What is the effect of the business cycles on an individual’s happiness?

write one page presentation notes, just introduction to this article. DO NOT use other resources, read this article and write a introduction including the answers of:

What is the effect of the business cycles on an individual’s happiness?

what is the research question?

why it is important?

why we care?

THE MACROECONOMICS OF HAPPINESS

Rafael Di Tella, Robert J. MacCulloch, and Andrew J. Oswald*

Abstract—We show that macroeconomic movements have strong effects on the happiness of nations. First, we find that there are clear microeco- nomic patterns in the psychological well-being levels of a quarter of a million randomly sampled Europeans and Americans from the 1970s to the 1990s. Happiness equations are monotonically increasing in income, and have similar structure in different countries. Second, movements in reported well-being are correlated with changes in macroeconomic vari- ables such as gross domestic product. This holds true after controlling for the personal characteristics of respondents, country fixed effects, year dummies, and country-specific time trends. Third, the paper establishes that recessions create psychic losses that extend beyond the fall in GDP and rise in the number of people unemployed. These losses are large. Fourth, the welfare state appears to be a compensating force: higher unemployment benefits are associated with higher national well-being.

I. Introduction

NEWSPAPERS regularly report changes in macroeco-nomic variables. It is also known that economic vari- ables predict voters’ actions and political outcomes (Frey and Schneider, 1978). These facts suggest that aggregate economic forces matter to people. Yet comparatively little is known empirically about how human well-being is influ- enced by macroeconomic fluctuations.1 When asked to eval- uate the cost of a business cycle downturn, most economists measure the small drop in gross domestic product.

This paper adopts a different approach. It begins with international data on the reported well-being levels of hun- dreds of thousands of individuals. The paper’s first finding is that there are strong microeconomic patterns in the data, and that these patterns are similar in a number of countries. Happiness data behave in a predictable way. We then show that, after controlling for the characteristics of people and countries, macroeconomic forces have marked and statisti- cally robust effects on reported well-being. GDP affects a country’s happiness. Furthermore, pure psychic costs from recessions appear to be large. As well as the losses from a fall in GDP, and the direct costs of recession to those falling unemployed, a typical business cycle downturn of one year’s length would have to be compensated by giving each citizen—not just unemployed citizens—approximately $200 per year.2 This loss is over and above the GDP cost of a year of recession. It is an indirect, or “fear,” effect that is

omitted from economists’ standard calculations of the cost of cyclical downturns.

In spite of a long tradition studying aggregate economic fluctuations, there is disagreement among economists about the seriousness of their effects. One view, associated with Keynes, argues that recessions are expensive disruptions to the economic organization of society. Recessions involve considerable losses—underutilization of invested capacity, emotional costs to those who lose their jobs, and distribu- tionalunfairness.Adifferentviewisadoptedby real-business- cycle theorists. They argue that Keynesians overestimate the costs of business cycles: downturns follow booms, and business cycles do not affect the average level of economic activity. Given that individuals are optimizing, recessions are desirable adjustments to productivity shocks. This means that the costs of business cycles are small—perhaps only 0.1% of total consumption in the United States (Lucas, 1987).3 Consequently, these economists have turned their attention to economic growth and away from fluctuations.

Our paper derives a measure of the costs of an economic downturn that can be used in such debates. In doing so, the paper employs data of a kind more commonly found in the psychology literature. Collected in standard economic and social surveys, the data provide self-reported measures of well-being, such as responses to questions about how happy and satisfied individual respondents are with their lives. We begin by showing that life-satisfaction regression equa- tions—where individuals’ subjective well-being levels are regressed on the personal characteristics of the respon- dents—have a broadly common structure across countries. A large set of personal characteristics has approximately the same influence on reported happiness, regardless of where well-being questions are being asked. This regularity sug- gests that happiness data contain potentially interesting information.

II. Conceptual Issues

From the outset, the paper has to face up to two concep- tual concerns. The first is caused by the approximately untrended nature of reported happiness [as noted by Richard Easterlin (1974)]. For the usual unit-root reasons, we cannot then regress happiness on trended variables such as GDP. This paper experiments with equations in which there are (i) year dummies, (ii) country-specific time trends, and (iii) change-in-GDP variables. The second conceptual problem is that variables such as GDP per capita, unemployment, and

Received for publication July 12, 2000. Revision accepted for publica- tion September 9, 2002.

* Harvard Business School, Princeton University, and University of Warwick, respectively.

For helpful comments, we thank James Stock (editor) as well as George Akerlof, Danny Blanchflower, Andrew Clark, Ben Friedman, Duncan Gallie, Sebastian Galiani, Julio Rotemberg, Hyun Shin, John Whalley, and seminar participants at Oxford, Harvard, and the 1997 NBER Behavioral Macro Conference. The third author is grateful to the Economic and Social Research Council (macroeconomics program) for research support. The working paper version of this paper is “The Macroeconomics of Happi- ness,” Center for Economic Performance 19, (July 1997).

1 It is known that suicide rose markedly in the Great Depression, but that was probably too extreme an episode to allow any easy judgement.

2 In 1985 U.S. dollars, which is the middle of our sample.

3 Even when market imperfections are introduced, the costs rise by only a factor of 5, and they are significantly lower if borrowing is allowed: see Atkeson and Phelan (1994). A different approach to measuring the costs of business cycles, using asset prices, is developed in Alvarez and Jermann (1999).

The Review of Economics and Statistics, November 2003, 85(4): 809–827 © 2003 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

inflation are not exogenous. These variables are influenced by politicians’ choices; their choices are shaped by reelec- tion probabilities; those probabilities in turn can depend on the feeling of contentment among a country’s citizens. A further possible source of simultaneity is that happier people may work harder and thus produce more output. It is not straightforward to find believable macroeconomic instru- ments that can identify the well-being equation. Instead, the paper experiments with different forms of lag structures, to attempt to see if movements in macroeconomic forces lead, later on, to movements in well-being.

Traditionally, economists assume that it is sufficient to pay attention to decisions. This is because people’s choices should reveal their preferences. More recently, however, it has been suggested that an alternative is to focus on expe- rienced utility, a concept that emphasises the pleasures derived from consumption (for example, Kahneman and Thaler, 1991). Kahneman, Wakker, and Sarin (1997) pro- vide an axiomatic defense of experienced utility with appli- cations to economics. We make the assumption that survey measures of happiness are closer to experienced utility than to the decision utility of standard economic theory. Al- though a number of conceptual questions remain unan- swered (for example, with respect to how people are af- fected by comparisons and reference points), it has been argued by some that self-reports of satisfaction may help deal with the challenges posed by the need to understand experienced utility (see Rabin, 1998, for instance).

There has been comparatively little research by econo- mists on the data on reported well-being. Richard Easterlin (1974) began what remains a small literature, and recently updated his work in Easterlin (1995). Other contributions include Gruber and Mullainathan (2002), Von Praag and Frijters (1999), Ng (1996, 1997), Blanchflower and Oswald (1999), Frank (1985), Inglehart (1990), Fox and Kahneman (1992), Frey and Stutzer (2000), Konow and Earley (1999), Oswald (1997), Winkelmann and Winkelmann (1998), Gardner and Oswald (2001), and Alesina, Di Tella, and MacCulloch (2001). Di Tella, MacCulloch, and Oswald (2001) study people’s preferences over inflation and unem- ployment. Di Tella and MacCulloch (1999) use happiness data to examine the properties of partisan versus opportu- nistic voting models. See Frey and Stutzer (2002) for a review.

The paper’s main data source is the Euro-Barometer Survey Series. Partly the creation of Ronald Inglehart at the University of Michigan, the surveys record happiness and life-satisfaction scores of approximately 300,000 people living in twelve European countries over the period 1975– 1992. We also use the United States General Social Survey. It records similar kinds of information on approximately 30,000 individuals over the period 1972–1994. Section III introduces our happiness data and studies how they are affected by personal characteristics.

It is well known that individuals’ answers to well-being questions can be influenced by order and framing effects within a survey, and by the number of available answer categories (in our main data set, there are only four). Apart from the pragmatic defense that we are constrained by the data as collected, some of these problems can be reduced by averaging across large numbers of observations, and by the inclusion of country fixed effects in the macroeconomic regressions. Section IV describes our empirical strategy.

Section V studies the relationship between well-being data and national income per capita. The survey questions do not ask people whether they like economic booms. Instead, respondents are asked how happy they feel with their lives, and their collective answers can be shown— unknown to the respondents themselves—to move system- atically with their nation’s GDP.4 In section VI we calculate the effect of other macroeconomic variables, such as the unemployment rate, on happiness. We then use these results to calculate the costs of recessions.

Section VII studies what happens to reported happiness when governments try to reduce the impact of economic fluctuations. The focus here is on the welfare state, and especially on the impact upon well-being of an unemploy- ment benefit system. We show that countries with more generous benefit systems are happier (or, more strictly speaking, say that they are happier). Some economists who study European unemployment have claimed a causal link between the region’s relatively generous welfare provision and its unemployment problems. By making life too easy for the unemployed, the argument goes, the welfare states of Europe have taken away the incentive to work and so fostered voluntary joblessness. We test, and fail to find evidence for, this common supposition. Contrary to conven- tional wisdom, the gap in happiness between the employed and the unemployed has stayed the same since the 1970s. It has apparently not become easier, over the decades, to be out of work in Europe.

Section VIII summarizes.

III. Happiness Data and Microeconometric Patterns

A random sample of Europeans is interviewed each year and asked two questions, among others, that are of interest here. The first is “Taking all things together, how would you say things are these days—would you say you’re very happy, fairly happy, or not too happy these days?” (small “Don’t know” and “No answer” categories are not studied here). The surveys also report the answers of 271,224 individuals across 18 years to a “life satisfaction” question. This ques- tion is included in part because the word happy translates imprecisely across languages. It asks, “On the whole, are

4 Thus, our approach differs from that of Shiller (1996), Di Tella and MacCulloch (1996b), Boeri, Borsch-Supan, and Tabellini (2001), Luttmer (2001), and MacCulloch (2001), who use survey data directly related to the issue being studied (inflation, unemployment benefits, welfare state reform, redistribution, and revolutions, respectively).

THE REVIEW OF ECONOMICS AND STATISTICS810

you very satisfied, fairly satisfied, not very satisfied, or not at all satisfied with the life you lead?” (Once again, the small “Don’t know” and “No answer” categories are again not studied.)

Raw well-being data are presented in Tables 1 and 2. We focus principally on life satisfaction data because they are available for a longer period of time—from 1975 to 1992 instead of just to 1986. Happiness and life satisfaction are correlated (the correlation coefficient is 0.56 for the period 1975–1986). Blanchflower and Oswald (1999) have shown that where British data on both are available, the micro- econometric equations have almost identical forms. Our paper finds, in a later table, the same for Europe. The Appendix presents summary statistics, describes the data sets, gives equations individually for nations, and explains how our later macroeconomic variables are measured. Table 1 provides a cross-tabulation of life satisfaction for Europe.

The analysis also examines well-being data from the United States General Social Survey (1972–1994). There is a similar happiness question that reads “Taken all together, how would you say things are these days—would you say that you are very happy, pretty happy, or not too happy?” (Small “Don’t know” and “No answer” categories are not studied in this paper.) This was asked in each of 23 years

and covers 26,668 individuals. There was no life satisfac- tion question for the United States. Table 2 summarizes the happiness responses for the United States. With only three response categories, this question may be less revealing than the life-satisfaction question, which offers four. An odd number of categories may allow less introspection, since people can choose the middle category when unsure of their choice.

Taking at face value the numbers in tables 1 and 2, well-being scores appear to be skewed towards the top of the possible answer distribution. In other words, individuals seem to answer optimistically. On average they say that they are fairly happy and very satisfied. Whatever the appropriate interpretation of this pattern, it is clear that in both Europe and the United States the unemployed and divorced are much less content. These events are two of the largest negatives in life. Marriage and high income, by contrast, are associated with high well-being scores. These are two of the largest positives.

To consider the case for happiness regression equations, are there good reasons why economists should use subjec- tive well-being data in formal analysis?

One is a market-based argument: people who study men- tal health and happiness for a living (psychologists) use

TABLE 1.—LIFE SATISFACTION IN EUROPE: 1975 TO 1992

Reported Life Satisfaction

All (%)

Unemployed (%)

Marital Status

Married (%)

Divorced (%)

Very satisfied 27.29 16.19 28.90 19.18 Fairly satisfied 53.72 44.70 53.85 51.80 Not very satisfied 14.19 25.52 12.98 20.90 Not at all satisfied 4.80 13.59 4.27 8.11

Reported Life Satisfaction

Sex Income Quartiles

Male (%)

Female (%)

1st (Lowest)

2nd 3rd 4th (Highest)

Very satisfied 26.81 27.75 22.80 24.98 28.07 33.07 Fairly satisfied 54.45 53.01 50.43 54.25 55.66 54.38 Not very satisfied 13.90 14.47 18.86 15.65 12.66 9.82 Not at all satisfied 4.84 4.77 7.92 5.11 3.61 2.73

Based on 271,224 observations. All numbers are expressed as percentages.

TABLE 2.—HAPPINESS IN THE UNITED STATES: 1972 TO 1994

Reported Happiness

All (%)

Unemployed (%)

Marital Status

Married (%)

Divorced (%)

Very happy 32.66 17.75 39.54 19.70 Pretty happy 55.79 52.66 52.51 61.75 Not too happy 11.55 29.59 7.95 18.55

Reported Happiness

Sex Income Quartiles

Male (%)

Female (%)

1st (Lowest)

2nd 3rd 4th (Highest)

Very happy 31.95 33.29 24.07 29.46 34.80 40.78 Pretty happy 56.33 55.31 56.04 58.02 56.22 53.14 Not too happy 11.72 11.39 19.88 12.52 8.98 6.08

Based on 26,668 observations. All numbers are expressed as percentages.

THE MACROECONOMICS OF HAPPINESS 811

such data. There are thousands of papers that do so in psychology and other social-science journals. Unless econ- omists believe they know more about human psychology than psychologists, there is a case for considering how such survey information can inform the discipline of economics. A second argument is that the data pass so-called validation exercises. For example, Pavot et al. (1991) establish exper- imentally that people who report themselves as happy tend to smile more.5 Diener (1984) shows that people who say they are happy are independently rated by those around them as happy. Konow and Earley (1999) describe other ways in which subjective well-being data have been vali- dated. Self-reported measures of well-being are also corre- lated with physiological responses and electrical readings in the brain (for example, Sutton and Davidson, 1997). An- other of the checks is that, as explained, different measures of self-reported well-being seem to exhibit high correlations with one another. Third, we regressed suicide rates on country-by-year average reported happiness, using the same panel of countries used later in the paper. We controlled for year dummies and country fixed effects, and corrected for heteroskedasticity using White’s method. Consistent with the hypothesis that well-being data contain useful informa- tion, the regression evidence revealed that higher levels of national reported well-being are associated with lower na- tional suicide rates (statistically significant at the 6% level). Last, we obtained an approximate measure of consistency by comparing the structure of happiness responses across countries.

A single individual’s answers on a well-being question- naire are unlikely to be reliable: there is no natural scaling to allow cross-person comparison of terms like “happy” or “satisfied.” However, in a well-being regression equation that uses large samples, this difficulty is less acute. In some settings, measurement error does little harm in a dependent variable (though well-being variables would be less easy to use as independent variables).

Tables 3, 4, and 5 present microeconometric well-being equations for Europe and the United States. Because of data limitations, Table 4 cannot be estimated over the full set of years.

The equations of tables 3–5 include a dummy for the year when the survey was carried out (and, in the case of the Europe-wide data, for the country where the respondent lives). Two features stand out. One is that—comparing for example table 4 with table 5—approximately the same personal characteristics are statistically associated with hap- piness in Europe and in the United States. Another, on closer examination, is that the relative sizes of the effects do not vary dramatically between the two sides of the Atlantic. For example, the consequences of employment status, of being a widow, and of income appear to be similar in the United States and Europe. The effect of unemployment is always

large: it is equivalent to dropping from the top to the bottom income quartile. Similar results obtain if we examine the individual nations within Europe (in the appendix). The regression evidence here is consistent with the idea that unemployment is a major economic source of human dis- tress [as in the psychiatric stress data of Clark and Oswald (1994)]. More generally, independent of the country where the respondent lives, the same personal characteristics ap- pear to be correlates with reported happiness. Having family income classified within a higher income quartile increases the likelihood that a respondent says he or she is satisfied with life. This effect is monotonic. To an economist, it is reminiscent of the utility function of standard economics. A strong life cycle pattern in well-being also emerges. In every country in our sample, happiness is U-shaped in age.

IV. Empirical Strategy

In order to estimate the costs of aggregate economic fluctuations, we start by evaluating the role of national5 See also Myers (1993).

TABLE 3.—LIFE SATISFACTION EQUATION FOR EUROPE, ORDERED PROBIT: 1975 TO 1992

Independent Variable Coefficient Standard

Error

Unemployed �0.505 0.020 Self-employed 0.060 0.012 Retired 0.068 0.014 Home 0.036 0.009 School 0.012 0.020 Male �0.066 0.007 Age �0.028 0.001 Age squared 3.2e�4 1.3e�5 Income quartile:

Second 0.143 0.011 Third 0.259 0.013 Fourth (highest) 0.397 0.017

Education to age: 15–18 years old 0.060 0.009 �19 years old 0.134 0.013 Still studying 0.159 0.022

Marital status: Married 0.156 0.010 Divorced �0.269 0.017 Separated �0.328 0.025 Widowed �0.145 0.013

Number of children: 1 �0.032 0.008 2 �0.042 0.010 �3 �0.094 0.016

Country: Belgium 0.498 0.051 Netherlands 0.887 0.022 Germany 0.363 0.023 Italy �0.110 0.034 Luxembourg 0.756 0.026 Denmark 1.206 0.032 Ireland 0.590 0.043 Britain 0.533 0.019 Greece �0.187 0.043 Spain 0.205 0.020 Portugal �0.234 0.037

Number of observations: 271,224. Log likelihood � �276,101. �2(50) � 10,431. Cut1 � �1.67, Cut2 � �0.80, Cut3 � 0.87. The regression includes year dummies from 1975 to 1992. The base country is France. The exact question for the dependent variable is: “On the whole, are you very satisfied, fairly satisfied, not very satisfied or not at all satisfied with the life you lead?”

Dependent variable: reported life satisfaction.

