research happiness report

First World Happiness Report Launched at the United Nations

View World Happiness Report Download PDF of World Happiness Report

The happiest countries in the world are all in Northern Europe (Denmark, Norway, Finland, Netherlands). Their average life evaluation score is 7.6 on a 0-to-10 scale. The least happy countries are all poor countries in Sub-Saharan Africa (Togo, Benin, Central African Republic, Sierra Leone) with average life evaluation scores of 3.4. But it is not just wealth that makes people happy: Political freedom, strong social networks and an absence of corruption are together more important than income in explaining well-being differences between the top and bottom countries. At the individual level, good mental and physical health, someone to count on, job security and stable families are crucial.

These are among the findings of the first ever World Happiness Report ( download PDF ), commissioned for the April 2nd United Nations Conference on Happiness (mandated by the UN General Assembly). The report, published by the Earth Institute and co-edited by the institute’s director, Jeffrey Sachs, reflects a new worldwide demand for more attention to happiness and absence of misery as criteria for government policy. It reviews the state of happiness in the world today and shows how the new science of happiness explains personal and national variations in happiness.

The report shows that, where happiness is measured by how happy people are with their lives:

• Happier countries tend to be richer countries. But more important for happiness than income are social factors like the strength of social support, the absence of corruption and the degree of personal freedom.
• Over time as living standards have risen, happiness has increased in some countries, but not in others (like for example, the United States). On average, the world has become a little happier in the last 30 years (by 0.14 times the standard deviation of happiness around the world).
• Unemployment causes as much unhappiness as bereavement or separation. At work, job security and good relationships do more for job satisfaction than high pay and convenient hours.
• Behaving well makes people happier.
• Mental health is the biggest single factor affecting happiness in any country. Yet only a quarter of mentally ill people get treatment for their condition in advanced countries and fewer in poorer countries.
• Stable family life and enduring marriages are important for the happiness of parents and children.
• In advanced countries, women are happier than men, while the position in poorer countries is mixed.
• Happiness is lowest in middle age.

As case studies, the report describes in detail how happiness is measured in Bhutan and the United Kingdom, and it lays out how the Organisation for Economic Co-operation and Development plans to promote standard methods of data collection in different countries. The report itself proposes two evaluative questions that should be asked by social surveys of representative populations in all countries:

• Taking all things together, how happy would you say you are? (where 0 means extremely unhappy, and 10 means extremely happy)
• All things considered, how satisfied are you with your life as a whole nowadays? (where 0 means extremely dissatisfied and 10 means extremely satisfied.)

If possible, it would also be desirable to ask separate questions about how people experience their day- to-day existence.

CONTACTS: Richard Layard: +44 (7790) 906 206 John Helliwell: [email protected]

MORE INFORMATION: Erin Trowbridge, communications director, Earth Institute: [email protected]

Reading Lists +

The review +, how-to guide for happiness surveys, which increasingly drive public policy.

13 March 2024

Research by

• Daniel J. Benjamin
• Kristen Cooper
• Ori Heffetz
• Miles Kimball
• Public Policy
• Behavioral Economics

Advice for researchers aims to help improve both data collection and its interpretation

Economists are asking if we, the people, are happy with our lives. Unfortunately, they don’t understand all of us when we answer.

Researchers peg the sentiment correctly for many people by looking at their answers on happiness surveys. But they unwittingly misinterpret answers to those same questions from quite a few other people who took the surveys. That means the conclusions they draw don’t necessarily reflect reality. 

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While this might seem like a niche little issue for research communities, the possible consequences of these errors range from mildly entertaining to alarming. Late-night TV hosts take note: Finland may not be the happiest country on earth, despite the prestigious World Happiness Report declaring it so year after year. More seriously, New Zealand may have steered too much money toward mental health and not enough toward education when it incorporated findings from happiness surveys into government spending priorities. Other nations on the path toward similar happiness-based policies may get it wrong, too.

Overestimating on Happiness?

UCLA Anderson’s Daniel Benjamin and his co-authors have published multiple papers describing credibility-killing issues that sometimes arise when researchers use self-reported well-being (happiness surveys) to measure collective desires. And they have analyzed and tweaked hundreds of survey questions in attempts to fix the problems.

Their cautionary messag e — they heartily encourage survey usage but point out a whole lot of red flags — is a bit of a wet blanket on a powerful international movemen t . Around the world, governments want to incorporate more happiness data as criteria for policy decisions, such as whether to aggressively lower unemployment or invest more money in health efforts. Benjamin’s team supports the efforts by working with policymakers to measure national happiness but warns that the field still needs a lot more research to make the data consistently reliable. 

A new pap er by Benjamin, Gordon College’s Kristen Cooper, Cornell’s Ori Heffetz and University of Colorado’s Miles Kimball pulls together practical advice for improving happiness data that they uncovered in past studies. Aimed at designers who generate the survey questions, as well as at the researchers and policymakers who analyze the answers, the study gives concrete suggestions for avoiding those red-flag issues. 

The core problem with happiness data, Benjamin recounts in a phone interview, is widespread inconsistency in how people interpret the survey questions. 

Survey Answers and Assumptions

Consider this popular survey question: “Taking all things together, how happy would you say you are (on a scale of 1-10)?” Does “all things together” mean my entire lifetime or all the things affecting me now or what I’m worried about for the future? What if I’m normally very happy, but my kid’s temporary problem has me seriously stressed out? And is my 7 the same level of happiness as everyone else’s? Researchers and their subjects offer different answers to those questions with worrisome frequency, according to studies by Benjamin and co-authors. (Benjamin’s previou s work offers a detailed explanation of those studies and more examples of question confusion.)

The new study walks through assumptions researchers make about answers captured in the surveys, as well as evidence of why they are problematic — including showing, in some cases, how a researcher’s conclusions might be reversed by making the wrong assumption.

The big picture advice for surveyors and researchers, Benjamin says, is to think about the assumptions that underlie how the answers to any given survey question are interpreted. Then consider what it means if those assumptions are not the same as those held by any of your survey takers. 

The more specific suggestions range from the straightforward — request and incorporate paradata, which is the process by which data was collected,  (which survey centers often withhold), or add calibration questions that measure how people use response scales — to the highly technical. They are neatly divided and summarized with different options for those generating the data (the surveyors writing the questions and collecting answers) or researchers and policymakers working with datasets they did not create.

The paper was created at the invitation of the Annual Review of Economics, which unlike most peer-reviewed journals , publishes summaries of research in a field rather than original research.

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Professor of Behavioral Economics and Genoeconomics

About the Research

Benjamin, D.J., Cooper, K., Heffetz, O., & Kimball, M. (2023). From Happiness Data to Economic Conclusions .

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World happiness report

Helliwell, John , Layard, Richard and Sachs, Jeffrey (2012) World happiness report. . The Earth Institute, Columbia University, New York, USA.

The report, published by the Earth Institute and co-edited by the institute’s director, Jeffrey Sachs, reflects a new worldwide demand for more attention to happiness and absence of misery as criteria for government policy. It reviews the state of happiness in the world today and shows how the new science of happiness explains personal and national variations in happiness.

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World Happiness Report 2020 Project

Our research questions.

The following five research questions guided the direction of our project.

• What factors (i.e. GDP, social support, perception of government corruption) are most indicative of a country’s overall happiness and why? Are there any noticeable correlations between factors?
• How does the methodology by which the World Happiness Report determines happiness compare to other surveys (i.e. Gallup’s Positive Experience Index, Where-to-be-born Index, Legatum Prosperity Index) about happiness/well-being? Does this affect how happiness is measured?
• What is the relationship between freedom and happiness? If there exists a clear overall correlation, what factors contribute to the trend? Otherwise, why might different countries have different relationships between freedom and happiness?
• Do any regional trends of happiness exist? What different factors could create this difference? Are there any outliers to these countries, and if so, which ones and why? 
• What types of political policies do the top ten happiest countries share? If so, can these same policies be used for less happy countries and why or why not?

Place in Literature

Current perspectives about world happiness.

Many scholars are currently researching what various factors can contribute to happiness. Multiple studies focus on the data provided within the World Happiness Report 2020 to try to draw conclusions from that information, such as attempting to find regional trends of happiness (Gligorić 2018) or finding economic patterns related to happiness (​​Di Tella 2003). 

However, other researchers are interested in potential biases related to this happiness measurement. There is debate on what standard the happiness in the World Happiness Report is based on, particularly since the report is made in the United States. In particular, many are exploring whether this western standard for happiness has an inherent bias when creating this report (Gardiner 2020). Since happiness can be culturally subjective, others debate whether or not these unique cultures have an influence on a country’s happiness and whether or not the World Happiness Report accurately reflects that (Veenhoven 2012). While in general scholars have found that this report is the best standardized way to measure happiness, there are an infinite number of potential factors that can affect happiness within a country such as current events or economic status that researchers continue to analyze. 

The Science of Happiness in Positive Psychology 101

Whether on a global or an individual level, the pursuit of happiness is one that is gaining traction and scientific recognition.

There are many definitions of happiness, and we will also explore those in this article. For now, we invite you to think of a time when you were happy. Were you alone? With others? Inside? Outside.

At the end of this article, revisit that memory. You may have new insight as to what made that moment “happy,” as well as tips to train your brain towards more happiness.

Before you continue, we thought you might like to download our three Happiness & Subjective Wellbeing Exercises for free . These detailed, science-based exercises will help you or your clients identify sources of authentic happiness and strategies to boost wellbeing.

This Article Contains:

A definition of happiness, a look at the science of happiness, the scientific research on happiness at work, 17 interesting facts and findings, a study showing how acts of kindness make us happier, the global pursuit of happiness, measures of happiness, four qualities of life.

• How to Train your Brain for Happiness

A Take-Home Message

In general, happiness is understood as the positive emotions we have in regards to the pleasurable activities we take part in through our daily lives.

Pleasure, comfort, gratitude, hope, and inspiration are examples of positive emotions that increase our happiness and move us to flourish. In scientific literature, happiness is referred to as hedonia (Ryan & Deci, 2001), the presence of positive emotions and the absence of negative emotions.

In a more broad understanding, human wellbeing is made up of both hedonic and Eudaimonic principles, the literature on which is vast and describes our personal meaning and purpose in life (Ryan & Deci, 2001).

Research on happiness over the years has found that there are some contributing correlational factors that affect our happiness. These include (Ryan & Deci, 2001):

• Personality Type
• Positive Emotions versus Negative Emotions
• Attitude towards Physical Health
• Social Class and Wealth
• Attachment and Relatedness
• Goals and Self-Efficacy
• Time and Place.

So what is the “ science of happiness? ”

This is one of those times when something is exactly what it sounds like – it’s all about the science behinds what happiness is and how to experience it, what happy people do differently, and what we can do to feel happier.

This focus on happiness is new to the field of psychology; for many decades – basically since the foundation of psychology as a science in the mid- to late-1800s – the focus was on the less pleasant in life. The field focused on pathology, on the worst-scenario cases, on what can go wrong in our lives.

Although there was some attention paid to wellbeing, success, and high functioning, the vast majority of funding and research was dedicated to those who were struggling the most: those with severe mental illness, mental disorders, or those who have survived trauma and tragedy.

While there’s certainly nothing wrong with doing what we can to raise up those who are struggling, there was an unfortunate lack of knowledge about what we can do to bring us all up to a higher level of functioning and happiness.

Positive psychology changed all of that. Suddenly, there was space at the table for a focus on the positive in life, for “ what thoughts, actions, and behaviors make us more productive at work, happier in our relationships, and more fulfilled at the end of the day ” (Happify Daily, n.d.).

The science of happiness has opened our eyes to a plethora of new findings about the sunny side of life.

Current research and studies

For instance, we have learned a lot about what happiness is and what drives us.

Recent studies have shown us that:

• Money can only buy happiness up to about $75,000 – after that, it has no significant effect on our emotional wellbeing (Kahneman & Deaton, 2010).
• Most of our happiness is not determined by our genetics, but by our experiences and our day-to-day lives (Lyubomirsky et al., 2005).
• Trying too hard to find happiness often has the opposite effect and can lead us to be overly selfish (Mauss et al., 2012).
• Pursuing happiness through social means (e.g., spending more time with family and friends) is more likely to be effective than other methods (Rohrer et al., 2018).
• The pursuit of happiness is one place where we should consider ditching the SMART goals; it may be more effective to pursue “vague” happiness goals than more specific ones (Rodas et al., 2018).
• Happiness makes us better citizens – it is a good predictor of civic engagement in the transition to adulthood (Fang et al., 2018).
• Happiness leads to career success, and it doesn’t have to be “natural” happiness – researchers found that “experimentally enhancing” positive emotions also contributed to improved outcomes at work (Walsh et al., 2018).
• There is a linear relationship between religious involvement and happiness. Higher worship service attendance is correlated with more commitment to faith, and commitment to faith is related to greater compassion. Those more compassionate individuals are more likely to provide emotional support to others, and those who provide emotional support to others are more likely to be happy (Krause et al., 2018). It’s a long road, but a direct one!

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There’s been a ton of research on the effects of happiness in the workplace. Much of this is driven by companies who want to find a way to improve productivity, attract new talent, and get a dose of good publicity, all at the same time. After all, who wouldn’t want to do business with and/or work for a company full of happy employees?

Although the jury is still out on exactly how happy employees “should” be for maximum productivity, efficiency, and health, we have learned a few things about the effects of a happy workforce:

• People who are happy with their jobs are less likely to leave their jobs, less likely to be absent, and less likely to engage in counterproductive behaviors at work.
• People who are happy with their jobs are more likely to engage in behavior that contributes to a happy and productive organization, more likely to be physically healthy, and more likely to be mentally healthy.
• Happiness and job performance are related—and the relationship likely works in both directions (e.g., happy people do a better job and people who do a good job are more likely to be happy).
• Unit- or team-level happiness is also linked to positive outcomes, including higher customer satisfaction, profit, productivity, employee turnover, and a safer work environment.
• In general, a happier organization is a more productive and successful organization (Fisher, 2010).

To sum up the findings we have so far, it’s easy to see that happiness at work does matter – for individuals, for teams, and for organizations overall. We don’t have all the answers about exactly how the relationship between happiness and productivity works, but we know that there is a relationship there.

Lately, many human resources managers, executives, and other organizational leaders have decided that knowing there’s a relationship is good enough evidence to establish happiness-boosting practices at work, which means that we have a lot of opportunities to see the impact of greater happiness at work in the future.

Research in this field is booming, and new findings are coming out all the time. Here are a few of the most interesting facts and findings so far:

• Happiness is linked to lower heart rate and blood pressure, as well as healthier heart rate variability.
• Happiness can also act as a barrier between you and germs – happier people are less likely to get sick.
• People who are happier enjoy greater protection against stress and release less of the stress hormone cortisol.
• Happy people tend to experience fewer aches and pains, including dizziness, muscle strain, and heartburn.
• Happiness acts as a protective factor against disease and disability (in general, of course).
• Those who are happiest tend to live significantly longer than those who are not.
• Happiness boosts our immune system, which can help us fight and fend off the common cold.
• Happy people tend to make others happier as well, and vice versa – those who do good, feel good!
• A portion of our happiness is determined by our genetics (but there’s still plenty of room for attitude adjustments and happiness-boosting exercises!).
• Smelling floral scents like roses can make us happier.
• Those who are paid by the hour may be happier than those on salary (however, these findings are limited, so take them with a grain of salt!).
• Relationships are much more conducive to a happy life than money.
• Happier people tend to wear bright colors; it’s not certain which way the relationship works, but it can’t hurt to throw on some brighter hues once in a while—just in case!
• Happiness can help people cope with arthritis and chronic pain better.
• Being outdoors – especially near the water – can make us happier.
• The holidays can be a stressful time, even for the happiest among us – an estimated 44% of women and 31% of men get the “holiday blues.”
• Happiness is contagious! When we spend time around happy people, we’re likely to get a boost of happiness as well.

Newman (2015) is the source for the first six facts and findings, and Florentine (2016) for the latter 11 .

Feeling blue? Treat yourself to a decadent dessert.

Feeling frustrated after an argument with a friend? Skip your workout and have an extra scoop of ice cream.

The message is clear: If you want to feel happy, you should focus on your own wishes and desires. Yet this is not the advice that many people grew up hearing. Indeed, most of the world’s religions (and grandmothers everywhere) have long suggested that people should focus on others first and themselves second.

Psychologists refer to such behavior as prosocial behavior and many recent studies have shown that when people have a prosocial focus, doing kind acts for others, their own happiness increases.

But how does prosocial behavior compare to treating yourself in terms of your happiness? And does treating yourself really make you feel happy?

Nelson et al. (2016) presented their research answering these questions.

Participants were divided into four groups and given new instructions each week for four weeks.

One group was instructed to perform random acts of kindness for themselves (such as going shopping or enjoying a favorite hobby); the second group was instructed to perform acts of kindness for others (such as visiting an elderly relative or helping someone carry groceries); the third group was instructed to perform acts of kindness to improve the world (such as recycling or donating to charity); the fourth group was instructed to keep track of their daily activities.

Each week, the participants reported their activities from the previous week, as well as their experience of positive and negative emotions.

At the beginning, the end, and again two weeks after the four-week period, participants completed a questionnaire to assess their psychological flourishing. As a measure of overall happiness, the questionnaire included questions about psychological, social, and emotional wellbeing .

The Results

The results of the study were striking. Only participants who engaged in prosocial behavior demonstrated improvements in psychological flourishing.

Participants who practiced prosocial behavior demonstrated increases in positive emotions from one week to the next. In turn, these increases in feelings such as happiness, joy, and enjoyment predicted increases in psychological flourishing at the end of the study. In other words, positive emotions appeared to have been a critical ingredient linking prosocial behavior to increases in flourishing.

But what about the people who treated themselves?

