Gasoline purchases are an essential part of the American way of life. There were about 250 million motor vehicles in the United States in 2008 – just under a vehicle per person. Americans drive an average of more than 11,000 miles per year and gasoline purchases are an essential part of most households’ budgets. Between 1995 and 2003, gasoline prices in the U.S. averaged about $1.49 a gallon, with average prices rising above $2.00 in 2004. By the summer of 2008, gasoline prices had reached a national average of $4.11 per gallon. At that time, Americans earning less than $15,000 a year were spending as much as 15 percent of their household income on gasoline – double the proportion from seven years earlier. In addition, unpredictable fuel costs make planning monthly household expenditures difficult, which can be detrimental to individual welfare and even to the overall economy.

Gasoline prices fell in the aftermath of the 2009 economic crisis. Prior and during the financial crisis, rising gasoline prices were seen as a symptom of an uncertain economic situation, as well as evidence of the questionable sustainability of our future oil supply. Gasoline prices abated along with the decrease of economic activity that accompanied the onset of the recession, reaching their minimum in late December 2008. A few months later, as the economy entered a gradual recovery phase, gasoline prices also trended upward. In contrast to the previous period of great uncertainty about future oil supplies, however, these price trends were considered more positively as signs of the U.S. economic recovery.

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I’ve written here before about my research with Betsey Stevenson showing that economic development is associated with rising life satisfaction. Some people find this result surprising, but it’s the cleanest interpretation of the available data. Yet over the past few days, I’ve received calls from several journalists asking whether Richard Easterlin had somehow debunked these findings. He tried. But he failed.

Rather than challenge our careful statistical tests, he’s simply offered a new mishmash of statistics that appear to make things murkier.

For those of you new to the debate, the story begins with a series of papers that Richard Easterlin wrote between 1973 and 2005, claiming that economic growth is unrelated to life satisfaction. In fact, these papers simply show he failed to definitively establish such a relationship. In our 2008 Brookings Paper, Betsey and I systematically examined all of the available happiness data, finding that the relationship was there all along: rising GDP yields rising life satisfaction. More recent data reinforces our findings. Subsequently, Easterlin responded in of papers circulated in early 2009. That’s the research journalists are now asking me about. But in a paper released several weeks ago, Betsey, Dan Sacks and I assessed Easterlin’s latest claims, and found little evidence for them.

Let’s examine Easterlin’s three main claims.

1. GDP and life satisfaction rise together in the short-run, but not the long-run. False. Here’s an illustrative graph. We take the main international dataset — the World Values Survey — and in order to focus only on the long-run, compare the change in life satisfaction for each country from the first time it was surveyed until the last, the corresponding growth in GDP per capita. Typically, this is a difference taken over 18 years (although it ranges from 8 to 26 years). The graph shows that long-run rises in GDP are positively associated with growth in life satisfaction.

This graph includes the latest data, and Dan generated it just for this blog post. In fact, Easterlin was responding to our earlier work, which showed each of the comparisons one could make between various waves of this survey: Wave 1 was taken in the early ‘80s; Wave 2 in the early ‘90s; Wave 3 in the mid-late ‘90s; Wave 4 mostly in the early 2000s. And in each of these comparisons, you see a positive association — sometimes statistically significant, sometimes not.

What should we conclude from this second graph? Given the typically-significant positive slopes, you might conclude that rising GDP is associated with rising life satisfaction. It’s also reasonable to say that these data are too noisy to be entirely convincing. But the one thing you can’t conclude is that these data yield robust proof that long-run economic growth won’t yield rising life satisfaction. Yet that’s what Easterlin claims.

2. The income-happiness link that we document is no longer apparent when one omits the transition economies. Also false. One simple way to see this is to note that in the first graph the transition countries are shown in gray. Even when you look only at the other countries, it’s hard to be convinced that economic growth and life satisfaction are unrelated. To see the formal regressions showing this, read Table 3 of our response. (Aside: Why eliminate these countries from the sample?)

Or we could just look to another data source which omits the transition economies. For instance, the graph below shows the relationship between life satisfaction and GDP for the big nine European nations that were the members of the EU when the Eurobarometer survey started. Over the period 1973-2007, economic growth yielded higher satisfaction in eight of these nine countries. And while we’re puzzled by the ninth — the increasingly unhappy Belgians — we’re not going to drop them from the data! And if you think Belgium is puzzling, too, then we’ve done our job.