THE REVIEW OF ECONOMICS AND STATISTICS812

income per capita (GDP) in affecting individuals’ reported happiness. A fundamental issue is the potential role of reference groups, that is, the possibility that individuals care about their position relative to others in society and not just about the absolute level of income (see, for example, East- erlin, 1974; Diener, 1984; Frank, 1985; Fox & Kahneman, 1992). Hence we estimate a regression that controls for, first, the income quartile to which the respondent’s family belongs and, second, also the average income per capita in the country. A key parameter of interest is the coefficient on GDP in a happiness regression equation of the form

HAPPYjit � � GDPit � � Personaljit � εi � �t � �jit, (1)

where HAPPYjit is the well-being level reported by individ- ual j in country i in year t, and GDPit is the gross domestic product per capita in that country (measured in constant 1985 dollars). Personaljit is a vector of personal character- istics of the respondents, which include income quartile, gender, marital status, education, whether employed or

unemployed, age, and number of children.6 In some speci- fications, country-specific time trends are also added. Be- cause many of the personal variables are potentially endog- enous, a later section of the paper checks alternative econometric specifications in which only exogenous vari- ables, such as age and gender, are used as microeconomic controls. The data set does not contain the person’s income, only the quartile of the income distribution within which it lies.

We also include a country fixed effect εi and a year fixed effect �t. The first captures unchanging cultural and insti- tutional influences on reported happiness within nations, and the second any global shocks that are common to all countries in each year. The data are made up of a series of cross sections, so no individual person-specific effects can be included. The categorical nature of the data is dealt with by the use of an ordered probit model. To obtain the correct standard errors, an adjustment is made for the fact that the level of aggregation of the left-hand variable, happiness, is different than those of the right-hand macroeconomic vari- ables.7

6 An alternative two-step procedure that allows the coefficients on personal characteristics to vary across countries is explained in our working paper. Results are available upon request.

7 See Moulton (1986) for a discussion of the necessary correction to the standard errors. Although the present study uses repeated cross-sectional data on large numbers of individuals living in each country and year, for

TABLE 4.—HAPPINESS EQUATION FOR EUROPE, ORDERED PROBIT: 1975 TO 1986

Independent Variable Coefficient Standard

Error

Unemployed �0.390 0.023 Self-employed 0.038 0.016 Retired 0.060 0.020 Home 0.060 0.015 School �0.015 0.031 Male �0.067 0.013 Age �0.035 0.002 Age squared 3.6e�4 1.9e�5 Income quartile:

Second 0.131 0.014 Third 0.259 0.017 Fourth (highest) 0.378 0.019

Education to age: 15–18 years old 0.025 0.012 �19 years old 0.076 0.019

Marital status: Married 0.249 0.017 Divorced �0.291 0.027 Separated �0.398 0.040 Widowed �0.197 0.021

Number of children: 1 �0.033 0.012 2 �0.041 0.016 �3 �0.111 0.027

Country: Belgium 0.559 0.054 Netherlands 0.850 0.023 Germany 0.146 0.017 Italy �0.366 0.048 Luxembourg 0.389 0.037 Denmark 0.656 0.052 Ireland 0.548 0.053 Britain 0.360 0.027 Greece �0.467 0.058 Spain 0.132 0.028 Portugal �0.179 0.040

Number of observations � 103,990. Log likelihood � �92,127. �2(42) � 4,575. Cut1 � �1.21, Cut2 � �0.59. The regression includes year dummies from 1975 to 1992. The base country is France. The exact question for the dependent variable is: “Taking all things together, how would you say you are these days—would you say you’re very happy, fairly happy, or not too happy these days?”

Dependent variable: reported happiness.

TABLE 5.—HAPPINESS EQUATION FOR THE UNITED STATES, ORDERED PROBIT: 1972 TO 1994

Independent Variable Coefficient Standard

Error

Unemployed �0.379 0.041 Self-employed 0.074 0.023 Retired 0.036 0.031 Home 0.005 0.023 School 0.176 0.055 Other �0.227 0.067 Male �0.125 0.016 Age �0.021 0.003 Age squared 2.8e�4 3.0e�5 Income quartile:

Second 0.161 0.022 Third 0.279 0.023 Fourth (highest) 0.398 0.025

Education: High school 0.091 0.019 Associate/junior college 0.123 0.040 Bachelor’s 0.172 0.027 Graduate 0.188 0.035

Marital status: Married 0.380 0.026 Divorced �0.085 0.032 Separated �0.241 0.046 Widowed �0.191 0.037

Number of children: 1 �0.112 0.025 2 �0.074 0.024 �3 �0.119 0.024

Number of observations � 26,668. Log likelihood � �23941.869. �2(50) � 2269.64. Cut1 � �1.217, Cut2 � �0.528. The regression includes year dummies from 1972 to 1994. The exact question for the dependent variable is: “Taken all together, how would you say things are these days? Would you say you are very happy, pretty happy, or not too happy?”

Dependent variable: reported happiness.

THE MACROECONOMICS OF HAPPINESS 813

Easterlin (1974) points out that happiness data appear to be untrended over time. By contrast, nations grow richer over the years, so income per capita is trended. Hence, if happiness is a stationary variable and the equation is wrongly specified, then � in a simple regression equation is likely, for standard reasons, to be biased towards zero.8 In that case, a potential solution is to focus on the growth rate of GDP or to study macroeconomic variables measured relative to trend.

We explore this issue. The paper includes time dummies for the panel of countries, studies different lengths of lag, and experiments with a simple distributed lag structure. We also include country-specific time trends (along with the year and country fixed effects) and change-in-GDP vari- ables. These issues are not simply technical ones. The economics of the problem suggests that we should allow for the presence of adaptation effects, whereby, other things equal, high levels of income in the past might fail to produce large effects on happiness because they lead to higher aspirations and altered comparisons. This is related to a particularly important question. Does higher GDP have permanent effects on a nation’s well-being? Conventional economics assumes that it does. The inherited wisdom in this field, due to Richard Easterlin and others, is that it may not and that a concern for relative income is what could explain the untrended nature of happiness survey responses (see for example Easterlin, 1974; Blanchflower & Oswald, 1999). Another possibility is that GDP does buy extra happiness, but that other factors have gradually been wors- ening in industrial societies through the decades, and these declines have offset the benefits from extra real income. If so, it might be possible to make the idea that GDP buys happiness compatible with the fact that well-being survey data do not trend upwards. A panel approach, with country and year dummies and country-specific time trends, would then provide an appropriate testing ground. Furthermore, controlling for the income quartiles to which individuals belong to in our regressions provides some reassurance that the results on aggregate income do not just reflect concerns for relative income (with the reference group based on the whole economy).

If income per capita can be shown to affect happiness, a regression designed to value other macroeconomic influ- ences can be estimated. This has the following form:

HAPPYjit � � GDPit � � Unempit � Macroit � Personaljit � εi � �t � �jit, (2)

where Unempit is the unemployment rate in country i in year t, and Macroit is a vector of other macroeconomic variables that may influence well-being. Macroit includes Inflationit, the rate of change of consumer prices in country i and year t, and Benefitit, the generosity of the unemployment benefit system, which is here defined as the income replacement rate. To explore possible problems of simultaneity, in some equations we use only personal controls that are exogenous (such as gender and age) and study macroeconomic vari- ables measured with a time lag.

In most regression equations, this paper’s specifications include as a regressor a personal variable for whether the individual is unemployed. That enables us, because we are then controlling for the personal cost of joblessness, to test for any extra losses from recessions—including economy- wide indirect psychic losses of a kind normally ignored by economists. As the effect of the business cycle on personal unemployment is thus controlled for within the microeco- nomic regressors, a correction has to be done later, when the whole cost of a recession is being calculated, to add those personal costs back into the calculation. In other words, an increase in joblessness can affect well-being through at least two channels. One is the direct effect: some people become unhappy because they lose their jobs. The second is that, perhaps because of fear, a rise in the unemployment rate may reduce well-being even among those who are in work or looking after the home. To calculate the full losses from a recession, these two effects have to be added together.

The paper also examines the way that governments have tried to alleviate the costs of business-cycle downturns. It has often been argued that the European welfare state has allowed life to become too easy for the jobless—and thus made recessions more lasting. Structural unemployment in Europe is routinely blamed on the continent’s welfare sys- tem. To test this hypothesis in a new way, we use well-being data. The paper restricts the sample to those individuals who are either employed or unemployed (thus excluding the retired, those keeping house, and those attending school). A regression of the following form is then estimated:

HAPPYjit � � Benefitit � � MacroBit � � Personaljit

εi � �t � � Benefitit � � MacroBit

� Personaljit � �i � �t) � Dunemjit

�jit,

a review of the issues surrounding estimation using individual-level panel data with fixed effects and discrete dependent variables, see Arellano and Honore (2001).

8 Easterlin (1974) made this observation looking at U.S. data. It is not the norm, however, in our sample of 12 European countries. Life- satisfaction data exhibit an upward trend in Italy and Germany, while in Belgium they seem to have a downward trend. If anything, other European countries present a drift towards more happiness, although the effect in general is not statistically significant. For more on the specific country trends, the reader is referred to our working paper.

TABLE 6.—SUMMARY STATISTICS, 12 EUROPEAN NATIONS: 1975 TO 1992

Statistic Obs. Mean Std. Dev. Min Max

Reported life satisfaction 271,224 2.035 0.778 0 3 GDP per capita (1985

U.S.$) 190 7,809 2,560 2,145 12,415 �GDP per capita 190 244 234 �968 902 Benefit replacement rate 190 0.302 0.167 0.003 0.631 Inflation rate 190 0.079 0.056 �0.007 0.245 Unemployment rate 190 0.086 0.037 0.006 0.211

THE REVIEW OF ECONOMICS AND STATISTICS814

where Dunemjit is a dummy taking the value 1 if respondent j is unemployed and 0 otherwise. Personaljit is the same vector of personal characteristics defined above (which includes Dunemjit), and MacroBit is a vector of macroeco- nomic variables (GDP per capita, inflation rate, and unem- ployment rate). Our interest is the value of �, which is the interaction effect of benefits on the happiness gap, that is, on the difference in well-being between employed people and unemployed people.

The size of different variables’ effects on well-being is of interest. Unfortunately, there is no straightforward, intuitive way to think of what the coefficients mean in an ordered probit. However, the formula for a calculation is as follows. In our main regression equations there are three cutpoints: call them a, b, and c. If a person’s happiness score (mea- sured in utils) is equal to H, then the chance that she will declare herself “very happy” (the top category) is Prob- (“very happy”) � F(H � c), where F� is the standard cumulative normal distribution.9 If for example, H � c, then F(0) � 0.5 (or, in other words, a 50% chance). To interpret the coefficients, therefore, if a change in an ex- planatory variable leads to a change �H in one’s happiness score, the change in the probability of calling oneself “very happy” will go up by �Prob(“very happy”) � F(H �H � c) � F(H � c).

As background, table 6 sets out the means and standard deviations for the macroeconomic variables, and table 7 contains correlation coefficients.

V. The Effect of GDP on Happiness

The first hypothesis to be tested is whether macroeco- nomic movements feed through into people’s feelings of well-being. A second task is to calculate the size of any effects. In order to put a value on recessions and booms, the paper compares the marginal effect of income on happiness with the marginal effect of an unemployment upturn on happiness. In other words, it calculates the marginal rate of substitution between GDP and unemployment.

Recessions mean there are losses in real output, and higher levels of joblessness. By exploiting well-being data, it is possible to test for additional costs. We find that there

is evidence for what appear to be important psychic losses that are usually ignored in economic models.

Table 8 presents simple specifications for happiness equa- tions in which macroeconomic influences are allowed to enter. It focuses on GDP, and, for transparency, examines a variety of lag lengths. Column (1) of table 8 regresses reported well-being on the set of personal characteristics of the respondent and on the country’s current GDP per capita. The GDP variable enters with a coefficient of 1.1 and a standard error of 0.34 (where GDP here has been scaled in the regressions by a factor of 10,000). The data cover a dozen nations from 1975 to 1992. To control for country and year effects, dummies for these are included. Since we are controlling in column 1 of table 8 for the quartile to which the respondent’s family income belongs, the coefficient on GDP reflects the effect of an absolute increase in national income on individual happiness while keeping constant the relative position of the respondent. There is evidence of a positive and well-determined effect of GDP per capita on individuals’ perceived well-being. An extra $1,000 in GDP per capita (in 1985 dollars) has systematic and nonnegli- gible consequences.10 It can be shown that it raises the proportion of people in the top happiness category (“very satisfied” with their lives) by approximately 3.6 percentage points, which takes this category from 27.3% to 30.9%.11 It lowers the proportion in the bottom category (“not at all satisfied” with life) by 0.7 percentage points, from 4.8% to 4.1%.12 In these data, contemporaneous happiness and GDP are strongly correlated.

To help understand the dynamics, and to check robust- ness, columns (2) and (3) of table 8 give corresponding results when lagged levels of GDP are used. Going back one

9 More formally, a person’s happiness score is the predicted value of the underlying continuous variable from the ordered probit regression given their observed personal characteristics.

10 Value in 2001 dollars equals value in 1985 dollars multiplied by approximately 1.6. Hence we are considering a rise of $1,600 when expressed in 2001 values.

11 This is calculated as follows: the average predicted happiness score, H, for the column 1 regression equals 1.16. A $1000 rise in GDP per capita increases the predicted happiness score by �H � 0.00011 � 1000 � 0.11. The top cutpoint c � 1.84. Hence �Prob(“very satis- fied”) � F(1.16 0.11 � 1.84) � F(1.16 � 1.84) � 0.284 � 0.248 � 0.036. Similar calculations can be done to find a confidence interval for this point estimate (where one standard error below and above the GDP coefficient equals 0.8 and 1.4, respectively). The interval is (0.025, 0.048).

12 Since �Prob(“Not at all satisfied”) � F(�0.70 � (1.16 0.11)) � F(�0.70 � 1.16) � 0.024 � 0.031 � �0.007, where the bottom cutpoint a � �0.70.

TABLE 7.—CORRELATION COEFFICIENTS, 12 EUROPEAN NATIONS: 1975 TO 1992

Reported Life Satisfaction

GDP per Capita (1985 U.S.$)

�GDP per Capita

Benefit Replacement

Rate Inflation

Rate

Reported life satisfaction 1 GDP per capita (1985 U.S.$) 0.209 1 �GDP per capita 0.056 0.278 1 Benefit replacement rate 0.281 0.471 0.111 1 Inflation rate �0.161 �0.659 �0.379 �0.521 1 Unemployment rate �0.023 �0.151 0.062 �0.016 �0.230

THE MACROECONOMICS OF HAPPINESS 815

TABLE 8.—LIFE SATISFACTION AND GDP, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable (1) (2) (3) (4) (5) (6)

GDP per capita 1.094 1.220 (0.335) (0.763)

GDP per capita (�1) 0.927 0.575 (0.357) (1.283)

GDP per capita (�2) 0.640* �0.875 (0.389) (0.870)

�GDP per capita 0.953 (0.719)

�GDP per capita (�1) 1.761 (0.780)

Personal Characteristics

Unemployed �0.502 �0.503 �0.504 �0.502 �0.505 �0.504 (0.020) (0.019) (0.019) (0.020) (0.020) (0.020)

Self-employed 0.062 0.061 0.061 0.061 0.060 0.060 (0.011) (0.011) (0.012) (0.012) (0.012) (0.012)

Retired 0.068 0.068 0.068 0.068 0.067 0.068 (0.014) (0.014) (0.014) (0.014) (0.014) (0.014)

Home 0.036 0.036 0.036 0.036 0.036 0.036 (0.009) (0.009) (0.009) (0.009) (0.009) (0.009)

School 0.014 0.015 0.014 0.014 0.011 0.012 (0.020) (0.020) (0.020) (0.020) (0.020) (0.020)

Male �0.067 �0.067 �0.066 �0.067 �0.066 �0.066 (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)

Age �0.028 �0.028 �0.028 �0.028 �0.028 �0.028 (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Age squared 3.1e�4 3.1e�4 3.2e�4 3.1e�4 3.2e�4 3.1e�4 (1.3e�5) (1.3e�5) (1.3e�5) (1.3e�5) (1.3e�5) (1.3e�5)

Income quartile:

Second 0.144 0.144 0.144 0.144 0.143 0.143 (0.011) (0.011) (0.011) (0.011) (0.011) (0.011)

Third 0.261 0.260 0.260 0.261 0.259 0.260 (0.013) (0.013) (0.013) (0.013) (0.013) (0.014)

Fourth (highest) 0.398 0.398 0.398 0.397 0.397 0.397 (0.017) (0.017) (0.017) (0.017) (0.017) (0.017)

Education to age:

15–18 years old 0.061 0.061 0.061 0.061 0.061 0.061 (0.009) (0.009) (0.009) (0.009) (0.009) (0.009)

�19 years old 0.134 0.134 0.133 0.135 0.135 0.136 (0.013) (0.013) (0.013) (0.013) (0.013) (0.013)

Marital status:

Married 0.156 0.156 0.156 0.156 0.156 0.156 (0.010) (0.010) (0.010) (0.010) (0.010) (0.010)

Divorced �0.269 �0.269 �0.269 �0.269 �0.269 �0.269 (0.017) (0.017) (0.017) (0.017) (0.017) (0.017)

Separated �0.328 �0.328 �0.327 �0.329 �0.328 �0.329 (0.025) (0.025) (0.025) (0.024) (0.025) (0.024)

Widowed �0.144 �0.144 �0.144 �0.144 �0.145 �0.145 (0.013) (0.013) (0.013) (0.013) (0.013) (0.013)

THE REVIEW OF ECONOMICS AND STATISTICS816

year makes little difference: the coefficient on lagged na- tional income per capita in a well-being equation is only slightly reduced. Column (2) of table 8 thus continues to display a well-determined GDP effect. Things weaken in column (3), which goes back to a 2-year lag of GDP; but the coefficient remains positive, with a t-statistic of approxi- mately 1.7. Year dummies (not reported) enter significantly. They are trended down over the period, so some general force, common to these European nations, is acting to reduce people’s feelings of happiness. Our paper will not attempt to uncover what it might be, but this remains a potentially important topic for future research.

It might be argued that, despite the inclusion of the year dummies, the mix of an I(0) happiness variable with an I(1) GDP regressor still provides an unpersuasive estimator for the effect of national income on well-being. There seem to be two potential solutions. The first is to shift focus entirely to the growth rate in income. As an intermediate step that helps assess how restrictive this shift might be, we include in column 4 of table 8 a set of variables for GDP per capita current, lagged once and lagged twice (this is, of course, an unrestricted version of entering the level of GDP and its change). As might be expected, the GDP terms in column (4) of table 8 are then individually insignificantly different from 0. Nevertheless, solving out for the implied long-run equation, the steady-state coefficient on GDP per capita is positive and similar in absolute value (equality cannot be rejected) to the coefficient on GDP per capita in columns (1) and (2) of table 8. This point estimate is inconsistent with the idea of complete adaptation—the idea that individuals entirely adjust to their income levels after a while and only derive happiness from increases in income—although the standard errors themselves in column (4) are large.