They did not show the same increases in positive emotions or psychological flourishing as those who engaged in acts of kindness. In fact, people who treated themselves did not differ in positive emotions, negative emotions, or psychological flourishing over the course of the study compared to those who merely kept track of their daily activities.

This research does not say that we shouldn’t treat ourselves, show ourselves self-love when we need it, or enjoy our relaxation when we have it. However, the results of this study strongly suggest that we are more likely to reach greater levels of happiness when we exhibit prosocial behavior and show others kindness through our actions.

In world economic circles, Richard Easterlin investigated the relationship between money and wellbeing.

The Easterlin paradox—”money does not buy happiness” (Mohun, 2012)—sparked a new wave of thinking about wealth and wellbeing.

In 1972, Bhutan chose to pursue a policy of happiness rather than a focus on economic growth tracked via their gross domestic product (GDPP). Subsequently, this little nation has been among the happiest, ranking amongst nations with far superior wealth (Kelly, 2012).

More global organizations and nations are becoming aware and supportive of the importance of happiness in today’s world. This has lead to The United Nations inviting nations to take part in a happiness survey, resulting in the “ World Happiness Report ,” a basis from which to steer public policy. Learn about the World Happiness Report for 2016 .

The United Nations also established  World Happiness Day , March 20 th , which was the result of efforts of the Bhutan Kingdom and their Gross National Happiness initiative (Helliwell et al., 2013).

Organizations such as the  New Economic Foundation are playing an influential role as an economic think tank that focuses on steering economic policy and development for the betterment of human wellbeing.

Ruut Veenhoven, a world authority on the scientific study of happiness, was one of the sources of inspiration for the United Nations General Assembly (2013) adopting happiness measures. Veenhoven is a founding member of the World Database of Happiness , which is a comprehensive scientific repository of happiness measures worldwide.

The objective of this organization is to provide a coordinated collection of data, with common interpretation according to a scientifically validated happiness theory, model, and body of research.

At this point, you might be wondering: Is it possible to measure happiness? Many psychologists have devoted their careers to answering this question and in short, the answer is yes.

Happiness can be measured by these three factors: the presence of positive emotions, the absence of negative emotions, and life satisfaction (Ryan & Deci, 2001). It is a uniquely subjective experience, which means that nobody is better at reporting on someone’s happiness than the individuals themselves.

For this reason scales, self-report measures, and questionnaires are the most common formats for measuring happiness. The most recognized examples are the following:

• The PANAS (Positive Affect and Negative Affect Schedule);
• The SWLS (Satisfaction With Life Scale) ;
• The SHS (Subjective Happiness Scale)

However, there are  many instruments available to measure happiness that have proven reliable and valid over time (Hefferon & Boniwell, 2011).

Of the four dimensions, satisfaction is our personal subjective measure of happiness as we interpret life as a whole. Veenhoven’s (2010) global research into happiness suggests that happiness is possible for many.

This is an overview of his Four Qualities:

Using Veenhoven’s Four Qualities it is possible to assess the happiness of any country.

Liveability of environment

This dimension includes factors such as law, freedom, schooling, employment, electricity or gas, etc. It is a measurement of how well an environment meets what Maslow proposed as our basic needs (safety, security, shelter, food) (Maslow, 1943).

Life-ability of individuals

The ability of individuals to deal with life is important; both mental and physical health are identified as important factors, together with social values of solidarity, tolerance, and love (Veenhoven, 2010).

Utility of life

In this dimension, Veenhoven (2010) references a higher-order meaning, for example, religious affiliations.

Uchida et al. (2014) found that high levels of national disaster negatively impacted a nation’s level of happiness.

Satisfaction

Happiness is a complex construct that cannot be directly controlled. Through policy and individual and organizational action, one can endeavor to influence and increase happiness (Veenhoven, 2010).

However, happiness is a subjective experience and only once we change the way we perceive the world can we really begin sharing and creating happiness for others.

But is it possible to train yourself to be happier?

The answer is yes!

How to Train Your Brain for Happiness

At birth, our genetics provide us a set point that accounts for some portion of our happiness. Having enough food, shelter, and safety account for another portion.

There’s also quite a bit of happiness that’s entirely up to us (Lyubomirsky et al., 2005).

By training our brain through awareness and exercises to think in a happier, more optimistic, and more resilient way, we can effectively train our brains for happiness.

New discoveries in the field of positive psychology show that physical health, psychological wellbeing, and physiological functioning are all improved by how we learn to “feel good” (Fredrickson, et al., 2000).

What Are The Patterns We Need To “Train Out” of Our Brains?

• Perfectionism  – Often confused with conscientiousness, which involves appropriate and tangible expectations, perfectionism involves inappropriate levels of expectations and intangible goals. It often produces problems for adults, adolescents, and children.
• Social comparison  – When we compare ourselves to others we often find ourselves lacking. Healthy social comparison is about finding what you admire in others and learning to strive for those qualities. However, the best comparisons we can make are with ourselves. How are you better than you were in the past?
• Materialism – Attaching our happiness to external things and material wealth is dangerous, as we can lose our happiness if our material circumstances change (Carter & Gilovich, 2010).
• Maximizing  – Maximizers search for better options even when they are satisfied. This leaves them little time to be present for the good moments in their lives and with very little gratitude (Schwartz et al., 2002).

Misconceptions About Mind Training

Some of the misconceptions about retraining your brain are simply untrue. Here are a few myths that need debunking:

1. We are products of our genetics so we cannot create change in our brains.

Our minds are malleable. Ten years ago we thought brain pathways were set in early childhood. In fact, we now know that there is huge potential for large changes through to your twenties, and neuroplasticity is still changing throughout one’s life.

The myelin sheath that covers your neural pathways gets thicker and stronger the more it is used (think of the plastic protective covering on wires); the more a pathway is used, the stronger the myelin and the faster the neural pathway. Simply put, when you practice feeling grateful, you notice more things to be grateful for.

2. Brain training is brainwashing.

Brainwashing is an involuntary change. If we focus on training our mind to see the glass half full instead of half empty, that is a choice.

3. If we are too happy we run the risk of becoming overly optimistic.

There is no such thing as overly optimistic, and science shows that brain training for positivity includes practices like  mindfulness and gratitude. No one has ever overdosed on these habits.

How Is The Brain Wired For Happiness?

Our brains come already designed for happiness. We have caregiving systems in place for eye contact, touch, and vocalizations to let others know we are trustworthy and secure .

Our brains also regulate chemicals like oxytocin.

People who have more oxytocin trust more readily, have increased tendencies towards monogamy, and exhibit more caregiving behavior. These behaviors reduce stress which lowers production of hormones like cortisol and inhibits the cardiovascular response to stress (Kosfeld et al., 2005).

The following TED talk provides an insight into how we can overcome our negative mental patterns:

If happiness has little to do with having too many resources, then it is an inner state that we have the power to cultivate. The above video even offers specific exercises for you to try. Just by doing them, you are actively re-wiring your brain towards calm and happy sensations.

Meanwhile, this TED talk gives a better understanding of how to wire your brain to accept the positivity and happiness in your life:

The negativity bias that Dr. Rick Hanson discusses can help us understand how we can activate and “install” positive thinking as part of our core brain chemistry. If you don’t have a moment to watch either of these videos now, make time for it later—they are rich with relevant data and tips.

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Happiness is the overall subjective experience of our positive emotions. There are many factors which influence our happiness, and ongoing research continues to uncover what makes us happiest.

This global pursuit of happiness has resulted in measures such as the World Happiness Report, while the World Happiness Database is working to collaborate and consolidate the existing happiness pursuits of different nations.

We are living in a time when the conditions for happiness are known. This can be disheartening at times when there is much negativity in the world.

There is, however, good news in this situation: neuroplasticity.

The human brain is wired for happiness and positive connections with others. It is actually possible to experience and learn happiness despite what has been genetically hardwired.

In a world where the focus on happiness is growing and the mirror is turning back towards ourselves, the happiness of the world relies on the happiness within each one of us and how we act, share, and voice the importance of happiness for everyone.

What are the steps you are taking to make yourself and others happier? Let us know by leaving a comment below!

We hope you enjoyed reading this article. Don’t forget to download our three Happiness Exercises for free .

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• Fang, S., Galambos, N. L., Johnson, M. D., & Krahn, H. J. (2018). Happiness is the way: Paths to civic engagement between young adulthood and midlife.  International Journal of Behavioral Development, 42 (4), 425–433.
• Fisher, C. D. (2010). Happiness at work.  International Journal of Management Reviews ,  12 (4), 384–412.
• Florentine, E. (2016, July 1).  11 Scientific facts about happiness.  Bustle . Retrieved from https://www.bustle.com/articles/169675-11-scientific-facts-about-happiness-that-youll-want-to-know.
• Fredrickson, B. L., Mancuso, R. A., Branigan, C., & Tugade, M. M. (2000). The undoing effect of positive emotions . Motivation and Emotion , 24 (4), 237–258.
• Happify Daily. (n.d.).  What is the science of happiness? Retrieved from https://www.happify.com/hd/what-is-the-science-of-happiness/.
• Hefferon, K., & Boniwell, I. (2011). Positive psychology: Theory, research, and applications . Open University Press.
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• Kelly, A. (2012) Gross national happiness in Bhutan: the big idea from a tiny state that could change the world. The Guardian . Retrieved from: http://www.theguardian.com/world/2012/dec/01/bhutan-wealth-happiness-counts?CMP=share_btn_link
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• Krause, N., Ironson, G., & Hill, P. (2018). Religious involvement and happiness: Assessing the mediating role of compassion and helping others.  The Journal of Social Psychology ,  158 (2), 256–270.
• Lyubomirsky, S., Sheldon, K. M., & Schkade, D. (2005). Pursuing happiness: The architecture of sustainable change.  Review of General Psychology, 9 (2), 111–131.
• Maguire, E., Gadian, D., Johnsrude, I., Good, C., Ashburne, J., Frackowiak, R., & Frith, C. (2000). Navigation-related structural change in the hippocampi of taxi drivers . Proceedings of the National Academy of Sciences , 97(8), 4398-4403.
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• Newman, K. M. (2015, July 28). Six ways happiness is good for your health . Greater Good Magazine .  Retrieved from https://greatergood.berkeley.edu/article/item/six_ways_happiness_is_good_for_your_health
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What our readers think.

Thank you for this beautiful well written article. I came across it during my research regarding the science of happiness. The beauty in writing this post is the power to influence souls in a positive manner many who you will not meet.

Sending some love and light to you and all those who get to read your blog.

Being in the field of Human Resource for four decades, coming across and dealing with millions of minds, after reading your article, gives a feeling that I have learnt something new today…

Thank you and congratulations for such a informative work.

God bless…

Thank you for your search light into one of the nerve center of our generation. i will like to use part of this in my upcoming book

Hello Katherine, Now reading https://positivepsychology.com/happiness/ Salute to you for enriching us. Nearly hundred of us relatives are creating an audio book for our blind uncle about life skills. Any quote from you that I can add in the document? Will be grateful. regards, Prabodh Sirur

Hi Prabodh,

Wow, that sounds like a lovely gift for your uncle! We actually have a couple of posts containing quotes about happiness, so you may want to take a look at those for some inspiration. You can find those here and here .

Hope this helps, and good luck with the audiobook!

– Nicole | Community Manager

Thanks for your article, I translated this article for a mental health lesson and I really enjoyed this article.

Thank you for this super helpful article!!

Thank You for such an Informative and Detailed Article on Science of Happiness. I am a Budding Happiness Life Coach and stumbled on this Article. This gives me more understanding of Happiness in Scientific way, with your permission, I would like to share my learning in my course. Thank You and looking forward for more such Articles. Thank You and God Bless You

Hi Srinivas, Thank you for your lovely feedback. We’re glad you liked the article. Feel free to share it with others by clicking ‘Yes’ on the ‘Was this article useful to you’ button. From there, a range of sharing options will appear. – Nicole | Community Manager

Thanks, very nice lecture and informative But I wish to know more about role of religious effects on Happiness? another thing is it ok to translate lecture to other language and share it? Regards Dr Eirebi Albogasim

Hi Dr. Albogasim, Thanks for reading. There’s quite a bit of research showing that those who practice religion tend to be happier than the general population ( here’s an article on the topic). And yes, feel free to translate and share the lecture. – Nicole | Community Manager

I stumbled on your article as I am researching on Happiness to publish my 3rd book. Thanks for sharing! A very elaborate and informative article. The “Take home message” is very encouraging. And I vouch for the neuroplasticity of the brain. We can train ourselves to be Happy. Once we change our attitude, it is easy to be Happy. I learnt how to be Happy at the age of 23. Few years back I posted an article sharing my findings on Happiness in this Linked-in forum. Please see the link for the same https://www.linkedin.com/pulse/easy-happy-ramesh-thota-pmp-cqa/ . Appreciate if you can share your views.

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Managing Happiness

Happiness is within your control. Write your own ending.

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What you'll learn.

Explore diverse definitions of happiness and understand its function in everyday life

Learn how genetic, social, and economic influences impact your happiness

Apply the science of the mind, body, and community to manage emotions and behaviors for greater happiness

Develop a happiness portfolio focused on your deepest goals and desires

Recognize how success and achievement impact short versus long-term happiness

Write your ending — build happiness strategies for your work and life at any age or stage

Course description

What is happiness? What makes you happy?’ Can you get happier through study and effort? 

Maybe you have pondered these questions over the course of your life, but haven’t been able to come up with any definitive answers. Still, you’d like to think that happiness is something you can understand and manage, right?

This is a class that answers these questions and shows you how you can use the answers to build a happier life. It introduces you to the modern science of human well-being and shows you how to practice it. Unlike other happiness courses, Managing Happiness goes a step further and demonstrates how you can share the ideas with others, thus bringing more happiness and love to the world and supercharging your own well-being efforts.

Led by Harvard professor, author, social scientist, and former classical musician Arthur Brooks, this course will introduce cutting-edge survey tools, the best research, and trends in social science, positive psychology, neuroscience, and philosophy to help learners unlock the strategies to create a more purposeful life, full of long-lasting enjoyment and satisfaction. Managing Happiness uses philosophical and technical insights to challenge your assumptions about happiness — helping you break bad habits that hold you back and build good ones you can use for the rest of your life.

Happiness is a core competency for those that want to be in charge of their lives — both personally and professionally. The concepts learned in this course will lead to enduring improvements and lifelong learning. At the end of the course, you will take away key concepts and actionable insights to apply to your daily routines. People around you will notice the difference.

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Report: Canada is the 2nd happiest country among the G7

According to the 2024 World Happiness Report (WHR), Canada trails only countries in the European Union (EU) concerning overall happiness among all surveyed age groups.

The World Happiness Report is an annual publication crafted in partnership between Gallup, the Wellbeing Research Centre at the University of Oxford (United Kingdom, UK), the United Nations’ (UN’s) Sustainable Development Solutions Network and the WHR’s Editorial Board.

Based on “a three-year average” of what the WHR calls “life evaluations”, the 2024 version of this report assesses the happiness of people in more than 140 countries “during different life stages and of those in different generations.” This is on top of including an overall happiness ranking for all ages in each country.

Note: The WHR says that life evaluations are based on responses to the Gallup World Poll, which “asks respondents to evaluate their current life as a whole using the image of a ladder, with the best possible life for them as a 10 and [the] worst possible as a 0.”

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Specifically, in addition to its overall rankings, the report divides each country’s population into these four groups:

The Young: Under 30 years old

• Lower Middle: 30 – 44 years old
• Upper Middle: 45 – 59 years old

The Old: 60 years old and above

Where does Canada rank among the G7?

As defined by Global Affairs Canada , the G7, or Group of Seven, is “a grouping of seven of the world’s advanced economies.” This group of countries includes Canada, France, Germany, Italy, Japan, the UK, the United States (US) and the EU.

Overall rankings

In terms of overall happiness (of all ages), Canada ranks 2nd among all G7 nations in the WHR 2024.

Trailing only some countries in the EU – Finland (1), Denmark (2), Sweden (4), Netherlands (6), Luxembourg (8) and Austria (14) – Canada (15) ranked higher than all other G7 nations in overall happiness:

• UK: 20th in overall happiness
• US: 23th in overall happiness
• Germany: 24th in overall happiness
• France: 27th in overall happiness
• Italy: 41st in overall happiness
• Japan: 51st in overall happiness

Rankings by age group

Among the G7, here is where Canada ranked in each of the age groups/generations noted above:

In this age group, Canada ranked 5th of 7, ahead of only the US and Japan.

Lower Middle: 30 to 44 years old

In this age group, Canada ranked 4th of 7, ahead of Italy, the US and Japan.

Upper Middle: 45 to 59 years old

In this age group, Canada ranked 2nd of 7, behind only some countries in the EU (Finland, Sweden, Denmark, Netherlands and Luxembourg).

In this age group, Canada again ranked 2nd of 7. Once again, Canada trailed only some countries in the EU (Denmark, Finland, Norway, Sweden and Netherlands) in this category.

How Canada’s WHR 2024 ranking compares with its 2023 U.S. News ranking

Although different publications use different methodologies and factors to rank countries, Canada’s place among the happiest countries in the G7 according to the WHR 2024 coincides with its ranking as the 2nd best country in the world overall according to the U.S. News’ Best Countries ranking for 2023.

Last year’s U.S. News ranking placed Canada behind only Switzerland in the overall standings. Additionally, U.S. News ranked Canada in the top seven countries (of 87 total) for nearly half of its 10 subcategories. Specifically, Canada ranked:

• 2nd for Agility*
• 2nd for starting a career
• 2nd for racial equality
• 3rd for Quality of Life
• 4th for Social Purpose**
• 4th for education
• 6th for women
• 6th for pursuing a comfortable retirement
• 6th in terms of most transparent countries
• 7th for studying abroad
• 7th for raising kids

*U.S. News says that agility is about a country’s ability to adapt and respond to obstacles, adding that “these countries are seen as the most adaptable to change.”