3. Surveys show that financial satisfaction in Latin American countries has declined as their economies have grown. Perhaps true. But how are surveys of financial satisfaction relevant to a debate about life satisfaction? And why focus on Latin America, rather than the whole world? In fact, when you turn to the question we are actually debating — life satisfaction —these same surveys suggest that those Latin American countries which have had the strongest growth have seen the largest rise in life satisfaction. This finding isn’t statistically significant, but that’s simply because there’s not a lot of data on life satisfaction in Latin America! (Given how sparse these data are, we didn’t report them in our paper.)

What’s going on here?

Now it’s reasonable to ask how it is that others arrived at a different conclusion. Easterlin’s Paradox is a non-finding. His paradox simply describes the failure of some researchers (not us!) to isolate a clear relationship between GDP and life satisfaction.

But you should never confuse absence of evidence with evidence of absence. Easterlin’s mistake is to conclude that when a correlation is statistically insignificant, it must be zero. But if you put together a dataset with only a few countries in it — or in Easterlin’s analysis, take a dataset with lots of countries, but throw away a bunch of it, and discard inconvenient observations — then you’ll typically find statistically insignificant results. This is even more problematic when you employ statistical techniques that don’t extract all of the information from your data. Think about it this way: if you flip a coin three times, and it comes up heads all three times, you still don’t have much reason to think that the coin is biased. But it would be silly to say, “there’s no compelling evidence that the coin is biased, so it must be fair.” Yet that’s Easterlin’s logic.

There’s a deeper problem, too. The results I’ve shown you are all based on analyzing data only from comparable surveys. And when you do this, you find rising incomes associated with rising satisfaction. Instead, Easterlin and co-authors lump together data from very different surveys, asking very different questions. It’s not even clear how one should make comparisons between a survey (in the US) asking about happiness, a survey (in Japan) asking about “circumstances at home,” surveys of life satisfaction in Europe based on a four-point scale, and global surveys based on a ten-point scale. Easterlin’s non-result appears only when comparing non-comparable data.

If you want to advocate against economic growth — and to argue that it won’t help even in the world’s poorest nations — then you should surely base such radical conclusions on findings rather than non-findings, and on the basis of robust evidence.

A final thought

Why not look at the levels of economic development and satisfaction? The following graph does this, displaying amazing new data coming from the Gallup World Poll. There’s no longer any doubt that people in richer countries report being more satisfied with their lives.

Is this relevant? Easterlin argues it isn’t — that he’s only concerned with changes in GDP. But the two are inextricably linked. If rich countries are happier countries, this begs the question: How did they get that way? We think it’s because as their economies developed, their people got more satisfied. While we don’t have centuries’ worth of well-being data to test our conjecture, it’s hard to think of a compelling alternative.

Justin Wolfers’ column titled “Debunking the Easterlin Paradox, Again” dismisses Richard Easterlin’s work as just plain wrong. I argue here, as I have elsewhere, that where you come out on the Easterlin paradox depends on the happiness question (and therefore the definition of happiness) that you use, as well as the sample of countries and the period of time.

Richard Easterlin finds no clear country-by-country relationship between average per capita GDP and life satisfaction (among wealthy countries), despite a clear relationship between income and happiness at the individual level within countries. Easterlin also found – and continues to find, based on methods different from Wolfers’ – an absence of a relationship between life satisfaction and long-term changes in GDP per capita.

Different well-being questions measure different dimensions of “happiness”, and, in turn, they correlate differently with income (something they themselves show at the end of their last paper, and admit that the relationship between income and well-being is complex). The best possible life question – which Justin Wolfers and Betsey Stevenson primarily use in the first work, and also in the second – asks respondents to compare their life today to the best possible life they can imagine for themselves. This introduces a relative component, and, not surprisingly, the question correlates most closely with income of all of the available subjective well-being questions. Life satisfaction, which they use in the second work, also correlates with income more than open-ended happiness, life purpose or affect questions, but not as closely as the best possible life question.

Wolfers and Stevenson used the most recent and extensive sample of countries available from the Gallup World Poll, and, as the measure of “happiness”, the best possible life question therein, and challenged the Easterlin paradox. In more recent work, with Stevenson and Dan Sacks (2010), referenced in this blog, the authors look at the relationship between life satisfaction and economic growth, based on the World Values survey and GDP levels and the best possible life question, based on the Gallup World Poll. They isolate a clear relationship between life satisfaction and GDP levels, and their statistical analysis is spot on.