Columns (5) and (6) turn attention to growth in national income, �GDP per capita and �GDP per capita (�1). These are defined, respectively, for one lag and two lags

[where the former measures GDP minus GDP (�1), and the latter measures GDP (�1) minus GDP (�2)]. The latter, �GDP per capita (�1), in column (6) of table 8, is positive, well defined, and economically important in size. Hence there is evidence in our data that bursts of GDP produce temporarily higher happiness. Those sympathetic to the Easterlin hypoth- esis can find support in column (6) of table 8.

Another check is to include country-specific time trends. We do this—repeating the earlier analysis of table 8 to allow an exact comparison—in table 9. Here the set of personal characteristics has been estimated in the same (one-step) way as in table 8, with extremely similar coefficients, so those personal coefficients are not reported individually in the tables. Other specification changes, such as using log GDP, do not change the main results of our paper.

The results are again supportive of the idea that increases in national income are associated with higher reported happiness. Column (1) of table 9 shows that the current GDP per capita enters with a similar coefficient into the specification without country-specific trends. However, in columns (2) and (3), lagged GDP levels are now weaker than before, with one sign reversing itself. In column (4) of table 9, all three of the GDP terms are again entered together. In this case the steady-state coefficient is poorly determined and now numerically close to 0. By contrast, in columns (5) and (6), the change-in-GDP variables work even more strongly than in table 8.

We draw the conclusion that there is evidence in these data for the existence of both level and change effects on nations’ happiness. First, consistent with standard economic theory, it appears that well-being is robustly correlated, in a variety of settings, with the current GDP. As far as we know, this is the first empirical finding of its kind. Second, re- ported well-being is also correlated with growth in GDP, and this result is consistent with adaptation theories in which the benefits of real income wear off over time.

TABLE 8.—(CONTINUED)

Independent Variable (1) (2) (3) (4) (5) (6)

Number of children:

1 �0.032 �0.032 �0.032 �0.032 �0.032 �0.032 (0.008) (0.008) (0.008) (0.008) (0.008) (0.008)

2 �0.043 �0.042 �0.042 �0.042 �0.043 �0.042 (0.010) (0.010) (0.010) (0.010) (0.010) (0.010)

�3 �0.095 �0.094 �0.094 �0.095 �0.094 �0.094 (0.016) (0.016) (0.016) (0.016) (0.016) (0.016)

Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time trends No No No No No No

Pseudo-R2 0.08 0.08 0.08 0.08 0.08 0.08 Number of observations 271,224 271,224 271,224 271,224 271,224 271,224

Standard errors in parentheses. Bold-face: significant at 5% level; *: at 10% level. Cutpoints (standard errors) are �0.70 (0.30), 0.18 (0.31), 1.84 (0.31) for reg. (1); �0.86 (0.32), 0.01 (0.32), 1.68 (0.32) for reg. (2); �1.13 (0.34), �0.26 (0.34), 1.41 (0.34) for reg. (3); �0.84 (0.34), 0.04 (0.34),

1.70 (0.34) for reg. (4); �1.65 (0.07), �0.77 (0.07), 0.89 (0.07) for reg. (5); �1.63 (0.07), �0.76 (0.07), 0.91 (0.07) for reg. (6). GDP is scaled by a factor of 10,000. Dependent variable: reported life satisfaction.

THE MACROECONOMICS OF HAPPINESS 817

Finally, lagged levels of GDP are statistically significant in certain specifications.

To go decisively beyond these conclusions, and to try to say whether it is level effects or change effects that domi- nate the data, will probably require longer runs of data than are available to us.13 Our conjecture is that there is strong adaptation, so that human beings get used to a rise in national income, but that not all of the benefits of riches dissipate over time. Hence GDP matters, even in the long run, but there are strong �GDP effects in the short run. Whether that conjecture will survive future research remains to be seen.

VI. Costs of Recessions

Having established that income is correlated with happiness, we turn to other macroeconomic variables to see if their inclusion removes the correlation between happiness and GDP. It does not. Table 10, for example, repeats the previous anal- ysis, and incorporates also the rate of unemployment, the inflation rate, and an indicator of the generosity of the welfare state. Column (1) in table 10 demonstrates that the macro variables enter with the signs that might be expected. All are statistically significant at normal confidence levels.

How costly are recessions? It can be shown that there are large losses over and above the GDP decline and rise in personal unemployment. To demonstrate this, we use a slightly unusual welfare measure.

To explore economic significance, we take as a yardstick a downturn that is equal to an increase in the unemployment

rate of 1.5 percentage points. The number 1.5 was chosen by taking the average of the eleven full business cycles in the United States since the Second World War, and dividing by 2 to get the average unemployment deviation. It is then possible to calculate, from the coefficients in column 1 of table 10, the marginal rate of substitution between GDP per capita and unemployment. Pure psychic losses can then be estimated. The ratio of the two coefficients implies that, to keep their life satisfaction constant, individuals in these economies would have to be given, on top of compensation for the direct GDP decline, extra compensation per year of approximately 200 dollars each (0.015 � 1.91/0.00014).14

Measured in 2001 dollars, that is 330. This would have to be paid to the average citizen, not just to those losing their jobs. Such a calculation makes the implicit assumption that, over the relevant range, utility is linear, so that the margin is equal to the average. This seems justifiable for normal recessions, where national income changes by only a few percent, but it might not for a major slump in which national income fell dramatically.

Column (6) in table 10 allows us to make these calcula- tions using the growth rate in GDP per capita. The estimated coefficients indicate that the average person (employed or unemployed) would experience no change in well-being if, in the event of a business downturn which increased the rate

13 As a start in this direction we included a level term in regression (5) in table 8. The coefficient on GDP per capita is 1.057 (standard error � 0.356), while that on �GDP per capita equals 0.429 (s.e. � 0.757), so in this specification the level effect dominates. Including country-specific time trends brings the coefficients closer in size and significance.

14 This number, of course, has a standard error attached. The factor 0.015 comes from the assumption that a typical economic downturn adds 1.5 percentage points to unemployment. The factor 1.91 is the coefficient on unemployment rate in table 10, column (1). The divisor 0.00014 comes from the coefficient of 1.4 on GDP in column (1) of Table 10, after rescaling back by a factor of 10,000.

TABLE 9.—LIFE SATISFACTION AND GDP, WITH COUNTRY-SPECIFIC TIME TRENDS, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable (1) (2) (3) (4) (5) (6)

GDP per capita 1.031 1.133* (0.455) (0.626)

GDP per capita (�1) 0.301 0.654 (0.500) (0.888)

GDP per capita (�2) �0.801 �1.652 (0.492) (0.716)

�GDP per capita 1.390 (0.552)

�GDP per capita (�1) 1.920 (0.620)

Personal characteristics Yes Yes Yes Yes Yes Yes Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time trends Yes Yes Yes Yes Yes Yes

Pseudo-R2 0.09 0.09 0.09 0.09 0.08 0.08 Number of observations 271,224 271,224 271,224 271,224 271,224 271,224

Standard errors in parentheses. Boldface means significant at the 5% level; *, at 10% level. Cutpoints (standard errors) are �1.37 (0.43), �0.49 (0.43), 1.18 (0.43) for reg. (1); �1.01 (0.42), �0.13 (0.42), 1.54 (0.42) for reg. (2); �0.51 (0.42), 0.37 (0.42), 2.04 (0.42) for reg. (3); �0.69 (0.40), 0.19

(0.40), 1.86 (0.41) for reg. (4); �0.96 (0.37), �0.08 (0.37), 1.59 (0.37) for reg. (5); �0.82 (0.30), 0.06 (0.30), 1.73 (0.30) for reg. (6). GDP is scaled by a factor of 10,000. Dependent variable: reported life satisfaction.

THE REVIEW OF ECONOMICS AND STATISTICS818

of unemployment by 1.5 percentage points, his/her income were to be increased by approximately 3%.15

Such calculations underestimate the full cost to society of a rise in joblessness. The reason for the underestimation is that these regressions hold constant the personal cost of being unemployed (as a microeconomic regressor). It can be calculated from column (1) in table 10 that an increase in the unemployment rate from 0% to 1.5% would have a cost in utils—for want of a better term—equal to approximately 0.029 (1.91 times 0.015). This is for the average citizen, whether employed or unemployed. On the other hand, a person who becomes unemployed experiences an actual loss (in utils) equal to 0.5. This number comes from the coeffi- cient on being unemployed in column (1) in table 10 (which is unreported but is similar to those given in table 8). The full social cost of an increase of 1.5 percentage points in the unemployment rate in well-being units is therefore the sum of two components: it is (0.5 � 0.015) (1.91 � 0.015) � 0.0075 0.029 � 0.036.16 Measured in dollars this is equal

to approximately $260 (�0.036/0.00014). For an individual who loses her job during the recession the actual loss is approximately $3,800, that is, (0.5 0.029)/0.00014.

The regressions in table 10 establish that high unemploy- ment in the economy is unpleasant even for people who are employed. One possibility is that this is some form of fear-of-unemployment effect (see for instance Blanch- flower, 1991). There may also be a—presumably fairly small—taxation effect, because if unemployment goes up, the people at large have to pay more tax to fund the increased bill for unemployment benefits. The indirect ef- fects, when added to the direct ones on those who actually lose their jobs, amount to a substantial well-being cost. This stands in contrast to the view that unemployment involves layoffs with short and relatively painless jobless spells. The ex post effect on someone who actually loses his or her job is 20 times larger than the effect on those who still have a job. The indirect fear losses are even larger, in aggregate, because they affect more people.

The large well-being cost of losing a job shows why a rise in a nation’s unemployment might frighten workers. Be- coming unemployed is much worse than is implied by the drop in income alone. The economist’s standard method of judging the disutility from being laid off focuses on pecu- niary losses. According to our calculations, that is a mistake,

15 Since 0.015 � 1.95/0.000118 � 248 dollars, which represents 3.2% of the average GDP per capita across the nations and years in the sample (�248/7809).

16 The following calculations may help clarify this. Call the total welfare in society W � (1 � u) E uV, where u is the unemployment rate and E and V are the utilities of being employed and unemployed respectively. The function E is defined over net income (because it includes taxes), inflation, and unemployment, and the function V is defined over benefits, unemployment, and inflation. Then dW/du � (1 � u) dE/du u dV/du � (E � U). The expressions dE/du and dV/du can be thought of fear-of-unemployment effects for the employed and the unemployed

respectively. The third term is the personal cost of falling unemployed. The first two terms sum to 1.91, whereas the third term equals 0.50.

TABLE 10.—LIFE SATISFACTION AND MACROECONOMIC VARIABLES, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable (1) (2) (3) (4) (5) (6)

GDP per capita 1.408 1.305* 1.132 1.020 (0.361) (0.784) (0.552) (0.668)

GDP per capita (�1) 0.576 0.628 (1.305) (0.890)

GDP per capita (�2) �0.561 �1.455 (0.842) (0.698)

�GDP per capita 0.775 1.184 (0.725) (0.583)

Benefit replacement rate 1.027 1.026 0.665 0.883 0.854 0.769 (0.219) (0.223) (0.213) (0.363) (0.359) (0.372)

Unemployment rate �1.909 �1.845 �2.703 �1.291 �1.481 �1.954 (0.664) (0.675) (0.694) (0.823) (0.722) (0.673)

Inflation rate �0.994 �0.963 �0.780 �1.042* �0.804 �0.845 (0.464) (0.480) (0.470) (0.585) (0.601) (0.600)

Personal characteristics Yes Yes Yes Yes Yes Yes Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time trends No No No Yes Yes Yes

Pseudo-R2 0.08 0.08 0.08 0.09 0.09 0.09 Number of observations 271,224 271,224 271,224 271,224 271,224 271,224

Standard errors in parentheses. Boldface means significant at the 5% level; *, at the 10% level. Cutpoints (standard errors) are �0.31 (0.34), 0.57 (0.35), 2.24 (0.35) for reg. (1); �0.41 (0.37), 0.47 (0.38), 2.14 (0.38) for reg. (2); �1.67 (0.12), �0.80 (0.12), 0.87 (0.12) for reg. (3); �2.39 (0.62), �1.51

(0.62), 0.16 (0.62) for reg. (4); �1.40 (0.61), �0.52 (0.61), 1.15 (0.61) for reg. (5); �1.54 (0.46), �0.66 (0.46), 1.01 (0.46) for reg. (6). GDP is scaled by a factor of 10,000. Dependent variable: reported life satisfaction.

THE MACROECONOMICS OF HAPPINESS 819

because it understates the full well-being costs, which, according to the data, appear to be predominantly nonpe- cuniary.

The coefficients in table 10 also allow us to put a value on the cost of inflation by comparing the marginal effect of income on happiness with the marginal effect of an inflation upturn on happiness. In other words, we can also calculate the marginal rate of substitution between GDP and inflation. Using the ratio of the two coefficients on GDP per capita and the inflation rate in column (1) implies that, to keep his/her life satisfaction constant, an individual would have to be given compensation of approximately 70 dollars (0.01 � 0.99/0.00014) for each 1-percentage-point rise in inflation.

A. Simultaneity and Other Tests

Happiness, personal characteristics, and macroeconomic variables might be simultaneously determined. It is hard to think of a convincing instrument in such a setting. A full treatment of these issues will have to be left for future research and different data sets. Some reassurance in this respect can be obtained by running regressions where only

truly exogenous personal characteristics are included, such as age and gender, and where all macroeconomic variables are entered with a lag. Table 11 checks the outcome. The substantive conclusions remain the same as in earlier ta- bles.17

Another interesting issue is how well-being in a country is affected by the amount of inequality. Assume utility functions are concave. Then it might be thought that in- equality must automatically reduce the average level of happiness. We hope to tackle this issue properly in future work, but one test was done on these data. Provided that income inequality depends negatively on welfare generosity (and we would expect that government help for the poorest would reduce inequality), higher unemployment benefits in a society should raise the happiness of lower-income people relative to higher-income people. Given concavity, the poor dislike their relative position more than rich people like

17 We also experimented with regressions that included several lagged changes in GDP per capita. In a specification that adds the second lagged change in GDP to the specification in column (6) in Table 11, the coefficient on �GDP per capita (�1) equals 1.734 (s.e. � 0.575), and the coefficient on �GDP per capita (�2) equals 0.238 (s.e. � 0.574).

TABLE 11.—LIFE-SATISFACTION REGRESSIONS AND EXOGENEITY, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable (1) (2) (3) (4) (5) (6)

GDP per capita (�1) 1.275 2.315 0.521 1.518 (0.361) (0.826) (0.503) (0.680)

GDP per capita (�2) �2.025 �1.471 (1.357) (0.957)

GDP per capita (�3) 0.987 �0.421 (0.805) (0.606)

�GDP per capita (�1) 1.608 1.771 (0.713) (0.549)

Benefit replacement rate (�1) 0.907 0.911 0.592 1.238 1.249 1.254 (0.235) (0.235) (0.217) (0.375) (0.384) (0.389)

Unemployment rate (�1) �1.659 �1.765 �2.426 �0.929 �1.314 �1.188* (0.726) (0.688) (0.709) (0.746) (0.703) (0.637)

Inflation rate (�1) �0.718 �0.712 �0.550* �0.633* �0.417 �0.464 (0.313) (0.333) (0.322) (0.375) (0.372) (0.360)

Personal Characteristics

Male �0.019 �0.019 �0.019 �0.018 �0.019 �0.019 (0.007) (0.007) (0.007) (0.007) (0.007) (0.007)

Age �0.014 �0.014 �0.014 �0.014 �0.014 �0.014 (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)

Age squared 1.4e�4 1.4e�4 1.4e�4 1.4e�4 1.4e�4 1.4e�4 (1.2e�5) (1.2e�5) (1.2e�5) (1.2e�5) (1.1e�5) (1.2e�5)

Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time trends No No No Yes Yes Yes

Pseudo-R2 0.06 0.06 0.06 0.06 0.07 0.07 Number of observations 271,224 271,224 271,224 271,224 271,224 271,224

Standard errors in parentheses. Boldface means significant at the 5% level; *, at the 10% level. Cutpoints (standard errors) are �0.48 (0.36), 0.36 (0.36), 1.98 (0.37) for reg. (1); �0.48 (0.38), 0.36 (0.39), 1.99 (0.39) for reg. (2); �1.69 (0.10), �0.85 (0.10), 0.77 (0.10) for reg. (3); �2.41 (0.53), �1.56

(0.53), 0.06 (0.53) for reg. (4); �1.70 (0.55), �0.85 (0.55), 0.77 (0.55) for reg. (5); �2.19 (0.36), �1.34 (0.37), 0.28 (0.37) for reg. (6). GDP is scaled by a factor of 10,000. Dependent variable: reported life satisfaction.

THE REVIEW OF ECONOMICS AND STATISTICS820

their own. As a test, therefore, we repeated all the regression specifications reported in the earlier table 4 but also in- cluded interactions of our measure of benefit generosity with each of the income quartiles. As expected, the results show a significantly positive differential effect (at the 5% level) of benefits on the happiness of the poor relative to the rich.

VII. Happiness Evidence on the Role of the Welfare State

Tables 10 and 11 show that the coefficient on benefits, our indicator of the generosity of publicly provided unemploy- ment insurance, is positively correlated with happiness levels and is well defined statistically. Column (1) in table 10 implies that individuals who live in a country such as Ireland, where the replacement rate averaged 0.28 over the sample period, would be willing to pay 214 dollars (U.S. 1985) to live in a country with a more generous welfare state such as France, where the replacement rate averaged 0.31.18 In terms of table 10’s column (6), which includes country-specific time trends and has a well-defined coefficient on �GDP per capita, people seem to be willing to forgo growth rates of 2.5% in order to see an improvement in the summary measure of the parameters of the unemployment benefit system from the Irish level to the French level. Such numbers should, however, probably be thought of as upper bounds on the correct esti- mates, because the regressions cannot adjust for the need in an improved welfare state for higher taxes. It is worth recalling,

however, that there are potential identification problems in all macroeconomic analysis of this kind. We require the social safety net here to be uncorrelated with omitted variables in the happiness equation.19

Besides providing a way to assess the returns from a welfare state, this paper’s approach can be used to shed light on the validity of one criticism of European-style welfare states. A number of economists have argued that generous welfare provision has made life too easy for the unemployed, leading to poor labor market performance in a number of European countries. The average OECD-calculated benefit replacement rate across the sample of countries rose from 0.31 to 0.35 over the period of our data. The strictness with which benefit rules were enforced, moreover, is believed by some observers to have diminished.