**U.S. News describes social purpose as “the ability of a country’s citizens to rally around certain causes they feel strongly about. These countries are seen as being the most progressive, inclusive and committed to social justice.”

More: Where Canada ranked in U.S. News’ Best Countries ranking for 2023

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Research in India

One of the foundation’s main focus areas of work is happiness research in India. Some of the research work is shared below namely India Happiness Report 2020, India Cities Happiness Report 2020 and media articles. These reports have inputs and endorsements from many global happiness experts.

We would love to help you with happiness research in your organisation. Kindly write to us at [email protected]  

INDIA HAPPINESS REPORT 2020

The study is based on a nationwide survey covering 16,950 people between March and July 2020 by Professor Rajesh K Pillania. He is recognised for his extensive research, jointly ranked number one in average research productivity among management faculty (including IIMs & IITs) in India between 1968 to 2014.

In the happiness rankings of states and union territories, Mizoram, Punjab, Andaman and Nicobar Islands are the top three. Among the big states, Punjab, Gujarat, and Telangana are among the top three states whereas, among smaller states, Mizoram, Sikkim, and Arunachal Pradesh are the top three states in happiness rankings. Among union territories, Andaman and Nicobar Islands, Puducherry, and Lakshadweep are the top three union territories in happiness rankings. The results show marital status, age group, education, and income level are overall positively related to happiness and married people are happier than unmarried people.

The spirit of India is quite resilient and the impact of COVID-19 varies across states and union territories. It varies from the worst possible to the best possible among individuals in the study.

Maharashtra, Delhi, and Haryana have shown the worst possible impact of COVID-19 on happiness, whereas Puducherry and Jammu and Kashmir are neutral and Manipur, Andaman and Nicobar Islands, and Lakshadweep have shown the best possible impact of COVID-19 on happiness.

The spirit of India is quite resilient and the impact of COVID-19 varies across states and union territories. It varies from the worst possible to the best possible among individuals in the study. Maharashtra, Delhi, and Haryana have shown the worst possible impact of COVID-19 on happiness, whereas Puducherry and Jammu and Kashmir are neutral and Manipur, Andaman and Nicobar Islands, and Lakshadweep have shown the best possible impact of COVID-19 on happiness.

The report contains insights from various thought leaders on happiness. 

Historian and biographer, Professor Rajmohan Gandhi, grandson of Mahatma Gandhi, emphasises that Mahatma Gandhi believed that the approbation of one’s conscience for one’s actions is the true source of happiness.

Professor Sir Cary Cooper, a leading global scholar in occupational health and wellness research, highlights that the mental well-being and happiness of employees and citizens is the true measure of success.

Dr. Ashley Whillans, Assistant Professor, Harvard Business School, and a leading scholar in the time, money, and happiness research field, emphasises that people who value time over money report greater well-being.

Dr. Emma Seppälä, Science Director, Stanford Center for Compassion and Altruism Research and Education, and Co-Director Wellness, Yale Center for Emotional Intelligence, shares her conclusion that kind and compassionate people are the happiest and most fulfilled in a sustained manner throughout their lives.

Jennifer Moss, CBC Columnist, and UN Happiness Council Member, stresses that appreciating the opposites may be the key to sustaining a healthy mind-set, and happiness.

Dr. Dasho Karma Ura, Head, Centre for Bhutan and Gross National Happiness (GNH) Studies, highlights that GNH studies show that both material and nonmaterial conditions contribute to happiness.

Devdutt Pattanaik, a popular writer, writes that happiness requires all three goddesses: L (Lakshmi) i.e. the goddess of wealth, Saraswati (S) i.e. the goddess of knowledge and Durga (D) i.e. the goddess of power.

Dr. Rajendra Singh, popularly known as ‘Jal Purush, Waterman of India’, insists that lasting happiness comes by giving equal respect to humanity and nature.

People are optimistic about the future and generally scored more on happiness after five years compared to scores today. In the future happiness rankings after five years, Manipur, Andaman and Nicobar Islands, and Gujarat are the top three.

Dr. T.V. Rao, Chairman TVRLS and often referred to as the ‘One of the Fathers of Human Resource Development (HRD)’ in India, stresses that it is time to review all HRD policies in the corporate sector, government, and all sections of society, and redesign them to create happiness at work.

The three key takeaways for governments, organisations, and individuals are, first, different states and union territories are at different levels of happiness rankings. There is a pressing need for more discussions, focus, and the application of happiness in the Indian context. Second, knowing is not enough, happiness needs to be practised. Third, choose and put into practice all or some or at least one of the insights from this report.

INDIA CITIES HAPPINESS REPORT 2020

First India Cities Happiness Report is covering thirty-four major cities measuring happiness across the country, the contributing factors to people’s happiness, the impact of COVID-19 on happiness, and insights from global thought leaders.

The study is based on a nationwide survey covering 13,000 people during October- November 2020 by Professor Rajesh K Pillania. He is recognised for his extensive research, jointly ranked number one in average research productivity among management faculty (including IIMs & IITs) in India between 1968 to 2014.

John F. Helliwell, Co-Editor (with Jeffry Sachs and Richard Layard) of the World Happiness Report, Professor Emeritus, Vancouver School of Economics, University of British Columbia shares that Rajesh Pillania and his team did a signal service in extending the scope of world happiness research by providing data for 36 Indian states in India Happiness Report 2020. The India Cities Happiness Report 2020 further deepens understanding by monitoring the quality of life in more than 30 major cities.

In the happiness rankings of cities, Ludhiana, Ahmedabad, and Chandigarh are the top three. Among the Tier-I cities, Ahmedabad, Hyderabad and New Delhi are among the top three, whereas, among Tier-II cities, Ludhiana, Chandigarh and Surat are the top three cities in happiness rankings.

The results show age group, education, and income level are overall positively related to happiness, and marital status is negatively related to happiness i.e. unmarried people are happier than married people in big cities.

Jaime Lerner, World-renowned Architect & Urban Planner, Former President of the International Union of Architects and, Chairman, Jaime Lerner Arquitetos Associados, and Among 25 Most Influential Thinkers in the World (Time magazine, 2010),  stresses on Remembering Togetherness for happiness in cities and emphasises that quality public spaces are the glue that can hold together sharing, trust, connectedness, a sense of civic duty, responsibility and pride because public spaces are the theatres where urban life happens.

The spirit of India is quite resilient, and the impact of COVID-19 varies across cities. It varies from the worst possible to the best possible among individuals in the study. Bengaluru, Kochi and Kolkata have shown the worst possible impact of COVID-19 on happiness.

Francesc Miralles, Co-author of the Bestselling book Ikigai: The Japanese Secret to a Long and Happy Life, pinpoints we often believe that happiness is the absence of problems, and that’s a big mistake.

The report contains insights from various thought leaders on happiness including Ruut Veenhoven, Pioneer and World Authority on the Scientific Study of Happiness, Emeritus Professor of Social Conditions for Human Happiness, Erasmus University Rotterdam in the Netherlands (EHERO), and, Director, World Database of Happiness; John F. Helliwell, Co-Editor (with Jeffry Sachs and Richard Layard) of the World Happiness Report, Professor Emeritus, Vancouver School of Economics, University of British Columbia, and Distinguished Fellow, Canadian Institute of Advanced Research; Jaime Lerner, World-renowned Architect and Urban Planner, Former President of the International Union of Architects, Chairman, Jaime Lerner Arquitetos Associados and, Among 25 most Influential Tthinkers in the World (Time magazine, 2010); Carlo Ratti, Director, MIT Senseable City Lab, Founding Partner, Carlo Ratti Associati and, Co-chair of the World Economic Forum’s Global Future Council on Cities and Urbanization; Richard Florida, one of the World’s Leading Urbanists, University Professor at University of Toronto’s School of Cities and Rotman School of Management, A Distinguished Fellow at NYU’s Schack School of Real Estate, and, Founder of the Creative Class Group; Padma Bhushan M. B. Athreya, Recognised as one of the Founders and Pioneers of the Indian Management Movement, and Ex-Professor London Business School, and Ex-Professor IIM- Calcutta; and, Francesc Miralles, Co-author of Bestselling book Ikigai: The Japanese Secret to a Long and Happy Life.

People are optimistic about the future and generally scored more on happiness after five years compared to scores today. In the future happiness rankings after five years, Ludhiana, Jammu and Amritsar are the top three.

Carlo Ratti, Director, MIT Senseable City Lab and Co-chair of the World Economic Forum’s Global Future Council on Cities and Urbanization, highlights that the key issue cities are facing is the relationship between the natural and the artificial worlds resulting in more happiness; and, don’t focus just on new technologies but use them to build cities for lovers and friends.

The three key takeaways for governments, organisations, and individuals are; first, different cities are at different levels of happiness rankings. There is a pressing need for more discussion, focus, and the application of happiness in the Indian context. Second, knowing is not enough; happiness needs to be practised. Third, choose and put into practice all or some or at least one of the insights from this report.

Media Articles

World Happiness Report 2020

The World Happiness Report is a landmark survey of the state of global happiness that ranks 156 countries by how happy their citizens perceive themselves to be. The World Happiness Report 2020 for the first time ranks cities around the world by their subjective well-being and digs more deeply into how the social, urban and natural environments combine to affect our happiness.

Read the Report

• Chapter 1 Environments for Happiness: An Overview
• Chapter 2 Social Environments for World Happiness
• Chapter 3 Cities and Happiness: A Global Ranking and Analysis
• Chapter 4 Urban-Rural Happiness Differentials Across the World
• Chapter 5 How Environmental Quality Affects Our Happiness
• Chapter 6 Sustainable Development and Human Well-Being
• Chapter 7 The Nordic Exceptionalism: What Explains Why the Nordic Countries Are Constantly Among the Happiest in the World
• Annex: Using a New Global Urban-Rural Definition, Called the Degree of Urbanisation, to Assess Happiness
• Download the Report

Appendices & Data

This is the eighth World Happiness Report . We use this Foreword, the first we have had, to offer our thanks to all those who have made the Report possible over the past eight years, and to announce our expanding team of editors and partners as we prepare for our 9th and 10th reports in 2021 and 2022. The first seven reports were produced by the founding trio of co-editors assembled in Thimphu in July 2011 pursuant to the Bhutanese Resolution passed by the General Assembly in June 2011, that invited national governments to “give more importance to happiness and well-being in determining how to achieve and measure social and economic development.” The Thimphu meeting, chaired by Prime Minister Jigme Y. Thinley and Jeffrey D. Sachs, was called to plan for a United Nations High-Level Meeting on ‘Well-Being and Happiness: Defining a New Economic Paradigm’ held at the UN on April 2, 2012. The first World Happiness Report was prepared in support of that meeting, bringing together the available global data on national happiness and reviewing evidence from the emerging science of happiness.

The preparation of the first World Happiness Report was based in the Earth Institute at Columbia University, with the research support of the Centre for Economic Performance at the LSE and the Canadian Institute for Advanced Research, through their grants supporting research at the Vancouver School of Economics at UBC. The central base for the reports has since 2013 been the Sustainable Development Solutions Network (SDSN) and The Center for Sustainable Development at Columbia University directed by Jeffrey D. Sachs. Although the editors and authors are volunteers, there are administrative and research support costs, covered most recently through a series of research grants from the Ernesto Illy Foundation and illycaffè.

Although the World Happiness Reports have been based on a wide variety of data, the most important source has always been the Gallup World Poll, which is unique in the range and comparability of its global series of annual surveys. The life evaluations from the Gallup World Poll provide the basis for the annual happiness rankings that have always spurred widespread interest. Readers may be drawn in by wanting to know how their nation is faring, but soon become curious about the secrets of life in the happiest countries. The Gallup team has always been extraordinarily helpful and efficient in getting each year’s data available in time for our annual launches on International Day of Happiness, March 20th. Right from the outset, we received very favourable terms from Gallup, and the very best of treatment. Gallup researchers have also contributed to the content of several World Happiness Reports . The value of this partnership was recognized by two Betterment of the Human Conditions Awards from the International Society for Quality of Life Studies. The first was in 2014 for the World Happiness Report, and the second, in 2017, went to the Gallup Organization for the Gallup World Poll.

From 2020, Gallup will be a full data partner, in recognition of the importance of the Gallup World Poll to the contents and reach of the World Happiness Report . We are proud to embody in this more formal way a history of co-operation stretching back beyond the first World Happiness Report to the start of the Gallup World Poll itself.

We have had a remarkable range of expert contributing authors over the years, and are deeply grateful for their willingness to share their knowledge with our readers. Their expertise is what assures the quality of the reports, and their generosity is what makes it possible. Thank you.

Our editorial team has been broadening over the years. In 2017, we added Jan-Emmanuel De Neve, Haifang Huang, and Shun Wang as Associate Editors, joined in 2019 by Lara Aknin. From 2020, Jan-Emmanuel De Neve has become a co-editor, and the Oxford Wellbeing Research Centre thereby becomes a fourth research pole for the Report.

Sharon Paculor has for several years been the central figure in the production of the reports, and we now wish to recognize her long-standing dedication and excellent work with the title of Production Editor. The management of media has for many years been managed with great skill by Kyu Lee of the Earth Institute, and we are very grateful for all he does to make the reports widely accessible. Ryan Swaney has been our web designer since 2013, and Stislow Design has done our graphic design work over the same period. Juliana Bartels, a new recruit this year, has provided an important addition to our editorial and proof-reading capacities. All have worked on very tight timetables with great care and friendly courtesy.

Our group of partners has also been enlarged, and now includes the Ernesto Illy Foundation, illycaffè, Davines Group, Blue Chip Foundation, The William, Jeff and Jennifer Gross Family Foundation, and Unilever’s largest ice cream brand Wall’s.

Our data partner is Gallup, and institutional sponsors now include the Sustainable Development Solutions Network (SDSN), the Center for Sustainable Development at Columbia University, the Centre for Economic Performance at the LSE, the Vancouver School of Economics at UBC, and the Wellbeing Research Centre at Oxford.

For all of these contributions, whether in terms of research, data, or grants, we are enormously grateful.

John Helliwell, Richard Layard, Jeffrey D. Sachs, and Jan Emmanuel De Neve, Co-Editors; Lara Aknin, Haifang Huang and Shun Wang, Associate Editors; and Sharon Paculor, Production Editor

• Our work is public. Data for Figure 2.1 for each corresponding year are freely downloadable. The survey measure of SWB (Subjective Well-being) is from the Gallup World Poll (GWP). Please reference the report accordingly (see Citation).
• Statistical Appendix for Chapter 2
• Data for Figure 2.1
• Data for Figures 2.2, 2.3, and Appendix 2
• Data for Figure 2.4
• Data for Table 2.1
• Statistical Appendix 3 for Chapter 2
• Chapter 3 Appendix
• Chapter 4 Appendix
• Chapter 5 Appendix
• Chapter 6 Appendix

John F. Helliwell, Richard Layard, Jeffrey D. Sachs, and Jan Emmanuel De Neve, Co-Editors; Lara Aknin, Haifang Huang and Shun Wang, Associate Editors; and Sharon Paculor, Production Editor

Helliwell, John F., Richard Layard, Jeffrey Sachs, and Jan-Emmanuel De Neve, eds. 2020. World Happiness Report 2020. New York: Sustainable Development Solutions Network

978-1-7348080-0-1

Final_Project:World Happiness Report

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Zhongyue Lin

July 13, 2023

Introduction

Happiness, a subjective experience characterized by a state of well-being, satisfaction, and the prevalence of positive emotions over negative ones, is a complex construct to measure. Recognizing its multidimensional nature, the World Happiness Report employs an interdisciplinary approach to gauge happiness across various countries. The dataset for this report, obtained from Kaggle’s platform ( https://www.kaggle.com/datasets/mathurinache/world-happiness-report ), presents a unique opportunity to delve into the intricacies of happiness and its driving factors.

The World Happiness Report, an annual survey, assesses happiness levels in 153 countries worldwide, relying on data from the Gallup World Poll. The methodology involves asking respondents to rank their current life on a scale of 0 to 10, where 10 signifies the best imaginable life, and 0 represents the worst possible existence. The country’s average responses constitute its happiness score, leading to a global happiness ranking. The dataset not only includes these scores but also accounts for various factors like GDP per capita, healthy life expectancy, social support, freedom to make life choices, generosity, and perceptions of corruption, contributing to the overall understanding of happiness dynamics.

Data Overview

The dataset consists of eight CSV files spanning from 2015 to 2022, each containing happiness scores and their explanatory factors. However, the variable names differ across years, and some datasets after 2017 feature additional statistical data. To streamline the analysis, the variable names have been standardized, and extra statistical data have been appropriately processed.

Research questions

The dataset from the World Happiness Report paves the way for a myriad of research questions:

Influential Factors on Happiness: This aspect delves into the significant drivers of national happiness, including economic, social factors, and the role of corruption perception. To dissect these relationships, tools such as correlation and regression analyses will be deployed.

Happiness Differences Among Countries: This dimension investigates the disparities in happiness across countries, identifying potential patterns linked to geographic, economic, or cultural variations. Comparative analyses can elucidate these patterns.

Temporal Evolution of Happiness and Factors: This facet focuses on how happiness and its influencing factors have evolved over time. Time series analysis can be instrumental in identifying such trends.

Impact of a Specific Factor on Happiness: This area zeroes in on the effects of individual factors, such as GDP per capita or perceived corruption, on happiness. This focus will help guide effective policy initiatives through a detailed factor analysis.

