GDP per capita that used as a control variable has a positive impact on life expectancy at a 1% level. These results support the evidence of Barlow and Vissandjee ( 1999 ), Or ( 2000 ), and Shahbaz et al. ( 2019 ). Individuals living in countries with high per capita income are expected to have higher welfare and have a longer life expectancy (Judge, 1995 ). In low-income countries where people still suffer from having difficulty in meeting basic human needs, increasing per capita income may lead to better nutritional status, easier access to advanced treatment methods and technology.

4 Conclusion

In this study, the effects of globalization and democracy on life expectancy are empirically investigated in low-income countries. While globalization and democracy indexes are used as proxy indicators of “Partnerships for the Goals (SDG 17),” life expectancy used a proxy of “Good Health and Well-Being (SDG 3).” With this, it is aimed to examine the existence of contradiction between those SDGs. In the estimation of the long-run relationship between the variables, second-generation panel data analysis methods that consider cross-sectional dependency are used. According to the results, the globalization index and its subcomponents such as economic, social, and political globalization are important instruments to achieve a healthier society. In addition, higher levels of democracy lead to higher levels of life expectancy. Finally, GDP per capita growth improves health status of countries.

The findings obtained from our study show that economic, social, and political integration of countries and democracy accelerate the process of achieving a healthier society. Therefore, it is seen that SDG3 and SDG17 targets are compatible with each other. In order to achieve SDG3, economic, social, and political integration between countries should be encouraged and democratic institutions should be improved. Policy makers should remove the barriers on globalization, and they should promote participation on international organizations and public–private and civil society partnerships.

Those countries are Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, The Gambia, Haiti, Madagascar, Malawi, Mali, Nepal, Niger, Rwanda, Sierra Leone, and Togo.

Alam, M. S., Raza, S. A., Shahbaz, M., & Abbas, Q. (2016). Accounting for contribution of trade openness and foreign direct investment in life expectancy: The long-run and short-run analysis in Pakistan. Social Indicators Research, 129 (3), 1155–1170.

Article   Google Scholar  

Ali A, & Audi M (2016). The impact of income inequality, environmental degradation and globalization on life expectancy in Pakistan: An empirical analysis. MPRA Working Paper, No. 71112.

Bai, J., & Kao, C. (2006). On the estimation and inference of a panel cointegration model with cross-sectional dependence In panel data econometrics theoretical contributions and empirical applications . Bingley: Emerald Group Publishing Limited.

Google Scholar  

Baltagi, B. (2008). Econometric analysis of panel data . New York: Wiley.

Barlow, R., & Vissandjee, B. (1999). Determinants of national life expectancy. Canadian Journal of Development Studies/Revue canadienne d’études du développement, 20 (1), 9–29.

Beck, T., Maimbo, S. M., Faye, I., & Triki, T. (2011). Financing Through the crisis and beyond . Africa: The World Bank.

Book   Google Scholar  

Bergh, A., & Nilsson, T. (2010). Good for living? On the relationship between globalization and life expectancy. World Development, 38 (9), 1191–1203.

Besley, T., & Kudamatsu, M. (2006). Health and democracy. American Economic Review, 96 (2), 313–318.

Buss, P. M. (2002). Globalization and disease: In an unequal world, unequal health! Cadernos de Saúde Pública, 18, 1783–1788.

Chapman, A. R. (2009). Globalization, human rights, and the social determinants of health. Bioethics, 23 (2), 97–111.

Chudik A, & Pesaran, MH (2013) Large panel data models with cross-sectional dependence: a survey. CAFE Research Paper , (13.15).

Cohen, M. S., Chen, Y. Q., McCauley, M., Gamble, T., Hosseinipour, M. C., Kumarasamy, N., & Godbole, S. V. (2011). Prevention of HIV-1 infection with early antiretroviral therapy. New England journal of medicine, 365 (6), 493–505.

Article   CAS   Google Scholar  

Cutler, D., Deaton, A., & Lleras-Muney, A. (2006). The determinants of mortality. Journal of economic perspectives, 20 (3), 97–120.

De Hoyos, R. E., & Sarafidis, V. (2006). Testing for cross-sectional dependence in panel-data models. The stata journal, 6 (4), 482–496.

Deaton, A. (2004). Health in an age of globalization (No. w10669) . Cambridge: National Bureau of Economic Research.

Dollar, D. (2001). Is globalization good for your health? Bulletin of the world Health Organization, 79, 827–833.

CAS   Google Scholar  

Dreher, A. (2006). Does globalization affect growth? Evidence from a new index of globalization. Applied economics, 38 (10), 1091–1110.

Dreher, A., & Gaston, N. (2008). Has globalization increased inequality? Review of International Economics , 16 (3), 516–536.

Dreher, A., Gassebner, M., & Siemers, L. H. (2012). Globalization, economic freedom, and human rights. Journal of Conflict Resolution, 56 (3), 516–546.

Franco, Á., Álvarez-Dardet, C., & Ruiz, M. T. (2004). Effect of democracy on health: Ecological study. BMJ, 329 (7480), 1421–1423.

Freedom House (2019). List of Electoral Democracies in 2019. https://freedomhouse.org/report-types/freedom-world (Access Date: 11.13.2019).

Gelleny, R. D., & McCoy, M. (2001). Globalization and government policy independence: The issue of taxation. Political Research Quarterly, 54 (3), 509–529.

Grossman, G. M., & Helpman, E. (2015). Globalization and growth. American Economic Review, 105 (5), 100–104.

Gygli, S., Haelg, F., Potrafke, N., & Sturm, J. E. (2019). The KOF globalisation index–revisited. The Review of International Organizations , 14 , 543–574.

Ha, E. (2012). Globalization, government ideology, and income inequality in developing countries. The journal of Politics, 74 (2), 541–557.

Halisçelik, E., & Soytas, M. A. (2019). Sustainable development from millennium 2015 to Sustainable Development Goals 2030. Sustainable Development, 27 (4), 545–572.

Harrison, A. (2006). Globalization and poverty (No. w12347) . Cambridge: National Bureau of Economic Research.

Hu, F. B. (2011). Globalization of diabetes: the role of diet, lifestyle, and genes. Diabetes Care, 34 (6), 1249–1257.

Judge, K. (1995). Income distribution and life expectancy: A critical appraisal. BMJ, 311 (7015), 1282–1285.

Kabir, M. (2008). Determinants of life expectancy in developing countries. The journal of Developing areas, 41, 185–204.

Labonté, R., Schrecker, T., Packer, C., & Runnels, V. (Eds.). (2009). Globalization and health: Pathways, evidence and policy . Abingdon: Routledge.

Love, J. L. (1980). Raul Prebisch and the origins of the doctrine of unequal exchange. Latin American Research Review, 15 (3), 45–72.

Marshall, M. G., & Jaggers, K. (2002). Polity IV Project: Political regime characteristics and transitions, 1800–2002: Dataset users’ manual . Maryland: University of Maryland.

Menyah, K., Nazlioglu, S., & Wolde-Rufael, Y. (2014). Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach. Economic Modelling, 37, 386–394.

Or, Z. (2000). Determinants of health outcomes in industrialized countries: A pooled, cross-country, time-series analysis. OECD Economic Studies, 1, 53–78.

Owen, A. L., & Wu, S. (2007). Is trade good for your health? Review of International Economics, 15 (4), 660–682.

Patterson, A. C., & Veenstra, G. (2016). Politics and population health: Testing the impact of electoral democracy. Health & place, 40, 66–75.

Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. CESifo Working Paper (No. 1229).

Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica , 74 (4), 967–1012.

Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of applied econometrics, 22 (2), 265–312.

Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142 (1), 50–93.

Pesaran, M. H., Ullah, A., & Yamagata, T. (2008). A bias-adjusted LM test of error cross-section independence. The Econometrics Journal, 11 (1), 105–127.

Rao, B. B., & Vadlamannati, K. C. (2011). Globalization and growth in the low income African countries with the extreme bounds analysis. Economic Modelling, 28 (3), 795–805.

Safaei, J. (2006). Is democracy good for health? International Journal of Health Services, 36 (4), 767–786.

Saint Akadiri, S., Alola, A. A., Olasehinde-Williams, G., & Etokakpan, M. U. (2020). The role of electricity consumption, globalization and economic growth in carbon dioxide emissions and its implications for environmental sustainability targets. Science of The Total Environment, 708, 134653.

Sen, A. (1999). Development as freedom . New York: Knopf.

Shahbaz, M., Shafiullah, M., & Mahalik, M. K. (2019). The dynamics of financial development, globalisation, economic growth and life expectancy in sub-Saharan Africa. Australian Economic Papers, 58 (4), 444–479.

Swamy, P. A. (1970). Efficient inference in a random coefficient regression model. Econometrica: Journal of the Econometric Society, 38, 311–323.

Swiss Economic Institute. (2020). KOF Globalization Index. https://kof.ethz.ch/en/forecasts-and-indicators/indicators/kof-globalisation-index.html (Access Date: December, 2019).

Tausch, A. (2015). Is globalization really good for public health? The International journal of health planning and management, 31 (4), 511–536.

The United Nations (2019). Sustainable Development Goal Indicators. https://unstats.un.org/sdgs/indicators/Global%20Indicator%20Framework%20after%202019%20refinement_Eng.pdf (Access Date: 25.12.2019).

Ulucak, R., & Bilgili, F. (2018). A reinvestigation of EKC model by ecological footprint measurement for high, middle and low income countries. Journal of cleaner production, 188, 144–157.

Welander, A., Lyttkens, C. H., & Nilsson, T. (2015). Globalization, democracy, and child health in developing countries. Social Science and Medicine, 136, 52–63.

Westerlund, J. (2007). Estimating cointegrated panels with common factors and the forward rate unbiasedness hypothesis. Journal of Financial Econometrics, 5 (3), 491–522.

Westerlund, J., & Edgerton, D. L. (2007). A panel bootstrap cointegration test. Economics Letters, 97 (3), 185–190.

World Bank (2019). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators (Access Date: December, 2019).

World Health Organization. (2016). Health in 2015: from MDGs to SDGs 2015 . Geneva: World Health Organization.

Zafar, M. W., Saud, S., & Hou, F. (2019a). The impact of globalization and financial development on environmental quality: Evidence from selected countries in the Organization for Economic Co-operation and Development (OECD). Environmental science and pollution research, 26 (13), 13246–13262.

Zafar, M. W., Shahbaz, M., Hou, F., & Sinha, A. (2019b). From nonrenewable to renewable energy and its impact on economic growth: The role of research & development expenditures in Asia-Pacific Economic Cooperation countries. Journal of cleaner production, 212, 1166–1178.

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Guzel, A.E., Arslan, U. & Acaravci, A. The impact of economic, social, and political globalization and democracy on life expectancy in low-income countries: are sustainable development goals contradictory?. Environ Dev Sustain 23 , 13508–13525 (2021). https://doi.org/10.1007/s10668-021-01225-2

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Article contents

Global migration: causes and consequences.

• Benjamin Helms Benjamin Helms Department of Politics, University of Virginia
• , and  David Leblang David Leblang Department of Politics, Frank Batten School of Leadership and Public Policy, University of Virginia
• https://doi.org/10.1093/acrefore/9780190228637.013.631
• Published online: 25 February 2019

International migration is a multifaceted process with distinct stages and decision points. An initial decision to leave one’s country of birth may be made by the individual or the family unit, and this decision may reflect a desire to reconnect with friends and family who have already moved abroad, a need to diversify the family’s access to financial capital, a demand to increase wages, or a belief that conditions abroad will provide social and/or political benefits not available in the homeland. Once the individual has decided to move abroad, the next decision is the choice of destination. Standard explanations of destination choice have focused on the physical costs associated with moving—moving shorter distances is often less expensive than moving to a destination farther away; these explanations have recently been modified to include other social, political, familial, and cultural dimensions as part of the transaction cost associated with migrating. Arrival in a host country does not mean that an émigré’s relationship with their homeland is over. Migrant networks are an engine of global economic integration—expatriates help expand trade and investment flows, they transmit skills and knowledge back to their homelands, and they remit financial and human capital. Aware of the value of their external populations, home countries have developed a range of policies that enable them to “harness” their diasporas.