Recent studies by Kahneman and Deaton (2010), and Diener and colleagues (2010), for example, find that happiness in a life evaluation sense (as measured by the best possible life question) correlates much more closely with income than does happiness in a life experience sense (as measured by affect or more open ended happiness questions). This holds within the United States (Kahneman and Deaton) and across countries (Diener et al.).

My own work on Latin America, with Soumya Chattopadhyay and Mario Picon, tested various questions against each other and finds a similar difference in correlation, with affect and life purpose questions having the least correlation with income and the best possible life question the most. My work on happiness in Afghanistan found that Afghans were happier than the world average (on par with Latin Americans) as measured by an open ended happiness question, and 20 percent more likely to smile in a day than Cubans. Yet they scored much lower than the world average on the best possible life question. This is not a surprise. While naturally cheerful and able to make the best of their lot, the Afghans also know that the best possible life is outside Afghanistan.

Thus the conclusions that one draws on whether there is an Easterlin paradox or not in part rest on the definition of happiness, and therefore the question that is used as the basis of analysis. Wolfers and co-authors find a clear relationship between GDP levels and life satisfaction and best possible life – clearly important dimensions of well-being. Yet in the same paper they find much less clear relationships when they use happiness, affect and life purpose questions.  

There is also the question of the sample of countries, and whether one is examining cross section or time series data. The most recent debate with Easterlin is about the trends over time rather than cross-sectional patterns. Dropping the transition economies, as Easterlin does, may be a mistake, as Wolfers contends. But it is also important to recognize the extent to which including a large sample of countries that experienced unprecedented economic collapse and associated drops in happiness alters the slope in the cross-country income-happiness relationship (making it steeper). Wolfers also criticizes Easterlin for relying on financial satisfaction data for his Latin American time series sample (because there is not enough life satisfaction data); financial satisfaction correlates closely, but not perfectly, with life satisfaction. Easterlin’s technique allows for the inclusion of a much larger sample of middle income developing countries, a sample of countries that one can imagine is very important to the growth and happiness debate. Wolfers and co-authors use far fewer Latin American countries because comparable life satisfaction data is limited. Either approach is plausible and, as with all work with limited data, is not perfect. But I would not go as far as calling one or the other “plain wrong”.

Finally, there is the simpler question of giving credit where credit is due. We would not be having this debate, nor would we have a host of analysis on well-being beyond what is measured by income, had Easterlin not triggered our thinking on this with his original study of happiness and income over three decades ago (and his patient and thoughtful mentoring of many economists since then). In the big picture of things, Easterlin had the idea.

The Roma people, the largest minority group in Europe and in many European countries, trail other ethnic groups in almost every characteristic that defines well-being. Perhaps of greatest importance, the Roma are less educated than other ethnic groups. But they also suffer from excess health problems, high unemployment, poverty, and political weakness. The Roma population of Bulgaria is certainly no less disadvantaged than the Roma in other countries. An especially poignant example of Bulgarian Roma disadvantage is that the death rate among children under age 1, a prime indicator of children’s health in any nation, is 25 per 1,000 for Roma children as compared with 9.9 for children of Bulgarian ethnic origin. The mathematics of death almost before life gets started is a symbolic indicator of the Roma burden in Bulgaria. Similarly, research conducted for UNICEF by the University of York shows that the poverty rate among Roma children in Bulgaria is 92 percent, perhaps the highest poverty rate for any ethnic group in Europe. By contrast, the poverty rate among children of Bulgarian heritage is less than half as high at 43 percent.

It is not surprising, then, that over at least the past decade, the European Union (EU) and most European governments, joined by the Open Society Foundation, the World Bank, and other organizations, have created important initiatives to address all these problems. It is possible to think that now is an historic moment in which European governments and dominant ethnic groups, after eight or nine centuries of the most pernicious types of discrimination against the Roma, are finally, albeit often reluctantly, admitting the problems facing their Roma populations and their own role in creating and sustaining these problems. Equally important, most of the Central and Eastern European (CEE) governments, where discrimination against the Roma has been and continues to be particularly intense, are gradually adopting policies to address the problems.

To the extent that the moment of Roma opportunity has arrived, perhaps the most important force moving Bulgaria and other CEE nations in the direction of integration and inclusion is the EU. In the period leading up to the ascension of Bulgaria and other CEE nations to membership in the EU, all the new member states were required to meet a host of conditions required by the EU as the price of admission. Among these conditions were laws outlawing discrimination and requiring equality of educational opportunity. The CEE nations complied with the EU directive to pass such laws, but implementation of the laws in Bulgaria and other nations has been something less than aggressive.