By thoroughly exploring these questions, the dataset will yield valuable insights into the multifaceted dynamics of happiness, thereby providing actionable guidance for policy decisions aimed at enhancing national well-being.Data

Data Reading

In our research process, we collected data from the Happiness Index spanning eight years, from 2015 to 2022. We meticulously loaded each year’s data into our system, assigning a distinct identifier to ensure clarity and ease of access. To preserve the chronology, a ‘year’ column was added to each dataset. A preliminary examination of the initial entries from each year was performed, providing us an overview of the data and preparing us for subsequent analysis stages.

Data Standardization

After collecting the data, the next critical step was to standardize the eight years of Global Happiness datasets. The data was sorted based on the ‘Ladder score’, a measure of happiness, to maintain uniformity. Key column names were harmonized across all datasets, and certain columns were converted to a numeric format to facilitate analysis. We addressed potential inconsistencies by adjusting column names and scales, ensuring data quality and laying the groundwork for accurate and consistent analysis.

Uniform variable name

Data Integration

The final preparatory step was to merge the individual datasets from 2015 to 2022 into a single, comprehensive dataset. During this integration, we retained only the necessary columns, standardized country names, and converted some columns to more suitable data types. Countries not consistently present across all years were filtered out to maintain data consistency. We also generated statistical summaries of the numeric columns for each year to give a snapshot of the general tendencies in the data. The result is a systematically organized, paginated table that is primed for deeper and more thorough analysis.

Visualizations & Analysis

Q1: how does happiness differ by country, categorical data integration.

In this part of the process, we enhanced our dataset by adding two new labels - ‘Continent’ and ‘Developed’. ‘Continent’ helped us categorize countries based on geographical location, while ‘Developed’ served to distinguish countries according to their economic development stage. With these new classifications, we were able to conduct more nuanced comparisons of happiness levels, not just across countries but also across different geographical regions and stages of development.

Data Harmonization

We addressed any inconsistencies in our dataset, specifically focusing on country names. For instance, we found a discrepancy with ‘Palestinian Territories’ being present in the ‘avg_score’ dataset but absent from the ‘world_map’ dataset. To rectify this, we cross-referenced both datasets for the occurrence of ‘Palestinian’ to ensure the accuracy of our data and enable proper mapping in later stages. This careful harmonization ensures the integrity of our data, setting the stage for more detailed and accurate analyses.

Exploring Global Happiness Disparities

With the data systematically categorized and harmonized, we explored the global disparities in happiness, taking into account geographical location, economic status, and cultural factors. The incorporation of ‘Continent’ and ‘Developed’ labels in our dataset added depth to our understanding of these disparities.

Visualizing the average happiness index for each country revealed significant differences in happiness levels across different continents and levels of economic development. Notably, the gap in happiness scores between developed and developing countries appears to be narrowing, indicating progress in improving life quality in the developing world.

These findings highlight the importance of crafting policies that consider these factors in order to enhance global well-being. Future research must continue to explore these relationships in depth, to inform more targeted and effective policy recommendations.

Q2:Influential Factors on Happiness

Quantifying influential factors on happiness.

Our study extended beyond just identifying trends and patterns in happiness scores. It aimed to quantify the strength and direction of relationships between several predictor variables (such as GDP per Capita, Life Expectancy, Freedom, and others) and happiness scores. This goal was achieved by building a linear regression model, which, unlike visualization, provided us with precise measures of these relationships.

This statistical modeling approach allowed us to test hypotheses regarding each predictor’s effect on happiness scores and offer predictive capabilities for future happiness scores based on new data - feats that are beyond the scope of visualization alone.

Key Determinants of Happiness

The factors we identified as significantly contributing to happiness were GDP per Capita, Family support, Life Expectancy, Freedom, and Generosity. In contrast, Government Corruption was found to detract from happiness. However, these elements only accounted for about 72.83% of happiness score variance, implying that there may be additional, as yet unconsidered factors that could play a role.

We also found potential interconnectedness among these factors that might further influence happiness levels, suggesting a need for further exploration. For instance, GDP per Capita might impact Life Expectancy, Family support, or Freedom, and Government Corruption might affect Freedom and Generosity.

While our findings shed light on these relationships, it’s important to remember that correlation does not imply causation. Determining causal relationships requires more in-depth research.

Multivariate Regression Analysis Insights

Our multivariate regression analysis provided key insights into the determinants of happiness. GDP per Capita, Life Expectancy, Family support, Freedom, Generosity, and Government Corruption were found to significantly influence happiness levels. However, the interaction between GDP per Capita and Life Expectancy wasn’t found to have a significant impact.

While our model explained approximately 79.65% of the variance in happiness scores, the remainder indicates the presence of other influential factors yet to be explored.

Addressing Data Gaps

During our analysis, we noticed a gap in our dataset, specifically the ‘Government_Corruption’ data for the ‘United Arab Emirates’ in 2018. To maintain the integrity of our model, we calculated the average ‘Government_Corruption’ score for this country from 2015 to 2017 and used this value as an estimate for the missing 2018 data.

Unveiling Complex Relationships

Our updated model, which accounted for the combined effect of Freedom and Government Corruption, still identified GDP per Capita, Family support, Life Expectancy, and Generosity as the most impactful factors on happiness scores. Even with this added interaction, the explanatory power of our model remained unchanged, indicating that Freedom and Government Corruption might not interact significantly to affect happiness levels.

Notably, we discovered a significant relationship between a country’s GDP per Capita and its level of Generosity on its happiness score. This interaction, alongside other key predictors like Family support, Life Expectancy, Freedom, and Development Level, enhanced our understanding and prediction of happiness scores.

Our comprehensive analysis delved into an array of factors influencing happiness, from economic indicators like GDP per Capita to socio-cultural aspects such as Freedom and Generosity. We also explored the impact of Life Expectancy, Family support, Government Corruption, geographic regions, and development levels, and even considered the interactive effects of certain combinations.

We found that while some factors significantly influenced happiness scores, others did not. Importantly, the interplay between GDP per Capita and Generosity was found to be a critical determinant of happiness. Nevertheless, around 20% of the differences in happiness scores were unexplained by our model, indicating the existence of other influential factors yet to be discovered.

This study underscores the complex nature of happiness and highlights the need for continued exploration in this captivating field of research.

Q3:Temporal Evolution of Happiness and Factors

The changing dynamics of happiness over time.

Our investigation into the temporal evolution of happiness has yielded some compelling insights. As the years progress, the key drivers of happiness appear to be undergoing intriguing transformations.

Notably, the impacts of GDP per capita, family support, and personal freedom on happiness have all shown significant temporal fluctuations. Intriguingly, the influence of wealth, denoted by GDP per capita, and personal freedom on happiness seem to be on a gradual decline. Conversely, the role of family support in determining our sense of happiness appears to be gaining increased importance over time.

However, our model couldn’t wholly capture this complex evolution of happiness. While it managed to explain approximately 73.52% of the changes in happiness scores over time, there was still an average difference of 0.5613 between our predicted and actual happiness scores. This suggests the presence of additional influential factors, which we have yet to explore.

In essence, these findings reveal a dynamic picture of happiness and its determinants, emphasizing the evolving influence of different life aspects on our well-being. This invites further research to understand these unexplored elements and their role in the intricate evolution of happiness.

Q4:Impact of a Specific Factor on Happiness

Exploring the influence of specific factors on happiness.

Our deep dive into the determinants of happiness has yielded some intriguing findings. In this analysis, we concentrated on variables such as per capita GDP, family support, life expectancy, freedom, generosity, and government corruption, unraveling their unique relationships with happiness.

For instance, wealth - denoted as GDP per capita - demonstrated a robust positive correlation with happiness. This relationship suggests that an increase in a nation’s wealth can lead to a corresponding elevation in the happiness of its citizens. Specifically, for each unit increase in GDP per capita, we observed a substantial 1.92 unit surge in happiness scores.

Yet, this consistent pattern was not universal across all variables. Freedom, generosity, and government corruption presented high variability in their impacts on happiness, implying that these relationships might be under the influence of other, more intricate factors. For example, the effect of government corruption on happiness could be contingent on a nation’s level of economic development.

These insights emphasize the need to consider a multifaceted array of influences that contribute to our well-being. Further exploration may involve refining our current models or integrating new variables to account for the variability observed. Ultimately, the goal is to foster a more nuanced understanding of the key elements underpinning our sense of happiness.

Case Study:China & USA

Comparative analysis: china and usa.

The choice of China and the United States as case studies stems from their prominent global roles, contrasting cultural, social, and political systems, and pragmatic considerations related to data analysis. The original dataset encompasses a vast amount of data spanning numerous countries (135 countries with 8 years of complete data). Consequently, it’s beyond the scope of this analysis to delve into every country individually. As the two largest economies worldwide, China and the U.S. wield significant global influence. Their paths to their current statuses have been distinctly different, as are their societal values. Examining the determinants of happiness in these two nations can provide valuable insights into how various factors contribute to societal well-being within diverse contexts. Additionally, comparing these two countries may shed light on how different economic and political systems can shape citizen happiness.

In our investigation into the determinants of happiness, we considered factors such as GDP per capita, family support, life expectancy, freedom, generosity, government corruption, as well as their interactions with time and location, specifically within the context of China and the United States. Interestingly, none of these factors emerged as significant predictors of happiness scores using commonly accepted thresholds.

Despite the model accounting for nearly all the variance in happiness (R-squared value of 0.9993), the high residual standard error coupled with low degrees of freedom suggests potential overfitting. Essentially, our model may be too precisely fitted to this particular dataset, thereby restricting its applicability to other contexts or future data.

It’s vital to remember that a high R-squared value alone doesn’t assure a robust model. Furthermore, given our study’s observational nature, we can’t establish with certainty that the factors we studied cause changes in happiness.

Our investigation emphasizes the complexity inherent in predicting happiness and underscores the necessity for further nuanced analysis to fully understand the interplay of these determinants.

Critical Reflection

Throughout this project, I extensively utilized R and its associated packages for data processing, visualization, and modeling. While R is indeed a powerful and flexible tool, its application was not without challenges and limitations.

One of the notable hurdles in the data visualization process was overplotting. In scenarios where data points were densely clustered for specific variables, it was challenging to discern clear patterns within the graphs. Potential countermeasures, such as employing more complex visualizations like 2D kernel density plots or introducing jittering to minimize overlap, were not explored within the scope of this project, and they remain avenues for future enhancement.

Further on data visualization, the geographical heatmaps constructed to illustrate happiness indices across various countries, although insightful, were found to be somewhat limited in their interactive capabilities. Users are unable to click or hover over particular regions on the map for additional information due to their static nature. Future improvements could involve integrating such interactive features to enhance user engagement and information dissemination.

As I delved into data analysis, the choice to deploy linear models was a conscious decision given their ability to reveal intricate relationships between variables. The influence and direction of independent variables on the dependent variable could be intuitively comprehended through the sign and magnitude of the coefficients. Moreover, linear models allowed for some degree of control over confounding variables, a crucial aspect when exploring a multifaceted concept like happiness.

Despite their merits, the limitations of linear models must be acknowledged. These models assume a linear relationship between independent and dependent variables, which may not always align with real-life scenarios, where relationships could be nonlinear. Additionally, the presuppositions of independent and homoscedastic error terms may not always hold.

To circumvent these challenges, we could consider more complex models such as polynomial regression models or models with interaction effects. These are especially pertinent if we suspect the relationship between happiness and other factors to be nonlinear or influenced by other variables. However, such models are computationally more demanding, complex, and may pose interpretability challenges. Thus, the model selection process invariably involves a trade-off between complexity, interpretability, and computational efficiency.

Another pitfall of modeling approaches that emerged from this study is the potential for overfitting. Overfit models can be overly precise, limiting their applicability to other contexts or future data. Care must be exercised when employing models, remaining cognizant of their underlying assumptions and potential limitations.

In conclusion, this project, despite presenting challenges, offered invaluable lessons. The encountered obstacles illuminated the complexities inherent in data analysis and underscored the importance of thoughtful model selection. These experiences will undoubtedly enrich my future research pursuits, stimulating exploration of additional analytical tools and methodologies, all while developing a more nuanced understanding of social science phenomena.

J, A. (2018, March 2). Developed and Developing Countries: World Bank Classification | Economics. Economics Discussion. https://www.economicsdiscussion.net/economic-development/developed-and-developing-countries-world-bank-classification-economics/30010

Sustainable Development Solutions Network. (2023). World Happiness Report. Worldhappiness.report. https://worldhappiness.report/

Technical References

Kieran Healy. (2019). Data visualization : a practical introduction. Princeton University Press.

Kuhn, M., & Silge, J. (2022). Tidy Modeling with R. O’Reilly Media, Incorporated.

Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10). https://doi.org/10.18637/jss.v059.i10

Wickham, H. (2019). Advanced R, Second Edition. CRC Press.

Wickham, H., & Grolemund, G. (2017). R for data science : import, tidy, transform, visualize, and model data. O’reilly.

Wickham, H., Sievert, C., & Springer. (2016). Ggplot2 : Elegant Graphics For Data Analysis. Cham, Schweiz] Springer.

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The GoodHome Report

The Happiness Research Institute & Kingfisher plc, 2019

What makes a happy Home, and what are the different conceptions of it across 10 countries in Europe?

The GoodHome Report is a major new international study which has been undertaken by the Happiness Research Institute and Kingfisher plc. The report looks at the impact of our homes on our overall happiness and wellbeing. The study surveyed 13,489 people and conducted 78 in-depth personal interviews with people from across 10 countries in Europe.

A key finding is that the home is significantly more important to our happiness than our income or job. Size, location and home ownership have far less impact on happiness than we might expect. 

Take a look at the short version here .

Download report here

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

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Kim Parker is director of social trends research at Pew Research Center .

Teens and Video Games Today

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From poverty to empowerment: Raising the bar for sustainable and inclusive growth

Growth, inclusion, and sustainability are connected, often complementing one another but sometimes pulling in different directions. 1 While inclusion intersects with issues of race and gender, this report focuses on economic inclusion for the population as a whole. MGI and McKinsey have a large body of research examining inclusion from racial and gender perspectives. Similarly, while sustainability encompasses many priorities, this research focuses specifically on the net-zero transition. This research explores how growth can contribute to higher living standards and a greener world, building on the tremendous progress of the past half century. Specifically, it looks at the economics of addressing both poverty and climate change in a decisive way—as well as the trade-offs involved.

We focus on established global aspirations without imposing constraints on the ambitions. On the sustainability side, the Paris Agreement laid out a framework to limit temperature rise to well below 2.0°C (and preferably to 1.5°C) relative to preindustrial levels. In response, many countries have committed to reaching net-zero emissions. On inclusion, while the world has made historic strides against extreme poverty, development experts and economists have discussed setting a higher bar for living standards. The UN Sustainable Development Goals (SDGs) propose achieving adequate nutrition, health, education, clean water, energy, and living conditions for all. The concept of economic empowerment used in this research captures these aspirations. For each country, we estimate the point at which individuals can meet their essential needs and begin to have some security. This does not undermine the goal of eliminating extreme poverty; it explores how to move further toward a world in which people realize more of their own potential.

The actions taken (or not) in this decade will determine what kind of world the next generation will inherit. This research therefore considers how much progress could be feasible by 2030. 2 We use a 2020 starting point to give a clear decade-long view of potential progress. Scenarios from the Network for Greening the Financial System (NGFS), the basis for our sustainability analysis, use 2020 as their starting point. Based on investment in low-emissions assets and increases in empowerment in 2021 and 2022, the scale of spending needed this decade has not dramatically shifted. The time frame is intentional. At today’s level of emissions, the world’s carbon budget for holding to a 1.5°C path is expected to run out around the end of the decade. In addition, 2030 is the target for the SDGs. Without faster progress on empowerment, the next generation could enter adulthood ill-equipped for the jobs of the future, putting many at risk of falling further behind.

Key findings

• This research considers growth, inclusion, and sustainability as parts of a connected system. It assesses the extent to which accelerated growth can further the two defining societal aspirations of our time: raising minimum living standards and limiting global warming. It also frames the choices countries face in a decisive decade that will determine the state of the world in 2050.
• Beyond ending poverty, the next challenge is progressing toward economic empowerment, which enables people to realize more of their potential. Economic growth has fueled tremendous poverty reduction in the past half century. Many have argued that the $2.15 per day extreme poverty line needs a complementary benchmark to gauge progress beyond that point. We frame this higher bar as the empowerment line, the level at which people can afford to meet essential needs such as nutrition, housing, healthcare, and education; they also gain a modest sense of security and have reduced risk of slipping back into poverty. Empowerment starts at $12 per day in purchasing power parity terms globally, with regional variations to account for different norms and costs. As of 2020, some 730 million people lived in extreme poverty, while 4.7 billion were below the empowerment line.
• The pursuit of economic empowerment must be viewed in conjunction with global net-zero commitments. Addressing the causes of climate change is a pressing economic and social challenge—and at today’s emissions levels, the carbon budget to limit warming to 1.5°C is trending toward being exhausted by 2030. Achieving net-zero emissions, as many countries have pledged to do, would require a major increase in investment and in the capacity of energy and resource systems.
• The dual goals pose tensions that need to be managed. Rapid improvement in living standards could raise demand for energy- and emissions-intensive products and services (although historical patterns could change if new consumers shift behaviors). A disorderly net-zero transition could increase energy and other costs for consumers and cause labor market frictions, creating a disproportionate burden for low-income households; if people feel it is crowding prospects for their lives to improve, support could waver. At the same time, not acting to curb temperature rise could harm economies, and the poorest populations are most heavily exposed to physical risks.
• The combined empowerment and net-zero investment gaps amount to an enormous 8 percent of global GDP annually over the decade. We quantify the cumulative spending boost that would close both gaps by 2030. Lifting everyone above the empowerment threshold implies that the people currently below it would need 40 percent more spending power on average by 2030 (even more in sub-Saharan Africa and India). To get on a net-zero trajectory, the world would need to muster an additional $41 trillion in low-emissions investment (above continued 2020 spending levels, cumulatively through 2030). These are shifts in income, consumption, and investment of an unprecedented magnitude.
• Businesses and the market economy can generate half the combined resources through growth and innovation. This involves not only maintaining baseline growth but also boosting productivity even further through investment in technology, new businesses, and human capital. Accelerated growth and better-paying jobs could close almost two-thirds of the global empowerment gap. On the climate transition, even with current policies, we see potential for almost $10 trillion of low-emissions alternatives to become viable for private actors, especially in power and mobility. All told, growth and innovation, even without policy changes, could unlock just over a third of the step-up needed in net-zero spending.
• Beyond what market forces can address under current policies, substantial gaps remain—and so do hard choices about whether and how to fill them. Growth and innovation alone could generate progress that would be historic in and of itself. Yet closing both gaps in full would take even more than what they can deliver without new policies and incentives. We estimate the unfilled economic gap at 4 percent of GDP per year globally, or $40 trillion, cumulatively through the decade. Developing countries account for nearly two-thirds of this.
• Additional societal commitments could accelerate progress but come with their own risks. Combined public and private action could deliver housing, healthcare, education, and food that is more affordable and leads to better outcomes, potentially unlocking $3 trillion of benefits to those below the empowerment line. Public finance support could change the risk and cost profiles of net-zero investments, unlocking a further $17 trillion from private actors over the decade. However, such extensive commitments could distort the baseline economy. In a scenario where high-income economies choose to shoulder both gaps for the world, it would amount to 3.5 percent of their own GDP annually; the global financial system would need to accommodate higher cross-border flows.
• Empowering large populations while getting on a net-zero trajectory would take a global push for growth, innovation, and collaboration. Growth boosts economic empowerment and creates the financing capacity for net zero. The upside is compelling: some 2.1 billion people could move above the empowerment line and 600 million people out of poverty, taking significant steps on their journey toward full economic empowerment. Yet addressing residual gaps would take bolder innovation in finance, technology, industry, and policy. The possibilities include creating new multilateral financing vehicles; integrating low-income countries into global trade in a way that lifts local communities and small businesses; developing sustainable cities with affordable housing; and designing effective carbon markets. Private actors, governments, and nonprofits would need to combine their capabilities and expertise—and think without limits about how they can contribute to meeting this moment.