We first approach this problem by partitioning the sample into employed and unemployed workers, and estimating a similar set of regressions to those presented in table 10. Columns (1) and (2) in table 12 show that happiness and benefits are positively correlated for both the unemployed and the employed subsample. Moreover, the two coeffi- cients on the benefits variable, 1.25 and 1.44, are similar. Hence an increase in the generosity of unemployment ben- efits helps the well-being of the unemployed and employed by a similar amount (perhaps because the employed know they may in the future lose their jobs, and the jobless know

18 Since (0.31 � 0.28) � 1.0/0.00014 � 214 dollars.

19 The literature that can be used as a guide in the search for instruments in this context is small. Di Tella and MacCulloch (1996a) presents some theory and evidence behind the determination of unemployment benefits. See also the voting model of Wright (1986).

TABLE 12.—LIFE SATISFACTION OF THE EMPLOYED AND UNEMPLOYED AND THE WELL-BEING GAP, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable Employed Unemployed Gap Employed Unemployed Gap

(1) (2) (3) (4) (5) (6)

GDP per capita 1.418 1.053* 0.208 (0.439) (0.614) (0.714)

�GDP per capita 1.028 0.991 0.084 (0.853) (1.110) (1.249)

Benefit replacement rate 1.248 1.438 �0.385 0.910 1.227 �0.480 (0.268) (0.408) (0.510) (0.247) (0.395) (0.497)

Unemployment rate �1.660 �3.046 1.788 �2.486 �3.573 1.573 (0.747) (1.096) (1.256) (0.778) (1.033) (1.177)

Inflation rate �1.388 �1.602 0.422 �1.117 �1.551* 0.634 (0.508) (0.809) (0.836) (0.506) (0.857) (0.871)

Personal characteristics Yes Yes Yes Yes Yes Yes Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time trends No No No No No No

Pseudo-R2 0.09 0.06 0.10 0.09 0.06 0.09 Number of observations 136,570 12,493 149,063 136,570 12,493 149,063

Standard errors in parentheses. Boldface means significant at the 5% level; *, at the 10% level. Cutpoints (standard errors) are �0.27 (0.42), 0.63 (0.43), 2.38 (0.43) for reg. (1); �0.58 (0.65), 0.31 (0.65), 1.70 (0.65) for reg. (2); �0.33 (0.42), 0.56 (0.42), 2.28 (0.43) for reg. (3); �1.71 (0.13), �0.81 (0.13),

0.94 (0.13) for reg. (4); �1.58 (0.23), �0.69 (0.23), 0.70 (0.23) for reg. (5); �1.69 (0.13), �0.80 (0.13), 0.92 (0.13) for reg. (6). GDP is scaled by a factor of 10,000. The gap equations are derived by combining the samples of employed and unemployed people, and then estimating a life satisfaction equation in which, as well as the usual microeconomic regressors, a set of

interaction terms are included. These interact a dummy for being unemployed with each of the independent variables. The reported coefficients, in columns (3) and (6), are the coefficients on those interaction terms. Dependent variable: reported life satisfaction.

THE MACROECONOMICS OF HAPPINESS 821

they may find a job). More formally, column (3) of table 12, which estimates the difference in the corresponding coeffi- cient estimate across the two subsamples, is a test of the hypothesis that the welfare state made life too easy for the unemployed (at least relative to the employed). That hypothe- sis is not supported by the data. The reason is that the benefits variable enters the gap equation—where the gap can be thought of as the difference in well-being between those with jobs and those looking for a job—with a coefficient that is

insignificantly different from zero. Table 13 redoes the equa- tions to check for robustness to country-specific time trends.

Further evidence comes from direct examination of the data on the life satisfaction of employed and unemployed Europeans. Figures 1 and 2 plot the raw numbers. As figure 1 shows, there is no marked rise over time in the happiness of the jobless compared to those in jobs. The two series run roughly together over the years. Figure 2, which is a plot of the gap itself, in fact reveals a slight widening of the difference

TABLE 13.—LIFE-SATISFACTION REGRESSIONS BY EMPLOYMENT STATUS, WITH COUNTRY-SPECIFIC TIME TRENDS, ORDERED PROBIT REGRESSIONS, EUROPE: 1975 TO 1992

Independent Variable Employed Unemployed Gap Employed Unemployed Gap

(1) (2) (3) (4) (5) (6)

GDP per capita 1.394 2.473 �0.133 (0.642) (0.911) (0.999)

�GDP per capita 1.463 1.592 �0.294 (0.708) (1.061) (1.213)

Benefit replacement rate 1.068 1.403 �0.477 0.915 1.061 �0.253 (0.443) (0.536) (0.728) (0.442) (0.539) (0.719)

Unemployment rate �0.858 �2.233* 1.683 �1.709 �4.093 2.880 (0.969) (1.248) (1.415) (0.785) (1.058) (1.210)

Inflation rate �1.540 �1.498* 0.162 �1.295 �1.096 �0.035 (0.642) (0.845) (0.718) (0.658) (0.880) (0.746)

Personal characteristics Yes Yes Yes Yes Yes Yes Country fixed effects Yes Yes Yes Yes Yes Yes Year fixed effects Yes Yes Yes Yes Yes Yes Country-specific time Yes Yes Yes Yes Yes Yes

Pseudo-R2 0.09 0.06 0.10 0.09 0.06 0.10 Number of observations 136,570 12,493 149,063 136,570 12,493 149,063

Standard errors in parentheses. Boldface means significant at the 5% level; *, at 10% level. Cutpoints (standard errors) are �2.76 (0.69), �1.86 (0.69), �0.11 (0.69) for reg. (1); �3.53 (1.15), �2.63 (1.15), �1.24 (1.15) for reg. (2); �2.73 (0.68), �1.84 (0.68), �0.12 (0.68) for reg. (3); �1.70 (0.48),

�0.80 (0.48), 0.95 (0.48) for reg. (4); �1.61 (1.06), �0.72 (1.07), 0.67 (1.07) for reg. (5); �1.68 (0.48), �0.79 (0.48), 0.93 (0.48) for reg. (6). GDP is scaled by a factor of 10,000. Dependent variable: reported life satisfaction.

FIGURE 1.—AVERAGE LIFE SATISFACTION OF EMPLOYED AND UNEMPLOYED EUROPEANS

Based on a random sample of 271,224 individuals. The numbers are on a scale where the lowest level of satisfaction is 1 and the highest 4.

THE REVIEW OF ECONOMICS AND STATISTICS822

in well-being levels (though it is not statistically significant) between the two groups. These life-satisfaction data seem to paint a clear picture. It has not become easier and less unpleas- ant, over this period, to be out of work in Europe.

VIII. Conclusions

This paper shows that macroeconomic movements have strong effects on the happiness of nations. It also suggests a new way to measure the costs of business cycle downturns.

We use psychological well-being data on a quarter of a million people across twelve European countries and the United States. The data come in the form of answers to questions such as “How happy are you?” or “How satisfied are you with life as a whole?” Ordered probit equations are estimated. Differences in people’s use of language are viewed as a component of the error term. Using normal regression techniques, the paper starts by showing that happiness data have a stable structure. Microeconometric well-being equations take the same general form in 12 European countries and the United States. An estimated happiness equation is increasing in income—like the econ- omist’s traditional utility function.

Macroeconomics matters. People’s happiness answers en masse are strongly correlated with movements in current and lagged GDP per capita. This is the main finding of the paper.

An important conceptual issue is whether improvements in national income lead to permanent or only temporary gains in national happiness. In other words, is it the level or change in GDP that influences well-being? After an exam- ination of a range of specifications, we conclude that there is statistical support for both kinds of channel. The persua- sive evidence for a change-in-GDP effect upon a country’s happiness is consistent with theories of adaptation. It seems likely, therefore, that some of the well-being gains from extra national income wear off over time. Our conjecture is that there

are strong habituation effects, so that human beings get used to a rise in national income, but that not all of the benefits of riches dissipate over time. Future research, with longer runs of data, will have to revisit that conjecture.20

Losses from recessions are large. It is not just that GDP drops and that some citizens lose their jobs. On top of those costs to society, and after controlling for personal charac- teristics of the respondents, year dummies, and country fixed effects, we estimate that individuals would need 200 extra dollars of annual income to compensate for a typical U.S.-size recession. In our sample, $200 is approximately 3% of per capita GDP. This loss is over and above the actual fall in income in a recession. One potential interpretation is that, in an economic downturn, people suffer a fear-of- unemployment effect.21 For those actually becoming unem- ployed, moreover, we conclude that falling unemployed is as bad as losing approximately 3,800 dollars of income a year. Standard economics tends to ignore what appear to be important psychic costs of recessions.

The methods developed in the paper have other applica- tions. Economists who analyze high European unemploy- ment, for example, often claim that the problem lies with a growing generosity of the welfare state in these countries: benefits have made life too easy for the unemployed. Using well-being data, the paper tests this hypothesis. It does not find evidence to support it.

There are likely to be other ways in which macroeconomics can harness the kind of subjective well-being data studied here.

20 This means that some explanation will have to be found for the negative trend in year dummies in the happiness equations estimated here.

21 Strictly speaking, our specifications imply that even unemployed people suffer a psychic or fear cost as the unemployment rate rises. One possible interpretation is that a higher unemployment rate makes a jobless person feel he or she is less likely to find work quickly.

FIGURE 2.—THE LIFE SATISFACTION GAP BETWEEN EMPLOYED AND UNEMPLOYED EUROPEANS WITH TREND LINE ADDED

Based on a random sample of 271,224 individuals.

THE MACROECONOMICS OF HAPPINESS 823

REFERENCES

Alesina, Alberto, Rafael Di Tella, and Robert MacCulloch, “Happiness and Inequality: Are Europeans and Americans Different?” NBER working paper no. 8198 (2001). Forthcoming in Journal of Public Economics.

Alvarez, Fernando, and Urban Jermann, “Using Asset Prices to Estimate the Costs of Business Cycles,” University of Chicago mimeograph (1999).

Arellano, M., and Honore, B., “Panel Data Models: Some Recent Devel- opments” in Handbook of Econometrics, J. Heckman and E. Learner (Eds.), Vol. 5 (2001).

Atkeson, Andrew, and Christopher Phelan, “Reconsidering the Costs of Business Cycles with Incomplete Markets,” in Stanley Fischer and Julio Rotemberg (Eds.), NBER Macroeconomics Annual, MIT Press (1994).

Blanchflower, David G., “Fear, Unemployment and Wage Flexibility,” Economic Journal, 101 (1991), 483–496.

Blanchflower, David G., and Andrew J. Oswald, “Well-Being over Time in Britain and the USA,” forthcoming in the Journal of Public Economics (1999).

Boeri, T., A. Borsch-Supan, and G. Tabellini, “Would You Like to Shrink the Welfare State? Opinions of European Citizens,” Economic Policy, 16 (April 2001).

Clark, Andrew, and Andrew J. Oswald, “Unhappiness and Unemploy- ment,” Economic Journal, 104 (1994), 648–659.

Diener, Edward, “Subjective Well-Being,” Psychological Bulletin, 93 (1984), 542–575.

Di Tella, Rafael, Robert MacCulloch, and Andrew J. Oswald, “Preferences over Inflation and Unemployment: Evidence from Happiness Sur- veys,” American Economic Review, 91:1 (2001), 335–342.

Di Tella, Rafael, and Robert MacCulloch, “The Determination of Unem- ployment Benefits,” Journal of Labor Economics 20:2 (2002), 404–434. “An Empirical Study of Unemployment Benefit Preferences,” IES

Working Paper N 179, Oxford University (February 1996b). “Partisan Social Happiness,” Harvard University mimeograph (1999).

Easterlin, Richard, “Does Economic Growth Improve the Human Lot? Some Empirical Evidence,” In P. A. David and M. W. Reder (Eds.), Nations and Households in Economic Growth: Essays in Honour of Moses Abramovitz (New York and London: Academic Press, 1974).

“Will Raising the Incomes of All Increase the Happiness of All?” Journal of Economic Behaviour and Organization, 27:1 (1995), 35–48.

Gardner, Jonathan, and Andrew Oswald, “Does Money Buy Happiness? A Longitudinal Study Using Data on Windfalls,” Warwick University mimeograph (2001).

Gruber, J., and Mellainathan, S., “Do Cigarette Taxes Make Smokers Happier?”, NBER working paper no. 8872 (2002).

Fox, C., and Daniel Kahneman, “Correlations, Causes and Heuristics in Surveys of Life Satisfaction,” Social Indicators Research, 27 (1992), 221–234.

Frank, Robert H., Choosing the Right Pond, New York and Oxford: Oxford University Press (1985).

Frey, Bruno S., and F. Schneider, “An Empirical Study of Politico- Economic Interaction in the US,” Review of Economics and Sta- tistics, 60:2 (1978), 174–183.

Frey, Bruno S., and Alois, Stutzer, “Happiness, Economy and Institu- tions,” Economic Journal, 110 (2000), 918–938.

“What Can Economists Learn from Happiness Research?” Jour- nal of Economic Literature, XL:2 (2002), 402–436.

Inglehart, Ronald, Culture Shift in Advanced Industrial Society (Princeton: Princeton University Press, 1990).

Kahneman, Daniel, and Richard Thaler, “Economic Analysis and the Psychology of Utility: Applications to Compensation Policy,” American Economic Review, 81:2 (1991), 341–346.

Kahneman, Daniel, Peter Wakker, and Rakesh Sarin, “Back to Bentham? Explorations of Experienced Utility,” Quarterly Journal of Eco- nomics, 112 (1997), 375–406.

Konow, J., and J. Earley, “The Hedonistic Paradox: Is Homo-Economicus Happier?” Loyola Marymount University mimeograph (1999).

Lucas, Robert E., Jr., Models of Business Cycles (New York: Basil Blackwell, 1987).

Luttmer, Erzo F. P., “Group Loyalty and the Taste for Redistribution,” Journal of Political Economy, 3:109 (2001), 500–528.

MacCulloch, Robert, “The Taste for Revolt,” Economics Letters (forthcoming).

Moulton, Brent R., “Random Group Effects and the Precision of Regres- sion Estimates,” Journal of Econometrics, 32 (1986), 385–397.

Myers, David, The Pursuit of Happiness (London: Aquarian, 1993). Ng, Yew-Kwang, “Happiness Surveys: Some Comparability Issues and an

Exploratory Survey Based on Just Perceivable Increments,” Social Indicators Research, 38 (1996), 1–27.

“A Case for Happiness, Cardinalism, and Interpersonal Compa- rability,” Economic Journal, 107 (1997), 1848–1858.

OECD, Jobs Study, Energy Balances of OECD Countries, Historical Statistics (Paris: OECD, 1994).

OECD, National Accounts of OECD Countries—Main Aggregates (Paris: OECD, 1997).

Oswald, Andrew J., “Happiness and Economic Performance,” Economic Journal, 107 (1997), 1815–1831.

Pavot, W., E. Diener, R. Colvin, and E. Sandvik, “Further Validation of the Satisfaction with Life Scale: Evidence for the Cross-Method Con- vergence of Well-Being Measures,” Journal of Personality Assess- ment, 57 (1991), 149–161.

Rabin, Matthew, “Psychology and Economics,” Journal of Economic Literature, 36 (1998), 11–46.

Shiller, Robert, “Why Do People Dislike Inflation?” NBER working paper no. 5539 (1996).

Sutton, S., and R. Davidson, “Prefrontal Brain Symmetry,” Psychological Science, 8:3 (1997), 204–210.

van Praag, B., and Frijters, P., “The Measurement of Welfare and Well- Being; the Leyden Approach,” in D. Kahneman, E. Diener, and N. Schwarz (Eds.), Well-being: The foundations of hedonic psychol- ogy. New York: Russell Sage Foundation (1999).

Winkelmann, Liliana, and Rainer Winkelmann, “Why Are the Unem- ployed So Unhappy?” Economica, 65:257 (1998), 1–15.

Wright, R., “The Redistributive Roles of Unemployment Insurance and the Dynamics of Voting,” Journal of Public Economics, 31 (1986), 377–399.

APPENDIX

1. Tables

TABLE A1.—LIFE-SATISFACTION EQUATIONS IN EUROPEAN NATIONS (ORDERED PROBITS), 1975 TO 1992

Independent Variable U.K. France Germany Italy

Unemployed �0.591 �0.258 �0.421 �0.538 (0.035) (0.028) (0.036) (0.033)

Self-employed 0.034 0.122 0.023 0.065 (0.029) (0.026) (0.029) (0.021)

Retired 0.113 0.351 0.079 0.057 (0.027) (0.030) (0.027) (0.027)

Home �3.5e�4 0.149 0.024 0.010 (0.022) (0.022) (0.022) (0.022)

School 0.051 0.245 0.027 0.031 (0.046) (0.034) (0.033) (0.031)

Male �0.104 �0.060 �0.029 0.012 (0.017) (0.015) (0.016) (0.016)

Age �0.027 �0.026 �0.008 �0.032 (0.003) (0.003) (0.003) (0.003)

Age squared 3.3e�4 3.0e�4 1.2e�4 3.2e�4 (2.9e�5) (3.0e�5) (2.9e�5) (2.9e�5)

Income quartiles: Second 0.225 0.213 0.186 0.184

(0.023) (0.020) (0.020) (0.019)

Third 0.368 0.371 0.319 0.297 (0.024) (0.021) (0.021) (0.020)

Fourth (highest) 0.561 0.580 0.452 0.392 (0.026) (0.023) (0.022) (0.021)

Education to age: 15–18 years old 0.035 0.117 0.001 0.044

(0.021) (0.018) (0.018) (0.019)

�19 years old 0.116 0.243 0.110 0.055 (0.028) (0.021) (0.023) (0.020)

THE REVIEW OF ECONOMICS AND STATISTICS824

TABLE A1.—(CONTINUED)

Independent Variable U.K. France Germany Italy

Marital status: Married 0.153 0.043 0.154 0.210

(0.023) (0.022) (0.023) (0.021)

Divorced �0.281 �0.179 �0.330 �0.235 (0.042) (0.043) (0.037) (0.086)

Separated �0.347 �0.241 �0.408 �0.250 (0.063) (0.069) (0.076) (0.065)

Widowed �0.114 �0.175 �0.078 �0.069 (0.034) (0.036) (0.033) (0.033)

Number of children: 1 �0.101 �0.079 �0.014 �4.27e�4

(0.022) (0.019) (0.021) (0.018)

2 �0.128 �0.075 �0.027 �0.004 (0.024) (0.023) (0.028) (0.025)

�3 �0.199 �0.169 �0.046 �0.071 (0.037) (0.033) (0.049) (0.048)

Observations 25,565 28,841 28,151 29,263

Cut1 �1.853 �1.636 �1.944 �1.493 (0.071) (0.069) (0.071) (0.066)