• immigration
• international political economy
• factor flows
• gravity models

Introduction

The steady growth of international labor migration is an important, yet underappreciated, aspect of globalization. 1 In 1970 , just 78 million people, or about 2.1% of the global population, lived outside their country of birth. By 1990 , that number had nearly doubled to more than 150 million people, or about 2.8% of the global population (United Nations Population Division, 2012 ). Despite the growth of populist political parties and restrictionist movements in key destination countries, the growth in global migration shows no signs of slowing down, with nearly 250 million people living outside their country of birth as of 2015 . While 34% of all global migrants live in industrialized countries (with the United States and Germany leading the way), 38% of all global migration occurs between developing countries (World Bank, 2016 ).

Identifying the causes and consequences of international labor migration is essential to our broader understanding of globalization. Scholars across diverse academic fields, including economics, political science, sociology, law, and demography, have attempted to explain why individuals voluntarily leave their homelands. The dominant thread in the labor migration literature is influenced by microeconomics, which posits that individuals contemplating migration are rational, utility-maximizing actors who carefully weigh the potential costs and benefits of leaving their country of origin (e.g., Borjas, 1989 ; Portes & Böröcz, 1989 ; Grogger & Hanson, 2011 ). The act of migration, from this perspective, is typically conceptualized as an investment from which a migrant expects to receive some benefit, whether it be in the form of increased income, political freedom, or enhanced social ties (Schultz, 1961 ; Sjaastad, 1962 ; Collier & Hoeffler, 2014 ).

In this article we go beyond the treatment of migration as a single decision and conceive of it as a multifaceted process with distinct stages and decision points. We identify factors that are relevant at different stages in the migration process and highlight how and when certain factors interact with others during the migration process. Economic factors such as the wage differential between origin and destination countries, for example, may be the driving factor behind someone’s initial decision to migrate (Borjas, 1989 ). But when choosing a specific destination, economic factors may be conditioned by political or social conditions in that destination (Fitzgerald, Leblang, & Teets, 2014 ). Each stage or decision point has distinguishing features that are important in determining how (potential) migrants respond to the driving forces identified by scholars.

This is certainly not a theoretical innovation; migration has long been conceived of as a multi-step process, and scholars often identify the stage or decision point to which their argument best applies. However, most interdisciplinary syntheses of the literature on international labor migration do not provide a systematic treatment of this defining feature, instead organizing theoretical and empirical contributions by field of study, unit or level of analysis, or theoretical tradition (e.g., Portes & Böröcz, 1989 ; Massey et al., 1993 ; European Asylum Support Office, 2016 ). Such approaches are undoubtedly valuable in their own right. Our decision to organize this discussion by stage allows us to understand this as a process, rather than as a set of discrete events. As a result, we conceptualize international labor migration as three stages or decision points: (a) the decision to migrate or to remain at home, (b) the choice of destination, and (c) the manner by which expatriates re-engage—or choose not to re-engage—with their country of origin once abroad. We also use these decision points to highlight a number of potential new directions for future research in this still-evolving field.

Figure 1. Global migration intentions by educational attainment, 2008–2017.

Should I Stay or Should I Go, Now?

The massive growth in international labor migration in the age of globalization is remarkable, but the fact remains that over 95% of the world’s population never leave their country of origin (United Nations Population Division, 2012 ). Figure 1 shows the percentage of people who expressed an intention to move abroad between 2008 and 2017 by educational attainment, according to data from the Gallup World Poll. Over this time period, it appears that those who were highly educated expressed intent to migrate in greater numbers than those who had less than a college education, although these two groups have converged in recent years. What is most striking, however, is that a vast majority of people, regardless of educational attainment, expressed no desire to move abroad. Even though absolute flows of migrants have grown at a near-exponential rate, relative to their non-migrating counterparts, they remain a small minority. What factors are important in determining who decides to migrate and who decides to remain at home? 2

From Neoclassical Economics to the Mobility Transition

Neoclassical economic models posit that the primary driving factor behind migration is the expected difference in wages (discounted future income streams) between origin and destination countries (Sjaastad, 1962 ; Borjas, 1989 ; Clark, Hatton, & Williamson, 2007 ). All else equal, when the wage gap, minus the costs associated with moving between origin and destination, is high, these models predict large flows of labor migrants. In equilibrium, as more individuals move from origin to destination countries, the wage differential narrows, which in turn leads to zero net migration (Lewis, 1954 ; Harris & Todaro, 1970 ). Traditional models predict a negative monotonic relationship between the wage gap and the number of migrants (e.g., Sjaastad, 1962 ). However, the predictions of neoclassical models are not well supported by the empirical record. Empirical evidence shows that, at least in a cross-section, the relationship between economic development and migration is more akin to an inverted U. For countries with low levels of per capita income, we observe little migration due to a liquidity constraint: at this end of the income distribution, individuals do not have sufficient resources to cover even minor costs associated with moving abroad. Increasing income helps to decrease this constraint, and consequently we observe increased levels of emigration as incomes rise (de Haas, 2007 ). This effect, however, is not monotonic: as countries reach middle-income status, declining wage differentials lead to flattening rates of emigration, and then decreasing rates as countries enter later stages of economic development. 3

Some research explains this curvilinear relationship by focusing on the interaction between emigration incentives and constraints : for example, increased income initially makes migration more affordable (reduces constraints), but also simultaneously reduces the relative economic benefits of migrating as the wage differential narrows (as potential migrants now have the financial capacity to enhance local amenities) (Dao, Docquier, Parsons, & Peri, 2016 ). The theoretical underpinnings of this interaction, however, are not without controversy. Clemens identifies several classes of theory that attempt to explain this curvilinear relationship—a relationship that has been referred to in the literature as the mobility transition (Clemens, 2014 ). These theories include: demographic changes resulting from development that also favor emigration up to a point (Easterlin, 1961 ; Tomaske, 1971 ), the loosening of credit restraints on would-be migrants (Vanderkamp, 1971 ; Hatton & Williamson, 1994 ), a breakdown of information barriers via the building of transnational social networks (Epstein, 2008 ), structural economic changes in the development process that result in worker dislocation (Zelinsky, 1971 ; Massey, 1988 ), the dynamics of economic inequality and relative deprivation (Stark, 1984 ; Stark & Yitzhaki, 1988 ; Stark & Taylor, 1991 ), and changing immigration policies in destination countries toward increasingly wealthy countries (Clemens, 2014 ). While each of these play some role in the mobility transition curve, Dao et al. ( 2016 ) run an empirical horse race between numerous explanations and find that changing skill composition resulting from economic development is the most substantively important driver. Economic development is correlated with an increase in a country’s level of education; an increase in the level of education, in turn, is correlated with increased emigration. However, traditional explanations involving microeconomic drivers such as income, credit constraints, and economic inequality remain important factors (Dao et al., 2016 ). The diversity of explanations offered for the mobility transition curve indicates that while most research agrees the inverted-U relationship is an accurate empirical portrayal of the relationship between development and migration, little theoretical agreement exists on what drives this relationship. Complicating this disagreement is the difficulty of empirically disentangling highly correlated factors such as income, skill composition, and demographic trends in order to identify robust causal relationships.

Political Conditions at the Origin

While there is a scholarly consensus around the mobility transition and the role of economic conditions, emerging research suggests that the political environment in the origin country may also be salient. We do not refer here to forced migration, such as in the case of those who leave because they are fleeing political persecution or violent conflict. Rather, we focus on political conditions in the homeland that influence a potential migrant’s decision to emigrate voluntarily. Interpretations of how, and the extent to which, political conditions in origin countries (independent of economic conditions) influence the decision to migrate have been heavily influenced by Hirschman’s “Exit, Voice, and Loyalty” framework (Hirschman, 1970 , 1978 ). Hirschman argues that the opportunity to exit—to exit a firm, an organization, or a country—places pressure on the local authorities; voting with one’s feet forces organizations to reassess their operations.

When applied to the politics of emigration, Hirschman’s framework generates two different hypotheses. On the one hand, politicians may allow, encourage, or force the emigration of groups that oppose the regime as a political safety valve of sorts. This provides the government with a mechanism with which to manage potential political challengers by encouraging their exit. On the other hand, politicians—especially those in autocracies—may actively work to prevent exit because they fear the emigration of economic elites, the highly skilled, and others who have resources vital to the survival of the regime. 4

A small number of studies investigate how local-level, rather than national, political circumstances affect a potential migrant’s calculus. The limited empirical evidence currently available suggests that local conditions are substantively important determinants of the emigration decision. When individuals are highly satisfied with local amenities such as their own standard of living, quality of public services, and overall sense of physical security, they express far less intention to migrate compared with highly dissatisfied individuals (Dustmann & Okatenko, 2014 ). Furthermore, availability of public transport and access to better education facilities decreases the propensity to express an intention to emigrate (Cazzuffi & Modrego, 2018 ). This relationship holds across all levels of wealth and economic development, and there is some evidence that satisfaction with local amenities matters as much as, or even more than, income or wealth (Dustmann & Okatenko, 2014 ).

Political corruption, on both national and local levels, also has substantively important effects on potential migrants, especially those who are highly skilled. Broadly defined as the use of public office for political gain, political corruption operates as both a direct and an indirect factor promoting emigration. 5 Firstly, corruption may have a direct effect on the desire to emigrate in that it can decrease the political and economic power of an individual, leading to a lower standard of living and poorer quality of life in origin countries. If the reduction in life satisfaction resulting from corruption is sufficiently high—either by itself or in combination with other “push” factors—then the exit option becomes more attractive (Cooray & Schneider, 2016 ). Secondly, corruption also operates through indirect channels that influence other push factors. Given the large literature on how political corruption influences a number of development outcomes, it is conceivable that corruption affects the decision-making process of a potential migrant through its negative effect on social spending, education, and public health (Mo, 2001 ; Mauro, 1998 ; Gupta, Davoodi, & Thigonson, 2001 ).

The combination of its direct and indirect impacts means that corruption could be a significant part of a migrant’s decision-making process. At present there is limited work exploring this question, and the research does not yield a consensus. Some scholars argue that political corruption has no substantive effect on total bilateral migration, but that it does encourage migration among the highly skilled (Dimant, Krieger, & Meierrieks, 2013 ). This is the case, the argument goes, because corruption causes the greatest relative harm to the utility of those who have invested in human capital, who migrate to escape the negative effect on their fixed investment. In contrast, others find that a high level of corruption does increase emigration at the aggregate level (Poprawe, 2015 ). More nuanced arguments take into account the intensity of corruption: low to moderate levels of corruption lead to increased emigration of all groups, and especially of the highly skilled. But at high levels of corruption, emigration begins to decrease, indicating that intense corruption can act as a mobility constraint (Cooray & Schneider, 2016 ). All of these existing accounts, however, employ state-level measures of corruption by non-governmental organizations, such as those produced by Transparency International. Scholars have yet to harness micro-level survey data to explore the influence of personal corruption perception on the individual’s decision-making process.