Since these are urgent, simultaneous challenges, we bring them together to offer a more holistic view, considering the interactions between growth, economic inclusion, and the net-zero transition (Exhibit 1). Productivity-driven growth lifts incomes and raises living standards while unlocking the financing capacity needed for a low-emissions future. Meanwhile, innovation that goes hand in hand with growth can bring down the costs of low-emissions technologies. This could lower the spending needed for the transition and reduce the risk of households facing higher costs as a result.

Yet tensions exist in the system. Global economic empowerment implies billions of people with growing demand for energy, while a disorderly net-zero transition could create challenges of affordability. Some may view investment in the transition as a project that crowds out prospects for their lives to improve—but since the poorest populations are most exposed to the physical risks of climate change, reducing those risks is part of ensuring general well-being.

This research sizes the empowerment and net-zero gaps and explores scenarios of how they could theoretically be closed. The empowerment gap is the cumulative boost in consumption needed to meet everyone’s essential needs by 2030, while the net-zero investment gap is the cumulative spending on low-emissions technologies needed over the decade, above what is happening at present. Since neither could be addressed instantaneously, we assume steadily upward progress over the decade. This hypothetical would require the equivalent of 8 percent of global GDP annually, with significant variations by region.

This is obviously a massive sum, and its scale leads us to explore how much market forces could deliver. We find that accelerated growth and business innovation could take the world halfway to closing the combined gaps. Companies can make major contributions and benefit from new opportunities, even under current policy frameworks.

Beyond this point, the remaining economic gaps leave societies with choices about whether to address both challenges in full, in part, or not at all. Countries might prioritize one of these transformations over the other, or leave both unaddressed beyond what market forces can do. They might also attempt to make partial progress on both fronts. Closing the gaps would require protecting baseline growth against headwinds, boosting productivity and innovation to maximum levels, and potentially making societal commitments equivalent to 2 percent of global GDP, as an annual average, over the decade ($20 trillion cumulatively). Importantly, societal commitments would activate more innovation and investment by private actors. But actions on this scale would also take economies into uncharted territory, demanding more attention to maintaining economic growth and stability.

Learn more about how we are accelerating sustainable inclusive growth

We frame the empowerment line as the level at which people can meet their essential needs and realize more of their potential. It has a global floor of $12 per day in PPP (versus the extreme poverty line of $2.15 PPP).

Societies are already spending on the twin priorities. In 2020, some 90 percent of the $1.4 trillion of global net-zero spending was either made by the public sector or subsidized in some way. About 20 percent of the consumption of people below the empowerment line was supported by public and social spending on in-kind transfers in 2020, by our estimates.

Are there further opportunities to close gaps without risking growth? All economies have constraints on fiscal resources. They would need to weigh those constraints against the implications of leaving urgent needs unaddressed—and against the potential longer-term payoff of an economically empowered population and a stable climate. Our research aims to provide ambition, provocation, and a fact base to inform these debates.

Economic empowerment raises living standards

More than a billion people have exited extreme poverty in recent decades. Yet large populations above this line lack adequate healthcare, quality education for their children, or decent housing. The SDGs incorporate higher aspirations, while the UN Development Programme calls to “expand the sense of possibility in people’s lives.” 3 Human development report 2021–22: Uncertain times, unsettled lives: Shaping our future in a transforming world , UN Development Programme, September 2022. When people have health, education, and stability, they are equipped to improve their own circumstances.

Continuing to raise the bar everywhere in the world

The World Bank’s extreme poverty line was recently updated from $1.90 to $2.15 per person per day (in purchasing power parity, or PPP, terms). 4 This 2022 update in the global poverty line also involved changing from 2011 PPP terms to 2017 PPP terms. But as more people exceed it, the world needs a complementary benchmark to track progress toward a higher living standard.

The concept of economic empowerment described in this research ensures that everyone has the means to access the full range of basics (Exhibit 2). Empowerment  still implies living in frugal circumstances. But people can begin to build a modest buffer for weathering emergencies and can invest in themselves to become more productive. 5 This concept is rooted in earlier MGI research that quantified the cost of a basket of essential goods and services for households in India. See From poverty to empowerment: India’s imperative for jobs, growth, and effective basic services , McKinsey Global Institute, February 2014.

When people rise meaningfully above poverty, many outcomes improve, including childhood mortality, life expectancy, years of schooling, and digital and financial inclusion. Life satisfaction increases when people shed the stress of not being able to make ends meet and can fulfill more of their material desires. 6 Daniel Kahneman and Angus Deaton, “High income improves evaluation of life but not emotional well-being,” Proceedings of the National Academy of Sciences , volume 107, issue 38, September 2010. Andrew T. Jebb et al., “Happiness, income satiation and turning points around the world,” Nature Human Behaviour , volume 2, 2018, found a similar relationship between life satisfaction and prosperity globally.

Image description: A circular diagram illustrates ten components of empowerment. Eight of them are characteristics of sufficiency, including food, healthcare, and education, and the other two are characteristics of security, including civic engagement and a savings buffer. End of image description.

How we quantify the higher bar

We start with consumption of $12 per person per day in PPP terms as a global floor, in line with other research (see sidebar, “Measuring economic inclusion”). For countries at higher income levels, we raise the line to account for local norms and the costs of food, housing and energy, safe water access, transportation, healthcare, education, clothing, and communication, using WageIndicator data as of 2022 and 2023. Purchasing power is consistently set to obtain that basket of goods plus a small margin for social activities and savings. 7 We note that having one empowerment threshold for a given country does not reflect how housing and other costs vary from region to region within the country; it costs more to live an empowered life in an expensive major city than in a poorer rural area. The housing may be a modest apartment; the transportation could be a transit pass, a used car, or perhaps a motorbike in some contexts.

Measuring economic inclusion

It’s been said that you can’t improve what you can’t measure. In the case of poverty, the challenge is not a lack of metrics but rather a proliferation of them. 1 Anthony B. Atkinson, Measuring poverty around the world , Princeton University Press, 2019. Starting with the holistic SDGs, economic inclusion can be framed as moving everyone toward health and well-being, education, affordable essentials, and sustainable communities.

Poverty can be more specifically expressed in monetary or nonmonetary terms. 2 Nonmonetary approaches include the Multidimensional Poverty Index developed by Sabina Alkire and James Foster, and the UN Development Programme’s Human Development Index. See Global multidimensional poverty index 2023 , Oxford Poverty & Human Development Initiative and UNDP, 2023. It is often calculated monetarily by looking at income or consumption, using both absolute and relative terms or a hybrid of the two (exhibit). The World Bank, for example, sets its global extreme poverty line at $2.15 per person per day in 2017 purchasing power parity terms. This is the median of national poverty lines in more than two dozen of the world’s poorest countries. 3 Updated from $1.90 in 2011 PPP. See Dean Jolliffe et al., Assessing the impact of the 2017 PPPs on the international poverty line and global poverty , World Bank policy research working paper number 9941, February 2022. To account for higher living standards as countries move up the development curve, the World Bank introduced poverty lines specific to lower-middle- and upper-middle-income economies. 4 R. Andres Castaneda Aguilar et al., “September 2022 global poverty update from the World Bank: 2017 PPPs and new data for India,” World Bank Data Blog, September 14, 2022.

Image description:

Two sets of vertical, stacked bar charts show an example of daily spending patterns that illustrates how the means to achieve sufficiency in basic needs varies by stages of development. The set of bar charts on the left shows two bars for the daily spending patterns of a low-/middle-income economy in 2017 PPP terms. One bar is for the extreme poverty line, at $2.15, and the other is for the empowerment line, at $12.

The set of bars on the right shows two bars and compares the breakdown of spending categories for a low-/middle-income economy empowerment line vs a high-income economy empowerment line. Figures are shown as a percent of total, and categories include food, housing, health, education, transportation, and all others. The low-/middle-income economy bar shows more spending on food than in a high-income economy. The high-income economy bar shows spending on housing equal to spending in a low-/middle-income economy but more spending on health compared to a low-/middle-income economy.

Below each set of bars, scaled circles visualize the population living below the specified line in 2020. In low-/middle-income economies, 0.7 billion live below the extreme poverty line and 3.7 billion live below the empowerment line; in high-income economies, 0.3 billion live below the empowerment line.

End of image description.

Another approach uses the extreme poverty threshold as a floor, combined with lines that rise with countries’ income levels. 5 See, for example, Martin Ravallion and Shaohua Chen, “A proposal for truly global poverty measures,” Global Policy , volume 4, issue 3, September 2013. Others have proposed an entirely relative line based on median income or consumption. 6 Christopher Garroway and Juan R. de Laiglesia, On the relevance of relative poverty for developing countries , OECD Development Centre, working paper number 314, September 2012.

Another set of literature uses the aspiration for everyone globally to reach a higher living standard. Development economist Lant Pritchett, for example, proposes using the high-income poverty threshold universally, arguing that there is basic unfairness in setting a line with lower living standards in developing countries. 7 Lant Pritchett, “Monitoring progress on poverty: The case for a high global poverty line,” in Eradicating global poverty: A noble goal, but how do we measure it? Emma Samman, ed., Overseas Development Institute working paper, 2013. The lower bound of a high-income poverty threshold has inspired definitions of a global middle class, a topic of debate. Abhijit Banerjee and Esther Duflo have explored the consumption patterns that point to someone exiting poverty and entering the global middle class. 8 Abhijit V. Banerjee and Esther Duflo, “What is middle class about the middle classes around the world?” Journal of Economic Perspectives , volume 22, number 2, spring 2008; and William Easterly, “The middle class consensus and economic development,” Journal of Economic Growth , volume 6, 2001.

The concept of economic empowerment in this research defines a minimum acceptable standard of living as having the means to afford nutrition, education, healthcare, housing, water and sanitation, and energy. Many of these aspirations are embodied in the SDGs; they are essential to enabling people to realize more of their potential. Empowerment starts with an absolute floor that lifts people past the point at which they are no longer at extreme risk of falling back into poverty. 9 Latin American economic outlook 2019: Development in transition , OECD, Economic Commission for Latin America and the Caribbean, CAF Development Bank of Latin America, and the European Union, 2019. Middle-class households have also been defined as “comfortably clear of the risk of poverty” in Anthony B. Atkinson and Andrea Brandolini, “On the identification of the middle class,” in Income inequality: Economic disparities and the middle class in affluent countries , Janet C. Gornick and Markus Jantti, eds., Stanford University Press, 2013. Research from Brookings economist Homi Kharas (cofounder of World Data Lab, one of the main sources of data for this analysis) suggests that this level is $12 per person per day in PPP terms. 10 Homi Kharas, The emerging middle class in developing countries , OECD Development Centre, working paper number 285, January 2010, defines the global middle-class line as $10 in 2005 PPP, since raised to $12 in 2017 PPP. Also using this general level are Surjit Singh Bhalla, Second among equals: The middle-class kingdoms of India and China , 2007; Nancy Birdsall, Nora Lustig, and Christian Meyer, The strugglers: The new poor in Latin America? Center for Global Development working paper number 337, 2013; and Rakesh Kochhar, “The pandemic stalls growth in the global middle class, pushes poverty up sharply,” Pew Research Center, March 2021. See also worlddata.io.

Since we aim to use a common definition of basic needs and security worldwide, why not an absolute PPP threshold? First, the data set from the WageIndicator Foundation that we use for setting thresholds above the global floor prices a consistent basket of essential goods and services, not the economy-wide basket used in PPP measures. 11 This data set compiles costs of essential goods (rather than the whole economy, which PPP indices measure). See Martin Guzi et al., Living wages and income worldwide , WageIndicator Foundation, 2023, and wageindicator.org. Second, some costs vary due to differing norms for the type or amount of a good or service related to empowerment (for example, the type of transportation required to secure a job or the minimum quantity of healthcare available to consumers). Our approach therefore gradually scales up empowerment lines for countries with progressively higher levels of income. 12 The combination of a floor with a gradual scaling-up approach is used by Dean Jolliffe and Espen Beer Prydz, “Societal poverty: A relative and relevant measure,” World Bank Economic Review , volume 35, issue 1, February 2021.

Our approach is consistent with economist Martin Ravallion’s view: “Any absolute line you choose will not adjust over time or across countries for differences in the costs of avoiding social exclusion and relative deprivation. . . . Where and when you live matters as to whether you should be considered poor at any given level of real consumption.” 13 Martin Ravallion, “Two goals for fighting poverty,” in Eradicating global poverty: A noble goal, but how do we measure it? Emma Samman, ed., Overseas Development Institute working paper, 2013. Nobel laureate Amartya Sen also notes that what is needed for daily life may differ across societies. 14 Amartya Sen, Development as freedom , Oxford University Press, 1999.

Empowerment is related to the “living wage” concept that has gained traction for employers and workers to evaluate wages against living costs. It has been broadly defined as the amount individuals need to earn to cover their basic household expenses plus taxes. 15 See, for example, Amy K. Glasmeier, Living Wage Calculator, livingwage.mit.edu. The empowerment line is a consumption-based counterpart that complements this income-based metric.

In both high- and low-income countries, we view empowerment as the point at which people can begin to invest in themselves and have a fuller range of choices about shaping their lives. This echoes Sen’s assertions that income alone does not reflect well-being. Economic empowerment conveys the ability to participate in society, the freedom to enjoy life, and individual agency.

Finally, economic inclusion raises the larger topics of inequality and redistribution. In this research, we determine what it would take to lift the poorest population segments, a goal that has widespread support. We explicitly do not model redistribution from the wealthiest segments as the means to achieve this. We also recognize that poverty intersects with issues of race and gender, but this analysis does not incorporate demographics.

We then convert from PPP terms to 2020 US dollars. Expressed that way, the empowerment threshold ranges between $3 and $50 per capita per day across the countries in our data set. 8 Iceland and Switzerland are outliers on the upper end of the empowerment line range and above $50. To give some examples, the line is about $3 per capita in Afghanistan and Sudan; $4 to $5 in India, Indonesia, and Nigeria; $8 to $11 in China, Mexico, South Africa, and Thailand; $15 to $45 in Australia, Denmark, Italy, Japan, and Poland; and $50 in the United States. Establishing each country’s threshold makes it possible to size its empowerment gap—the share of the population that falls short of sufficiency as well as the dollar amount that would bridge this gap.

Because we use a consumption-based metric, taxes and direct transfers are already taken into account. Cost-of-living thresholds are then adjusted for the estimated in-kind transfers provided in each country. Universal healthcare, for example, lowers out-of-pocket healthcare costs for individuals. We note, however, the challenges of accurately tracking how public services reach the targeted recipients. Indeed, one way for countries to advance empowerment is through logistical and operational improvements to ensure that social benefit programs can be accessed by their intended beneficiaries.

Finally, we note that empowerment is a per-person metric. Families that combine their resources would have better prospects for meeting their basic needs than individuals below this line living alone.

Driving sustainable and inclusive growth in G20 economies

Who is not fully economically empowered.

About 4.7 billion people worldwide (approximately 60 percent of the global population) are not yet fully economically empowered by this benchmark (Exhibit 3). 9 For both empowerment and sustainability analyses, we use regional groupings that follow NGFS conventions. Some 4.4 billion of them live in low- and middle-income countries; nearly half are in sub-Saharan Africa and India. Some may live in rural villages far from the nearest medical clinic; others are in crowded urban tenements.

For many people below the empowerment line, especially in the world’s major cities, the high cost of housing eats into other priorities.