Nor is EU ascension the only force driving the CEE nations to reduce discrimination against the Roma and other minorities. The Open Society, the World Bank, and a number of other private organizations, including several Roma nongovernmental organizations (NGOs), have initiated a sweeping program to promote inclusion of the Roma in the civil society of the CEE nations. Called the “Decade of Roma Inclusion” (2005-2015) the initiative is notable for getting all the CEE nations (plus Spain) to participate, to commit themselves to activities designed to promote inclusion and nondiscrimination, and to make a financial commitment to a fund administered by the World Bank to promote the initiative. As a part of the initiative, Bulgaria and the other participating nations originated ten-year action plans. The Bulgarian action plan, the purpose of which is to create a set of goals and activities that will promote Roma integration, includes proposals for education, health care, housing, employment, discrimination and equal opportunity, and culture.

An important part of the Decade program was the establishment of the Roma Education Fund in 2005. Eight nations (Canada, Greece, Ireland, Netherlands, Slovenia, Sweden, Switzerland, and the UK), as well as several international agencies including the Open Society, pledged a total of 34 million Euros to support Fund activities during the Roma decade. The major goal of the fund is to “support policies and programs which ensure quality education for Roma, including the desegregation of education systems.”

By joining the EU, Bulgaria and the other CEE nations brought themselves into a well-developed culture of inclusion and a complex system of interlocking laws and agencies that not only outlaw exclusion and discrimination, but provide funds to implement inclusion policies and to monitor the extent to which EU nations are aggressively implementing these laws. The laws and directives include the EU Charter of Fundamental Rights, the European Commission against Racism and Intolerance, the Racial Equality Directive, and several others. It would be a mistake to conclude that every EU member, even the original 15 EU nations with relatively more advanced economies and longer histories as democracies than the CEE nations, faithfully implement every component of the various legal requirements of being an EU member. Even so, EU requirements and funds have initiated both profound legal changes and a host of programs to increase the social, economic, political, and cultural inclusion of the Roma as well as studies and evaluations that bring some light to the actual situation of the Roma and other minorities in member nations. Given the all but inevitable distance between the laws on inclusion and discrimination the CEE nations passed in order to join the EU and the actual implementation of those laws, studies commissioned by various EU agencies and NGOs illuminate the gaps between policies and implementation.

An excellent example of such illumination is a 2006 study commissioned by the Economic and Scientific Policy program of the European Parliament. The report is a hard-hitting assessment of the status of Roma throughout Europe with regard to their legal status and socio-economic conditions. The latter category includes assessments of Roma exclusion from employment, education, social services, health care, and community integration. The upshot of the report is that although there may be some progress in these important areas of integration, the Roma are still a second-class group throughout the CEE nations. Seemingly, good laws have not yet produced good results. Laws may be changed, but changing human behavior and culture takes longer.

CEE governments and their defenders are reluctant to admit the lamentable lack of progress in Roma integration. In part for this reason, the European Commission, based on extensive evidence from evaluations, surveys, and news reports of often ferocious discrimination against the Roma, felt the need to publish “An EU Framework for National Roma Integration Strategies up to 2020” in April 2011. The need for a new framework is a clear signal that the EU Commission believes the CEE governments in general and Bulgaria in particular are not achieving the results the EU hoped for when it approved these nations for EU membership and is therefore trying to push the governments of these nations into further action.

Following publication of the Framework, the Open Society released one of the most thorough and provocative reports on the situation faced by the Roma in Europe and strategies that should be adopted to attack the wide range of Roma disadvantages. Appropriately entitled “Beyond Rhetoric,” the Open Society report includes entire chapters on two issues that I will examine in more detail below.

First, the Open Society strongly recommends that nations collect ethnically disaggregated data. Logically enough, the report holds that it is impossible to document the effects of policy initiatives on the Roma and other groups unless outcome data, including measures of health, education, housing, employment, income, and death rates by age, are collected for individual ethnic groups. So important are ethnically disaggregated data that the report goes so far as to recommend that, if necessary, governments should change their statistical systems to “incorporate ethnic data components into regular statistical surveys.” A second recommendation that deserves special attention is the report’s emphasis on early childhood education and care. Virtually every report about the Roma emphasizes the vital importance of education in fighting Roma exclusion, but the Open Society report strongly recommends that nations implementing the EU Framework should “give urgent consideration” to establishing an early child development fund to “support innovative early development programs and allow for scale up of what works.”