The Land of Hopes and Dreams

Given that an individual has decided to emigrate, the next decision point is to choose a destination country. Advanced industrial democracies, such as those in the OECD, are major migrant-receiving countries, but so are Russia and several Gulf countries including Saudi Arabia, Qatar, and the United Arab Emirates (World Bank, 2016 ). A country’s constellation of political, economic, and social attributes is crucial to understanding an emigrant’s choice of destination. Potential migrants weigh all of these factors simultaneously when choosing a destination: will the destination allow political rights for the migrant and their children, is access to the labor market possible, and does the destination provide an opportunity for reunification with friends and family? In this section we focus on the non-economic factors that draw migrants to certain countries over others. In addition, we emphasize how skill level adds layers of complexity to a migrant’s calculus.

Political Environment, Both Formal and Informal

As noted earlier, traditional neoclassical models and their extensions place wage differentials and associated economic variables at the heart of a migrant’s choice. Gravity models posit that migrants choose a destination country based on their expected income—which itself is a function of the wage rate and the probability of finding employment in the destination—less the costs associated with moving (Ravenstein, 1885 ; Todaro, 1969 ; Borjas, 1989 ). A rigid focus on economic factors, however, blinds us to the empirical reality that a destination country’s political environment influences what destination a migrant chooses (Borjas, 1989 ). A country’s legal and political rights structure for migrants, as well as its level of tolerance for newcomers, is critical to migrants discriminating between an array of potential destinations. Fitzgerald, Leblang, and Teets ( 2014 ) argue, for example, that states with restrictive citizenship policies and strong radical right anti-immigrant parties will receive fewer migrants, while states with relatively liberal citizenship requirements and weak radical right political movements will receive more migrants. In the rational actor framework, migrants seek countries with hospitable political environments to maximize both their political representation in government and their access to labor market opportunities as a result of citizenship rights and social acceptance (Fitzgerald et al., 2014 ).

Using a broad sample of origin countries and 18 destination countries, they find that relative restrictiveness of citizenship policies and level of domestic support for the radical right are substantively important determinants of global migratory flows. Further, they find that these political variables condition a migrant’s choice of destination: the relative importance of economic factors such as the unemployment rate or the wage differential diminishes as a destination country’s political environment becomes more open for migrants. In other words, when migrants are choosing a destination country, political considerations may trump economic ones—a finding that is an important amendment to the primarily economics-focused calculus of the initial stage of the immigration decision.

However, prior to choosing and entering a destination country, a migrant must also navigate a country’s immigration policy—the regulation of both migrant entry and the rights and status of current migrants. While it is often assumed that a relatively more restrictive immigration policy deters entry, and vice versa, a lack of quantitative data has limited the ability of scholars to confirm this intuition cross-nationally. Money ( 1999 ) emphasizes that the policy output of immigration politics does not necessarily correlate with the outcome of international migrant flows. There are a number of unanswered questions in this field, including: is immigration policy a meaningful determinant of global flows of migration? Do certain kinds of immigration policies matter more than others? How does immigration policy interact with other political and economic factors, such as unemployment and social networks?

Only a handful of studies analyze whether or not immigration policy is a significant determinant of the size and character of migratory flows. Perhaps the most prominent answer to this question is the “gap hypothesis,” which posits that immigration rates continue to increase despite increasingly restrictive immigration policies in advanced countries (Cornelius & Tsuda, 2004 ). Some subsequent work seems to grant support to the gap hypothesis, indicating that immigration policy may not be a relevant factor and that national sovereignty as it relates to dictating migrant inflows has eroded significantly (Sassen, 1996 ; Castles, 2004 ). The gap hypothesis is not without its critics, with other scholars arguing that the existing empirical evidence actually lends it little or no support (Messina, 2007 ).

A more recent body of literature does indicate that immigration policy matters. Brücker and Schröder ( 2011 ), for example, find that immigration policies built to attract highly skilled migrants lead to higher admittance rates. They also show that diffusion processes cause neighboring countries to implement similar policy measures. Ortega and Peri ( 2013 ), in contrast to the gap hypothesis literature, find that restrictive immigration policy indeed reduces migrant inflows. But immigration policy can also have unintended effects on international migration: when entry requirements increase, migrant inflows decrease, but migrant outflows also decrease (Czaika & de Haas, 2016 ). This indicates that restrictive immigration policy may also lead to reduced circular migrant flows and encourage long-term settlement in destination countries.

Disaggregating immigration policy into its different components provides a clearer picture of how immigration policy may matter, and whether certain components matter more than others. Immigration policy is composed of both external and internal regulations. External regulations refer to policies that control migrant entry, such as eligibility requirements for migrants and additional conditions of entry. Internal regulations refer to policies that apply to migrants who have already gained status in the country, such as the security of a migrant’s legal status and the rights they are afforded. Helbling and Leblang ( 2017 ), using a comprehensive data set of bilateral migrant flows and the Immigration Policies in Comparison (IMPIC) data set, find that, in general, external regulations prove slightly more important in understanding migrant inflows (Helbling, Bjerre, Römer, & Zobel, 2017 ). This indicates that potential migrants focus more on how to cross borders, and less on the security of their status and rights once they settle. They do find, however, that both external and internal components of immigration are substantively important to international migrant flows.

The effects of policy, however, cannot be understood in isolation from other drivers of migration. Firstly, poor economic conditions and restrictive immigration policy are mutually reinforcing: when the unemployment rate is elevated, restrictive policies are more effective in deterring migrant flows. An increase in policy effectiveness in poor economic conditions suggests that states care more about deterring immigration when the economy is performing poorly. Secondly, a destination country’s restrictive immigration policy is more effective when migrants come from origin countries that have a common colonial heritage. This suggests that cultural similarities and migrant networks help to spread information about the immigration policy environment in the destination country. Social networks prove to be crucial in determining how much migrants know about the immigration policies of destination countries, regardless of other cultural factors such as colonial heritage or common language (Helbling & Leblang, 2017 ). In summary, more recent work supports the idea that immigration policy of destination countries exerts a significant influence on both the size and character of international migration flows. Much work remains to be done in terms of understanding the nuances of specific immigration policy components, the effect of policy change over time, and through what mechanisms immigration policy operates.

Transnational Social Networks

None of this should be taken to suggest that only political and economic considerations matter when a potential migrant contemplates a potential destination; perhaps one of the biggest contributions to the study of bilateral migration is the role played by transnational social networks. Migrating is a risky undertaking, and to minimize that risk, migrants are more likely to move to destinations where they can “readily tap into networks of co-ethnics” (Fitzgerald et al., 2014 , p. 410). Dense networks of co-ethnics not only help provide information about economic opportunities, but also serve as a social safety net which, in turn, helps decrease the risks associated with migration, including, but not limited to, finding housing and integrating into a new community (Massey, 1988 ; Portes & Böröcz, 1989 ; Portes, 1995 ; Massey et al., 1993 ; Faist, 2000 ; Sassen, 1995 ; Light, Bernard, & Kim, 1999 ). Having a transnational network of family members is quite important to destination choice; if a destination country has an immigration policy that emphasizes family reunification, migrants can use their familial connections to gain economically valuable permanent resident or citizenship status more easily than in other countries (Massey et al., 1993 , p. 450; Helbing & Leblang, 2017 ). When the migrant is comparing potential destinations, countries in which that migrant has a strong social network will be heavily favored in a cost–benefit analysis.

Note, however, that even outside of a strict rational actor framework with perfect information, transnational social networks still may be quite salient to destination choice. An interesting alternative hypothesis for the patterns we observe draws on theories from financial market behavior which focus on herding. Migrants choosing a destination observe the decisions of their co-ethnics who previously migrated and assume that those decisions were based on a relevant set of information, such as job opportunities or social tolerance of migrants. New migrants then choose the same destination as their co-ethnics not based on actual exchanges of valuable information, but based solely on the assumption that previous migration decisions were based on rational calculation (Epstein & Gang, 2006 ; Epstein, 2008 ). This is a classic example of herding, and the existing empirical evidence on the importance of transnational social networks cannot invalidate this alternative hypothesis. One could also explain social network effects through the lens of cumulative causation or feedback loops: the initial existence of connections in destination countries makes the act of migration less risky and attracts additional co-ethnics. This further expands migrant networks in a destination, further decreasing risk for future waves of migrants, and so on (Massey, 1990 ; Fussel & Massey, 2004 ; Fussel, 2010 ).

No matter the pathway by which social networks operate, the empirical evidence indicates that they are one of the most important determinants of destination choice. Potential migrants from Mexico, for example, who are able to tap into existing networks in the United States face lower direct, opportunity, and psychological costs of international migration (Massey & Garcia España, 1987 ). This same relationship holds in the European context; a study of Bulgarian and Italian migrants indicates that those with “social capital” in a destination community are more likely to migrate and to choose that particular destination (Haug, 2008 ). Studies that are more broadly cross-national in nature also confirm the social network hypothesis across a range of contexts and time periods (e.g., Clark et al., 2007 ; Hatton & Williamson, 2011 ; Fitzgerald et al., 2014 ).

Despite the importance of social networks, it is, again, important to qualify their role in framing the choice of destinations. It seems that the existence of co-ethnics in destination countries most strongly influences emigration when they are relatively few in number. Clark et al. ( 2007 ), in their study of migration to the United States, find that the “friends and relatives effect” falls to zero once the migrant stock in the United States reaches 8.3% of the source-country population. In addition, social networks alone cannot explain destination choice because their explanatory power is context-dependent. For instance, restrictive immigration policies limiting legal migration channels and family reunification may dampen the effectiveness of networks (Böcker, 1994 ; Collyer, 2006 ). Social networks are not an independent force, but also interact with economic and political realities to produce the global migration patterns we observe.

The Lens of Skill

For ease of presentation, we have up to now treated migrants as a relatively homogeneous group that faces similar push and pull factors throughout the decision-making process. Of course, not all migrants experience the same economic, political, and social incentives in the same way at each stage of the decision-making process. Perhaps the most salient differentiating feature of migrants is skill or education level. Generally, one can discuss a spectrum of skill and education level for current migrants, from relatively less educated (having attained a high school degree or less) to relatively more educated (having attained a college or post-graduate degree). The factors presented here that influence destination choice interact with a migrant’s skill level to produce differing destination choice patterns.

A migrant’s level of education, or human capital, often serves as a filter for the political treatment he or she anticipates in a particular destination country. For instance, the American public has a favorable view of highly educated migrants who hold higher-status jobs, while simultaneously having an opposite view of migrants who have less job training and do not hold a college degree (Hainmueller & Hiscox, 2010 ; Hainmueller & Hopkins, 2015 ). Indeed, the political discourse surrounding migration often emphasizes skill level and education as markers of migrants who “should be” admitted, across both countries and the ideological spectrum. 6 While political tolerance may be a condition of entry for migrants in the aggregate, the relatively privileged status of highly educated and skilled migrants in most destination countries may mean that this condition is not as salient.

While it is still an open question to what extent immigration policy influences international migration, it is clear that not all migrants face evenly applied migration restrictions. Most attractive destination countries have policies that explicitly favor highly skilled migrants, since these individuals often fill labor shortages in advanced industries such as high technology and applied science. Countries such as Australia, Canada, and New Zealand all employ so-called “points-based” immigration systems in which those with advanced degrees and needed skills are institutionally favored for legal entry (Papademetriou & Sumption, 2011 ). Meanwhile, the United States maintains the H-1B visa program, which is restricted by educational attainment and can only be used to fill jobs in which no native talent is available (USCIS). Even if destination countries decide to adopt more restrictive immigration policies, the move toward restriction has typically been focused on low-skilled migrants (Peters, 2017 ). In other words, even if immigration policy worldwide becomes more restrictive, this will almost certainly not occur at the expense of highly skilled migrants and will not prevent them choosing their most preferred destination.