Yet more than 300 million people in high-income countries also fall into this category, including just over a quarter of the population in the United States and in the European Union and United Kingdom. While even high-income countries have some degree of homelessness and deprivation, most of the population below the empowerment line in these regions does not experience such severe poverty. Yet some of their essential needs are not sufficiently met. In many cases, the high cost of housing eats into other priorities. People may not be able to invest in better education or training for themselves or their children. Closer to the threshold, a person may rent a basic apartment with a decently equipped kitchen; he may even own a TV, a mobile phone, or a used car. But living paycheck to paycheck means there is little savings to handle emergencies, move, or retire comfortably. Someone whose family members have disabilities may have limited prospects for employment without caregiving support, for example.

The family of four squeezed into a small studio apartment in Los Angeles is not fully empowered. Neither is the street vendor in Lima nor the subsistence farmer in Laos.

A horizontal bar chart shows the breakdown of the population by spending level in relation to the empowerment line globally and by regions. The first bar is the global bar, which shows 4.7 billion people, or 61% of the global population, live below the empowerment line. Regional breakdowns show that sub-Saharan Africa has the highest share of population below the empowerment line, at 90%, followed by India, at 77%. Japan has the lowest percentage of people below the empowerment line, 19%.

The magnitude of lifting everyone to empowerment

Our analysis assumes that people below the line gain a bit more spending power each year through 2030. Because we adopt a common time frame for the world, this ramp-up to full empowerment would be steeper for the poorest deciles and more gradual for deciles closer to the line.

Using these parameters, achieving universal empowerment by 2030 would involve boosting the cumulative consumption of 4.7 billion people worldwide over the decade by just over $37 trillion (the empowerment gap). This boost is equivalent to 40 percent of this cohort’s continued spending at 2020 levels. 10 The empowerment gap refers exclusively to the boost in spending power over 2020 levels. The current consumption of people below empowerment thresholds would amount to some $94 trillion over ten years, if extended at current levels. We note that the gap is the product of how the threshold and the timeline are set. Lowering the threshold or allowing this trajectory to play out over a longer time frame would produce different results.

Making progress toward closing the empowerment gap matters. For billions of people, achieving minimum living standards is the foremost existential issue. Their hopes involve getting out of unsustainably high debt, securing healthcare for their children, or moving in search of a better job. Leaving so many people in vulnerable circumstances imposes limits on growth and risks destabilizing societies.

Empowerment could yield long-term benefits—and not only for the individuals whose lives improve. It would eventually create a virtuous cycle. Many more people would have the skills and agency to participate in a knowledge-intensive and digital economy. They would also become consumers, fueling future growth.

The net-zero investment gap is the incremental low-emissions spending needed by 2030 to change the climate trajectory

Alongside the aspiration to raise living standards, countries and companies worldwide have committed to reducing emissions to net zero, aiming to limit global warming to 1.5°C relative to preindustrial levels in the current century. This research builds on scenarios from the Network for Greening the Financial System to quantify the low-emissions spending needed to get on this pathway by 2030 (see sidebar, “Measuring the net-zero investment need”). Across seven sectors globally, our analysis finds the biggest needs in power and mobility (Exhibit 4).

Square area charts show the low-emissions spending need and net-zero investment gap by energy and use sectors. From largest spending need to lowest, they are power, mobility, buildings, agriculture, industry, forestry, and hydrogen.

Each square is sized by each sector’s spending need, and each contains a shaded region that shows the proportion of spending need that is the net-zero investment gap. Power and buildings have the smallest gaps compared to other sectors proportionally. Globally, $55 trillion is the total for low-emissions spending need, and $41 trillion is the net-zero investment gap.

This research looks at scenarios of baseline economic growth (2.7 percent globally) and accelerated growth (3.4 percent globally). 11 Baseline growth relies on projections from Oxford Economics (aggregating different growth rates across countries). Accelerated growth is an adjusted scenario in which productivity gains add another 0.7 percentage point. Given the critical importance of growth to economic inclusion, we use the higher assumption for net zero, a scenario that could add an estimated 3 gigatons (Gt) of energy-related CO2 emissions in 2030 if historical relations of growth and emissions hold. This means that low-emissions spending would correspondingly need to scale up almost $5 trillion globally beyond what would be needed in a baseline scenario. In this high-growth world, getting on track for net zero would take cumulative investment and spending of $55 trillion on low-emissions assets over the decade—a step-up of $41 trillion as compared with simply extending 2020 levels. We refer to this step-up as the net-zero investment gap. 12 These figures differ from those in our 2022 report The net-zero transition: What it would cost, what it could bring . Here we focus only on low-emissions spending rather than total high- and low-emissions spending, and we use a 2030 rather than a 2050 time frame. This research also includes updated data and refined assumptions. At the same time, higher growth would expand the world’s financing capacity.

It is important to note that this $41 trillion figure does not reflect the world’s full energy and land-use investment; it excludes spending on high-emissions assets. Some high-emissions spending would continue, particularly in developing economies that are still expanding energy access, but overall global levels would fall. Some of the step-up in low-emissions spending could be captured as capital is reallocated away from high-emissions assets, provided that low-emissions alternatives become viable and cost competitive.

Measuring the net-zero investment need

We build on scenarios from the Network for Greening the Financial System (NGFS), adjusting for baseline and accelerated growth. NGFS scenarios are frequently used in risk analysis, provide regional granularity, and include a holistic view of emissions. This analysis is performed for approximately 50 key low-emissions technologies and 12 regions, addressing 85 percent of global greenhouse gas emissions. In some cases, NGFS variables were downscaled for more granular quantification. Our “investment” need includes both capital investment and consumer spending on items such as electric vehicles. We include only low-emissions investments such as solar and wind power, while excluding high-emissions investments in areas such as fossil fuels.

We build on the NGFS Net Zero 2050 scenario (with warming of 1.5°C by 2100) to estimate the incremental low-emissions investment that would be needed (the net-zero investment gap). The NGFS Current Policies scenario enables us to estimate how much spending is likely under current policy frameworks (with warming of about 3.0°C by 2100). Other “current policy” scenarios may produce slightly different warming outcomes, though all would find a gap with a net-zero trajectory.

We also employ the McKinsey Transition Finance Model to answer the question of who pays. First we determine, for each lever and region combination, the share of grant and concessional spending required to make low-emissions technologies cost competitive with high-emissions alternatives based on their total cost of ownership, and to compensate consumers and companies for the technological and market risks associated with them. We rely on this modeling even for 2020, due to limited data on present-day subsidies; however, where available, we have triangulated our results with actual data. The rest of the spending need is then split between private actors (corporations and consumers) and public actors (governments, state-owned enterprises, multilaterals, and philanthropies) based on historical patterns and expert input. We acknowledge the many uncertainties  in both this allocation and the size of the investment gap. 1 See The net-zero transition: What it would cost, what it could bring , McKinsey Global Institute, January 2022.

A note on data sources

The net-zero modeling used in this research relied on several proprietary McKinsey assets, including McKinsey Net Zero Analytics, McKinsey Hydrogen Insights, the McKinsey Center for Future Mobility, and McKinsey Power Solutions.

Among the external sources of data in this report, we acknowledge the International Energy Agency (Paris). We specifically relied on three IEA sources: Net zero by 2050 , 2021, https://www.iea.org/reports/net-zero-by-2050; World energy outlook 2021 , https://www.iea.org/reports/world-energy-outlook-2021; and Energy technology perspectives 2017 , https://www.iea.org/reports/energy-technology-perspectives-2017. All are license CC BY 4.0.

We note that some analysis in this research was derived from IEA material, and MGI is solely liable and responsible for it; it is not endorsed by the IEA in any manner. This holds true for all providers of the data that went into our analysis. We gratefully acknowledge their assistance and input, but the conclusions and any errors are our own.

Our analysis assumes that providing incentives for low-emissions spending through subsidies would produce the same outcome as discouraging high-emissions spending through taxes. In practice, however, more policy mechanisms are needed to limit high-emissions spending. Some scholars have pointed to carbon taxes and subsidies as complements rather than a binary choice, especially at early stages of the net-zero transition. 13 For example, see Daron Acemoglu et al., “The environmental and directed technical change,” American Economic Review , volume 102, number 1, February 2012.

Empowerment and the net-zero transition affect each other—and some tensions would need to be managed

As people move toward empowerment, their consumption rises. As mentioned earlier, our analysis builds in the assumption that higher economic growth increases the net-zero financing need, relying on the historical relationship of growth to the production and consumption of energy- and emissions-intensive products. Going further to achieve full empowerment by 2030 could push these needs—and therefore emissions—even higher than what is accounted for in this adjustment.

Using data from India, South Africa, the United Kingdom, and the United States, we estimate that moving everyone to the empowerment line could raise demand for energy-intensive products and services, and in turn emissions, by as much as an additional 15 percent above the effects of accelerated growth alone. 14 Data on household energy expenditures from the UK Office for National Statistics, US Consumer Expenditure Survey, Statistics South Africa, and India 68th Round of National Sample Survey. Energy expenditures are uplifted for each decile under the empowerment line, then used to estimate the relative increase in emissions per capita for each country (based on World Bank CO 2 energy-related emissions data for each country’s direct emissions). Does not include non-energy and non-CO 2 emissions, which could change the estimate. However, significant uncertainties surround the effects of growth and empowerment on emissions. Historical patterns could change, for example, if consumers shift behaviors.

Just as empowerment affects the net-zero transition, the reverse is also true. If interventions such as carbon taxes increase the costs of energy and other goods for consumers, they could create a disproportionate burden for people below the empowerment line. 15 Energy prices could rise in the near term, for example, if carbon prices are imposed before low-emissions energy sources are widely available and cost competitive. But they could also decline over the longer term (for example, due to the lower operating costs of renewable energy sources and through energy efficiency). Actions such as recycling carbon tax revenue into transfers or subsidies could protect low-income households and provide economic development for distressed communities. 16 See, for example, Jonathan L. Ramseur and Jane A. Leggett, Attaching a price to greenhouse gas emissions with a carbon tax or emissions fee: Considerations and potential impacts , US Congressional Research Service, 2019; Frederick van der Ploeg and Maria Chiara Paoli, “Recycling revenue to improve political feasibility of carbon pricing in the UK,” VoxEU, October 2021; and Baoping Shang, The poverty and distributional impacts of carbon pricing: Channels and policy implications , IMF working paper, 2021.

The net-zero transition could redistribute jobs across industries and regions.

The net-zero transition could produce a surge of jobs in construction, certain types of manufacturing, and operations. Previous MGI research found that job gains could slightly outweigh job losses globally. 17 The net-zero transition: What it would cost, what it could bring , McKinsey Global Institute, January 2022. See also World Employment and Social Outlook 2018: Greening with jobs , International Labour Organization, 2018. However, the small net impact disguises the possibility of substantial churn as jobs are redistributed across industries and regions. In addition, the jobs being added may require different skills.

These potential impacts on households and labor markets make it crucial to manage the transition effectively and support consumers and workers in the most affected regions and sectors.

The two aspirations also have complementary aspects. Not acting to curb temperature rise could harm growth—and empowerment—substantially through effects such as impairing the ability to work outdoors, agricultural losses, and damage to capital stock. Lower-income people would become even more exposed to hazards if climate change is not convincingly addressed. And research has shown that as households become more empowered, they are more likely to be aware of the risks of climate change and, in turn, lend support to net-zero policies. 18 Higher-income households are more likely to buy products with sustainability-related claims; see “ Consumers care about sustainability—and back it up with their wallets ,” McKinsey & Company, February 2023.

The gaps vary widely across regions

The empowerment and net-zero investment gaps vary in magnitude across different parts of the world, not only in absolute dollar terms but also relative to GDP.

In the timeline we have set to 2030, the global empowerment gap would be equivalent to about 4 percent of world GDP on average annually. However, it is only 1 percent of annual GDP in high-income regions, including Australia, Canada, the European Union and the United Kingdom, Japan, New Zealand, and the United States (Exhibit 5).

In developing regions, the starting point is harder. The total empowerment gap is the equivalent of 4 percent of GDP on average annually in the Middle East, 6 percent in Asia (not including China, India, or Japan), 7 percent in Latin America, 13 percent in India, and a daunting 45 percent in sub-Saharan Africa.

A table of three columns shows statistics on the empowerment gap by region. In the first column, a doughnut chart for each region shows the share of the global empowerment gap that region makes up. The second column shows a bar chart for each region that visualizes the annualized % of GDP equivalent, based on 2021–30. The third column lists the empowerment gap as a percentage of continued 2020 spending of people below the empowerment line. The table shows that lower-income regions, like sub-Saharan Africa, India, and Asia excluding China, India, and Japan generally account for a higher share of the $37 trillion empowerment gap.

The net-zero investment gap is also equivalent to about 4 percent of global GDP each year. It ranges from about 2 percent of GDP in Japan to 14 percent on average annually in India (Exhibit 6).

High-income regions have an annual net-zero investment gap on the order of about 3 percent of annual GDP on average, about four to five times higher than their 2020 levels of investment. Most developing regions have a larger net-zero investment gap relative to GDP. They face the twin challenges of replacing fossil fuel generation while substantially broadening energy access and meeting the energy needs of growing economies—and doing so in a low-emissions way. 19 NGFS scenarios account for difference in likely emissions reduction trajectories across developed and developing economies. Developed countries typically reach net zero earlier than developing countries.

A table of three columns shows statistics on the net-zero investment gap by region. In the first column, a doughnut chart for each region shows the share of the net-zero investment gap that region makes up. The second column shows a bar chart for each region that visualizes the annualized % of GDP equivalent, based on 2021–30. The third column lists the increase over 2020 levels of low-emissions spending. The table shows that each region has a unique share of the $41 trillion net-zero investment gap. China, US, and EU and UK account for the largest share of the gap.

Growth and business-led innovation could be the biggest drivers of economic empowerment

How could populations below the empowerment line gain more spending power? Our scenario starts with growth. By our estimates, aggregate baseline growth of 2.7 percent per year globally could generate enough income to give our target population the ability to meet some $14 trillion more of their needs over ten years. 20 The lift required for global empowerment is based on 2020 empowerment thresholds. We do not adjust annually, although the line may in fact rise due to increasing per capita income, changes in input costs, and other factors. Conversely, we also do not model the potential positive GDP implications of having many more empowered and productive workers. This could help lift 830 million people into empowerment by 2030 and bring some 160 million people out of poverty, reducing the share of the global population in poverty from 11 to 8 percent. 21 We use 20 percent of the empowerment line as a proxy for poverty. For countries at the floor of $12 PPP per day, this is slightly higher than the World Bank’s $2.15 line.

On top of this, businesses can improve productivity to accelerate global growth. Farm and non-farm sectors have the potential to raise productivity, in aggregate, by at least 0.5 to 1.0 percent each year across regions, as outlined in many prior MGI research  efforts. 22 Recent research includes The future of wealth and growth hangs in the balance (May 2023) and Rekindling US productivity for a new era (February 2023). This is not only about cost-saving efficiencies; it is also about innovation and new business creation, new types of work, and products and services that address new markets. If global growth could reach 3.4 percent annually by harnessing such opportunities, more resources would also become available for public goods and social spending.

Increasing investment and technology adoption will be key to these efforts. This creates the challenge—and the opportunity—to upskill workers to use those technologies and make successful job transitions into more productive sectors and better-paying occupations. Previous MGI research  has explored the scale of the skill shifts and occupational transitions that will likely be needed in the years ahead. 23 See, for example, Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages , McKinsey Global Institute, November 2017. Our analysis here suggests that roughly 10 percent of lower- and mid-skill workers could see their wages rise if they are equipped to take on higher-skill jobs by 2030 in response to technology, sector-specific growth opportunities, and other trends.

Businesses have a critical role here. About half of workers’ lifetime earnings  is due to skill building through work experience and learning on the job; this dynamic is especially important for those without educational credentials who start out in low-wage work. 24 Human capital at work: The value of experience , McKinsey Global Institute, June 2022. Businesses can become more productive by accelerating this process: during the pandemic, for example, US workers  moved into different occupations, including better-paying ones, at a rate 50 percent higher than in the past. 25 Generative AI and the future of work in America , McKinsey Global Institute, July 2023. But upskilling does not happen without intentional effort. It will be a heavy lift for businesses to improve this dynamic, especially where the process involves bringing people from subsistence farming into more productive work.

Faster economic growth could almost eliminate extreme poverty by 2030.

All told, higher growth combined with creating and filling more productive jobs could close an additional $10 trillion of the global empowerment gap beyond what baseline growth can deliver, by our estimates. This includes the impact of social and public transfers rising in line with higher growth. This could raise living standards and transform lives on a massive scale, lifting 2.1 billion people into empowerment and 600 million more out of poverty. In this scenario, the share of the global population below the empowerment line drops from 60 percent to 30 percent and the share in poverty shrinks to 3 percent over the decade.

Lower-income countries would take longer to achieve full empowerment. But accelerated economic growth could eliminate the most severe forms of poverty in much of the world by 2030 (although we note the unique difficulties in places where conflicts are ongoing, among other deep-rooted structural issues).

The toughest challenge is in sub-Saharan Africa. If economic growth remains at the baseline, the absolute numbers of those experiencing the most extreme deprivation might actually tick up as the population rises. But accelerated productivity-driven growth could cut that population in half, which translates to 250 million people exiting poverty. The gap remaining to fully erase poverty in this scenario amounts to $120 billion over a decade, equivalent to about 5 percent of total public spending in these countries, projected at historical rates. At the same time, living standards would continue to improve for the rest of the population. In a high-growth scenario, the population above 50 percent of the empowerment standard would rise from 260 million in 2020 to 550 million in 2030. Transforming so many lives would expand the continent’s possibilities.

Some $15 trillion of new low-emissions spending could be unlocked this decade through growth and innovation

How much low-emissions spending can be spurred by growth and innovation? And what role will private actors play? This depends on whether each low-emissions investment opportunity is “in the money”—that is, competitive in total cost of ownership relative to traditional alternatives. We have analyzed these by technology, sector, and region.