Cut2 �1.087 �0.715 �0.850 �0.511 (0.070) (0.069) (0.069) (0.066)

Cut3 0.556 1.136 1.086 1.206 (0.070) (0.069) (0.070) (0.066)

Log likelihood �25968 �29619 �25881 �31872

Belgium Netherlands Denmark Luxembourg

Unemployed �0.354 �0.532 �0.444 �0.915 (0.030) (0.032) (0.035) (0.135)

Self-employed �4.1e�4 0.052 0.012 0.015 (0.028) (0.033) (0.030) (0.052)

Retired 0.051 0.101 �0.084 7.84e5 (0.030) (0.032) (0.032) (0.053)

Home 0.073 0.015 0.009 0.071 (0.024) (0.023) (0.034) (0.044)

School 0.003 �0.011 0.039 0.034 (0.037) (0.035) (0.033) (0.068)

Male �0.045 �0.187 �0.133 �0.083 (0.017) (0.019) (0.016) (0.034)

Age �0.023 �0.041 �0.029 �0.028 (0.003) (0.003) (0.003) (0.005)

Age squared 2.4e�4 4.5e�4 3.5e�4 3.6e�4 (2.9e�5) (3.2e�5) (3.1e�5) (5.9e�5)

Income quartiles: Second 0.131 0.124 0.097 0.236

(0.022) (0.021) (0.024) (0.038)

Third 0.262 0.281 0.260 0.395 (0.024) (0.022) (0.027) (0.040)

Fourth (highest) 0.370 0.459 0.433 0.452 (0.026) (0.023) (0.028) (0.041)

Education to age: 15–18 years old 0.045 0.071 0.059 0.016

(0.019) (0.020) (0.021) (0.039)

�19 years old 0.092 0.064 0.091 0.050 (0.023) (0.023) (0.023) (0.047)

TABLE A1.—(CONTINUED)

Independent Variable Belgium Netherlands Denmark Luxembourg

Marital status: Married 0.085 0.169 0.147 0.161

(0.024) (0.024) (0.023) (0.042)

Divorced �0.340 �0.404 �0.186 �0.190 (0.047) (0.044) (0.040) (0.086)

Separated �0.286 �0.670 �0.249 �0.312 (0.053) (0.113) (0.079) (0.125)

Widowed �0.233 �0.266 �0.120 �0.188 (0.036) (0.039) (0.036) (0.066)

Number of children: 1 �0.043 �0.026 �0.042 0.040

(0.021) (0.022) (0.022) (0.038)

2 �0.020 �0.041 �0.034 �0.058 (0.027) (0.023) (0.027) (0.051)

�3 0.004 �0.080 �0.123 0.036 (0.041) (0.038) (0.050) (0.087)

Observations 25,304 28,118 26,738 8,051

Cut1 �2.350 �2.802 �2.686 �2.073 (0.084) (0.080) (0.078) (0.135)

Cut2 �1.511 �1.972 �1.870 �1.227 (0.083) (0.078) (0.074) (0.131)

Cut3 0.190 �0.199 �0.259 0.504 (0.082) (0.077) (0.073) (0.131)

Log likelihood �25233 �24879 �22179 �7460

Ireland Spain Portugal Greece

Unemployed �0.607 �0.406 �0.502 �0.280 (0.032) (0.047) (0.062) (0.049)

Self-employed 0.094 0.081 0.128 0.027 (0.026) (0.039) (0.034) (0.023)

Retired 0.089 0.153 0.007 0.092 (0.039) (0.043) (0.043) (0.033)

Home �0.045 0.082 �0.021 0.130 (0.028) (0.037) (0.035) (0.027)

School 0.012 0.022 0.116 0.089 (0.050) (0.049) (0.051) (0.039)

Male �0.164 0.012 �0.040 �0.007 (0.023) (0.028) (0.024) (0.020)

Age �0.024 �0.037 �0.034 �0.026 (0.003) (0.004) (0.004) (0.003)

Age squared 3.4e�4 3.8e�4 3.5e�4 2.8e�4 (3.5e�5) (4.0e�5) (4.2e�4) (3.2e�5)

Income quartiles: Second 0.129 0.132 0.126 0.197

(0.024) (0.032) (0.033) (0.022)

Third 0.248 0.244 0.213 0.318 (0.025) (0.033) (0.034) (0.024)

Fourth (highest) 0.485 0.355 0.414 0.490 (0.027) (0.036) (0.036) (0.025)

Education to age: 15–18 years old 0.126 �0.024 0.055 0.105

(0.020) (0.031) (0.032) (0.021)

�19 years old 0.204 0.021 �0.002 0.155 (0.030) (0.032) (0.032) (0.024)

THE MACROECONOMICS OF HAPPINESS 825

2. Data Sources

2.a The United States General Social Survey (1972–1994)

The General Social Surveys have been conducted by the National Research Center at the University of Chicago since 1972. Interviews have been undertaken during February, March, and April of 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1980, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1993, and 1994. There were no surveys in 1979, 1981, and 1992. There were a total of 32,380 completed interviews (1,613 in 1972, 1,504 in 1973, 1,484 in 1974, 1,490 in 1975, 1,499 in 1976, 1,530 in 1977, 1,532 in 1978, 1,468 in 1980, 1,506 in 1982, 354 in 1982 black oversample, 1,599 in 1983, 1,473 in 1984, 1,534 in 1985, 1,470 in 1986, 1,466 in 1987, 353 in 1987 black oversample, 1,481 in 1988, 1,537 in 1989, 1,372 in 1990, 1,517 in 1991, 1,606 in 1993, and 2,992 in 1994).

2.b The Euro-Barometer Survey Series (1975–1992)

The Euro-Barometer Surveys were conducted by various research firms operated within the European Community (E.C.) countries under the direction of the European Commission. Either a nationwide multistage probability sample or a nationwide stratified quota sample of persons aged 15 and over was selected in each of the E.C. countries. The cumulative data file used contains 36 attitudinal, 21 demographic, and 10 analysis variables selected from the Euro-Barometers, 3–38. Data for Belgium, France, Germany, Ire- land, Italy, Luxembourg, Netherlands, and the United Kingdom were avail- able for the full sample period (1975–1992), whereas data were only available from 1981 to 1992 for Greece and from 1985 to 1992 for both Spain and Portugal.

3. Data Definitions

● Reported life satisfaction: The answer to the Euro-Barometer Sur- vey question that asks, “On the whole, are you very satisfied, fairly

TABLE A2.—MEANS AND STANDARD DEVIATIONS FOR EUROPEAN LIFE SATISFACTION REGRESSION, 1975 TO 1992

Variable Mean Standard Deviation

Dependent variable: Reported life satisfaction 2.035 0.778

Independent variables: Unemployed 0.046 0.210 Self-employed 0.098 0.298 Retired 0.167 0.373 Home 0.211 0.408 School 0.072 0.258 Male 0.471 0.499 Age 43.4 17.6 Age squared 2192 1662 Income quartiles:

Second 0.248 0.432 Third 0.256 0.436 Fourth (highest) 0.253 0.435

Education to age: 15–18 years old 0.390 0.488 �19 years old 0.203 0.402

Marital status: Married 0.630 0.483 Divorced 0.026 0.159 Separated 0.010 0.100 Widowed 0.082 0.274

Number of children: 1 0.156 0.362 2 0.099 0.299 �3 0.039 0.193

Based on 271,224 observations.

TABLE A3.—MEANS AND STANDARD DEVIATIONS FOR THE U.S. HAPPINESS REGRESSION, 1972 TO 1994

Variable Mean Standard Deviation

Dependent variable: Reported happiness 2.211 0.631

Independent variables: Unemployed 0.032 0.175 Self-employed 0.112 0.316 Retired 0.119 0.323 Home 0.164 0.370 School 0.018 0.132 Other 0.011 0.106 Male 0.471 0.499 Age 44.7 16.9 Age squared 2280 1674 Income quartiles:

Second 0.240 0.427 Third 0.266 0.442 Fourth (highest) 0.266 0.442

Education: High school 0.523 0.500 Associate/junior college 0.040 0.196 Bachelor’s 0.129 0.335 Graduate 0.058 0.233

Marital status: Married 0.612 0.487 Divorced 0.104 0.305 Separated 0.033 0.178 Widowed 0.090 0.286

Number of children: 1 0.158 0.365 2 0.244 0.430 �3 0.329 0.470

Based on 26,668 observations.

TABLE A1.—(CONTINUED)

Independent Variable Ireland Spain Portugal Greece

Marital status: Married 0.114 0.114 �0.008 0.169

(0.023) (0.034) (0.034) (0.027)

Divorced �0.072 �0.055 �0.246 �0.183 (0.257) (0.150) (0.092) (0.073)

Separated �0.535 �0.075 �0.334 �0.374 (0.079) (0.100) (0.116) (0.147)

Widowed �0.142 �0.157 �0.222 �0.126 (0.038) (0.051) (0.052) (0.043)

Number of children: 1 �0.051 0.003 �0.037 �2.63e�4

(0.025) (0.030) (0.027) (0.022)

2 �0.070 �0.014 �0.052 �0.001 (0.026) (0.036) (0.036) (0.026)

�3 �0.104 �0.053 �0.157 0.080 (0.025) (0.055) (0.059) (0.053)

Observations 20,075 10,973 12,497 20,003

Cut1 �2.103 �2.012 �1.803 �1.108 (0.080) (0.103) (0.096) (0.084)

Cut2 �1.423 �0.963 �0.819 �0.314 (0.079) (0.102) (0.096) (0.084)

Cut3 0.102 0.479 1.316 1.004 (0.078) (0.102) (0.096) (0.084)

Log likelihood �21029 �12324 �12082 �24879

The regressions include country dummies and year dummies from 1975 to 1992. Dependent variable: reported life satisfaction.

THE REVIEW OF ECONOMICS AND STATISTICS826

satisfied, not very satisfied or not at all satisfied with the life you lead?” (The small “Don’t know” and “No answer” categories are not studied here.)

● Reported happiness: The answer to the U.S. General Social Survey and Euro-Barometer questions that ask, “Taken all together, how would you say things are these days—would you say that you are very happy, pretty happy, or not too happy?” (The small “Don’t know” and “No answer” categories are not studied here.)

● Benefit replacement rate: The OECD index of (pretax) replacement rates (unemployment benefit entitlements divided by the corresponding wage). It attempts to capture the situation of a representative or average individual. Consequently, the unweighted mean of 18 numbers based on the following scenarios is determined: (1) three unemployment durations (for persons with a long record of previous employment); the first year, the second and third years, and the fourth and fifth years of

employment; (2) three family and income situations: a single person, a married person with a dependent spouse, and a married person with a spouse in work; and (3) two different levels of previous earnings: average and two-thirds of average earnings [for further details see the OECD Jobs Study (OECD, 1994)]. Since this index was calculated only for odd-numbered years, for even-numbered years we made a linear interpolation.

● Unemployment rate: The standardized unemployment rate from the CEP OECD data set.

● Inflation rate: The inflation rate as measured by the rate of change in consumer prices, from CEP OECD Data Set.

● GDP per capita: Real GDP per capita at the price levels and exchange rates of 1985 (in U.S. dollars) from OECD National Accounts (OECD, 1997).

● �GDP per capita: GDP per capita minus GDP per capita (�1).

THE MACROECONOMICS OF HAPPINESS 827

This article has been cited by:

1. Thu T. Nguyen, Hsien-Weng Meng, Sanjeev Sandeep, Matt McCullough, Weijun Yu, Yan Lau, Dina Huang, Quynh C. Nguyen. 2018. Twitter-derived measures of sentiment towards minorities (2015–2016) and associations with low birth weight and preterm birth in the United States. Computers in Human Behavior 89, 308-315. [Crossref]

2. Marloes M. Hoogerbrugge, Martijn J. Burger. 2018. Neighborhood-Based social capital and life satisfaction: the case of Rotterdam, The Netherlands. Urban Geography 39:10, 1484-1509. [Crossref]

3. Dennis Wesselbaum. 2018. Happiness over the financial crisis. Oxford Development Studies 1-21. [Crossref] 4. T. Tavor, L. D. Gonen, M. Weber, U. Spiegel. 2018. The Effects of Income Levels and Income Inequalities on Happiness. Journal

of Happiness Studies 19:7, 2115-2137. [Crossref] 5. Dong Zhou, Langchuan Peng. 2018. The Relationship Between the Gender Gap in Subjective Well-Being and Leisure Activities in

China. Journal of Happiness Studies 19:7, 2139-2166. [Crossref] 6. João Silvestre, Tanya Araújo, Miguel St. Aubyn. 2018. Individual Satisfaction and Economic Growth in an Agent-Based Economy.

Computational Economics 11. . [Crossref] 7. Janine Jongbloed. 2018. Higher education for happiness? Investigating the impact of education on the hedonic and eudaimonic well-

being of Europeans. European Educational Research Journal 17:5, 733-754. [Crossref] 8. Andrew G Haldane. 2018. How Monetary Policy Affects Your Gross Domestic Product. Australian Economic Review 51:3, 309-335.

[Crossref] 9. Yipeng Tang. 2018. What makes rural teachers happy? An investigation on the subjective well-being (SWB) of Chinese rural teachers.

International Journal of Educational Development 62, 192-200. [Crossref] 10. Li-Hsuan Huang. 2018. Well-being and volunteering: Evidence from aging societies in Asia. Social Science & Medicine . [Crossref] 11. Fabio D’Orlando, Francesco Ferrante. 2018. Macroeconomic priorities revisited: the behavioural foundations of stabilization policies.

Cambridge Journal of Economics 42:5, 1255-1275. [Crossref] 12. Tiken Das, Manesh Choubey. 2018. Do the heterogeneous determinants of life satisfaction affect differently across borrowers of diverse

credit sources? A propensity score approach. International Journal of Social Economics 45:8, 1142-1158. [Crossref] 13. Mariangela Bonasia, Oreste Napolitano, Nicola Spagnolo. 2018. Happy PIIGS?. Journal of Happiness Studies 19:6, 1763-1782. [Crossref] 14. Mark Borgschulte, Paco Martorell. 2018. Paying to Avoid Recession: Using Reenlistment to Estimate the Cost of Unemployment.

American Economic Journal: Applied Economics 10:3, 101-127. [Crossref] 15. Venke Furre Haaland. 2018. Ability Matters: Effects of Youth Labor-Market Opportunities on Long-Term Labor-Market Outcomes.

The Scandinavian Journal of Economics 120:3, 794-825. [Crossref] 16. Philip D. Parker, Gawaian Bodkin-Andrews, Rhiannon B. Parker, Nicholas Biddle. 2018. Trends in Indigenous and Non-Indigenous

Multidomain Well-Being. Emerging Adulthood 24, 216769681878201. [Crossref] 17. Jolanda Hessels, Efstratia Arampatzi, Peter van der Zwan, Martijn Burger. 2018. Life satisfaction and self-employment in different

types of occupations. Applied Economics Letters 25:11, 734-740. [Crossref] 18. Emilio Colombo, Valentina Rotondi, Luca Stanca. 2018. Macroeconomic conditions and well-being: do social interactions matter?.

Applied Economics 50:28, 3029-3038. [Crossref] 19. Paul Marx, Christoph Giang Nguyen. 2018. Political participation in European welfare states: does social investment matter?. Journal

of European Public Policy 25:6, 912-943. [Crossref] 20. CONGMIN PENG, PO-WEN SHE. 2018. “RAISE CHILDREN TO FIGHT AGAINST AGING”: THE DETERMINANTS OF

ELDERLY WELLBEING IN TODAY’S CHINA. The Singapore Economic Review 15, 1842003. [Crossref] 21. Yuan Li, Dabo Guan, Shu Tao, Xuejun Wang, Kebin He. 2018. A review of air pollution impact on subjective well-being: Survey

versus visual psychophysics. Journal of Cleaner Production 184, 959-968. [Crossref] 22. Alberto Montagnoli, Mirko Moro. 2018. The Cost of Banking Crises: New Evidence from Life Satisfaction Data. Kyklos 71:2, 279-309.

[Crossref] 23. Camille Landais, Pascal Michaillat, Emmanuel Saez. 2018. A Macroeconomic Approach to Optimal Unemployment Insurance:

Applications. American Economic Journal: Economic Policy 10:2, 182-216. [Crossref] 24. Camille Landais, Pascal Michaillat, Emmanuel Saez. 2018. A Macroeconomic Approach to Optimal Unemployment Insurance: Theory.

American Economic Journal: Economic Policy 10:2, 152-181. [Crossref] 25. Wen-Hao Chen, Feng Hou. 2018. The Effect of Unemployment on Life Satisfaction: A Cross-National Comparison Between Canada,

Germany, the United Kingdom and the United States. Applied Research in Quality of Life 77. . [Crossref]

26. Victoria Mousteri, Michael Daly, Liam Delaney. 2018. The scarring effect of unemployment on psychological well-being across Europe. Social Science Research 72, 146-169. [Crossref]

27. Lucía Macchia, Anke C. Plagnol. 2018. Life Satisfaction and Confidence in National Institutions: Evidence from South America. Applied Research in Quality of Life 88. . [Crossref]

28. Philip R Lane, Livio Stracca. 2018. Can appreciation be expansionary? Evidence from the euro area. Economic Policy 33:94, 225-264. [Crossref]

29. Carolina Ortega Londoño, Daniel Gómez Mesa, Lina Cardona-Sosa, Catalina Gómez Toro. 2018. Happiness and Victimization in Latin America. Journal of Happiness Studies 6. . [Crossref]

30. Bidisha Chakraborty, Souparna Maji, Anamika Sen, Isha Mallik, Sayantan Baidya, Esha Dwibedi. 2018. A Study on Happiness and Related Factors Among Indian College Students. Journal of Quantitative Economics 5. . [Crossref]

31. Benjamin Schalembier. 2018. An Evaluation of Common Explanations for the Impact of Income Inequality on Life Satisfaction. Journal of Happiness Studies 65. . [Crossref]

32. Donghwan Kim. 2018. Cross-National Pattern of Happiness: Do Higher Education and Less Urbanization Degrade Happiness?. Applied Research in Quality of Life 13:1, 21-35. [Crossref]

33. Richard A. Burns. 2018. The Utility of Between-Nation Subjective Wellbeing Comparisons Amongst Nations Within the European Social Survey. Journal of Happiness Studies 88. . [Crossref]

34. Santi Budría, Ada Ferrer-I-Carbonell. 2018. Life Satisfaction, Income Comparisons and Individual Traits. Review of Income and Wealth 118. . [Crossref]

35. Masanori Kuroki. 2018. Subjective well-being and minimum wages: Evidence from U.S. states. Health Economics 27:2, e171-e180. [Crossref]

36. Ed Diener, Richard E. Lucas, Shigehiro Oishi. 2018. Advances and Open Questions in the Science of Subjective Well-Being. Collabra: Psychology 4:1, 15. [Crossref]

37. Minhaj Mahmud, Yasuyuki Sawada. Urbanization and Subjective Well-Being in Bangladesh 215-232. [Crossref] 38. Amitai Etzioni. Happiness Is the Wrong Metric 3-40. [Crossref] 39. Amitai Etzioni. Bring Back the Moral Wrestler 41-52. [Crossref] 40. Ha Trong Nguyen, Luke Brian Connelly. 2018. Out of sight but not out of mind: Home countries’ macroeconomic volatilities and

immigrants’ mental health. Health Economics 27:1, 189-208. [Crossref] 41. Nicholas Apergis. 2018. The Impact of Greenhouse Gas Emissions on Personal Well-Being: Evidence from a Panel of 58 Countries

and Aggregate and Regional Country Samples. Journal of Happiness Studies 19:1, 69-80. [Crossref] 42. Mattheus Brenig, Till Proeger. 2018. Putting a Price Tag on Security: Subjective Well-Being and Willingness-to-Pay for Crime

Reduction in Europe. Journal of Happiness Studies 19:1, 145-166. [Crossref] 43. Marko Vladisavljević, Vladimir Mentus. 2018. The Structure of Subjective Well-Being and Its Relation to Objective Well-Being

Indicators: Evidence from EU-SILC for Serbia. Psychological Reports 003329411875633. [Crossref] 44. Daniel A. Hojman, Álvaro Miranda. 2018. Agency, Human Dignity, and Subjective Well-being. World Development 101, 1-15.