Bring It on Home to Me

This article began by asserting that international labor migration is an important piece of globalization, as significant as cross-border flows of capital, goods, and services. This section argues that migrant flows enhance flows of capital and commodities. Uniquely modern conditions such as advanced telecommunications, affordable and efficient international travel, and the liberalization of financial flows mean that diasporas—populations of migrants living outside their countries of origin—and home countries often re-engage with each other (Vertovec, 2004 ; Waldinger, 2008 ). This section reviews some of the newest and most thought-provoking research on international labor migration, research that explores diaspora re-engagement and how that re-engagement alters international flows of income, portfolio and foreign direct investment (FDI), trade, and migratory flows themselves.

Remittances

As previously argued, migration is often driven by the prospect of higher wages. Rational, utility-maximizing migrants incur the cost of migration in order to earn increased income that they could not earn at home. But when migrants obtain higher wages, this additional increment to income is not always designated for individual consumption. Often, migrants use their new income to send remittances, direct transfers of money from one individual to another across national borders. Once a marginal financial flow, in 2015 remittances totaled $431 billion, far outpacing foreign aid ($135 billion) and nearly passing private debt and portfolio equity ($443 billion). More than 70% of total global remittances flow into developing countries (World Bank, 2016 ). In comparison with other financial flows such as portfolio investment and FDI, remittances are more impervious to economic crises, suggesting that they may be a countercyclical force to global downturns (Leblang, 2017 ).

Remittances represent one of the most common ways in which migrants re-engage with their homeland and alter both global income flows and distribution. Why do migrants surrender large portions of their new income, supposedly the very reason they migrated in the first place, to their families back home? New economics of labor migration (NELM) theory argues that immigration itself is motivated by a family’s need or demand for remittances—that remittances are an integral part of a family’s strategy for diversifying household financial risk (Stark & Bloom, 1985 ). Remittances “are a manifestation of informal contractual agreements between migrants and the households from which they move,” indicating that remitting is not an individual-level or purely altruistic action but rather occurs in a larger social context, that of one’s immediate or extended family (European Asylum Support Office, 2016 , p. 15).

The impact of migrant remittances on countries of origin is multifaceted yet somewhat ambiguous. Most scholarly work focuses on whether remittances positively or negatively influence existing economic conditions. A number of studies find that remittances modestly reduce poverty levels in developing countries (Adams & Page, 2005 ; Yang & Martinez, 2006 ; Acosta, Calderon, Fajnzybler, & Lopez, 2008 ; Lokshin, Bontch-Osmolovski, & Glinskaya, 2010 ). On other measures of economic well-being, such as growth, inequality, and health, the literature is quite mixed and no definitive conclusions can be drawn. For instance, some studies find that remittances encourage investment in human capital (Yang, 2008 ; Adams & Cuecuecha, 2010 ), while others find no such effect and suggest that families typically spend remittances on non-productive consumption goods (Chami, Fullenkamp, & Jahjah, 2003 ). Here we can only scratch the surface of the empirical work on remittances and economic outcomes. 7

Some of the most recent research in the field argues that remittances have a distinct political dimension, affecting regime support in developing countries and altering the conditions in which elections are held. Ahmed ( 2012 ), grouping remittances with foreign aid, argues that increased remittances allow autocratic governments to extend their tenure in office. These governments can strategically channel unearned government and household income to finance political patronage networks, which leads to a reduced likelihood of autocratic turnover, regime collapse, and mass protests against the regime. More recent research posits nearly the exact opposite: remittances are linked to a greater likelihood of democratization under autocratic regimes. Escriba-Folch, Meseguer, and Wright ( 2015 ) argue that since remittances directly increase household incomes, they reduce voter reliance on political patronage networks, undermining a key tool of autocratic stability.

Remittances may also play an important role in countries with democratic institutions, yet more research is needed to fully understand the conditions under which they matter and their substantive impact. Particularly, remittances may alter the dynamics of an election as an additional and external financial flow. There is evidence of political remittance cycles : the value of remittances spikes in the run-up to elections in developing countries. The total value of remittances to the average developing country increases by 6.6% during election years, and by 12% in elections in which no incumbent or named successor is running (O’Mahony, 2012 ). The effect is even larger in the poorest of developing countries. Finer-grained tests of this hypothesis provide additional support: using monthly and quarterly data confirms the existence of political remittance cycles, as well as using subnational rather than cross-national data (Nyblade & O’Mahony, 2014 ). However, these studies do not reveal why remittances spike, or what the effects of that spike are on electoral outcomes such as vote share, campaign financing, and political strategy.

Remittances represent a massive international financial flow that warrants more scholarly attention. While there are numerous studies on the relationship between remittances and key economic indicators, there remains much room for further work on their relationship to political outcomes in developing countries. Do remittances hasten the downfall of autocratic regimes, or do they contribute to autocratic stability? In democratic contexts, do remittances substantively influence electoral outcomes, and if so, which outcomes and how? Finally, do remittances prevent even more migration because they allow one “breadwinner from abroad” to provide for the household that remains in the homeland? While data limitations are formidable, these questions are important to the study of both international and comparative political economy.

Bilateral Trade

The argument that migrant or co-ethnic networks play an important role in international economic exchange is not novel. Greif ( 1989 , 1993 ) illustrates the role that the Maghrebi traders of the 11th century played in providing informal institutional guarantees that facilitated trade. This is but a single example. Cowen’s historical survey identifies not only the Phoenicians but also the “Spanish Jews [who] were indispensable for international commerce in the Middle Ages. The Armenians controlled the overland route between the Orient and Europe as late as the nineteenth century . Lebanese Christians developed trade between the various parts of the Ottoman empire” (Cowen, 1997 , p. 170). Rauch and Trindade ( 2002 ) provide robust empirical evidence linking the Chinese diaspora to patterns of imports and exports with their home country.

A variety of case studies document the importance of migrant networks in helping overcome problems of information asymmetries. In his study of Indian expatriates residing in the United States, Kapur ( 2014 ) documents how that community provides U.S. investors with a signal of the work ethic, labor quality, and business culture that exists in India. Likewise, Weidenbaum and Hughes ( 1996 ) chronicle the Bamboo Network—the linkages between ethnic Chinese living outside mainland China and their homeland—and how these linkages provide superior access to information and opportunities for investment.

Connections between migrant communities across countries affect cross-national investment even when these connections do not provide information about investment opportunities. In his work on the Maghrebi traders of the 11th century , Greif argues that this trading network was effective because it was able to credibly threaten collective punishment by all merchants if even one of them defected (Greif, 1989 , 1993 ). Grief shows that this co-ethnic network was able to share information regarding the past actions of actors (they could communicate a reputation)—something that was essential for the efficient functioning of markets in the absence of formal legal rules. Weidenbaum and Hughes reach a similar conclusion about the effectiveness of the Bamboo Network, remarking that “if a business owner violates an agreement, he is blacklisted. This is far worse than being sued, because the entire Chinese networks will refrain from doing business with the guilty party” (Hughes, 1996 , p. 51).

Migrants not only alter the flow of income by remitting to their countries of origin, but also influence patterns of international portfolio investment and FDI. Most existing literature on international capital allocation emphasizes monadic factors such as the importance of credible commitments and state institutional quality, failing to address explicitly dyadic phenomena that may also drive investment. Diaspora networks, in particular, facilitate cross-border investment in a number of ways. They foster a higher degree of familiarity between home and host countries, leading to a greater preference for investment in specific countries. Diaspora networks can also decrease information asymmetries in highly uncertain international capital markets in two ways. Firstly, they can provide investors with salient information about their homeland, such as consumer tastes, that can influence investment decision-making. Secondly, they can share knowledge about investment opportunities, regulation and procedures, and customs that decrease transaction costs associated with cross-border investment (Leblang, 2010 ). This place of importance for migrants suggests to the broader international political economy literature the importance of non-institutional mechanisms for channeling economic activity.

Although the hypothesized link between migrants and international investment has only recently been identified, the quantitative evidence available supports that hypothesis. Leblang ( 2010 ), using dyadic cross-sectional data, finds that diaspora networks “have both a substantively significant effect and a statistically significant effect on cross-border investment,” including international portfolio investment and FDI (p. 584). The effect of bilateral migratory flows correlates positively with the degree of information asymmetry: when informational imperfections are more pervasive in a dyad, migrants (especially the highly skilled) play a disproportionately large role in international capital allocation (Kugler, Levinthal, & Rapoport, 2017 ). Other quantitative studies find substantively similar results for FDI alone (e.g., Javorcik, Özden, Spatareanu, & Neagu, 2011 ; Aubry, Rapoport, & Reshef, 2016 ).

Many questions still remain unanswered. Firstly, does the effect of migrants on investment follow the waves of the global economy, or is it countercyclical as remittances have been shown to be? Secondly, how does this additional investment, facilitated by migrants, affect socioeconomic outcomes such as inequality, poverty, and economic development (Leblang, 2010 )? Does the participation of migrants lead to more successful FDI projects in developing countries because of their ability to break down information barriers? Within portfolio investment, do migrants lead to a preference for certain asset classes over others, and if so, what are the effects on bilateral and international capital markets? These are just a few directions in an area ripe for additional research.

Return Migration and Dual Citizenship

Besides financial flows, migrants themselves directly contribute to global flows of capital by returning to their countries of origin in large numbers. This phenomenon of return migration—or circular migration—can come in a few temporal forms, including long-term migration followed by a permanent return to a country of origin, or repeat migration in which a migrant regularly moves between destination and origin countries (Dumont & Spielvogel, 2008 ). While comparable data on return migration is scarce, some reports suggest that 20% to 50% of all immigrants leave their destination country within five years after their arrival (e.g., Borjas & Bratsberg, 1996 ; Aydemir & Robinson, 2008 ; Bratsberg, Raaum, & Sørlie, 2007 ; Dustmann & Weiss, 2007 ). An independent theoretical and empirical account of return migration does not yet exist in the literature and is beyond the scope of this paper. But in the rational actor framework, motivations to return home include a failure to realize the expected benefits of migration, changing preferences toward a migrant’s home country, achievement of a savings or other economic goal, or the opening of additional employment opportunities back home due to newly acquired experience or greater levels of economic development (Dumont & Spielvogel, 2008 ).

While most migration literature treats the country of origin as a passive actor that only provides the conditions for migration, new literature on return migration gives home country policies pride of place. Origin countries can craft policies that encourage diaspora re-engagement, incentivizing individuals to return home. Dual citizenship, for example, is an extension of extraterritorial rights, allowing migrants to retain full legal status in their home country. Dual citizenship “decreases the transaction costs associated with entering a host country’s labor market and makes it easier for migrants to return home” (Leblang, 2017 , p. 77). This leads migrants to invest their financial resources in the form of remittances back home as well as their valuable human capital. When states provide such extraterritorial rights, expatriates are 10% more likely to remit and 3% more likely to return home. Dual citizenship is also associated with a doubling of the dollar amount of remittances received by a home country (Leblang, 2017 ). These striking results suggest that in addition to the power of migrants to affect cross-border flows of money and people, countries of origin can also play a significant role.

Conclusion and Future Directions

This brief article has attempted to synthesize a broad range of literature from political science, economics, sociology, migration studies, and more to construct an account of international labor migration. To do so, the migratory process was broken down into distinct stages and decision points, focusing particularly on the decision to migrate, destination choice, and the re-engagement of migrants with their homeland. In doing so, the article also discussed the interlinkages of international migration with other fields of study in international political economy, including cross-border financial flows, trade, and investment. Through a multiplicity of approaches, we have gained a greater understanding of why people decide to move, why they decide to move to one country over another, and how and why they engage with the global economy and their homeland. Despite this intellectual progress, there remain many paths for future research at each stage of the migratory process; we highlight just a few of them here.