Beyond these specific recommendations, the Open Society report emphasizes that the EU Commission stated explicitly in its Framework document that “member states do not properly use EU money for the purpose of effective social and economic integration of Roma. As if this judgment, which seems to represent the views of many EU agencies, the World Bank, the Open Society, and many Roma groups themselves, needed additional reinforcement, a United Nations expert on minority issues visited Bulgaria this summer and called upon the government to “turn its policies on Roma integration into concrete action.” She went on to give what seems to represent the views of all these groups on the flaws in the Bulgarian government’s approach to fighting Roma exclusion: “Many policies seem to remain largely only rhetorical undertakings aimed at external audiences – official commitments that are not fulfilled in practice.” The result, according to the UN expert, is that “all the evidence demonstrates that Roma remain in desperate circumstances at the very bottom of the socio-economic ladder.” In particular, she mentioned that the access of Roma children to quality education “remains overwhelmingly unfulfilled.”

If CEE nations are now entering a period in which governments will be working, often ineffectively or at a very modest pace, to improve the conditions of the Roma, judging by the efforts of other nations to reduce discrimination against minority groups and by the stately rate of progress so far in the CEE nations, it can be assumed that the fight for Roma equality in Bulgaria will be measured in decades. In the U.S., for example, the Civil Rights movement of the 1950s and 1960s was largely successful. By the mid-1960s, vital court decisions had dismantled major parts of the system of legal discrimination against blacks and the federal government had enacted programs to ensure voting rights and other fundamental rights to blacks. To enhance the legal war on poverty and discrimination, the federal government also initiated an army of social programs designed to boost the education, health, employment, housing, and political participation of the poor in general and blacks in particular. Yet today, nearly half a century after achieving legal rights and the initiation of large-scale government inclusion programs, blacks (and Hispanics) still trail whites by large margins in education, income, housing, poverty levels, and health. Although achieving significant progress against discrimination may require decades or generations, discrimination will not diminish until strong legal, economic, and social forces are mobilized against it. Expecting a long struggle cannot be a reason not to begin.

If the history of making substantial progress in overcoming ethnic discrimination in the U.S. can serve as a rough comparison to the situation of the Roma in CEE nations, several factors are going to be vital in the fight of the Roma to overcome discrimination and exclusion in Bulgaria and throughout Europe. These factors include an antidiscrimination plan, aggressive implementation of the plan by all levels of government, leadership by the Roma themselves, educational progress by Roma children and young adults, political activism by the Roma people, a media committed to accurate reporting and fairness, and a civil society that reflects underlying public opinion favoring integration and opposed to discrimination. Most of these factors appear to be present in Bulgaria, often in rudimentary and brittle form, but present and in many cases moving in the right direction nonetheless. The progress that is just now beginning can be greatly enhanced by the efforts of groups that have the resources, the will, and the vision to roll up their sleeves and help promote Roma inclusion.

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ABSTRACT

In recent decades economists have turned their attention to data that asks people how happy or satisfied they are with their lives. Much of the early research concluded that the role of income in determining well-being was limited, and that only income relative to others was related to well-being. In this paper, we review the evidence to assess the importance of absolute and relative income in determining well-being. Our research suggests that absolute income plays a major role in determining well-being and that national comparisons offer little evidence to support theories of relative income. We find that well-being rises with income, whether we compare people in a single country and year, whether we look across countries, or whether we look at economic growth for a given country. Through these comparisons we show that richer people report higher well-being than poorer people; that people in richer countries, on average, experience greater well-being than people in poorer countries; and that economic growth and growth in well-being are clearly related. Moreover, the data show no evidence for a satiation point above which income and well-being are no longer related.

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Access to information and communication technology through cell phones, the internet, and electronic media has increased exponentially around the world. While a few decades ago cell phones were a luxury good in wealthy countries, our data show that today over half of respondents in Sub-Saharan Africa and about 80 percent of those in Latin America and Southeast Asia have access to cell phones. In addition to making phone calls and text messaging, cell phones are used for activities such as accessing the internet and social network sites. Meanwhile, the launch of mobile banking gives access to these technologies an entirely new dimension, providing access to financial services in addition to information and communication technology. It is estimated that in Kenya, where the mobile banking “revolution” originated, there are some 18 million mobile money users (roughly 75 percent of all adults). Given the expanding role of information technology in today’s global economy, in this paper we explore whether this new access also enhances well-being.