[Crossref] 45. Mauro Gallegati. Axiomatic Economics: The Biggest Dying Paradigm 1-16. [Crossref] 46. Ayse Y. Evrensel. 2018. Contradictory effects of religiosity on subjective well-being. Cogent Economics & Finance 6:1, 1-26. [Crossref] 47. Sefa Awaworyi Churchill, Samuelson Appau, Lisa Farrell. 2017. Religiosity, income and wellbeing in developing countries. Empirical

Economics 39. . [Crossref] 48. Elena Ianchovichina. Symptoms of a Broken Social Contract 93-111. [Crossref] 49. Gregor Gonza, Anže Burger. 2017. Subjective Well-Being During the 2008 Economic Crisis: Identification of Mediating and

Moderating Factors. Journal of Happiness Studies 18:6, 1763-1797. [Crossref] 50. Almudena Moreno Mínguez. 2017. The Role of Family Policy in Explaining the International Variation in Child Subjective Well-

Being. Social Indicators Research 134:3, 1173-1194. [Crossref] 51. Xiaogang Wu, Jun Li. 2017. Income inequality, economic growth, and subjective well-being: Evidence from China. Research in Social

Stratification and Mobility 52, 49-58. [Crossref] 52. Bent Greve. 2017. How to Measure Social Progress?. Social Policy & Administration 51:7, 1002-1022. [Crossref] 53. Gerard J. van den Berg, Ulf G. Gerdtham, Stephanie von Hinke, Maarten Lindeboom, Johannes Lissdaniels, Jan Sundquist, Kristina

Sundquist. 2017. Mortality and the business cycle: Evidence from individual and aggregated data. Journal of Health Economics 56, 61-70. [Crossref]

54. Hidehiro Sugisawa, Ken Harada, Yoko Sugihara, Shizuko Yanagisawa, Masaya Shinmei. 2017. Socioeconomic status disparities in late- life disability based on age, period, and cohort in Japan. Archives of Gerontology and Geriatrics . [Crossref]

55. Sujarwoto Sujarwoto, Gindo Tampubolon, Adi Cilik Pierewan. 2017. Individual and Contextual Factors of Happiness and Life Satisfaction in a Low Middle Income Country. Applied Research in Quality of Life 9. . [Crossref]

56. Nattavudh Powdthavee, Richard V. Burkhauser, Jan-Emmanuel De Neve. 2017. Top incomes and human well-being: Evidence from the Gallup World Poll. Journal of Economic Psychology 62, 246-257. [Crossref]

57. Daphna Gross-Manos. 2017. Material well-being and social exclusion association with children’s subjective Well-being: Cross-national analysis of 14 countries. Children and Youth Services Review 80, 116-128. [Crossref]

58. Eugenio Proto, Andrew J. Oswald. 2017. National Happiness and Genetic Distance: A Cautious Exploration. The Economic Journal 127:604, 2127-2152. [Crossref]

59. Fabrice Murtin, Romina Boarini, Juan Carlos Cordoba, Marla Ripoll. 2017. Beyond GDP: Is There a Law of One Shadow Price?. European Economic Review . [Crossref]

60. Deniz Gevrek, Marilyn Spencer, David Hudgins, Valrie Chambers. 2017. I can’t get no satisfaction. Personnel Review 46:5, 1019-1043. [Crossref]

61. Pierluigi Conzo, Giulia Fuochi, Letizia Mencarini. 2017. Fertility and Life Satisfaction in Rural Ethiopia. Demography 54:4, 1331-1351. [Crossref]

62. Mikko Weckroth, Teemu Kemppainen, Danny Dorling. 2017. Socio-economic stratification of life satisfaction in Ireland during an economic recession: A repeated cross-sectional study using the European Social Survey. Irish Journal of Sociology 25:2, 128-149. [Crossref]

63. Mohammad Reza Farzanegan, Tim Krieger, Daniel Meierrieks. 2017. Does terrorism reduce life satisfaction?. Applied Economics Letters 24:13, 893-896. [Crossref]

64. Anders Ejrnaes, Bent Greve. 2017. Your position in society matters for how happy you are. International Journal of Social Welfare 26:3, 206-217. [Crossref]

65. Niclas Berggren, Christian Bj?rnskov, Therese Nilsson. 2017. What Aspects of Society Matter for the Quality of Life of a Minority? Global Evidence from the New Gay Happiness Index. Social Indicators Research 132:3, 1163-1192. [Crossref]

66. Bram Roudijk, Rogier Donders, Peep Stalmeier. 2017. Cultural values: can they explain self-reported health?. Quality of Life Research 26:6, 1531-1539. [Crossref]

67. Peter Howley, Emma Dillon, Kevin Heanue, David Meredith. 2017. Worth the Risk? The Behavioural Path to Well-Being. Journal of Agricultural Economics 68:2, 534-552. [Crossref]

68. Tom Lane. 2017. How does happiness relate to economic behaviour? A review of the literature. Journal of Behavioral and Experimental Economics 68, 62-78. [Crossref]

69. Zheng Fang. 2017. Panel Quantile Regressions and the Subjective Well-Being in Urban China: Evidence from RUMiC Data. Social Indicators Research 132:1, 11-24. [Crossref]

70. Lilian Lopes Ribeiro, Emerson Luis Lemos Marinho. 2017. Gross National Happiness in Brazil: An analysis of its determinants. EconomiA 18:2, 156-167. [Crossref]

71. Michael Minkov, Michael Harris Bond. 2017. A Genetic Component to National Differences in Happiness. Journal of Happiness Studies 18:2, 321-340. [Crossref]

72. Ngan Lam Thi Tran, Robert W. Wassmer, Edward L. Lascher. 2017. The Health Insurance and Life Satisfaction Connection. Journal of Happiness Studies 18:2, 409-426. [Crossref]

73. Matteo Migheli. 2017. Size of Town, Level of Education and Life Satisfaction in Western Europe. Tijdschrift voor economische en sociale geografie 108:2, 190-204. [Crossref]

74. Celso Iglesias-García, Pilar A. Sáiz, Patricia Burón, Fernando Sánchez-Lasheras, Luis Jiménez-Treviño, Sergio Fernández-Artamendi, Susana Al-Halabí, Paul Corcoran, M. Paz García-Portilla, Julio Bobes. 2017. Suicide, unemployment, and economic recession in Spain. Revista de Psiquiatría y Salud Mental (English Edition) 10:2, 70-77. [Crossref]

75. Trinidad Beleche. 2017. Domestic violence laws and suicide in Mexico. Review of Economics of the Household 100. . [Crossref] 76. Peter Howley. 2017. Less money or better health? Evaluating individual’s willingness to make trade-offs using life satisfaction data.

Journal of Economic Behavior & Organization 135, 53-65. [Crossref] 77. Duha T. Altindag, Junyue Xu. 2017. Life Satisfaction and Preferences over Economic Growth and Institutional Quality. Journal of

Labor Research 38:1, 100-121. [Crossref] 78. Bettina Roth, Elisabeth Hahn, Frank M. Spinath. 2017. Income Inequality, Life Satisfaction, and Economic Worries. Social

Psychological and Personality Science 8:2, 133-141. [Crossref]

79. 전전전, 전전전. 2017. Analysis on the Effect between the Community Perception and Happiness: Focusing on the Participants of the Community Business in Chungcheongnam-do. Journal of Local Government Studis 29:1, 137-166. [Crossref]

80. Carsten Schröder, Shlomo Yitzhaki. 2017. Revisiting the evidence for cardinal treatment of ordinal variables. European Economic Review 92, 337-358. [Crossref]

81. Ozan Eksi, Neslihan Kaya. 2017. Life Satisfaction and Keeping Up with Other Countries. Journal of Happiness Studies 18:1, 199-228. [Crossref]

82. Terence C. Cheng, Nattavudh Powdthavee, Andrew J. Oswald. 2017. Longitudinal Evidence for a Midlife Nadir in Human Well- being: Results from Four Data Sets. The Economic Journal 127:599, 126-142. [Crossref]

83. Iddisah Sulemana, Abdul Malik Iddrisu, Jude E. Kyoore. 2017. A Micro-Level Study of the Relationship Between Experienced Corruption and Subjective Wellbeing in Africa. The Journal of Development Studies 53:1, 138-155. [Crossref]

84. Mehmet Fatih Aysan, Ummugulsum Aysan. The Effect of Employment Status on Life Satisfaction in Europe 335-347. [Crossref] 85. Ya Ding. 2017. Personal Life Satisfaction of China’s Rural Elderly: Effect of the New Rural Pension Programme. Journal of International

Development 29:1, 52-66. [Crossref] 86. José Manuel Cordero, Javier Salinas-Jiménez, M Mar Salinas-Jiménez. 2017. Exploring factors affecting the level of happiness across

countries: A conditional robust nonparametric frontier analysis. European Journal of Operational Research 256:2, 663-672. [Crossref] 87. Shigehiro Oishi, Ed Diener, Léandre Bouffard. 2017. LE BONHEUR, BUT DES POLITIQUES PUBLIQUES?. Revue québécoise

de psychologie 38:1, 237. [Crossref] 88. Yasuharu Tokuda, Takashi Inoguchi. Interpersonal Mistrust and Unhappiness Among Japanese People 89-102. [Crossref] 89. Yasuharu Tokuda, Masamine Jimba, Haruo Yanai, Seiji Fujii, Takashi Inoguchi. Interpersonal Trust and Quality-of-Life: A Cross-

Sectional Study in Japan 103-122. [Crossref] 90. Yasuharu Tokuda, Seiji Fujii, Takashi Inoguchi. Individual and Country-Level Effects of Social Trust on Happiness: The Asia

Barometer Survey 123-139. [Crossref] 91. Wei Xiao, Zhi-Fang Su. 2017. Does social insurance in China enhance people’s well-being?. Journal of Interdisciplinary Mathematics

20:3, 821. [Crossref] 92. Oumar Bouare. 2017. Comparing Countries’ Life Satisfaction and Their Level Curve of Life Satisfaction over Time: An Analytical

Framework. Psychology 08:14, 2346. [Crossref] 93. Shawn Grover, John F. Helliwell. 2017. How’s Life at Home? New Evidence on Marriage and the Set Point for Happiness. Journal

of Happiness Studies . [Crossref] 94. Matic Novak, Marko Pahor. 2017. Using a multilevel modelling approach to explain the influence of economic development on the

subjective well-being of individuals. Economic Research-Ekonomska Istraživanja 30:1, 705-720. [Crossref] 95. Yasuyuki Sawada, Michiko Ueda, Tetsuya Matsubayashi. Government Partisanship and Suicide 137-161. [Crossref] 96. Yasuyuki Sawada, Michiko Ueda, Tetsuya Matsubayashi. The Effect of Government Suicide Prevention Programs 179-203. [Crossref] 97. Federica Liberini, Michela Redoano, Eugenio Proto. 2016. Happy Voters. Journal of Public Economics . [Crossref] 98. Petr Sunega, Martin Lux. 2016. Subjective perception versus objective indicators of overcrowding and housing affordability. Journal

of Housing and the Built Environment 31:4, 695-717. [Crossref] 99. Vladimir Otrachshenko, Olga Popova, José Tavares. 2016. Psychological costs of currency transition: evidence from the euro adoption.

European Journal of Political Economy 45, 89-100. [Crossref] 100. Ann L. Owen, Anne Phillips. 2016. How Does the Life Satisfaction of the Poor, Least Educated, and Least Satisfied Change as

Average Life Satisfaction Increases?. Journal of Happiness Studies 17:6, 2389-2406. [Crossref] 101. Hidehiro Sugisawa, Ken Harada, Yoko Sugihara, Shizuko Yanagisawa, Masaya Shinmei. 2016. Socioeconomic status and self-rated

health of Japanese people, based on age, cohort, and period. Population Health Metrics 14:1. . [Crossref] 102. Matti Hovi, Jani-Petri Laamanen. 2016. Mind the gap? Business cycles and subjective well-being. Applied Economics Letters 23:17,

1206-1209. [Crossref] 103. Heinz Welsch, Jan Kühling. 2016. Macroeconomic performance and institutional change: evidence from subjective well-being data.

Journal of Applied Economics 19:2, 193-217. [Crossref] 104. Robin Samuel, Andreas Hadjar. 2016. How Welfare-State Regimes Shape Subjective Well-Being Across Europe. Social Indicators

Research 129:2, 565-587. [Crossref] 105. Leonardo Morlino, Mario Quaranta. 2016. What is the impact of the economic crisis on democracy? Evidence from Europe.

International Political Science Review 37:5, 618-633. [Crossref] 106. Shu Cai, Albert Park. 2016. Permanent income and subjective well-being. Journal of Economic Behavior & Organization 130, 298-319.

[Crossref]

107. André van Hoorn, Esther-Mirjam Sent. 2016. Consumer Capital as the Source of Happiness: The Missing Economic Theory Underlying the Income-Happiness Paradox. Journal of Economic Issues 50:4, 984-1002. [Crossref]

108. Cristina Borra, Francisco Gómez-García. 2016. Wellbeing at Work and the Great Recession: The Effect of Others’ Unemployment. Journal of Happiness Studies 17:5, 1939-1962. [Crossref]

109. Gregori Baetschmann, Kevin E. Staub, Raphael Studer. 2016. Does the stork deliver happiness? Parenthood and life satisfaction. Journal of Economic Behavior & Organization 130, 242-260. [Crossref]

110. Veroniek Collewaert, Frederik Anseel, Michiel Crommelinck, Alain De Beuckelaer, Jacob Vermeire. 2016. When Passion Fades: Disentangling the Temporal Dynamics of Entrepreneurial Passion for Founding. Journal of Management Studies 53:6, 966-995. [Crossref]

111. Arthur S. Alderson, Tally Katz-Gerro. 2016. Compared to Whom? Inequality, Social Comparison, and Happiness in the United States. Social Forces 95:1, 25-54. [Crossref]

112. Felix Requena. 2016. Rural–Urban Living and Level of Economic Development as Factors in Subjective Well-Being. Social Indicators Research 128:2, 693-708. [Crossref]

113. Christopher L. Ambrey, Christopher M. Fleming, Matthew Manning, Christine Smith. 2016. On the Confluence of Freedom of the Press, Control of Corruption and Societal Welfare. Social Indicators Research 128:2, 859-880. [Crossref]

114. Alexander Jakubow. 2016. Subjective Well-Being and the Welfare State: Giving a Fish or Teaching to Fish?. Social Indicators Research 128:3, 1147-1169. [Crossref]

115. Chris M. Herbst, John Ifcher. 2016. The increasing happiness of US parents. Review of Economics of the Household 14:3, 529-551. [Crossref]

116. Benjamin Radcliff, Gregory Shufeldt. 2016. Direct Democracy and Subjective Well-Being: The Initiative and Life Satisfaction in the American States. Social Indicators Research 128:3, 1405-1423. [Crossref]

117. Mohsen Joshanloo, Dan Weijers. 2016. Religiosity Moderates the Relationship between Income Inequality and Life Satisfaction across the Globe. Social Indicators Research 128:2, 731-750. [Crossref]

118. choi yena. 2016. The Study on Factors Determining Life Satisfaction in Jeollabukdo : Focusing on individual and Regional Factors. Korean Journal of Local Government & Administration Studies 30:3, 291-312. [Crossref]

119. Robin Nunkoo, Kevin Kam Fung So. 2016. Residents’ Support for Tourism. Journal of Travel Research 55:7, 847-861. [Crossref] 120. Roya Kelishadi, Shirin Djalalinia, Mostafa Qorbani, Morteza Mansourian, Mohammad Esmaeil Motlagh, Gelayol Ardalan, Hamid

Asayesh, Hossein Ansari, Ramin Heshmat. 2016. Self-Rated Health and Life Satisfaction in Iranian Children and Adolescents at the National and Provincial Level: The CASPIAN-IV Study. Iranian Red Crescent Medical Journal 18:12. . [Crossref]

121. Bodo Knoll, Hans Pitlik. 2016. Who benefits from big government? A life satisfaction approach. Empirica 43:3, 533-557. [Crossref] 122. Quynh C. Nguyen, Suraj Kath, Hsien-Wen Meng, Dapeng Li, Ken R. Smith, James A. VanDerslice, Ming Wen, Feifei Li. 2016.