We know that income differentials, social ties, and local political conditions are important variables influencing the migration process. Yet the question remains: why do a small but growing number of people choose to leave while the overwhelming majority of people remain in their country of birth? Here, individual- or family-level subjective characteristics may be significant. There are a handful of observational studies that explore the relationship between subjective well-being or life satisfaction and the intention to migrate, with the nascent consensus being that life dissatisfaction increases the intention to migrate (Cai, Esipova, Oppenheimer, & Feng, 2014 ; Otrachshenko & Popova, 2014 ; Nikolova & Graham, 2015 ). But more research on intrinsic or subjective measures is needed to understand (a) their independent importance more fully and (b) how they interact with objective economic, political, and social factors. For instance, do those who are more optimistic migrate in larger numbers? Do minority individuals who feel they live in an environment in which diversity is not accepted feel a greater urge to leave home? Synthesizing these types of subjective variables and perceptions with the more prominent gravity-style models could result in a more complete picture of the international migration process.

For the “typical” migrant, one who is relatively less educated than the population in the chosen destination and does not have specialized skills, social networks are key to minimizing the risk of migrating and quickly tapping into economic opportunities in destination countries. Does this remain true for those who are highly educated? Although little empirical research exists on the topic, greater human capital and often-accompanying financial resources may operate as a substitute for the advantages offered by social networks, such as housing, overcoming linguistic barriers, and finding gainful employment. This would indicate that the “friends and family effect” is not as influential for this subset of migrants. Economic considerations, such as which destination offers the largest relative wage differential, or political considerations, such as the ease of quickly acquiring full citizenship rights, may matter more for the highly skilled. Neoclassical economic models of migration may best capture the behavior of migrants who hold human capital and who have the financial resources to independently migrate in a way that maximizes income or utility more broadly.

Since we have focused on international migration as a series of discrete decision points in this article, we have perhaps underemphasized the complexity of the physical migration process. In reality, migrants often do not pick a country and travel directly there, but travel through (perhaps several) countries of transit such as Mexico, Morocco, or Turkey along the way (Angel Castillo, 2006 ; Natter, 2013 ; Icduygu, 2005 ). There is little existing theoretical work to understand the role of transit countries in the migratory process, with much of it focusing on the potential for cooperation between destination and transit countries in managing primarily illegal immigration (Kahana & Lecker, 2005 ; Djajic & Michael, 2014 ; Djajic & Michael, 2016 ). Another related strand of the literature focuses on how wealthy destination countries are “externalizing” their immigration policy, encompassing a broader part of the migratory process than simply crossing a physically demarcated border (Duvell, 2012 ; Menjivar, 2014 ). But many questions remain, such as the following: how do we understand those who desire to enter, say, the United States, but instead relocate permanently to Mexico along the way? How do countries of transit handle the pressure of transit migrants, and how does this affect economic and political outcomes in these countries?

Finally, the focus of nearly all literature on international migration (and this article as a byproduct) implicitly views advanced economies as the only prominent destinations. However, this belies the fact that 38% of all migration stays within the “Global South” (World Bank, 2016 ). While there is certainly some literature on this phenomenon (see Ratha & Shaw, 2007 ; Gindling, 2009 ; Hujo & Piper, 2007 ), international political economy scholars have yet to sufficiently tackle this topic. The overarching research question here is: do the same push and pull factors that influence the decision to migrate and destination choice apply to those who migrate within the Global South? Do we need to construct new theories of international migration with less emphasis on factors such as wage differentials and political tolerance, or are these sufficient to understand this facet of the phenomenon? If we fail to answer these questions, we may miss explaining a significant proportion of international migration with its own consequences and policy implications.