Neither of the authors is an expert on information technology. The real and potential effect of information technology on productivity, development, and other economic outcomes has been studied extensively by those who are. Building on past research on the economics of well-being and on the application of the well-being metrics to this particular question, we hope to contribute an understanding of how the changes brought about by information and communication technology affect well-being in general, including its non-income dimensions.

Our study has two related objectives. The first is to understand the effects of the worldwide increase in communications capacity and access to information technology on human well-being. The second is to contribute to our more general understanding of the relationship between well-being and capabilities and agency. Cell phones and information technology are giving people around the world – and particularly the poor – new capabilities for making financial transactions and accessing other services which were previously unavailable to them. We explore the extent to which the agency effect of having access to these capabilities manifests itself through both hedonic and evaluative aspects of well-being.

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Paris and Rome may be famous for romance, but it’s Filipinos who get the most love. That, at least, is a conclusion that can be drawn from a global love survey conducted by the Gallup Organization.

In our latest column for Bloomberg View, we mine the unique Gallup data for insights into the nature of love and its relationship to nationality, age, money and economic development. The survey, conducted in 136 countries, posed the question: “Did you experience love for a lot of the day yesterday?”

In honor of Valentine’s Day, we thought readers might be interested in seeing the full ranking. So here goes. The first number after each country name is the percentage of respondents who said they had experienced love the previous day. The second (in parentheses) is the sample size for the country.

1. Philippines 93% (2193)
2. Rwanda 92% (1495)
3. Puerto Rico 90% (495)
4. Hungary 89% (1002)
5. Cyprus 88% (988)
6. Trinidad and Tobago 88% (506)
7. Paraguay 87% (1986)
8. Lebanon 86% (970)
9. Costa Rica 85% (1985)
10. Cambodia 85% (1961)
11. Nigeria 84% (1965)
12. Guyana 83% (486)
13. Spain 83% (998)
14. Mexico 82% (989)
15. Tanzania 82% (1941)
16. Ecuador 82% (2126)
17. Jamaica 82% (534)
18. Venezuela 82% (997)
19. Cuba 82% (978)
20. Brazil 82% (1038)
21. Laos 81% (1947)
22. Argentina 81% (1985)
23. Belgium 81% (1015)
24. Canada 81% (1006)
25. Greece 81% (996)
26. U.S. 81% (1224)
27. Denmark 80% (1003)
28. Portugal 80% (995)
29. Netherlands 80% (993)
30. Vietnam 79% (1901)
31. New Zealand 79% (1775)
32. Italy 79% (1000)
33. Colombia 79% (1994)
34. Madagascar 78% (998)
35. Uruguay 78% (1969)
36. Turkey 78% (985)
37. Dominican Republic 78% (1976)
38. United Arab Emirates 77% (961)
39. Saudi Arabia 77% (978)
40. Chile 76% (1982)
41. Malawi 76% (1997)
42. Ghana 76% (1986)
43. South Africa 76% (1968)
44. Australia 76% (1199)
45. Panama 75% (1995)
46. Zambia 74% (1971)
47. Kenya 74% (1965)
48. Namibia 74% (996)
49. Nicaragua 74% (1988)
50. Germany 74% (1214)
51. Ireland 74% (992)
52. Sweden 74% (993)
53. U.K. 74% (1200)
54. Switzerland 74% (986)
55. Montenegro 74% (800)
56. Austria 73% (984)
57. France 73% (1217)
58. Kuwait 73% (934)
59. Finland 73% (993)
60. El Salvador 73% (2000)
61. Pakistan 73% (2253)
62. Zimbabwe 72% (1989)
63. Honduras 72% (1947)
64. Peru 72% (1982)
65. Egypt 72% (1024)
66. Serbia 72% (1474)
67. Bosnia and Herzegovina 72% (1896)
68. Sierra Leone 71% (1986)
69. India 71% (3140)
70. Taiwan 71% (984)
71. Bangladesh 70% (2200)
72. Belize 70% (464)
73. Croatia 69% (958)
74. Macedonia 69% (1000)
75. Mozambique 69% (996)
76. Bolivia 69% (1948)
77. Liberia 68% (988)
78. Iran 68% (963)
79. China 68% (7206)
80. Slovenia 68% (1000)
81. Haiti 68% (471)
82. Norway 67% (992)
83. Sri Lanka 67% (1974)
84. Poland 67% (939)
85. Guatemala 67% (1988)
86. Uganda 66% (1961)
87. Sudan 66% (971)
88. Israel 66% (957)
89. Kosovo 65% (983)
90. Thailand 65% (2377)
91. Jordan 65% (998)
92. Albania 64% (855)
93. Guinea 62% (952)
94. Botswana 62% (999)
95. Angola 62% (957)
96. Burkina Faso 62% (1876)
97. Malaysia 61% (2115)
98. Mali 61% (984)
99. Niger 61% (1925)
100. Palestinian Territories 61% (991)
101. Romania 61% (937)
102. Senegal 61% (1805)
103. Indonesia 61% (2013)
104. Afghanistan 60% (1128)
105. Hong Kong 60% (789)
106. Cameroon 59% (1967)
107. Japan 59% (1138)
108. Nepal 59% (1965)
109. Bulgaria 59% (927)
110. Slovakia 58% (991)
111. Singapore 58% (3002)
112. Czech Republic 58% (992)
113. Mauritania 57% (1960)
114. Benin 56% (974)
115. South Korea 56% (2056)
116. Myanmar 55% (1047)
117. Latvia 54% (1942)
118. Togo 54% (988)
119. Estonia 53% (1800)
120. Lithuania 50% (1863)
121. Russia 50% (4667)
122. Chad 49% (1915)
123. Yemen 48% (959)
124. Ukraine 48% (1930)
125. Ethiopia 48% (1913)
126. Azerbaijan 47% (1824)
127. Tajikistan 47% (1847)
128. Moldova 46% (1937)
129. Kazakhstan 45% (1871)
130. Morocco 43% (1011)
131. Belarus 43% (1992)
132. Georgia 43% (1904)
133. Kyrgyzstan 34% (1969)
134. Mongolia 32% (928)
135. Uzbekistan 32% (962)
136. Armenia 29% (1954)