Only about 10 percent of the $1.4 trillion low-emissions investment in 2020 was fully private. Our model starts by assuming these levels continue over the decade. This would mean an additional $14 trillion coming on stream by 2030. 26 Our breakdown of spending across public and private actors is based on a granular bottom-up modeled assessment across technologies and regions. For the public sector, we include grants and concessional financing and direct public spending. We have triangulated our results from 2020 with external estimates and find them broadly in line. Any discrepancies are likely due to differences in how subsidies are accounted for.

On top of that, an additional $15 trillion in investment could occur, even without changes to the policy frameworks that existed in 2020. 27 This includes, for example, carbon taxes in place as of 2020 in the EU. Of this, $3 trillion could come from current investment simply rising in line with baseline growth (assuming that spending levels stay consistent as a share of GDP). The remaining $12 trillion could occur with accelerated economic growth and, more importantly, with technological advances on the horizon making low-emissions alternatives more cost competitive.

$10 trillion in low-emissions spending could become viable for businesses and consumers in this decade.

While some of this $15 trillion step-up would continue to be financed or subsidized by public budgets, the majority could consist of “in the money” spending by the private sector. Combined with continued spending at 2020 levels, some $10 trillion in low-emissions spending could become viable for private actors by 2030.

Where exactly are these “in the money” opportunities? The power and mobility sectors in China, Europe, India, and the United States collectively make up about 70 percent of this category—and these are precisely the areas with the biggest needs for investment. Action is already building in these areas. With new supply chains turning out batteries and a wider array of models hitting the market, electric vehicles are poised to become more affordable. Meanwhile, technology advances and continued cost reductions could create almost $700 billion of new viable investment opportunities across solar and wind generation in these regions.

The extent to which growth, innovation, and continued current policies could close the combined gaps varies by region

Market forces—the combination of higher productivity-driven growth, business innovation, and technology advances—plus the continuation of current policies and public commitments could move the world much further on both fronts. At the global level, these forces could close roughly half of the combined empowerment and net-zero investment gaps (Exhibit 7). By our estimates, just under one extra percentage point of growth reduces the unfilled empowerment gap by more than one percentage point of GDP. 28 While economic growth increases the low-emissions spending need to reach a net-zero trajectory, the unfilled gap remains largely constant as a share of GDP.

Image description: Two waterfall-style bar charts plot breakdowns of the $37 trillion inclusion spending gap and the $41 trillion sustainability gap. About two-thirds of the inclusion gap is covered by market-led opportunities and continued current policies, leaving $13 trillion unfilled. About one-third of the sustainability gap is covered, leaving $26 trillion unfilled. End of image description.

But growth and business-led innovation have uneven potential across countries (Exhibit 8).

By 2030, these two forces could fill roughly 55 to 85 percent of the empowerment gap in high-income regions. Across the rest of the world, the picture varies widely. The greatest potential lift could occur in India and China. Accelerated growth and business innovation could erase more than 90 percent of the empowerment gaps in both countries, lifting about 700 million people in India and over 730 million in China above the threshold by 2030. But these two forces may have lower impact by 2030 in many other developing countries.

For net zero, the potential impact of growth is less, as discussed previously. Growth and business-led innovation plus continued current policies could together fill about 30 to 60 percent of the gap, with economies in Asia (apart from India) at the lower end.

Two sets of horizontal bar charts show a regional breakdown of the potential of baseline growth and business-led innovation to fill gaps. The left side shows the empowerment gap, and the right side shows the net-zero investment gap. The bars are split into three categories: baseline growth, business-led innovation, and unfilled gap. The charts show that the portion of the gap that can be filled varies by region.

The residual gaps raise fundamental questions

After accounting for growth, business innovation, and continued current policies, the unfilled gaps amount to $40 trillion across both empowerment and net zero. This is the global total, cumulative through the decade, with roughly $13 trillion on the empowerment side and $26 trillion for net-zero investments through 2030. Each country and region has a unique share of this residual gap, depending on its current development challenges, its growth prospects, and how carbon-intensive its economy currently is (Exhibit 9). Developing countries account for nearly two-thirds of the residual gap globally.

Two treemap charts plot regional breakdowns of the two unfilled spending gaps over 2021–30. On the left is the $13.4 trillion empowerment gap, with the segment for Sub-Saharan Africa filling about half of the chart, with $7.2 trillion. On the right is the $26.2 trillion net-zero investment gap, with the largest segments including China at $5.8 trillion and the U.S. at $4.5 trillion.

Different outcomes are possible depending on the extent of growth, innovation, and public-private action

The empowerment opportunity for africa.

This report builds on NGFS scenarios for its net-zero analyses. We therefore use NGFS regional groupings for our economic empowerment analysis to make the two goals more comparable. Yet the African continent is bigger and more diverse than the focus on sub-Saharan countries implies.

Looking at the entirety of Africa adds in other major economies, including Algeria, Egypt, and Morocco. While 90 percent of the population in sub-Saharan Africa alone is below the empowerment line, that share shrinks to 85 percent for the entire continent. Africa’s gap to reach full empowerment is equivalent to 33 percent of GDP, down from 45 percent of regional GDP for sub-Saharan Africa alone.

Yet economic empowerment is not a binary condition, and what matters is progress along the continuum. Some 70 percent of the entire continent’s population was below 50 percent of full empowerment in 2020. Getting them above this intermediate benchmark would be a major stride in development. This would require a boost in spending power equivalent to 11 percent of GDP, roughly in line with India’s full empowerment gap—and significant progress is achievable through faster growth and business-led innovation.

Just as the story changes while zooming out to the full continent, it also becomes more nuanced when zooming in to individual countries. Beneath the regional aggregates are some economies that have stronger recent growth momentum and others with large populations closer to full empowerment. In Algeria, Botswana, Egypt, and Morocco, for example, market-led opportunities could close at least 70 percent of the full empowerment gaps—and get the entirety of these countries’ populations above the 50 percent benchmark. Meanwhile, countries such as Benin, Cote d’Ivoire, Ghana, Kenya, Senegal, and Tanzania could rely on market forces to get more than half of their populations to 50 percent of full empowerment.

In our scenario of accelerated growth, some 770 million people across the continent could be above 50 percent of the empowerment line by 2030—almost doubling the number in 2020 (exhibit). At the same time, the number of people living in extreme poverty would drop by just under 270 million over the decade. As noted in recent MGI research, African economies can accelerate these outcomes through digitization, talent development, regional collaboration, and industry champions. 1 Reimagining economic growth in Africa: Turning diversity into opportunity , McKinsey Global Institute, June 2023. These strategies could attract more international investment, creating self-sustaining momentum that transforms millions of lives.

A bar chart plots Africa’s population of 1.34 billion in 2020 and projected 1.65 billion in 2030, with segments showing different spending levels as a percentage of the empowerment line. In 2020, 400 million, or 30% of the population, are above 50% of the empowerment line, and in 2030, in a scenario of accelerated growth and business-led innovation, 770 million, or 47% of the population, are above 50% of the empowerment line.

The choices societies make about prioritizing these aspirations and putting resources into them can produce a broad range of outcomes.

If economic growth stays at the baseline, but innovation does not bring down the cost of low-emissions technologies as much as expected and no additional commitments are made, some 830 million people would cross the empowerment line by 2030. But some 3.9 billion would remain below it, and the world would be on a trajectory for over 3.0°C of warming in 2100. 29 Drawing on expected warming under the NGFS Current Policies scenario as of 2100.

Exhibit 10 shows the degrees of progress that could be achieved in line with higher growth, innovation, and commitments. While these are global results, the trade-offs differ across countries and regions.

Image description: In the first of 5 slides, 6 square matrices are arranged in 2 rows and 3 columns to show how gaps can be filled in different scenarios. The top row is for the $37 trillion empowerment gap, and the bottom row is for the $41 trillion net-zero investment gap. Each of the columns represents a scenario. The first scenario is for accelerated growth and innovation with continued policies. The second scenario shows societal commitment to filling the net-zero investment gap only. The third shows societal commitments toward filling both gaps. End of image description.

Image description: The second slide fills in some squares in each of the matrices to show how baseline growth can cover one-third of the $37 trillion empowerment gap and only about $3 trillion of the $41 trillion net-zero investment gap. End of image description.

Image description: The third slide fills in more squares to show how accelerated growth and business-led innovation can cover about two-thirds of the empowerment gap and one-third of the net-zero investment gap. End of image description.

Image description: The fourth slide fills in more squares to show how higher societal commitments can close the gaps. End of image description.

Image description: On the fifth slide, bullet points of statistics at the bottom of each scenario column show that higher societal commitments could put the world on a path to prevent an extra 1.5°C of warming and bring an additional 2.6 billion people, the rest of the world's population, over the empowerment line. End of image description.

• Innovation-led accelerated growth. Countries could choose to rely solely on maximizing what market forces can do. With higher economic growth and innovation delivering the anticipated productivity improvements and reductions in the price of low-emissions technologies, 2.1 billion people could move above the empowerment threshold, but the world would be on a 3.0°C warming path. This would produce much more progress, especially on the empowerment side, than the current trajectory, although it would be far from closing the gaps.
• Commitment to partially address either gap. Assuming high growth and innovation, societies could choose to address one of the residual gaps, leaving the other to be addressed by market forces alone. The exhibit illustrates societies choosing to tackle net zero completely but not empowerment. The choice is not binary, of course. Many combinations could yield partial progress on both challenges in tandem.
• Commitment to fully close both gaps. In this scenario, the global population would be fully empowered with a higher standard of living, and the world would be on track to achieve net zero by mid-century, hopefully limiting warming to 1.5°C by 2100. This would take a best-case scenario of global growth and innovation along with commitments that wholly—and effectively—address the combined $40 trillion residual gap over the decade.

The important assumption in the final two scenarios is that public commitments on such a scale would spur additional private activity and investment. However, it is possible that such extensive commitments could distort the baseline economy.

These scenarios lead us to three questions about how additional commitments could theoretically close the last-mile gaps as well as the implications for countries that lack the economic resources.

Question 1: How could societies get closer to full empowerment beyond what current market forces can do?

The options for closing the residual $13 trillion economic gap for universal empowerment involve delivering essential goods and services more affordably and effectively, improving work arrangements and pay, and injecting more direct support. As a thought experiment, we quantify some of these avenues, cautioning that the effects of intervention on this scale are not known (Exhibit 11).

Making housing, healthcare, education, and nutrition more affordable—and raising the bar for quality—can yield not only financial savings but greater well-being and human potential.

First, beyond incomes, one of the biggest factors determining empowerment is the price of essential goods and services. Multiple efficiencies could bring down these costs. Benchmarking against the productivity gains and outcome improvements that some countries have achieved in past decades, we estimate the potential to improve capacity and productivity in housing, healthcare, education, and nutrition. If these are passed on to consumers, they could yield some $3 trillion of benefits to those below the empowerment line (cumulatively through 2030). In effect, this would lower the empowerment threshold. In places where the public sector provides essential services, looking for operational efficiencies and raising the bar for quality can ensure that public funds are well spent. Beyond the financial savings, these could yield immense benefits in terms of well-being and human potential.

Image description: A waterfall-style bar chart plots a breakdown of a funding scenario that could potentially close the $37 trillion empowerment gap. It shows $20 trillion covered by private business actions under current market frameworks, $14 trillion of public support, and the rest mostly covered by public and private action to increase the affordability of essentials, including education, healthcare, housing, and food. End of image description.

For instance, we estimate that improved construction productivity could lower housing expenditures by 11 percent globally if all countries emulated their best-performing peers and these gains reached consumers. Health outcomes (expressed in healthy life expectancies) could improve by 36 percent globally, even keeping current levels of healthcare spending constant, if each country matched its best-performing peer over the next decade. Globally, we find an opportunity to improve learning outcomes (expressed as both years of schooling and test performance) by 42 percent, with the greatest potential gains in low- and middle-income countries.

Policies and incentives could spur more business attention and innovation in the affordable segments of the housing, healthcare, food, and education markets. In housing, for example, local governments can change regulations related to land use, density, and permitting to lower costs for private developers. They can also require a percentage of affordable units in larger multifamily projects or offer concessional finance to buyers and developers of affordable housing.

On a different front, more labor-friendly policies and business decisions to offer higher wages or benefits could address labor’s declining share of national incomes, particularly in high-income economies. This could occur alongside structural factors we have accounted for as part of economic growth, such as changing employment mixes.

For the remaining unfilled $10 trillion global gap, one option could be well-administered transfers to households. While better-paying jobs are the biggest driver of higher living standards, transfers can be targeted to those who do not benefit from these opportunities, especially the very poorest, those living in remote communities, children, the elderly, and people unable to work. In many places, there is room to make subsidy programs more transparent. Digital tools can spot leakages while streamlining eligibility processes and delivering benefits more efficiently. In addition, governments, philanthropies, social investors, development finance institutions, and multilateral agencies could consider increased direct funding for affordable housing, health, and quality education.

A $10 trillion incremental commitment to achieve full empowerment would be equivalent to about 3 percent of total global government budgets over the decade (assuming both accelerated growth and government spending held constant at its current share of GDP). But the regional differences are stark. The amount needed to close the gap in the United States, for example, equals about 1 percent of government spending, while in sub-Saharan Africa, it would take 1.3 times the region’s government spending. Even if the region’s gap could be closed through international transfers, uncertainties remain about the potential size and duration of such aid. Large capital flows could affect prices, labor markets, savings, and ultimately growth.

Question 2: What would it take to get on a true net-zero trajectory beyond what current market forces can do?

After accounting for market forces, technological advances, and the continuation of current policies, the residual unfilled net-zero investment gap is $26 trillion, cumulative through the decade. This is equivalent to 3 percent of global GDP annually.

Increased public commitments for net zero could activate even more private capital and create faster learning effects that bring down the costs of low-emissions technologies.

Fully addressing this unfilled economic gap would require a combined public–private effort. Higher public commitments could activate even more private capital and create even faster learning effects (that is, the lowering of costs as technologies mature and are deployed widely). For example, the vast majority of wind and solar will come on stream only if there is sufficient investment in transmission and distribution, which is largely a public-sector effort today in many parts of the world. All of this rests on the unproven assumption that these shifts do not damage the base economy.

We present a scenario illustrating how such commitments could play out if countries choose to make them. Beyond the levels of public funding suggested by growth and the continuation of current policies, we estimate that an injection of just under $10 trillion in public funding could potentially unlock almost $17 trillion in additional positive impact collectively to 2030. Public support could take the form of concessional finance (that is, lending below market rates), subsidies, and projects undertaken by state-owned enterprises and development finance institutions.

One-quarter of the total $55 trillion needed through 2030 could be private in-the-money spending (plus avoided spending), up from 10 percent in 2020. All told, some $31 trillion could potentially come from private actors (Exhibit 12), including what is expected to become cost competitive as well as what could be unlocked through additional policies and public finance. Public support alone makes up some 36 percent of the total in this scenario, down from half in 2020.

Image description: A waterfall-style bar chart plots a breakdown of the global spending needed to fill the $41 trillion net-zero investment gap. It shows $13 trillion coming from public support, $16 trillion from private sources influenced by that public support, $9 trillion from private consumer finance and commercial finance sources, and $4 trillion counted as avoided spending from accelerated learning. End of image description.

About 70 percent of crowded-in private spending could occur in the building and mobility sectors, based on our bottom-up modeling. Public support would be critical for building decarbonization, since heat pumps, a key technology, are not yet cost competitive relative to gas boilers. Similarly, there are significant opportunities in mobility, but public-sector support may still be needed, especially for heavy-duty electric vehicles , which are expected to take longer than battery electric passenger vehicles (BEVs) to become cost competitive. 30 “ Preparing the world for zero-emission trucks ,” McKinsey & Company, November 2022.

Such levels of public and private action could also yield up to $4 trillion in avoided investment, thanks to additional R&D, economies of scale, and learning by doing.

As with the empowerment gap, the $10 trillion of public commitment to be on track for net zero represents about 3 percent of total global government budgets over the decade (assuming both accelerated growth and government spending remain constant as a share of GDP). This ranges from less than 1 percent of current government budgets in the European Union and United Kingdom to 14 percent in India. The consequences of scaling up public commitments and international capital flows to this extent would be uncharted territory.

Even if the residual gap for net zero is not fully addressed, pursuing everything that market forces can do would already be a tremendous ramp-up in spending and progress. At this scale, and with this additional momentum, the environment becomes more fertile for breakthroughs and societal shifts that we cannot foresee today. This argues for a continued focus on growth and innovation.

Question 3: Will societies have the capacity and willingness for higher public and private commitments?

If governments choose to address some or all of the residual gaps, they could explore making their spending more efficient, reallocating existing spending, issuing new debt, or raising taxes. Capital could also come from philanthropies, multilateral agencies, or social investors.

Carbon pricing can play a role in spurring the switch away from high-carbon assets. We model how the need for public support to achieve both empowerment and net zero would change if carbon taxes, rather than subsidies, were the primary vehicle to shift incentives toward low-emissions spending. 31 We use carbon prices estimated by NGFS that range from about $78 per ton of emissions in emerging economies like India to about $300 in the United States. We found that they reduce the need for additional public support to reach net zero by 0.4 percentage point of GDP. At the same time, the residual empowerment gap would rise by 0.2 percentage point of GDP (on average annually) unless this effect is mitigated by revenue recycling. 32 Based on changes in private consumption seen in the National Institute of Economic and Social Research’s NiGEM model when shifting from a no-transition, no-physical-risk baseline to a net-zero scenario, looking forward to 2030. NiGEM incorporates NGFS carbon prices as taxes, as well as NGFS energy prices.