• Abreu, A. (2012). The New Economics of Labor Migration: Beware of Neoclassicals Bearing Gifts. Forum for Social Economics , 41 (1), 46–67.
• Acosta, P. , Calderon, C. , Fajnzybler, P. , & Lopez, H. (2008). What Is the Impact of International Remittances on Poverty and Inequality in Latin America? World Development , 36 (1), 89–114.
• Adams, R., Jr. (2011). Evaluating the Economic Impact of International Remittances on Developing Countries Using Household Surveys: A Literature Review. Journal of Development Studies , 47 (6), 809–828.
• Adams, R., Jr. , & Cuecuecha, A. (2010). Remittances, Household Expenditure and Investment in Guatemala. World Development , 38 (11), 1626–1641.
• Adams, R., Jr. , & Page, J. (2005). Do International Migration and Remittances Reduce Poverty in Developing Countries? World Development , 33 (10), 1645–1669.
• Ahmed, F. Z. (2012). The Perils of Unearned Foreign Income: Aid, Remittances, and Government Survival. American Political Science Review , 106 (1), 146–165.
• Akerman, S. (1976). Theories and Methods of Migration Research. In H. Runblom & H. Norman (Eds.), From Sweden to America: A History of the Migration . Minneapolis: University of Minnesota Press.
• Angel Castillo, M. (2006). Mexico: Caught Between the United States and Central America . Migration Policy Institute.
• Aubry, A. , Rapoport, H. , & Reshef, A. (2016). Migration, FDI, and the Margins of Trade. Mimeo . Paris School of Economics.
• Aydemir, A. , & Robinson, C. (2008). Global Labour Markets, Return, and Onward Migration. Canadian Journal of Economics , 41 (4), 1285–1311.
• Böcker, A. (1994). Chain Migration over Legally Closed Borders: Settled Immigrants as Bridgeheads and Gatekeepers. Netherlands Journal of Social Sciences , 30 (2), 87–106.
• Borjas, G. J. (1989). Economic Theory and International Migration. International Migration Review , 23 (3), 457–485.
• Borjas, G. J. , & Bratsberg, B. (1996). Who Leaves? The Outmigration of the Foreign-Born. Review of Economics and Statistics , 41 (4), 610–621.
• Bratsberg, B. , Raaum, O. , & Sørlie, K. (2007). Foreign-Born Migration to and from Norway. In Ç. Özden & M. Schiff (Eds.), International Migration, Economic Development and Policy . New York: Palgrave Macmillan.
• Brücker, H. , & Schröder, P. J. H. (2011). Migration regulation contagion. European Union Politics , 12 (3), 315–335.
• Cai, R. , Esipova, N. , Oppenheimer, M. , & Feng, S. (2014). International Migration Desires Related to Subjective Well-Being. IZA Journal of Migration , 3 (8), 1–20.
• Castles, S. (2004). Why Migration Policies Fail. Ethnic and Racial Studies , 27 (2), 205–227.
• Cazzuffi, C. , & Modrego, F. (2018). Place of Origin and Internal Migration Decisions in Mexico. Spatial Economic Analysis , 13 (1), 1–19.
• Chami, R. , Fullenkamp, C. , & Jahjah, S. (2003). Are Immigrant Remittance Flows a Source of Capital for Development ? IMF Working Paper 03/189.
• Clark, X. , Hatton, T. J. , & Williamson, J. G. (2007). Explaining US Immigration, 1971–1998. Review of Economics and Statistics , 89 (2), 359–373.
• Clemens, M. A. (2014). Does Development Reduce Migration ? IZA Discussion Paper No. 8592.
• Collier, P. , & Hoeffler, A. (2014). Migration, Diasporas and Culture: An Empirical Investigation . Unpublished manuscript.
• Collyer, M. (2006). When Do Social Networks Fail to Explain Migration? Accounting for the Movement of Algerian Asylum-Seekers to the UK. Journal of Ethnic and Migration Studies , 31 (4), 699–718.
• Constant, A. , & Massey, D. S. (2002). Return Migration by German Guestworkers: Neoclassical versus New Economic Theories. International Migration , 4 0(4), 5–38.
• Cooray, A. , & Schneider, F. (2016). Does Corruption Promote Emigration? An Empirical Examination. Journal of Population Economics , 29 , 293–310.
• Cornelius, W. A. , & Tsuda, T. (2004). Controlling Immigration: The Limits of Government Intervention . Stanford, CA: Stanford University Press.
• Cowen, R. (1997). Global Diasporas: An Introduction . London: Routledge.
• Czaika, M. , & de Haas, H. (2016). The Effect of Visas on Migration Processes. International Migration Review , 51 (4), 893–926.
• Dao, T. H. , Docquier, F. , Parsons, C. , & Peri, G. (2018). Migration and Development: Dissecting the Anatomy of the Mobility Transition. Journal of Development Economics , 132 , 88–101.
• Dao, T. H. , Docquier, F. , Parsons, C. , & Peri, G. (2016). Migration and Development: Dissecting the Anatomy of the Mobility Transition . IZA Discussion Paper No. 10272.
• De Haas, H. (2007). Turning the Tide? Why Development Will Not Stop Migration. Development and Change , 38 , 819–841.
• Dimant, E. , Krieger, T. , & Meierrieks, D. (2013). The Effect of Corruption on Migration, 1985–2000. Applied Economics Letters , 20 (13), 1270–1274.
• Djajic, S. , & Michael, M. S. (2014). Controlling Illegal Immigration: On the Scope for Cooperation with a Transit Country. Review of International Economics , 22 (4), 808–824.
• Djajic, S. , & Michael, M. S. (2016). Illegal Immigration, Foreign Aid, and the Transit Countries. CESifo Economic Studies , 572–593.
• Dumont, J.-C. , & Spielvogel, G. (2008). Return Migration: A New Perspective. International Migration Outlook 2008 . OECD, 166–212.
• Dustmann, C. , & Okatenko, A. (2014). Out-Migration, Wealth Constraints, and the Quality of Local Amenities. Journal of Development Economics , 110 , 52–63.
• Dustmann, C. , & Weiss, Y. (2007). Return Migration: Theory and Empirical Evidence from the UK. British Journal of Industrial Relations , 45 (2), 236–256.
• Duvell, F. (2012). Transit Migration: A Blurred and Politicized Concept. Population, Space and Place , 18 , 415–427.
• Easterlin, R. A. (1961). Influences in European Overseas Emigration Before World War I. Economic Development and Cultural Change , 9 (3), 331–351.
• Epstein, G. (2008). Herd and Network Effects in Migration Decision-Making. Journal of Ethnic and Migration Studies , 34 (4), 567–583.
• Epstein, G. , & Gang, I. (2006). The Influence of Others on Migration Plans. Review of Development Economics , 10 (4), 652–665.
• Escriba-Folch, A. , Meseguer, C. , & Wright, J. (2015). Remittances and Democratization. International Studies Quarterly , 59 (3), 571–586.
• European Asylum Support Office . (2016). The Push and Pull Factors of Asylum-Related Migration: A Literature Review .
• Faist, T. (2000). The Volume and Dynamics of International Migration and Transnational Social Space . New York: Oxford University Press.
• Fitzgerald, J. , Leblang, D. , & Teets, J. C. (2014). Defying the Law of Gravity: The Political Economy of International Migration. World Politics , 66 (3), 406–445.
• Fussel, E. (2010). The Cumulative Causation of International Migration in Latin America. Annals of the American Academy of Political and Social Science , 630 , 162–177.
• Fussel, E. , & Massey, D. (2004). The Limits to Cumulative Causation: International Migration from Mexican Urban Areas. Demography , 41 (1), 151–171.
• Gindling, T. H. (2009). South­–South Migration: The Impact of Nicaraguan Immigrants on Earnings, Inequality, and Poverty in Costa Rica. World Development , 37 (1), 116–126.
• Gould, J. D. (1979). European Inter-Continental Emigration 1815–1914: Patterns and Causes. Journal of European Economic History , 8 (3), 593–679.
• Greif, A. (1989). Reputation and Coalitions in Medieval Trade: Evidence on the Maghribi Traders. Journal of Economic History , 49 (4), 857–882.
• Greif, A. (1993). Contract Enforceability and Economic Institutions in Early Trade: The Maghribi Traders’ Coalition. American Economic Review , 83 (3), 525–548.
• Grogger, J. , & Hanson, G. H. (2011). Income Maximization and the Selection and Sorting of International Migrants. Journal of Development Economics , 95 , 42–57.
• Gupta, S. , Davoodi, H. , & Tiongson, E. (2001). Corruption and the Provision of Healthcare and Education Services. In A. Jain (Ed.), The Political Economy of Corruption . New York: Routledge.
• Hainmueller, J. , & Hiscox, M. J. (2010). Attitudes toward Highly Skilled and Low-Skilled Immigration: Evidence from a Survey Experiment. American Political Science Review , 104 (1), 61–84.
• Hainmueller, J. , & Hopkins, D. J. (2015). The Hidden Immigration Consensus: A Conjoint Analysis of Attitudes toward Immigrants. American Journal of Political Science , 59 (3), 529–548.
• Harris, J. R. , & Todaro, M. P. (1970). Migration, Unemployment and Development: A Two-Sector Analysis. American Economic Review , 60 (1), 126–142.
• Hatton, T. J. , & Williamson, J. G. (1994). What Drove the Mass Migrations from Europe in the Late Nineteenth Century? Population and Development Review , 20 (3), 533–559.
• Hatton, T. J. , & Williamson, J. G. (2011). Are Third World Emigration Forces Abating? World Development , 39 (1), 20–32.
• Haug, S. (2008). Migration Networks and Migration Decision-Making. Journal of Ethnic and Migration Studies , 34 (4), 585–605.
• Helbling, M. , Bjerre, L. , Römer, F. , & Zobel, M. (2017). Measuring Immigration Policies: The IMPIC-Database. European Political Science, 16 (1), 79–98.
• Helbling, M. , & Leblang, D. (forthcoming). Controlling Immigration? European Journal of Political Research .
• Hirschman, A. O. (1970). Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and Sates . Cambridge, MA: Harvard University Press.
• Hirsh, A. O. (1978). “Exit, Voice, and the State.” World Politics , 31 (1), 90–107.
• Hujo, K. , & Piper, N. (2007). South–South Migration: Challenges for Development and Social Policy. Development , 50 (4), 1–7.
• Icduygu, A. (2005). Transit Migration in Turkey: Trends, Patterns, and Issues . Euro-Mediterranean Consortium for Applied Research on International Migration Research Report 2005/04.
• Javorcik, B. , Özden, C. , Spatareanu, M. , & Neagu, C. (2011). Migrant Networks and Foreign Direct Investment. Journal of Development Economics , 94 , 231–241.
• Kahana, N. , & Lecker, T. (2005). Competition as a Track for Preventing Illegal Immigration. Economics of Governance , 6 , 33–39.
• Kapur, D. (2014). Political Effects of International Migration. Annual Review of Political Science , 17 , 479–502.
• Kugler, M. , Levinthal, O. , & Rapoport, H. (2017). Migration and Cross-Border Financial Flows . World Bank Policy Research Working Paper 8034.
• Leblang, D. (2010). Familiarity Breeds Investment: Diaspora Networks and International Investment. American Political Science Review , 104 (3), 584–600.
• Leblang, D. (2017). Harnessing the Diaspora: Dual Citizenship, Migrant Return, and Remittances. Comparative Political Studies , 50 (1), 75–101.
• Lewis, A. W. (1954). Economic Development with Unlimited Supplies of Labor. The Manchester School , 22 (2), 139–191.
• Lichter, D. T. (1983). Socioeconomic Returns to Migration among Married Women. Social Forces , 62 (2), 487–503.
• Light, I. , Bernard, R. B. , & Kim, R. (1999). Immigrant Incorporation in the Garment Industry of Los Angeles. International Migration Review , 33 (1), 5–25.
• Lokshin, M. , Bontch-Osmolovski, M. , & Glinskaya, E. (2010). Work-Related Migration and Poverty Reduction in Nepal. Review of Development Economics , 14 (2), 323–332.
• Massey, D. S. (1988). Economic Development and International Migration in Comparative Perspective. Population and Development Review , 14 (3), 383–413.
• Massey, D. S. (1990). Social Structure, Household Strategies, and the Cumulative Causation of Migration. Population Index , 56 (1), 3–26.
• Massey, D. S. , Arango, J. , Hugo, G. , Kouaouci, A. , Pellegrino, A. , & Taylor, J. E. (1993). Theories of International Migration: A Review and Appraisal. Population and Development Review , 19 (3), 431–466.
• Massey, D. S. , & Garcia España, F. (1987). The Social Process of International Migration. Science , 237 (4816), 733–738.
• Mauro, P. (1998). Corruption and the Composition of Government Expenditure. Journal of Public Economics , 69 , 263–279.
• Menjivar, C. (2014). Immigration Law Beyond Borders: Externalizing and Internalizing Border Controls in an Era of Securitization. Annual Review of Law and Social Science , 10 , 353–369.
• Messina, A. M. (2007). The Logics and Politics of Post-WWII Migration to Western Europe . Cambridge: Cambridge University Press.
• Mincer, J. (1978). Family Migration Decisions. Journal of Political Economy , 86 (51), 749–773.
• Miller, M. K. , & Peters, M. E. (2018). Restraining the Huddled Masses: Migration Policy and Autocratic Survival . British Journal of Political Science .
• Mo, P. H. (2001). Corruption and Economic Growth. Journal of Comparative Economics , 29 , 66–79.
• Money, J. (1999). Fences and Neighbors: The Political Geography of Immigration Control . Ithaca, NY: Cornell University Press.
• Morrison, D. R. , & Lichter, D. T. (1988). Migration and Female Employment. Journal of Marriage and Family , 50 (1), 161–172.
• Natter, K. (2013). The Formation of Morocco’s Policy Towards Irregular Migration (2000–2007): Political Rationale and Policy Processes. International Migration , 52 (5), 15–28.
• Nikolova, M. , & Graham, C. (2015). Well-Being and Emigration Intentions: New Evidence from the Gallup World Poll. Unpublished manuscript.
• Nyblade, B. , & O’Mahony, A. (2014). Migrants Remittances and Home Country Elections: Cross-National and Subnational Evidence. Studies in Comparative International Development , 49 (1), 44–66.
• O’Mahony, A. (2012). Political Investment: Remittances and Elections. British Journal of Political Science , 43 (4), 799–820.
• Ortega, F. , & Peri, G. (2013). The Effect of Income and immigration Policies on International Migration. Migration Studies , 1 (1), 47–74.
• Otrachshenko, V. , & Popova, O. (2014). Life (Dis)satisfaction and the Intention to Migrate: Evidence from Central and Eastern Europe. Journal of Socio-Economics , 48 , 40–49.
• Papademetriou, D. , & Sumption, M. (2011). Rethinking Points Systems and Employer-Based Selected Immigration . Migration Policy Institute.
• Peters, M. (2017). Trading Barriers: Immigration and the Remaking of Globalization . Princeton, NJ: Princeton University Press.
• Poprawe, M. (2015). On the Relationship between Corruption and Migration: Evidence from a Gravity Model of Migration. Public Choice , 163 , 337–354.
• Portes, A. (Ed.). (1995). The Economic Sociology of Immigration . New York: Russell Sage Foundation.
• Portes, A. , & Böröcz, J. (1989). Contemporary Immigration: Theoretical Perspectives on its Determinant and Modes of Incorporation. International Migration Review , 23 (3), 606–630.
• Rapoport, H. , & Docquier, F. (2006). The Economics of Migrants’ Remittances. In S.-C. Kolm & J. M. Ythier (Eds.), Handbook on the Economics of Giving, Altruism and Reciprocity . New York: Elsevier-North Holland.
• Ratha, D. , & Shaw, W. (2007). South-South Migration and Remittances . World Bank WP 102.
• Rauch, J. E. , & Trindade, V. (2002). Ethnic Chinese Networks in International Trade. Review of Economics and Statistics , 84 (1), 116–130.
• Ravenstein, E. G. (1885). The Laws of Migration. Journal of the Royal Statistical Society of London , 48 (2), 167–235.
• Sassen, S. (1995). Immigration and Local Labour Markets. In A. Portes (Ed.), The Economic Sociology of Immigration . New York: Russell Sage Foundation.
• Sassen, S. (1996). Losing Control? Sovereignty in the Age of Globalization . New York: Columbia University Press.
• Schultz, T. W. (1961). Investment in Human Capital. American Economic Review , 51 (1), 1–17.
• Severin, T. , & Martin, M. (2018). German Parties Edge Closer to Coalition with Migration Deal . Reuters, February 2.
• Sjaastad, L. A. (1962). The Costs and Returns of Human Migration. Journal of Political Economy , 70 (5), 80–93.
• Stark, O. (1984). Rural-To-Urban Migration in LDCs: A Relative Deprivation Approach. Economic Development and Cultural Change , 32 (3), 475–486.
• Stark, O. , & Bloom, D. E. (1985). The New Economics of Labor Migration. American Economic Review , 75 (2), 173–178.
• Stark, O. , & Levhari, D. (1982). On Migration and Risk in LDCs. Economic Development and Cultural Change , 31 (1), 191–196.
• Stark, O. , & Taylor, J. E. (1991). Migration Incentives, Migration Types: The Role of Relative Deprivation. The Economic Journal , 101 (408), 1163–1178.
• Stark, O. , & Yitzhaki, S. (1988). Migration as a Response to Relative Deprivation. Journal of Population Economics , 1 (1), 57–70.
• Taylor, J. E. (1999). The New Economics of Labour Migration and the Role of Remittances in the Migration Process. International Migration , 37 (1), 63–88.
• Todaro, M. P. (1969). A Model of Labor Migration and Urban Employment in Less Developed Countries. American Economic Review , 59 (1), 138–148.
• Tomaske, J. A. (1971). The Determinants of Intercountry Differences in European Emigration: 1881–1900. Journal of Economic History , 31 (4), 840–853.
• Transparency International . (2018). What is corruption
• United Kingdom Independence Party . (2015). UKIP Launches Immigration Policy .
• United Nations Population Division . (2012). Trends in Total Migrant Stock .
• United Nations Population Division . (2013). International Migration: Age and Sex Distribution. Population Facts, September.
• United States Citizenship and Immigration Services . (2018). H-1B Fiscal Year 2018 Cap Season .
• USA Today . (2014) (20 November). Full Text: Obama’s Immigration Speech .
• Vanderkamp, J. (1971). Migration Flows, Their Determinants and the Effects of Return Migration. Journal of Political Economy , 79 (5), 1012–1031.
• Vertovec, S. (2004). Migrant Transnationalism and Modes of Transformation. International Migration Review , 38 (3), 970–1001.
• Waldinger, R. (2008). Between “Here” and “There”: Immigrant Cross-Border Activities and Loyalties. International Migration Review , 42 (Spring), 3–29.
• Weidenbaum, M. , & Hughes, S. (1996). The Bamboo Network: How Expatriate Chinese Entrepreneurs are Creating a New Economic Superpower in Asia . New York: Martin Kessler Books.
• World Bank . (2016). Migration and Remittances Factbook 2016 . 3rd ed. Washington, DC: World Bank Group.
• Yang, D. (2008). International Migration, Remittances, and Household Investment: Evidence from Philippine Migrants’ Exchange Rate Shocks. The Economic Journal , 118 (528), 591–630.
• Yang, D. , & Martinez, C. (2006). Remittances and Poverty in Migrants Home Areas: Evidence from the Philippines. In C. Ozden & M. Schiff (Eds.), International Migration, Remittances and the Brain Drain . Washington, DC: World Bank.
• Zaiceva, A. , & Zimmerman, K. (2014). Migration and the Demographic Shift. IZA Discussion Paper #8743 .
• Zelinsky, W. (1971). The Hypothesis of the Mobility Transition. Geographical Review , 61 (2), 219–249.