Note: This content was first published on Bloomberg View on February 13, 2013.

On Valentine’s Day, even a dismal scientist’s mind turns to love. It’s a powerful feeling, with a value that goes far beyond the millions of chocolate boxes and bouquets that will be delivered this Feb. 14.

Survey data from the Gallup Organization, where Justin works as a senior scientist, allow us to take a uniquely deep look at the state of love around the world. In 2006 and 2007, Gallup went to 136 countries and asked people, “Did you experience love for a lot of the day yesterday?” It’s the largest such dataset ever collected.

The good news: Ours is a loving world. On a typical day, about 70 percent of people worldwide reported a love-filled day. In the U.S., 81 percent felt love, as did 81 percent of Canadians and 79 percent of Italians. Germany and the U.K. were less loving, with slightly less than 3 in 4 people reporting feeling loved. Surprisingly, the same was true of the supposedly romantic French. And if you’re in Japan, please hug someone: Only 59 percent of Japanese said they had experienced love the previous day.

Across the world as a whole, the widowed and divorced are the least likely to experience love. Married folks feel more of it than singles. People who live together out of wedlock report getting even more love than married spouses -- an interesting factoid for conservatives worried about the effects of cohabitation. Women get more love than men, particularly in the U.S.

Young Love

If you’re young and not feeling all that loved this Valentine’s Day, don’t despair: You’re not alone. Young adults are among the least likely to experience love. It gets better with age, ultimately peaking in the mid-30s or mid-40s in most countries before fading again into the twilight years.

Money is related to love. Those with more household income are slightly more likely to experience the feeling. Roughly speaking, doubling your income is associated with being about 4 percentage points more likely to be loved. Perhaps having more money makes it easier to find time for love.

That said, the data aren’t necessarily telling us that money can buy you love. It’s possible that other factors correlated with income, such as height or appearance, are the real source of attraction. Or maybe being loved gives you a boost in the labor market.

What’s perhaps more striking is how little money matters on a global level. True, the populations of richer countries are, on average, slightly more likely to feel loved than those of poorer countries. But love is still abundant in the poorer countries: People in Rwanda and the Philippines enjoyed the highest love ratios, with more than 9 in 10 people providing positive responses. Armenia, Uzbekistan, Mongolia and Kyrgyzstan, with economic output per person in the middle of the range, all had love ratios of less than 4 in 10.

Fun facts aside, we think there is a deeper and more consequential purpose to the study of love. Think about what love means to you. To us, it means caring about others and being cared for. Love is valuable, even if it is absent from both our national accounts and our political discourse.

In the language of economics, love is a form of insurance. It involves bonds of reciprocity that provide support when we’re feeling down, when we’re sick and when times are tough.