Most high-income countries theoretically have the resources to make higher commitments if they choose to, although how much debt countries can carry is the subject of ongoing debate. 33 See, for example, Christina D. Romer and David H. Romer, Fiscal space and the aftermath of financial crises: How it matters and why , Brookings Papers on Economic Activity, Spring 2019; and Oliver Blanchard, “Public debt and low interest rates,” American Economic Review , volume 109, number 4, April 2019. Yet the choice to aim for full empowerment, net zero, or both would involve difficult trade-offs with other national priorities.

Sustainability and inclusion are global projects, with ramifications that do not stop at national borders.

Achieving full empowerment and a net-zero trajectory in the current decade appears more challenging for lower- and middle-income countries. Allocating large amounts to the net-zero transition could eat into existing social welfare programs, potentially worsening the empowerment gap. India’s need for incremental public support to get on a net-zero pathway is more than 50 percent higher than the share of GDP that currently goes to social protection spending, for example. Debt, too, is problematic for the developing world: the IMF estimates that 60 percent of low-income countries are already in debt distress or approaching it. 34 “Debt dynamics,” in Crisis upon crisis: IMF annual report 2022 , International Monetary Fund, September 2022. See also The human cost of inaction: Poverty, social protection and debt servicing, 2020–2023 , UNDO Global Policy Network Brief, July 2023.

Yet sustainability and inclusion are global projects, with ramifications that do not stop at national borders. For context, if high-income countries were to take on the combined residual gaps in the entire world, it would require an amount equivalent to about 3.5 percent of their GDP on an average annual basis (up from less than 1 percent of GDP to bridge only their own residual gaps). Even if high-income societies were willing to bear that cost, the world would need a mix of mechanisms for cross-border flows that could include international aid, cross-border debt, assistance from multilateral institutions, and debt relief (including creative debt-for-nature or debt-for-climate swaps). New financial vehicles might need to be designed.

We are reaching a fork in the road

We undertook this exercise to show what is theoretically possible and inform the debate. Regardless of whether countries decide to increase public commitments, this research leads to two important takeaways.

The importance of productivity-driven growth cannot be overstated

Faster growth propels inclusion. Almost 40 percent of the empowerment gap can be closed by baseline growth—and, as noted earlier, just under one extra percentage point of growth reduces the unfilled empowerment gap by more than one percentage point of GDP.

Additionally, growth can give governments more fiscal flexibility. The incremental GDP growth from higher productivity would allow for more than $30 trillion in additional public debt to be incurred globally without raising the 2020 global public debt–to-GDP ratio. At a global level, and specifically for high-income regions, this additional debt capacity exceeds the incremental public support needed to fill the empowerment and net-zero investment gaps. It is a question of whether or not those countries choose to assume that kind of debt, and where to allocate it.

Visionary agendas are more likely to be pursued when the pie is growing and put aside when it is shrinking. 35 Benjamin M. Friedman, The moral consequences of economic growth , Knopf, 2005. While growth can’t overcome every structural challenge, it can create space for new solutions to take root. Although growth in its current form has increased both emissions and inequality in the past, businesses, institutions, and governments can address these externalities more directly.

Higher growth and innovation could bring 600 million more people out of poverty, taking steps on a longer journey toward empowerment.

For developing economies, the prospects for more people to exit poverty are inextricably linked to their ability to grow. These countries would need to double down on productivity, skill development, and technological leapfrogging. 36 See, for example, Reimagining growth in Africa: Turning diversity into opportunity , McKinsey Global Institute, June 2023. They may also need institutional reforms, from clearer legal frameworks for property rights to stronger oversight that prevents leakages of public spending. 37 Realizing property rights , Hernando de Soto and Francis Cheneval, eds., Frank/Wynkin de Worde, 2006. New collaborations may be needed to integrate low-income countries more fully into global flows of trade, finance, technology, and knowledge.

The upside is compelling: higher growth and innovation could lead to some 600 million people moving out of poverty, taking significant steps on their journey toward full economic empowerment. Even in the absence of greater commitments and international transfers, growth and the actions of businesses can unlock real progress that changes lives.

Innovation at scale is critical

Relentlessly focusing on technology development is one of the keys to getting to net zero and lowering the price tag associated with doing so. The significant recent drops in the costs of wind and solar power offer reason for hope. R&D, learning by doing, and scaling up eventually drive costs down. The faster this happens, the lower the risk of households facing higher energy costs.

On the inclusion side, innovation and technology adoption generate demand for higher skills and better jobs. Innovation is also needed to tap efficiency-boosting opportunities and bring down the costs (and prices) of basic needs, from housing and food to education and healthcare.

Innovation is also needed in a broader sense. Lifting minimum living standards and containing climate change would involve sweeping transformations, requiring bold approaches in policy, finance, technology, and industry. The possibilities could include creating new multilateral financing vehicles; integrating low-income countries into global flows of capital and trade in a way that lifts local communities and small businesses; developing sustainable cities with affordable housing; strengthening education and healthcare systems worldwide; and designing effective carbon markets, including incentives for countries to preserve biodiversity and critical carbon sinks.

Progress toward empowerment and net zero would depend on private actors, governments, and NGOs and nonprofits combining their capabilities and expertise—and thinking without limits about how they can contribute to meeting this moment. Regardless of whether countries fully close the gaps, they have real opportunities to build a more stable, prosperous future.

We recognize the scope of these challenges as well as the political realities and the gravitational pull of the status quo. Financing is only one aspect of what would need to be done; achieving consensus and moving toward implementation would be incredibly complex. Countries that decide to take on these generational transformations would need an entirely different magnitude of public–private cooperation. The size of the challenge is not a reason for resignation; it is a call for everyone to roll up their sleeves on what can be done today. Every incremental step forward advances the continuum of progress.

The executive summary of this report was originally published in August 2023. This page has since been updated with the full report download.

Anu Madgavkar is a partner of the McKinsey Global Institute, based in in New Jersey; Sven Smit , based in Amsterdam, chairs MGI. Mekala Krishnan is a partner with MGI, where Kevin Russell and Rebecca J. Anderson are senior fellows. Lola Woetzel and Kweilin Ellingrud are MGI directors, based in Shanghai and Minneapolis, respectively. Tracy Francis , a senior partner in the Sao Paolo office, leads McKinsey’s ESG initiatives.

This report was edited by Lisa Renaud, an MGI executive editor in Los Angeles.

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COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide

Wake-up call to all countries to step up mental health services and support.

In the first year of the COVID-19 pandemic, global prevalence of anxiety and depression increased by a massive 25%, according to a scientific brief released by the World Health Organization (WHO) today. The brief also highlights who has been most affected and summarizes the effect of the pandemic on the availability of mental health services and how this has changed during the pandemic.

Concerns about potential increases in mental health conditions had already prompted 90% of countries surveyed to include mental health and psychosocial support in their COVID-19 response plans, but major gaps and concerns remain.

“The information we have now about the impact of COVID-19 on the world’s mental health is just the tip of the iceberg,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This is a wake-up call to all countries to pay more attention to mental health and do a better job of supporting their populations’ mental health.”

Multiple stress factors

One major explanation for the increase is the unprecedented stress caused by the social isolation resulting from the pandemic. Linked to this were constraints on people’s ability to work, seek support from loved ones and engage in their communities.

Loneliness, fear of infection, suffering and death for oneself and for loved ones, grief after bereavement and financial worries have also all been cited as stressors leading to anxiety and depression. Among health workers, exhaustion has been a major trigger for suicidal thinking.

Young people and women worst hit

The brief, which is informed by a comprehensive review of existing evidence about the impact of COVID-19 on mental health and mental health services, and includes estimates from the latest Global Burden of Disease study, shows that the pandemic has affected the mental health of young people and that they are disproportionally at risk of suicidal and self-harming behaviours. It also indicates that women have been more severely impacted than men and that people with pre-existing physical health conditions, such as asthma, cancer and heart disease, were more likely to develop symptoms of mental disorders.

Data suggests that people with pre-existing mental disorders do not appear to be disproportionately vulnerable to COVID-19 infection. Yet, when these people do become infected, they are more likely to suffer hospitalization, severe illness and death compared with people without mental disorders. People with more severe mental disorders, such as psychoses, and young people with mental disorders, are particularly at risk.

Gaps in care

This increase in the prevalence of mental health problems has coincided with severe disruptions to mental health services, leaving huge gaps in care for those who need it most. For much of the pandemic, services for mental, neurological and substance use conditions were the most disrupted among all essential health services reported by WHO Member States. Many countries also reported major disruptions in life-saving services for mental health, including for suicide prevention.

By the end of 2021 the situation had somewhat improved but today too many people remain unable to get the care and support they need for both pre-existing and newly developed mental health conditions.

Unable to access face-to-face care, many people have sought support online, signaling an urgent need to make reliable and effective digital tools available and easily accessible. However, developing and deploying digital interventions remains a major challenge in resource-limited countries and settings.

WHO and country action

Since the early days of the pandemic, WHO and partners have worked to develop and disseminate resources in multiple languages and formats to help different groups cope with and respond to the mental health impacts of COVID-19. For example, WHO produced a story book for 6-11-year-olds, My Hero is You, now available in 142 languages and 61 multimedia adaptations, as well as a toolkit for supporting older adults available in 16 languages.

At the same time, the Organization has worked with partners, including other United Nations agencies, international nongovernmental organizations and the Red Cross and Red Crescent Societies, to lead an interagency mental health and psychosocial response to COVID-19. Throughout the pandemic, WHO  has also worked to promote the integration of mental health and psychosocial support across and within all aspects of the global response. 

WHO Member States have recognized the impact of COVID-19 on mental health and are taking action. WHO’s most recent pulse survey on continuity of essential health services indicated that 90% of countries are working to provide mental health and psychosocial support to COVID-19 patients and responders alike. Moreover, at last year’s World Health Assembly, countries emphasized the need to develop and strengthen mental health and psychosocial support services as part of strengthening preparedness, response and resilience to COVID-19 and future public health emergencies. They adopted the updated Comprehensive Mental Health Action Plan 2013-2030, which includes an indicator on preparedness for mental health and psychosocial support in public health emergencies.

Step up investment

However, this commitment to mental health needs to be accompanied by a global step up in investment. Unfortunately, the situation underscores a chronic global shortage of mental health resources that continues today. WHO’s most recent Mental Health Atlas showed that in 2020, governments worldwide spent on average just over 2% of their health budgets on mental health and many low-income countries reported having fewer than 1 mental health worker per 100 000 people.

Dévora Kestel, Director of the Department of Mental Health and Substance Use at WHO, sums up the situation: ”While the pandemic has generated interest in and concern for mental health, it has also revealed historical under-investment in mental health services. Countries must act urgently to ensure that mental health support is available to all.”

Media Contacts

Alison Brunier

Communications Officer World Health Organization

Carla Drysdale

AI Index: State of AI in 13 Charts

In the new report, foundation models dominate, benchmarks fall, prices skyrocket, and on the global stage, the U.S. overshadows.

This year’s AI Index — a 500-page report tracking 2023’s worldwide trends in AI — is out.

The index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. This year’s report covers the rise of multimodal foundation models, major cash investments into generative AI, new performance benchmarks, shifting global opinions, and new major regulations.

Don’t have an afternoon to pore through the findings? Check out the high level here.

A Move Toward Open-Sourced

This past year, organizations released 149 foundation models, more than double the number released in 2022. Of these newly released models, 65.7% were open-source (meaning they can be freely used and modified by anyone), compared with only 44.4% in 2022 and 33.3% in 2021.

But At a Cost of Performance?

Closed-source models still outperform their open-sourced counterparts. On 10 selected benchmarks, closed models achieved a median performance advantage of 24.2%, with differences ranging from as little as 4.0% on mathematical tasks like GSM8K to as much as 317.7% on agentic tasks like AgentBench.

Biggest Players

Industry dominates AI, especially in building and releasing foundation models. This past year Google edged out other industry players in releasing the most models, including Gemini and RT-2. In fact, since 2019, Google has led in releasing the most foundation models, with a total of 40, followed by OpenAI with 20. Academia trails industry: This past year, UC Berkeley released three models and Stanford two.

Industry Dwarfs All

If you needed more striking evidence that corporate AI is the only player in the room right now, this should do it. In 2023, industry accounted for 72% of all new foundation models.

Prices Skyrocket

One of the reasons academia and government have been edged out of the AI race: the exponential increase in cost of training these giant models. Google’s Gemini Ultra cost an estimated $191 million worth of compute to train, while OpenAI’s GPT-4 cost an estimated $78 million. In comparison, in 2017, the original Transformer model, which introduced the architecture that underpins virtually every modern LLM, cost around $900.

What AI Race?

At least in terms of notable machine learning models, the United States vastly outpaced other countries in 2023, developing a total of 61 models in 2023. Since 2019, the U.S. has consistently led in originating the majority of notable models, followed by China and the UK.

Move Over, Human

As of 2023, AI has hit human-level performance on many significant AI benchmarks, from those testing reading comprehension to visual reasoning. Still, it falls just short on some benchmarks like competition-level math. Because AI has been blasting past so many standard benchmarks, AI scholars have had to create new and more difficult challenges. This year’s index also tracked several of these new benchmarks, including those for tasks in coding, advanced reasoning, and agentic behavior.

Private Investment Drops (But We See You, GenAI)

While AI private investment has steadily dropped since 2021, generative AI is gaining steam. In 2023, the sector attracted $25.2 billion, nearly ninefold the investment of 2022 and about 30 times the amount from 2019 (call it the ChatGPT effect). Generative AI accounted for over a quarter of all AI-related private investments in 2023.

U.S. Wins $$ Race

And again, in 2023 the United States dominates in AI private investment. In 2023, the $67.2 billion invested in the U.S. was roughly 8.7 times greater than the amount invested in the next highest country, China, and 17.8 times the amount invested in the United Kingdom. That lineup looks the same when zooming out: Cumulatively since 2013, the United States leads investments at $335.2 billion, followed by China with $103.7 billion, and the United Kingdom at $22.3 billion.

Where is Corporate Adoption?

More companies are implementing AI in some part of their business: In surveys, 55% of organizations said they were using AI in 2023, up from 50% in 2022 and 20% in 2017. Businesses report using AI to automate contact centers, personalize content, and acquire new customers. 

Younger and Wealthier People Worry About Jobs

Globally, most people expect AI to change their jobs, and more than a third expect AI to replace them. Younger generations — Gen Z and millennials — anticipate more substantial effects from AI compared with older generations like Gen X and baby boomers. Specifically, 66% of Gen Z compared with 46% of boomer respondents believe AI will significantly affect their current jobs. Meanwhile, individuals with higher incomes, more education, and decision-making roles foresee AI having a great impact on their employment.

While the Commonwealth Worries About AI Products

When asked in a survey about whether AI products and services make you nervous, 69% of Aussies and 65% of Brits said yes. Japan is the least worried about their AI products at 23%.  

Regulation Rallies

More American regulatory agencies are passing regulations to protect citizens and govern the use of AI tools and data. For example, the Copyright Office and the Library of Congress passed copyright registration guidance concerning works that contained material generated by AI, while the Securities and Exchange Commission developed a cybersecurity risk management strategy, governance, and incident disclosure plan. The agencies to pass the most regulation were the Executive Office of the President and the Commerce Department. 

The AI Index was first created to track AI development. The index collaborates with such organizations as LinkedIn, Quid, McKinsey, Studyportals, the Schwartz Reisman Institute, and the International Federation of Robotics to gather the most current research and feature important insights on the AI ecosystem. 

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The Truth Behind ‘Runner’s High’ and Other Mental Benefits of Running

Reviewed By:

David J. Linden, Ph.D.

You may have experienced it — that relaxing feeling after a good run. Often referred to as “runner’s high,” the experience is usually attributed to a burst of endorphins released during exercise. But is that truly an endorphin rush you’re feeling, or something else?

David Linden, Ph.D. , a professor of neuroscience at the Johns Hopkins University School of Medicine, breaks down the phenomenon of runner’s high and other effects running has on the brain.

What Happens to Your Body — and Brain — During a Run

When you start out on your run, your body goes through a transition: Your breathing may become heavy, and you might notice your pulse quicken as the heart pumps harder to move oxygenated blood to your muscles and brain.

As you hit your stride, your body releases hormones called endorphins. Popular culture identifies these as the chemicals behind “runner’s high,” a short-lasting, deeply euphoric state following intense exercise. Surveys have revealed runner’s high to be rather rare, however, with a majority of athletes never experiencing it. “Indeed, many distance runners feel merely drained or even nauseated at the end of a long race, not blissful,” says Linden.

And though endorphins help prevent muscles from feeling pain, it is unlikely that endorphins in the blood contribute to a euphoric feeling, or any mood change at all. Research shows that endorphins do not pass the blood-brain barrier.

That relaxed post-run feeling may instead be due to endocannabinoids — biochemical substances similar to cannabis but naturally produced by the body.

Exercise increases the levels of endocannabinoids in the bloodstream, Linden explains. Unlike endorphins, endocannabinoids can move easily through the cellular barrier separating the bloodstream from the brain, where these mood-improving neuromodulators promote short-term psychoactive effects such as reduced anxiety and feelings of calm.

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Long-term Mental Benefits of Exercise

The mental benefits don’t stop when you finish your run — regular cardiovascular exercise can spark growth of new blood vessels to nourish the brain. Exercise may also produce new brain cells in certain locations through a process called neurogenesis, which may lead to an overall improvement in brain performance and prevent cognitive decline.

“Exercise has a dramatic antidepressive effect,” says Linden. “It blunts the brain’s response to physical and emotional stress.”

What’s more, the hippocampus — the part of the brain associated with memory and learning — has been found to increase in volume in the brains of regular exercisers. Other mental benefits include:

• Improved working memory and focus
• Better task-switching ability
• Elevated mood

By making running or jogging (or any aerobic exercise) a regular part of your routine, you stand to earn more than just physical gains over time. “Voluntary exercise is the single best thing one can do to slow the cognitive decline that accompanies normal aging,” says Linden.

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