1. Our use of the term international labor migration follows academic and legal conventions; we use the term migration to refer to the voluntary movement of people across national borders, either in a temporary or permanent fashion. This excludes any discussion of refugees, asylum seekers, or any other groups that are forced to migrate.

2. We do not have space in this article to delve into the theoretical and empirical work unpacking the effect of demographic characteristics—age, gender, marital status, household size, and so forth on the migration decision and on subsequent flows of migrants. For comprehensive reviews, see Lichter ( 1983 ), Morrison and Lichter ( 1988 ); United Nations Population Division ( 2013 ); and Zaiceva and Zimmerman ( 2014 ).

3. Zelinsky ( 1971 ) originally identified this relationship and termed it mobility transition curve . A wealth of empirical work supports Zelinsky’s descriptive theory in a number of contexts (see Akerman, 1976 ; Gould, 1979 ; Hatton & Williamson, 1994 ; and Dao et al., 2016 ).

4. For a review of the arguments as well as some empirical tests, see Miller and Peters ( 2018 ) and Docquier, Lodigiani, Rapoport, and Schiff ( 2018 ).

5. Transparency International. “What is corruption?”

6. For example, former United Kingdom Independence Party leader Nigel Farage has called for the United Kingdom to adopt an immigration system that only allows in highly skilled migrants (“UKIP launches immigration policy”). In 2014, US President Barack Obama emphasized that he wanted to attract international students to American universities and that they “create jobs, businesses, and industries right here in America” (USA Today: “Full text: Obama’s immigration speech”). A key issue in Germany’s 2018 government formation was the creation of skill-based migration laws (Severin & Martin, 2018 ).

7. For a more comprehensive review, see Rapoport and Docquier ( 2006 ); and Adams ( 2011 ).

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COVID-19 Crisis: Political and Economic Aftershocks

• Chris Miller
• March 5, 2020
• National Security Program

Nearly 100,000 people worldwide have been diagnosed with COVID-19, the new coronavirus that emerged in Wuhan, China, in late 2019. The human toll of the new virus has already been vast, with 3,300 deaths worldwide attributed to the virus and probably at least hundreds more that were unknowingly caused by undiagnosed infections. As medical experts struggle to limit the virus’ spread and devise treatments, it is already clear that the ramifications of COVID-19 will be visible beyond the sphere of public health. From Wuhan to Washington, the virus will have a major political and economic impact.

The most obvious economic effect of the virus is in China, which from late January has implemented an extraordinary quarantine, the likes of which had not been seen for decades. Not only Wuhan—a city of over 10 million people—but much of the country was subjected to quarantines of varying severity, preventing work and travel. In February, according to recently released data , Chinese economic activity was only a fraction of its usual level. As the world’s second largest economy, a crisis in China is guaranteed to have a global effect—as Chinese tourists stay home, Chinese consumers buy less, and Chinese factories fail to supply global markets.

Economic Impact

The virus’ economic impact did not stop in China. To understand the global effects, start with the countries to which the virus’ spread was first detected after it jumped from Wuhan across international borders. Japan and South Korea have reported substantial local spread of the virus, though South Korea’s confirmed infection numbers are far higher than Japan’s because Seoul has instituted a regime of mass testing, in contrast to Japan, which is only testing high-risk patients. In both countries, the virus will have major economic ramifications. Both trade extensively with China and were already suffering from China’s sharp quarantine-induced economic slowdown. Local quarantines and school shutdowns in South Korea and Japan have been far less disruptive than China’s mass shutdown, but will nevertheless slow these two countries—the world’s twelfth and third largest economies—substantially. The only outlier seems to be Taiwan, deeply integrated with China’s economy, yet having nevertheless succeeded so far in avoiding mass outbreaks.  

As the virus spread to Europe, the economic impact did, too. Italy, the European country with the most confirmed cases, is also one of the European countries least able to deal with the economic fallout. Because of its large debt burden, Italy is prohibited by European Union rules from running a substantial budget deficit. It will struggle to boost its economy without additional spending. Meanwhile, the European Central Bank has already cut its main interest rate to negative levels, so it is unlikely to follow the U.S. Federal Reserve in reducing interest rates to deal with the crisis.

The United States, which appears on a trajectory toward levels of infection similar to that of Italy, has more room with which to battle the economic effects of the coronavirus, if policymakers choose to use them. The Federal Reserve has already reduced its main interest rate by 0.5 percentage points, which should encourage businesses and consumers to borrow and spend. Congress just approved some additional spending, though the $8 billion package is tiny compared to the overall size of the U.S. economy, and so will have no macro effect. If Congress wanted to borrow and spend more, it could easily do so. If the United States wanted to borrow and spend more to deal with COVID-19, it easily could. Over the past week, the U.S. government’s borrowing costs have fallen substantially as investors have bought up U.S. government bonds, seeking safe assets in a time of uncertainty.

Political Impact

The political effects of the coronavirus in advanced economies could be as substantial as the economic effects. Leaders from South Korean President Moon Jae-in, Japanese Prime Minister Shinzō Abe, and U.S. President Donald Trump have been sharply criticized for mishandling the virus and allowing cases to increase. Speculation is growing that Prime Minister Abe may be forced to leave office earlier than expected, while if the coronavirus causes an economic slowdown or recession in the United States, then it could reduce the chances that President Trump is reelected. President Moon, meanwhile, faces a petition signed by hundreds of thousands of citizens to remove him from office. Taiwan seems to be the only country where the government’s approval rating has increased, thanks to deft handling of the virus by the Tsai Ing-wen administration.

Other centers of the coronavirus outbreak are far less capable of dealing with the virus. There is little hard data about the virus’ spread within North Korea, but the government has limited capacity to test or treat infections, and the virus could well spread out of control. Iran, too, has had a devastating outbreak, with reports suggesting that several dozen members of parliament are infected, along with probably thousands of others.

The broadest impact of the virus in political and economic terms is likely to be in the epidemic’s epicenter: China. There is little reason to expect that the Chinese Communist Party’s apparatus of censorship and repression can clamp down on dissent—even though it is obvious that the Communist Party covered up the virus’ impact in its early weeks, allowing it to spread. The bigger question is whether and how China can get its economy back running now that the virus is under control.

It has now been several weeks since Xi Jinping called for a full-scale resumption of economic activity, yet the economy is still working below normal capacity. Moreover, the methods by which Beijing is trying to restart the economy—encouraging local governments and state-owned firms to borrow and spend more—only exacerbate existing problems of excessive indebtedness and inefficiency. It is not guaranteed that China’s economy returns to its previous pattern of 6% annual growth. And if it does, this may be achieved only by a new, destabilizing debt binge that further entrenches the role of inefficient state-owned firms in China’s economy. China’s quarantine treatment looks likely to succeed in defeating the virus, but it comes with economically painful side effects.

The views expressed in this article are those of the author alone and do not necessarily reflect the position of the Foreign Policy Research Institute, a non-partisan organization that seeks to publish well-argued, policy-oriented articles on   American foreign policy and national security priorities.

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Eduardo levy yeyati and eduardo levy yeyati former nonresident senior fellow - global economy and development federico filippini federico filippini visiting professor - universidad torcuato di tella.

June 8, 2021

Introduction

The impact of the pandemic on world GDP growth is massive. The COVID-19 global recession is the deepest since the end of World War II (Figure 1). The global economy contracted by 3.5 percent in 2020 according to the April 2021 World Economic Outlook Report published by the IMF, a 7 percent loss relative to the 3.4 percent growth forecast back in October 2019. While virtually every country covered by the IMF posted negative growth in 2020 (IMF 2020b), the downturn was more pronounced in the poorest parts of the world (Noy et al. 2020) (Figure 2).

The impact of the shock is likely to be long-lasting. While the global economy is expected to recover this year, the level of GDP at the end of 2021 in both advanced and emerging market and developing economies (EMDE) is projected to remain below the pre-virus baseline (Figure 3). As with the immediate impact, the magnitude of the medium-term cost also varies significantly across countries, with EMDE suffering the greatest loss. The IMF (2021) projects that in 2024 the World GDP will be 3 percent (6 percent for low-income countries (LICs)) below the no-COVID scenario. Along the same lines, Djiofack et al. (2020) estimate that African GDP would be permanently 1 percent to 4 percent lower than in the pre-COVID outlook, depending on the duration of the crisis.  

The pandemic triggered a health and fiscal response unprecedented in terms of speed and magnitude. At a global scale, the fiscal support reached nearly $16 trillion (around 15 percent of global GDP) in 2020. However, the capacity of countries to implement such measures varied significantly. In this note, we identify three important preexisting conditions that amplified the impact of the shock:

• Fiscal space: The capacity to support household and firms largely depends on access to international financial markets,
• State capacity: Fast and efficient implementation of policies to support household and firms requires a substantial state capacity and well-developed tax and transfer infrastructure; and
• Labor market structure: A large share of informal workers facing significant frictions to adopt remote working, and high levels of poverty and inequality, deepen the deleterious impact of the crisis.

Additionally, the speed and the strength of the recovery will be crucially dependent on the capacity of the governments to acquire and roll out the COVID-19 vaccines.

This paper presents a succinct summary of the existing economic literature on the economic and fiscal impact of the pandemic, and a preliminary estimate of the associated economic cost. It documents the incidence of initial conditions (with a particular focus on the role of the labor market channel) on the transmission of the shock and the speed and extent of the expected recovery, summarizes how countries attempted to attenuate the economic consequences and the international financial institutions assisted countries, reports preliminary accounts of medium-term COVID-related losses, and concludes with some forward-looking considerations based on the lessons learned in 2020.

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The Digitalist Papers: A Vision for AI and Democracy

Stanford’s Digital Economy Lab taps multidisciplinary group of thinkers to offer insights on AI and governance in volume called  The Digitalist Papers.

The speed at which artificial intelligence is developing is mind-boggling. In 2023, industry produced  51 new machine learning models , and large language models became increasingly multimodal. 

These advancements are forcing individuals, companies, and governments to grapple with how to understand, regulate, and deploy the technology.

“There’s never been a technology that has the scale and scope of artificial intelligence,” said  Stanford Digital Economy Lab Director  Erik Brynjolfsson . “It’s impacting more types of tasks in the economy than ever before, progress is happening faster than ever, and the magnitude of the improvement is simply unprecedented.”

Earlier this year, Brynjolfsson was having conversations with colleagues about  The Federalist Papers , a series of 85 essays written by Alexander Hamilton, James Madison, and John Jay to promote the ratification of the Constitution. The essays laid out the challenges of the day and provided arguments for institutional innovation for a young democracy.

Today, AI stands to have a tremendous impact on how nations govern, how they engage with their citizens, and how they interact with industry. Policymakers face immediate and immense challenges around how to both work with and regulate this transformational technology.

Brynjolfsson and fellow faculty co-chairs Condoleezza Rice , Nathaniel Persily , and Alex “Sandy” Pentland had an idea: What if they gathered a multi-stakeholder, multidisciplinary group of leaders to create a modern-day Federalist Papers but designed to frame and inform the discourse about AI and governance? 

A few months later, they had assembled a group of 19 essayists (some writing in groups) and are now about to publish what they’re calling  The Digitalist Papers . 