More broadly, love has the power to mitigate the free-rider and moral hazard problems associated with social (and private) insurance. Bailing out a bank might encourage executives to take bigger risks in the future, but helping loved ones down on their luck has fewer incentive problems because our loved ones typically care for us in return. Such mutually beneficial relationships make us all more resilient in times of crisis. This is why the household remains one of the most powerful institutions for organizing not just families but also our economic lives.

If we can find more love for our fellow citizens, our society will function better. Hard as this may be to achieve in an era when trust in government, business and one another is low, it’s worth the effort. When you expand the boundaries of trust and reciprocity, you expand the boundaries of what is possible.

Note: This content was first published on Bloomberg View on February 13, 2013.

Many scholars have argued that once “basic needs” have been met, higher income is no longer associated with higher in subjective well-being. We assess the validity of this claim in comparisons of both rich and poor countries, and also of rich and poor people within a country. Analyzing multiple datasets, multiple definitions of “basic needs” and multiple questions about well-being, we find no support for this claim. The relationship between well-being and income is roughly linear-log and does not diminish as incomes rise. If there is a satiation point, we are yet to reach it.

Introduction

In 1974 Richard Easterlin famously posited that increasing average income did not raise average well-being, a claim that became known as the Easterlin Paradox. However, in recent years new and more comprehensive data has allowed for greater testing of Easterlin’s claim. Studies by us and others have pointed to a robust positive relationship between well-being and income across countries and over time (Deaton, 2008; Stevenson and Wolfers, 2008; Sacks, Stevenson, and Wolfers, 2013). Yet, some researchers have argued for a modified version of Easterlin’s hypothesis, acknowledging the existence of a link between income and well-being among those whose basic needs have not been met, but claiming that beyond a certain income threshold, further income is unrelated to well-being.

The existence of such a satiation point is claimed widely, although there has been no formal statistical evidence presented to support this view. For example Diener and Seligman (2004, p. 5) state that “there are only small increases in well-being” above some threshold. While Clark, Frijters and Shields (2008, p. 123) state more starkly that “greater economic prosperity at some point ceases to buy more happiness,” a similar claim is made by Di Tella and MacCulloch (2008, p. 17): “once basic needs have been satisfied, there is full adaptation to further economic growth.” The income level beyond which further income no longer yields greater well-being is typically said to be somewhere between $8,000 and $25,000. Layard (2003, p. 17) argues that “once a country has over $15,000 per head, its level of happiness appears to be independent of its income;” while in subsequent work he argued for a $20,000 threshold (Layard, 2005 p. 32-33). Frey and Stutzer (2002, p. 416) claim that “income provides happiness at low levels of development but once a threshold (around $10,000) is reached, the average income level in a country has little effect on average subjective well-being.”

Many of these claims, of a critical level of GDP beyond which happiness and GDP are no longer linked, come from cursorily examining plots of well-being against the level of per capita GDP. Such graphs show clearly that increasing income yields diminishing marginal gains in subjective well-being. However this relationship need not reach a point of nirvana beyond which further gains in well-being are absent. For instance Deaton (2008) and Stevenson and Wolfers (2008) find that the well-being–income relationship is roughly a linear-log relationship, such that, while each additional dollar of income yields a greater increment to measured happiness for the poor than for the rich, there is no satiation point.

In this paper we provide a sustained examination of whether there is a critical income level beyond which the well-being–income relationship is qualitatively different, a claim referred to as the modified-Easterlin hypothesis. As a statistical claim, we shall test two versions of the hypothesis. The first, a stronger version, is that beyond some level of basic needs, income is uncorrelated with subjective well-being; the second, a weaker version, is that the well-being–income link estimated among the poor differs from that found among the rich.

Claims of satiation have been made for comparisons between rich and poor people within a country, comparisons between rich and poor countries, and comparisons of average well-being in countries over time, as they grow. The time series analysis is complicated by the challenges of compiling comparable data over time and thus we focus in this short paper on the cross-sectional relationships seen within and between countries. Recent work by Sacks, Stevenson, and Wolfers (2013) provide evidence on the time series relationship that is consistent with the findings presented here.

To preview, we find no evidence of a satiation point. The income–well-being link that one finds when examining only the poor, is similar to that found when examining only the rich. We show that this finding is robust across a variety of datasets, for various measures of subjective well-being, at various thresholds, and that it holds in roughly equal measure when making cross-national comparisons between rich and poor countries as when making comparisons between rich and poor people within a country.

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