Leveraging geotagged Twitter data to examine neighborhood happiness, diet, and physical activity. Applied Geography 73, 77-88. [Crossref]

123. Gábor Hajdu, Tamás Hajdu. 2016. The Impact of Culture on Well-Being: Evidence from a Natural Experiment. Journal of Happiness Studies 17:3, 1089-1110. [Crossref]

124. Casey Boyd-Swan, Chris M. Herbst, John Ifcher, Homa Zarghamee. 2016. The earned income tax credit, mental health, and happiness. Journal of Economic Behavior & Organization 126, 18-38. [Crossref]

125. Chris M. Herbst, Joanna Lucio. 2016. HAPPY IN THE HOOD? THE IMPACT OF RESIDENTIAL SEGREGATION ON SELF- REPORTED HAPPINESS. Journal of Regional Science 56:3, 494-521. [Crossref]

126. Mario Quaranta, Sergio Martini. 2016. Does the economy really matter for satisfaction with democracy? Longitudinal and cross- country evidence from the European Union. Electoral Studies 42, 164-174. [Crossref]

127. Elias Soukiazis, Sara Ramos. 2016. The Structure of Subjective Well-Being and Its Determinants: A Micro-Data Study for Portugal. Social Indicators Research 126:3, 1375-1399. [Crossref]

128. Jie Zhou, Yu Xie. 2016. Does Economic Development Affect Life Satisfaction? A Spatial–Temporal Contextual Analysis in China. Journal of Happiness Studies 17:2, 643-658. [Crossref]

129. María Laura Arrosa, Néstor Gandelman. 2016. Happiness Decomposition: Female Optimism. Journal of Happiness Studies 17:2, 731-756. [Crossref]

130. Steffen Otterbach, Alfonso Sousa-Poza. 2016. Job insecurity, employability and health: an analysis for Germany across generations. Applied Economics 48:14, 1303-1316. [Crossref]

131. Edsel L. Beja. 2016. Measuring economic ill-being using objective and subjective indicators: evidence for the Philippines. International Review of Applied Economics 30:2, 151-166. [Crossref]

132. Martijn Hendriks, David Bartram. 2016. Macro-conditions and immigrants’ happiness: Is moving to a wealthy country all that matters?. Social Science Research 56, 90-107. [Crossref]

133. Alexandru Cojocaru. 2016. Does Relative Deprivation Matter in Developing Countries: Evidence from Six Transition Economies. Social Indicators Research 125:3, 735-756. [Crossref]

134. Diane Jarvis, Natalie Stoeckl, Hong-Bo Liu. 2016. The impact of economic, social and environmental factors on trip satisfaction and the likelihood of visitors returning. Tourism Management 52, 1-18. [Crossref]

135. Ingemar Johansson Sevä, Stig Vinberg, Mikael Nordenmark, Mattias Strandh. 2016. Subjective well-being among the self-employed in Europe: macroeconomy, gender and immigrant status. Small Business Economics 46:2, 239-253. [Crossref]

136. Francis Green, Alan Felstead, Duncan Gallie, Hande Inanc. 2016. Job-Related Well-Being Through the Great Recession. Journal of Happiness Studies 17:1, 389-411. [Crossref]

137. Lamar Pierce, Todd Rogers, Jason A. Snyder. 2016. Losing Hurts: The Happiness Impact of Partisan Electoral Loss. Journal of Experimental Political Science 3:01, 44-59. [Crossref]

138. Heinz Welsch, Jan Kühling. 2016. HOW HAS THE CRISIS OF 2008-09 AFFECTED SUBJECTIVE WELL-BEING? EVIDENCE FROM 25 OECD COUNTRIES. Bulletin of Economic Research 68:1, 34-54. [Crossref]

139. Antje Mertens, Miriam Beblo. 2016. Self-Reported Satisfaction and the Economic Crisis of 2007–2010: Or How People in the UK and Germany Perceive a Severe Cyclical Downturn. Social Indicators Research 125:2, 537-565. [Crossref]

140. Khadija Shams. 2016. Developments in the Measurement of Subjective Well-Being and Poverty: An Economic Perspective. Journal of Happiness Studies 17:6, 2213. [Crossref]

141. Quynh C Nguyen, Dapeng Li, Hsien-Wen Meng, Suraj Kath, Elaine Nsoesie, Feifei Li, Ming Wen. 2016. Building a National Neighborhood Dataset From Geotagged Twitter Data for Indicators of Happiness, Diet, and Physical Activity. JMIR Public Health and Surveillance 2:2, e158. [Crossref]

142. Emilio Moyano Díaz. Trends and Challenges for the Research of Happiness in Latin America 63-87. [Crossref] 143. Malte Hübner, Marcus Klemm. 2015. Preferences over inflation and unemployment in Europe: a north–south divide?. International

Review of Economics 62:4, 319-335. [Crossref] 144. Gus O’Donnell, Andrew J. Oswald. 2015. National well-being policy and a weighted approach to human feelings. Ecological Economics

120, 59-70. [Crossref] 145. Edsel L. Beja. 2015. Direct and indirect impacts of parenthood on happiness. International Review of Economics 62:4, 307-318.

[Crossref] 146. Jiayuan Li. Happiness: Conceptual Issues and Policy Implications 1-5. [Crossref] 147. Hania Fei Wu, Tony Tam. 2015. Economic Development and Socioeconomic Inequality of Well-Being: A Cross-Sectional Time-

Series Analysis of Urban China, 2003–2011. Social Indicators Research 124:2, 401-425. [Crossref] 148. Stephan J. Goetz, Meri Davlasheridze, Yicheol Han. 2015. County-Level Determinants of Mental Health, 2002–2008. Social Indicators

Research 124:2, 657-670. [Crossref] 149. Nikolaos Antonakakis, Alan Collins. 2015. The impact of fiscal austerity on suicide mortality: Evidence across the ‘Eurozone periphery’.

Social Science & Medicine 145, 63-78. [Crossref] 150. Kang-Rae Ma. 2015. Intergenerational Transmission of Wealth and Life Satisfaction. Applied Research in Quality of Life . [Crossref] 151. . Bibliography 277-314. [Crossref] 152. Shigehiro Oishi, Selin Kesebir. 2015. Income Inequality Explains Why Economic Growth Does Not Always Translate to an Increase

in Happiness. Psychological Science 26:10, 1630-1638. [Crossref] 153. Jia Wang, Yu Xie. 2015. Feeling good about the iron rice bowl: Economic sector and happiness in post-reform urban China. Social

Science Research 53, 203-217. [Crossref] 154. Ricardo Perez-Truglia. 2015. A Samuelsonian validation test for happiness data. Journal of Economic Psychology 49, 74-83. [Crossref] 155. Christian Breuer. 2015. Unemployment and Suicide Mortality: Evidence from Regional Panel Data in Europe. Health Economics 24:8,

936-950. [Crossref] 156. 전전전, 전전전, 전전전. 2015. A Synoptic Review of the Research on Happiness. Journal of Governmental Studies(JGS) 21:2, 95-130. [Crossref] 157. Anita Ratcliffe, Karl Taylor. 2015. Who cares about stock market booms and busts? Evidence from data on mental health. Oxford

Economic Papers 67:3, 826-845. [Crossref] 158. Steffen Lohmann. 2015. Information technologies and subjective well-being: does the Internet raise material aspirations?. Oxford

Economic Papers 67:3, 740-759. [Crossref] 159. Antonia Fernandez, Marina Della Giusta, Uma S. Kambhampati. 2015. The Intrinsic Value of Agency: The Case of Indonesia. World

Development 70, 92-107. [Crossref]

160. Qiush Feng, Joonmo Son, Yi Zeng. 2015. Prevalence and correlates of successful ageing: a comparative study between China and South Korea. European Journal of Ageing 12:2, 83-94. [Crossref]

161. Adi Cilik Pierewan, Gindo Tampubolon. 2015. Happiness and Health in Europe: A Multivariate Multilevel Model. Applied Research in Quality of Life 10:2, 237-252. [Crossref]

162. Jacob Gerner Hariri, Christian Bjørnskov, Mogens K. Justesen. 2015. Economic Shocks and Subjective Well-Being: Evidence from a Quasi-Experiment. The World Bank Economic Review lhv004. [Crossref]

163. Aviral Kumar Tiwari, Mihai Mutascu. 2015. The relationship between environmental degradation and happiness in 23 developed contemporary economies. Management of Environmental Quality: An International Journal 26:2, 301-321. [Crossref]

164. Jeremy K. Nguyen, Christopher M. Fleming, Jen-Je Su. 2015. Does Income Inequality Make Us Less Happy?. Australian Economic Review 48:1, 15-32. [Crossref]

165. Anita Ratcliffe. 2015. Wealth Effects, Local Area Attributes, and Economic Prospects: On the Relationship between House Prices and Mental Wellbeing. Review of Income and Wealth 61:1, 75-92. [Crossref]

166. Jenny E. Ligthart, Peter van Oudheusden. 2015. In government we trust: The role of fiscal decentralization. European Journal of Political Economy 37, 116-128. [Crossref]

167. E. Arampatzi, M. J. Burger, R. Veenhoven. 2015. Financial distress and happiness of employees in times of economic crisis. Applied Economics Letters 22:3, 173-179. [Crossref]

168. Nattavudh Powdthavee, Warn N. Lekfuangfu, Mark Wooden. 2015. What’s the good of education on our overall quality of life? A simultaneous equation model of education and life satisfaction for Australia. Journal of Behavioral and Experimental Economics 54, 10-21. [Crossref]

169. Monica Răileanu-Szeles. 2015. Explaining the Dynamics and Drivers of Financial Well-Being in the European Union. Social Indicators Research 120:3, 701-722. [Crossref]

170. Sehee Han. 2015. Social Capital and Subjective Happiness: Which Contexts Matter?. Journal of Happiness Studies 16:1, 241-255. [Crossref]

171. F.-B. Wietzke. 2015. Pathways from Jobs to Social Cohesion. The World Bank Research Observer 30:1, 95-123. [Crossref] 172. Channary Khun, Sajal Lahiri, Sokchea Lim. 2015. Do people really support trade restrictions? Cross-country evidence. The Journal

of International Trade & Economic Development 24:1, 132-146. [Crossref] 173. Edsel L. Beja. 2015. Empirics on the Long Run Relationship Between Economic Growth and Happiness. Forum for Social Economics

44:1, 3-17. [Crossref] 174. Y. H. Farzin, K. I. Akao. 2015. Poverty, social preference for employment, and natural resource depletion. Environmental Economics

and Policy Studies 17:1, 1-26. [Crossref] 175. Song Gao, Xiangyi Meng, Li Zhang. 2014. Fiscal Decentralization and Life Satisfaction: Evidence from Urban China. Social Indicators

Research 119:3, 1177-1194. [Crossref] 176. Yongwei Chen, Tao Li, Yupeng Shi, Yilun Zhou. 2014. Welfare Costs of Inflation: Evidence from China. Social Indicators Research

119:3, 1195-1218. [Crossref] 177. Edsel L. Beja. 2014. Income growth and happiness: reassessment of the Easterlin Paradox. International Review of Economics 61:4,

329-346. [Crossref] 178. Dilip V. Jeste, Andrew J. Oswald. 2014. Individual and Societal Wisdom: Explaining the Paradox of Human Aging and High Well-

Being. Psychiatry: Interpersonal and Biological Processes 77:4, 317-330. [Crossref] 179. Barbara Dluhosch, Daniel Horgos, Klaus W. Zimmermann. 2014. Social Choice and Social Unemployment-Income Cleavages: New

Insights from Happiness Research. Journal of Happiness Studies 15:6, 1513-1537. [Crossref] 180. Khadija Shams. 2014. Determinants of Subjective Well-Being and Poverty in Rural Pakistan: A Micro-Level Study. Social Indicators

Research 119:3, 1755-1773. [Crossref] 181. Wylie Bradford. 2014. Quo vadis : Does economic theory need a sustainability makeover?. The Economic and Labour Relations Review

25:4, 551-562. [Crossref] 182. Hee Seung Lee, Douglas A. Wolf. 2014. An Evaluation of Recent Old-Age Policy Innovations in South Korea. Research on Aging

36:6, 707-730. [Crossref] 183. John Ifcher, Homa Zarghamee. 2014. The Happiness of Single Mothers: Evidence from the General Social Survey. Journal of Happiness

Studies 15:5, 1219-1238. [Crossref] 184. Claudia Senik. 2014. The French unhappiness puzzle: The cultural dimension of happiness. Journal of Economic Behavior &

Organization 106, 379-401. [Crossref]

185. JOHN F. HELLIWELL, HAIFANG HUANG. 2014. NEW MEASURES OF THE COSTS OF UNEMPLOYMENT: EVIDENCE FROM THE SUBJECTIVE WELL-BEING OF 3.3 MILLION AMERICANS. Economic Inquiry 52:4, 1485-1502. [Crossref]

186. Jan Eichhorn. 2014. The (Non-) Effect of Unemployment Benefits: Variations in the Effect of Unemployment on Life-Satisfaction Between EU Countries. Social Indicators Research 119:1, 389-404. [Crossref]

187. Feng Hou. 2014. Keep Up with the Joneses or Keep on as Their Neighbours: Life Satisfaction and Income in Canadian Urban Neighbourhoods. Journal of Happiness Studies 15:5, 1085-1107. [Crossref]

188. Ewan Carr, Heejung Chung. 2014. Employment insecurity and life satisfaction: The moderating influence of labour market policies across Europe. Journal of European Social Policy 24:4, 383-399. [Crossref]

189. Shigehiro Oishi, Ed Diener. 2014. Can and Should Happiness Be a Policy Goal?. Policy Insights from the Behavioral and Brain Sciences 1:1, 195-203. [Crossref]

190. Tufan Ekici, Selda Koydemir. 2014. Social Capital, Government and Democracy Satisfaction, and Happiness in Turkey: A Comparison of Surveys in 1999 and 2008. Social Indicators Research 118:3, 1031-1053. [Crossref]

191. Jana Friedrichsen, Philipp Zahn. 2014. Political support in hard times: Do people care about national welfare?. European Journal of Political Economy 35, 23-37. [Crossref]

192. Olga Popova. 2014. Can religion insure against aggregate shocks to happiness? The case of transition countries. Journal of Comparative Economics 42:3, 804-818. [Crossref]

193. Alexandru Cojocaru. 2014. Fairness and inequality tolerance: Evidence from the Life in Transition Survey. Journal of Comparative Economics 42:3, 590-608. [Crossref]

194. Chris M. Herbst, Erdal Tekin. 2014. CHILD CARE SUBSIDIES, MATERNAL HEALTH, AND CHILD-PARENT INTERACTIONS: EVIDENCE FROM THREE NATIONALLY REPRESENTATIVE DATASETS. Health Economics 23:8, 894-916. [Crossref]

195. DARREN GRANT. 2014. WHAT MAKES A GOOD ECONOMY? EVIDENCE FROM PUBLIC OPINION SURVEYS. Economic Inquiry 52:3, 1120-1136. [Crossref]

196. Melike Wulfgramm. 2014. Life satisfaction effects of unemployment in Europe: The moderating influence of labour market policy. Journal of European Social Policy 24:3, 258-272. [Crossref]

197. Edsel L. Beja. 2014. Who is Happier: Housewife or Working Wife?. Applied Research in Quality of Life 9:2, 157-177. [Crossref] 198. Małgorzata Mikucka. 2014. Does Individualistic Culture Lower the Well-Being of the Unemployed? Evidence from Europe. Journal

of Happiness Studies 15:3, 673-691. [Crossref] 199. P. Flavin, A. C. Pacek, B. Radcliff. 2014. Assessing the Impact of the Size and Scope of Government on Human Well-Being. Social

Forces 92:4, 1241-1258. [Crossref] 200. Salmai Qari. 2014. Marriage, adaptation and happiness: Are there long-lasting gains to marriage?. Journal of Behavioral and

Experimental Economics 50, 29-39. [Crossref] 201. Edsel L. Beja. 2014. Subjective Well-Being Analysis of Income Inequality: Evidence for the Industrialized and Emerging Economies.

Applied Research in Quality of Life 9:2, 139-156. [Crossref] 202. Eleftherios Giovanis. 2014. Relationship between well-being and recycling rates: evidence from life satisfaction approach in Britain.

Journal of Environmental Economics and Policy 3:2, 201-214. [Crossref] 203. Lars Osberg, Andrew Sharpe. 2014. Measuring Economic Insecurity in Rich and Poor Nations. Review of Income and Wealth 60,

S53-S76. [Crossref] 204. Yonas Alem, Gunnar Köhlin. 2014. The Impact of Food Price Inflation on Subjective Well-being: Evidence From Urban Ethiopia.

Social Indicators Research 116:3, 853-868. [Crossref] 205. Adrian Chadi. 2014. Regional unemployment and norm-induced effects on life satisfaction. Empirical Economics 46:3, 1111-1141.

[Crossref] 206. Livio Stracca. 2014. Financial imbalances and household welfare: Empirical evidence from the EU. Journal of Financial Stability 11,

82-91. [Crossref] 207. Jiayuan Li, John W. Raine. 2014. The Time Trend of Life Satisfaction in China. Social Indicators Research 116:2, 409-427. [Crossref] 208. Anthony F Jorm, Siobhan M Ryan. 2014. Cross-national and historical differences in subjective well-being. International Journal of

Epidemiology 43:2, 330-340. [Crossref] 209. Dilip V. Jeste, Andrew J. Oswald. 2014. Individual and Societal Wisdom: Explaining the Paradox of Human Aging and High Well-

Being. Psychiatry: Interpersonal and Biological Processes 1-14. [Crossref] 210. Jing Jian Xiao. Money and Happiness: Implications for Investor Behavior 153-169. [Crossref]

211. Chu-Chia Lin, Tsung-Chi Cheng, Shu-Chen Wang. 2014. Measuring Subjective Well-Being in Taiwan. Social Indicators Research 116:1, 17-45. [Crossref]

212. J. Ignacio Gimenez-Nadal, Jose Alberto Molina. 2014. Regional unemployment, gender, and time allocation of the unemployed. Review of Economics of the Household 12:1, 105-127. [Crossref]

213. C. Senik. 2014. Wealth and happiness. Oxford Review of Economic Policy 30:1, 92-108. [Crossref] 214. Felicia A. Huppert. The State of Wellbeing Science 1-49. [Crossref] 215. Lars Osberg, Andrew Sharpe. The Impact of the Great Recession on Economic Wellbeing 1-27. [Crossref] 216. Juliet Michaelson Charles Seaford Saamah A, Nic Marks. Measuring what Matters 1-38. [Crossref] 217. Arthur Grimes, Les Oxley, Nicholas Tarrant. Does Money Buy Me Love? 1-33. [Crossref] 218. Ozge Gokdemir, Emine Tahsin. 2014. Factors that Influence the Life Satisfaction of Women Living in the Northern Cyprus. Social

Indicators Research 115:3, 1071-1085. [Crossref] 219. Chun-Hung A. Lin, Suchandra Lahiri, Ching-Po Hsu. 2014. Happiness and Regional Segmentation: Does Space Matter?. Journal

of Happiness Studies 15:1, 57-83. [Crossref] 220. Alexander Jakubow. 2014. State Intervention and Life Satisfaction Reconsidered: The Role of Governance Quality and Resource

Misallocation. Politics & Policy 42:1, 3-36. [Crossref] 221. Adi Cilik Pierewan, Gindo Tampubolon. 2014. Spatial dependence multilevel model of well-being across regions in Europe. Applied

Geography 47, 168-176. [Crossref] 222. Holger Bonin, Ulf Rinne. 2014. ‘Beautiful Serbia’ – objective and subjective outcomes of active labour market policy in a transition

economy. Economics of Transition 22:1, 43-67. [Crossref] 223. Richard A. Easterlin, Malgorzata Switek. Set Point Theory and Public Policy 201-217. [Crossref] 224. Alin I. Florea, Steven B. Caudill. 2014. Happiness, religion and economic transition. Economics of Transition 22:1, 1-12. [Crossref] 225. Nattavudh Powdthavee, Alois Stutzer. Economic Approaches to Understanding Change in Happiness 219-244. [Crossref] 226. J. Lonska. 2014. Comparative analysis of subjective well-being of Latvia’s inhabitants in the context of economic development of

European countries. SHS Web of Conferences 10, 00022. [Crossref] 227. Christopher L. Ambrey, Christopher M. Fleming. 2014. Life Satisfaction in Australia: Evidence from Ten Years of the HILDA Survey.