“We stand at a technological, economic, and political crossroads that demand creative rebuilding or reinvention of institutions,” said Brynjolfsson. “ The Digitalist Papers aims to bridge domains and disciplines by assembling experts from multiple fields – including economics, law, technology, management, and political science – alongside industry and civil society leaders.” 

Contributors were asked to focus their disciplinary expertise to address two key questions: 

• How is the world different now because of AI, and what does that mean for democratic institutions, governance, and governing?
• What is the vision, and what is your strategy to reach this vision? 

Across the volume’s 12 essays, these questions forced a close consideration of the role of AI in the evolving social and democratic landscape, especially in the United States. Each author offers a unique perspective, and collectively, the works put forward a vision in which our democratic institutions and society may not only survive but thrive in a world of powerful digital technologies such as AI. 

Themes span AI and governance, AI and civic engagement, AI regulation, and AI and democratic values. Here’s a brief summary of each essay:

On the changing nature of democracy

• Lawrence Lessig unpacks the assumptions underpinning our current democratic system and pinpoints its key vulnerabilities that AI will affect: the dependence of our democratic representatives on private resourcing and polarization. He advocates for “protected democratic deliberation” as a strategy to safeguard democracy in the AI era.
• Divya Siddarth, Saffron Huang, and  Audrey Tang analyzed the Taiwanese experience with digitally enabled citizen assemblies, known as Alignment Assemblies, and put forward a strategy to promote direct citizen engagement toward collaboratively defining the future of AI.
• Lily L. Tsai  and  Alex “Sandy” Pentland state that if AI raises the voices of constituents through representing them and their communities directly in the broader political sphere, then it may also deliver on the promise of direct democracy at scale.
• Sarah Friar and  Laura Bisesto highlight the strategy of digitally mediated engagement as a scaffold for broader, bigger missions in our analog societies.

On new models of governing

• Jennifer Pahlka notes that there is a strong link between diminished state capacity and civic disengagement, and advocates for understanding those constraints and using AI to build government capacity to attain more effective governance.
• Eric Schmidt bluntly makes the case that changing the existing model of organizing within the U.S. government is imperative in order to achieve our government’s purpose.

On AI and regulation

• John H. Cochrane argues that “it is AI regulation, not AI, that threatens democracy.” Free competition, in civil society, media, and academia, will address any ill effects of AI as it has for previous technological revolutions, not preemptive regulation.
• Nathaniel Persily expresses concern that undue panic over AI might, itself, constitute a democracy problem. He argues that exaggerating AI’s impact on the information ecosystem may undermine trust in all media, which would pose a greater cost to democracy than the occasional deepfake.
• Eugene Volokh critically reassesses the risks associated with concentrated power among entities that provide information on public affairs.

On shifting to democratic action

• Mona Hamdy, Johnnie Moore, and  E. Glen Weyl  advocate for a more inclusive, participatory framework that will integrate diverse perspectives and foster collaboration between technology and human society.
• Reid Hoffman and Greg Beato  dive into the governance structures of the AI itself, arguing it is crucial to consider broad, open access, and emphasize individual agency and participatory governance approaches.
• James Manyika concludes the volume with a look to the future and an ambitious agenda. Suppose we look back in 2050 from a society where AI was broadly beneficial. What went right?

Read and share the entire series at  the Digitalist Papers website.

Faculty co-chairs of  The Digitalist Papers are:

• Erik Brynjolfsson , Director of Stanford’s Digital Economy Lab
• Alex “Sandy” Pentland, Stanford HAI Fellow and MIT’s Toshiba Endowed Professor
• Nathaniel Persily, James B. McClatchy Professor of Law at Stanford Law School 
• Condoleezza Rice, 66th Secretary of State of the United States, Tad and Dianne Taube Director of the Hoover Institution and the Thomas and Barbara Stephenson Senior Fellow on Public Policy, and the Denning Professor in Global Business and the Economy at Stanford Graduate School of Business

Senior Editor: Angela Aristidou,  Assistant Professor in Strategy & Entrepreneurship at University College London, Visiting Scholar and Digital Fellow at the Stanford Digital Economy Lab, and the Stanford Institute for Human-Centered AI.

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition.  Learn more . 

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ENTROPY AND INTERNATIONAL TENSION: Essays on INternational Security, International Political Economy, and the Ukrainian Conflict Hardcover – Large Print, September 27, 2024

This book contains three sections on international security, international political economy, and the Ukrainian conflict. The section on international security contains 9 essays. The first three refer to an original model for international relations analysis based on the theory of entropy. In the first essay I present my model and I test it against historical events. In the other two essays I apply the entropic model for analyzing the contemporary international system, and for studying the effects of military expenditures on international tension. The fourth and fifth essays present a model for optimal allocation of military expenditures by two adversaries based on the optimal control theory of dynamic systems, and respectively, a mathematical explanation of the arms race spiral using differential equations. The other four essays included in the international security section deal with elements of US security policies and the concept of nationalism, and they focus on: - US foreign policy and world hegemony, - US assessments and policies regarding Russia presented in US National Security Strategies from 1994 to 2022, - the relevance of Mutual Assured Destruction doctrine in the contemporary international system, and - nation and nationalism in historical perspective. In the international political economy section are included two essays. In the first I offer two explanations of why China’s economic power is increasing faster than United States’ economic power, the two explanations being based on Adam Smith’s theory of wealth creation and on mathematical theory of dynamic systems. In the second essay I examine if the import tariffs generate economic growth or economic stagnation and economic decline. In the section on the Ukrainian conflict I include four essays in which I analyze the 2021 HMS Defender incident from the vantage point of the global balance of power, and I evaluate the 2022 counter-effects of West’s economic sanctions against Russia. I also assess the Ukrainian conflict from the perspective of Christian moral values, and I describe Romanian government’s position regarding the Ukrainian.

• Print length 367 pages
• Language English
• Publication date September 27, 2024
• Reading age 14 - 18 years
• Dimensions 8.25 x 1.02 x 11 inches
• ISBN-13 979-8989624508
• See all details

Product details

• ASIN ‏ : ‎ B0DGGWNRSF
• Publisher ‏ : ‎ Doru Tsaganea (September 27, 2024)
• Language ‏ : ‎ English
• Hardcover ‏ : ‎ 367 pages
• ISBN-13 ‏ : ‎ 979-8989624508
• Reading age ‏ : ‎ 14 - 18 years
• Item Weight ‏ : ‎ 2.25 pounds
• Dimensions ‏ : ‎ 8.25 x 1.02 x 11 inches

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Will High-Efficiency Cookstoves Save Lives?

Cleaner home energy can save households money and cut carbon emissions—but is only part of the way air pollution affects human health..

• By Ty Burke
• September 17, 2024
• CBR - Economics
• Share This Page

The World Health Organization considers air pollution the greatest environmental threat to public health, estimating that it kills more than 7 million people a year and attributing almost half of those deaths to household smoke from open fires and traditional stoves. To combat the problem, the United Nations and other groups have launched initiatives aimed at increasing access to clean-cooking methods—including subsidies for high-efficiency stoves.

But research by University of Pennsylvania’s Susanna B. Berkouwer  and Chicago Booth’s Joshua Dean , who conducted a study in Nairobi, Kenya, suggests that when it comes to the health effects of air pollution, the spikes associated with traditional cooking methods are only one part of a larger picture. Study participants who adopted high-efficiency cookstoves self-reported lower levels of respiratory symptoms such as headaches and coughing. Yet switching to these cleaner stoves had no effect on blood pressure, blood oxygen levels, or medical diagnoses such as pneumonia.

The findings suggest that respiratory symptoms are associated with the peaks in air pollution caused by cooking, while clinical health symptoms such as blood pressure are more closely tied to average levels of pollution exposure. The city’s ambient pollution—from sources such as industrial activity, vehicles, and agricultural burning—remained the same during the 3.5-year-long study.

Beyond the improvements in respiratory symptoms that they bring, high-efficiency cookstoves have other climate and social welfare benefits that make their adoption worthwhile and could justify a subsidy, the researchers argue.

“Burning less charcoal does reduce the peaks during cooking, and that’s correlated with reductions in self-recorded diagnoses,” says Dean. “But it doesn’t move average pollution exposure at all, partly because these peaks are just not that big a part of the day.” In short, he says, “in urban settings where people face both peak and ambient pollution, alleviating the peaks for improved cooking is not sufficient to make long-term impacts on chronic health conditions.”

This is particularly true in Nairobi, a city of 4.4 million people. Berkouwer and Dean’s experiment there offered one set of participants a hefty subsidy to induce them to buy high-efficiency stoves. For others, they set it low. These participants did not purchase a stove and thus served as a control group.

They may help . . . somewhat

In the study, high-efficiency stoves significantly reduced participants’ exposure to harmful particle emissions while cooking. However, they did little to change people’s overall average and peak exposure levels throughout the monitoring period.

Participants carried a backpack throughout their day equipped with devices that measured particulate matter and carbon monoxide—essentially, their exposure to ambient and peak emissions. They self-reported respiratory symptoms and later responded to a survey about chronic health diagnoses.

“Exposure levels during cooking with traditional stoves were appallingly high,” says Dean, “and these peaks seem to be a really important factor in the respiratory symptoms that people experienced.” Yet, there was no reduction in chronic health outcomes or reported diagnoses, Dean says, nor did they observe any changes in blood pressure or pulse oxygenation.

But high-efficiency cookstoves nevertheless yielded big benefits, the researchers say. For one, they saved households money. Berkouwer and Dean calculate that charcoal purchases amounted to about 20 percent of household income, and high-efficiency cookstoves cut a household’s charcoal consumption by nearly half.

“Even if the health benefits to high-efficiency cookstoves were less than might be expected, there would still be massive financial savings,” says Dean. “These households spent a huge amount of their money on energy. The stoves retailed for $40 at the time of the study, and the savings were more than $120 during the first year. That return on investment can help people obtain a livelihood.”

A second benefit is that the stoves could be among the most cost-effective ways to reduce carbon emissions. Each high-efficiency cookstove reduces CO2 emissions by approximately 3.5 tons per year. The researchers’ data indicate that this is far more cost-effective than many other carbon-abatement technologies. They calculate the cost of emissions reduction for the stoves to be about $5 per ton, while electric vehicles, for instance, struggle to break $100 per ton.

Moreover, the technology is scalable. Billions of people worldwide rely on traditional stoves, and replacing those stoves with cleaner versions would cut millions of tons of carbon emissions. Switching to high-efficiency stoves could therefore play a significant role in reducing greenhouse-gas emissions, Dean says. He notes that there is also high additionality—the emissions reductions achieved by replacing cookstoves would not occur otherwise. Many households that received subsidized stoves otherwise wouldn’t have purchased one, and nearly four years after the study, about 85 percent of them still have it.

Works Cited

Susanna B. Berkouwer and Joshua Dean, “ Private Actions in the Presence of Externalities: The Health Impacts of Reducing Air Pollution Peaks but Not Ambient Exposure ,” Working paper, March 2024.

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Youth unemployment and socio-economic development in south east nigeria: the nexus, eze, chukwukadibia c, chikeleze, okey f, okwueze, osondu f..

Youth unemployment is a critical challenge in Nigeria, particularly in the South East region, where it poses significant threat to socio-economic development. The study explores the multifaceted implications of youth unemployment on various aspects of society, including drug abuse, life expectancy, illiteracy, poverty, and criminality. Through an empirical investigation, the study examines the socio-economic impact of unemployment on young people in South East Nigeria, highlighting the region’s unique cultural, economic, and political dynamics. The findings revealed that youth unemployment hampers economic growth, exacerbates social inequalities, perpetuates poverty, and fosters socio unrest. The study concludes with policy recommendations to address the root causes of youth unemployment and foster inclusive socio-economic development in the region.

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