Social Indicators Research 115:2, 691-714. [Crossref] 228. Peter H. van der Meer. 2014. Gender, Unemployment and Subjective Well-Being: Why Being Unemployed Is Worse for Men than

for Women. Social Indicators Research 115:1, 23-44. [Crossref] 229. Marta Orviska, Anetta Caplanova, John Hudson. 2014. The Impact of Democracy on Well-being. Social Indicators Research 115:1,

493-508. [Crossref] 230. Eiji Yamamura. 2013. Trial experience, satisfaction and incentive to bring another lawsuit: Does aspiration level influence winners and

losers?. Japan and the World Economy 28, 125-131. [Crossref] 231. Huijun Liu, Shuzhuo Li, Marc W. Feldman. 2013. Gender in Marriage and Life Satisfaction Under Gender Imbalance in China: The

Role of Intergenerational Support and SES. Social Indicators Research 114:3, 915-933. [Crossref] 232. Oshrat Hochman, Nora Skopek. 2013. The impact of wealth on subjective well-being: A comparison of three welfare-state regimes.

Research in Social Stratification and Mobility 34, 127-141. [Crossref] 233. Jeffrey B. Nugent, Malgorzata Switek. 2013. Oil prices and life satisfaction: asymmetries between oil exporting and oil importing

countries. Applied Economics 45:33, 4603-4628. [Crossref] 234. Marta Portela, Isabel Neira, Maria del Mar Salinas-Jiménez. 2013. Social Capital and Subjective Wellbeing in Europe: A New Approach

on Social Capital. Social Indicators Research 114:2, 493-511. [Crossref] 235. Giovanna Gianesini. Negotiating family challenges by transforming traditional gender roles in new identities: Patterns of resilience and

parenthood in a sample of italian couples 277-316. [Crossref] 236. Hassan Gholipour Fereidouni, Youhanna Najdi, Reza Ekhtiari Amiri. 2013. Do governance factors matter for happiness in the MENA

region?. International Journal of Social Economics 40:12, 1028-1040. [Crossref] 237. Arie Sherman, Tal Shavit. 2013. The immaterial sustenance of work and leisure: A new look at the work–leisure model. The Journal

of Socio-Economics 46, 10-16. [Crossref] 238. Romina Boarini, Margherita Comola, Femke de Keulenaer, Robert Manchin, Conal Smith. 2013. Can Governments Boost People’s

Sense of Well-Being? The Impact of Selected Labour Market and Health Policies on Life Satisfaction. Social Indicators Research 114:1, 105-120. [Crossref]

239. Marzieh Abolhassani, Rob Alessie. 2013. Subjective Well-Being Around Retirement. De Economist 161:3, 349-366. [Crossref]

240. Olga N. Shemyakina, Anke C. Plagnol. 2013. Subjective Well-Being and Armed Conflict: Evidence from Bosnia-Herzegovina. Social Indicators Research 113:3, 1129-1152. [Crossref]

241. Barbara Dluhosch, Daniel Horgos. 2013. Trading Up the Happiness Ladder. Social Indicators Research 113:3, 973-990. [Crossref] 242. Indranil Dutta, James Foster. 2013. Inequality of Happiness in the U.S.: 1972-2010. Review of Income and Wealth 59:3, 393-415.

[Crossref] 243. Mauricio Jose Serpa Barros de Moura, Rodrigo De Losso da Silveira Bueno. 2013. Land title program in Brazil: Are there any changes

to happiness?. The Journal of Socio-Economics 45, 196-203. [Crossref] 244. Louise Grogan, Katerina Koka. 2013. Economic crises and wellbeing: Social norms and home production. Journal of Economic Behavior

& Organization 92, 241-258. [Crossref] 245. Leonardo Becchetti, Stefano Castriota, Luisa Corrado, Elena Giachin Ricca. 2013. Beyond the Joneses: Inter-country income

comparisons and happiness. The Journal of Socio-Economics 45, 187-195. [Crossref] 246. Santiago Budria. 2013. Are Relative-Income Effects Constant Across the Well-Being Distribution?. Journal of Happiness Studies 14:4,

1379-1408. [Crossref] 247. Amin Mohseni-Cheraghlou. 2013. Labor markets and mental wellbeing: Labor market conditions and suicides in the United States

(1979–2004). The Journal of Socio-Economics 45, 175-186. [Crossref] 248. Dimitris Ballas. 2013. What makes a ‘happy city’?. Cities 32, S39-S50. [Crossref] 249. Louis Tay, James K. Harter. 2013. Economic and Labor Market Forces Matter for Worker Well-Being. Applied Psychology: Health and

Well-Being 5:2, 193-208. [Crossref] 250. Leonardo Becchetti, Alessandra Pelloni. 2013. What are we learning from the life satisfaction literature?. International Review of

Economics 60:2, 113-155. [Crossref] 251. KITAE SOHN. 2013. SOURCES OF HAPPINESS IN INDONESIA. The Singapore Economic Review 58:02, 1350014. [Crossref] 252. Louis Tay, Lauren Kuykendall. 2013. Promoting happiness: The malleability of individual and societal subjective wellbeing.

International Journal of Psychology 48:3, 159-176. [Crossref] 253. Leonardo Becchetti, Elena Giachin Ricca, Alessandra Pelloni. 2013. The Paradox of Children and Life Satisfaction. Social Indicators

Research 111:3, 725-751. [Crossref] 254. Jan Urban, Vojtěch Máca. 2013. Linking Traffic Noise, Noise Annoyance and Life Satisfaction: A Case Study. International Journal

of Environmental Research and Public Health 10:5, 1895-1915. [Crossref] 255. Martin Halla, Friedrich G. Schneider, Alexander F. Wagner. 2013. Satisfaction with democracy and collective action problems: the

case of the environment. Public Choice 155:1-2, 109-137. [Crossref] 256. Arie Kapteyn, James P. Smith, Arthur Van Soest. 2013. Are Americans Really Less Happy with Their Incomes?. Review of Income

and Wealth 59:1, 44-65. [Crossref] 257. Ada Ferrer-i-Carbonell. 2013. Happiness economics. SERIEs 4:1, 35-60. [Crossref] 258. Leonardo Becchetti, Pierluigi Conzo. 2013. Credit access and life satisfaction: evaluating the nonmonetary effects of micro finance.

Applied Economics 45:9, 1201-1217. [Crossref] 259. . Mixed Effects Models 231-284. [Crossref] 260. PATRICK A. IMAM. 2013. IMPACT OF IMF-SUPPORTED PROGRAMS ON ECONOMIC SENTIMENTS: A

MULTINOMIAL ORDERED PROBIT ANALYSIS ON TRANSITION ECONOMIES. Journal of International Commerce, Economics and Policy 04:01, 1350003. [Crossref]

261. RICHARD A. EASTERLIN. 2013. HAPPINESS, GROWTH, AND PUBLIC POLICY †. Economic Inquiry 51:1, 1-15. [Crossref] 262. Chris M. Herbst. 2013. Welfare reform and the subjective well-being of single mothers. Journal of Population Economics 26:1, 203-238.

[Crossref] 263. Léandre Bouffard, Micheline Dubé. 2013. L’inégalité de revenus : un « virus » qui affecte la santé mentale et le bonheur. Santé mentale

au Québec 38:2, 215. [Crossref] 264. Patrick Stacey, David Thomas, Joe Nandhakumar. How Funny Are Games? Violent Games Content and Studio Well-Being 142-165.

[Crossref] 265. Satya Paul, Daniel Guilbert. 2013. Income–happiness paradox in Australia: Testing the theories of adaptation and social comparison.

Economic Modelling 30, 900-910. [Crossref] 266. Chaeyoon Lim, Thomas Sander. 2013. Does misery love company? Civic engagement in economic hard times. Social Science Research

42:1, 14-30. [Crossref] 267. Jorge Guardiola, Francisco González-Gómez, Ángel Lendechy Grajales. 2013. The Influence of Water Access in Subjective Well-Being:

Some Evidence in Yucatan, Mexico. Social Indicators Research 110:1, 207-218. [Crossref]

268. S. Katherine Nelson, Kostadin Kushlev, Tammy English, Elizabeth W. Dunn, Sonja Lyubomirsky. 2013. In Defense of Parenthood. Psychological Science 24:1, 3-10. [Crossref]

269. Steffen Rätzel. 2012. Labour Supply, Life Satisfaction, and the (Dis)Utility of Work*. The Scandinavian Journal of Economics 114:4, 1160-1181. [Crossref]

270. Maite Blázquez Cuesta, Santiago Budría. 2012. Deprivation and Subjective Well-Being: Evidence from Panel Data. Review of Income and Wealth n/a-n/a. [Crossref]

271. Zhiqiang Liu, Qingyan Shang. 2012. Individual well-being in urban China: The role of income expectations. China Economic Review 23:4, 833-849. [Crossref]

272. ARIE SHERMAN, TAL SHAVIT. 2012. How the lifecycle hypothesis explains volunteering during retirement. Ageing and Society 32:08, 1360-1381. [Crossref]

273. KATIE WRIGHT. 2012. Constructing human wellbeing across spatial boundaries: negotiating meanings in transnational migration. Global Networks 12:4, 467-484. [Crossref]

274. Sana El Harbi, Gilles Grolleau. 2012. Does self-employment contribute to national happiness?. The Journal of Socio-Economics 41:5, 670-676. [Crossref]

275. Leonardo Becchetti, Elena Giachin Ricca, Alessandra Pelloni. 2012. The Relationship Between Social Leisure and Life Satisfaction: Causality and Policy Implications. Social Indicators Research 108:3, 453-490. [Crossref]

276. Robert Metcalfe, Paul Dolan. 2012. Behavioural economics and its implications for transport. Journal of Transport Geography 24, 503-511. [Crossref]

277. Casey Boyd-Swan, Chris M. Herbst. 2012. Pain at the pump: Gasoline prices and subjective well-being. Journal of Urban Economics 72:2-3, 160-175. [Crossref]

278. Thomas Hansen. 2012. Parenthood and Happiness: a Review of Folk Theories Versus Empirical Evidence. Social Indicators Research 108:1, 29-64. [Crossref]

279. Daniel J Benjamin, Ori Heffetz, Miles S Kimball, Alex Rees-Jones. 2012. What Do You Think Would Make You Happier? What Do You Think You Would Choose?. American Economic Review 102:5, 2083-2110. [Crossref]

280. Christian Schubert. 2012. Is novelty always a good thing? Towards an evolutionary welfare economics. Journal of Evolutionary Economics 22:3, 585-619. [Crossref]

281. Malgorzata Switek. 2012. Life Satisfaction in Latin America: A Size-of-Place Analysis. Journal of Development Studies 48:7, 983-999. [Crossref]

282. Michael Ehrmann, Panagiota Tzamourani. 2012. Memories of high inflation. European Journal of Political Economy 28:2, 174-191. [Crossref]

283. Santiago Budría. 2012. The shadow value of employer-provided training. Journal of Economic Psychology 33:3, 494-514. [Crossref] 284. Tetsuya Matsubayashi, Michiko Ueda. 2012. Government Partisanship and Human Well-Being. Social Indicators Research 107:1,

127-148. [Crossref] 285. Ariel R. Belasen, R.W. Hafer. 2012. Well-being and economic freedom: Evidence from the States. Intelligence 40:3, 306-316. [Crossref] 286. A. Aslam, L. Corrado. 2012. The geography of well-being. Journal of Economic Geography 12:3, 627-649. [Crossref] 287. Felix FitzRoy, Jennifer Franz-Vasdeki, Elissaios Papyrakis. 2012. Climate Change Policy and Subjective Well-Being. Environmental

Policy and Governance 22:3, 205-216. [Crossref] 288. Andy Dickerson, Francis Green. 2012. Fears and realisations of employment insecurity. Labour Economics 19:2, 198-210. [Crossref] 289. Cahit Guven, Claudia Senik, Holger Stichnoth. 2012. You can’t be happier than your wife. Happiness gaps and divorce. Journal of

Economic Behavior & Organization 82:1, 110-130. [Crossref] 290. Peter Schwarz. 2012. Neighborhood effects of high unemployment rates: Welfare implications among different social groups. The

Journal of Socio-Economics 41:2, 180-188. [Crossref] 291. A. Rodriguez-Pose, K. Maslauskaite. 2012. Can policy make us happier? Individual characteristics, socio-economic factors and life

satisfaction in Central and Eastern Europe. Cambridge Journal of Regions, Economy and Society 5:1, 77-96. [Crossref] 292. Carl Davidson, Steven J. Matusz, Douglas Nelson. 2012. A Behavioral Model of Unemployment, Sociotropic Concerns, and the Political

Economy of Trade Policy. Economics & Politics 24:1, 72-94. [Crossref] 293. Luca Stanca. 2012. Suffer the little children: Measuring the effects of parenthood on well-being worldwide. Journal of Economic

Behavior & Organization 81:3, 742-750. [Crossref] 294. C. Mellander, R. Florida, J. Rentfrow. 2012. The creative class, post-industrialism and the happiness of nations. Cambridge Journal

of Regions, Economy and Society 5:1, 31-43. [Crossref] 295. Georgios Kavetsos. 2012. National Pride: War Minus the Shooting. Social Indicators Research 106:1, 173-185. [Crossref]

296. M. Gray, L. Lobao, R. Martin. 2012. Making space for well-being. Cambridge Journal of Regions, Economy and Society 5:1, 3-13. [Crossref]

297. Carsten Ochsen, Heinz Welsch. 2012. Who benefits from labor market institutions? Evidence from surveys of life satisfaction. Journal of Economic Psychology 33:1, 112-124. [Crossref]

298. Bert Van Landeghem. 2012. A test for the convexity of human well-being over the life cycle: Longitudinal evidence from a 20-year panel. Journal of Economic Behavior & Organization 81:2, 571-582. [Crossref]

299. M. A. Choudhary, P. Levine, P. McAdam, P. Welz. 2012. The happiness puzzle: analytical aspects of the Easterlin paradox. Oxford Economic Papers 64:1, 27-42. [Crossref]

300. A. Deaton. 2012. The financial crisis and the well-being of Americans: 2011 OEP Hicks Lecture*. Oxford Economic Papers 64:1, 1-26. [Crossref]

301. Matthew T. Gailliot. 2012. Happiness as Surplus or Freely Available Energy. Psychology 03:09, 702-712. [Crossref] 302. Nguyen Minh Duc  . Farmers’ Happiness from Fish Production: A Case Study in Vietnam 167-180. [Crossref] 303. Di Wang, Alistair Sutcliffe, Xiao-Jun Zeng. 2011. A trust-based multi-ego social network model to investigate emotion diffusion.

Social Network Analysis and Mining 1:4, 287-299. [Crossref] 304. CHANG-MING HSIEH. 2011. Money and happiness: does age make a difference?. Ageing and Society 31:08, 1289-1306. [Crossref] 305. Kate Ann Levin, Torbjorn Torsheim, Wilma Vollebergh, Matthias Richter, Carolyn A. Davies, Christina W. Schnohr, Pernille Due,

Candace Currie. 2011. National Income and Income Inequality, Family Affluence and Life Satisfaction Among 13 year Old Boys and Girls: A Multilevel Study in 35 Countries. Social Indicators Research 104:2, 179-194. [Crossref]

306. Tetsuya Matsubayashi, Michiko Ueda. 2011. The effect of national suicide prevention programs on suicide rates in 21 OECD nations. Social Science & Medicine 73:9, 1395-1400. [Crossref]

307. Carsten Ochsen. 2011. Subjective well-being and aggregate unemployment: further evidence. Scottish Journal of Political Economy 58:5, 634-655. [Crossref]

308. Linnea A. Polgreen, Nicole B. Simpson. 2011. Happiness and International Migration. Journal of Happiness Studies 12:5, 819-840. [Crossref]

309. Andrew E. Clark. 2011. Income and Happiness: Getting the Debate Straight. Applied Research in Quality of Life 6:3, 253-263. [Crossref] 310. Bruno S. Frey. 2011. Tullock challenges: happiness, revolutions, and democracy. Public Choice 148:3-4, 269-281. [Crossref] 311. David Madden. 2011. The Impact of an Economic Boom on the Level and Distribution of Subjective Well-Being: Ireland, 1994–

2001. Journal of Happiness Studies 12:4, 667-679. [Crossref] 312. Andreas Knabe, Steffen Rätzel. 2011. Quantifying the psychological costs of unemployment: the role of permanent income. Applied

Economics 43:21, 2751-2763. [Crossref] 313. Marina Della Giusta, Sarah Louise Jewell, Uma S. Kambhampati. 2011. Gender and Life Satisfaction in the UK. Feminist Economics

17:3, 1-34. [Crossref] 314. Fabio D’Orlando, Francesco Ferrante, Gabriele Ruiu. 2011. Culturally based beliefs and labor market institutions. The Journal of Socio-

Economics 40:2, 150-162. [Crossref] 315. PATRICK FLAVIN, ALEXANDER C. PACEK, BENJAMIN RADCLIFF. 2011. State Intervention and Subjective Well-Being in

Advanced Industrial Democracies. Politics & Policy 39:2, 251-269. [Crossref] 316. Leonardo Becchetti, Stefano Castriota, Nazaria Solferino. 2011. Development Projects and Life Satisfaction: An Impact Study on Fair

Trade Handicraft Producers. Journal of Happiness Studies 12:1, 115-138. [Crossref] 317. Francis Green. 2011. Unpacking the misery multiplier: How employability modifies the impacts of unemployment and job insecurity

on life satisfaction and mental health. Journal of Health Economics 30:2, 265-276. [Crossref] 318. John Knight, Ramani Gunatilaka. 2011. Does Economic Growth Raise Happiness in China?. Oxford Development Studies 39:1, 1-24.

[Crossref] 319. Monica Guillen-Royo. 2011. Reference group consumption and the subjective wellbeing of the poor in Peru. Journal of Economic

Psychology 32:2, 259-272. [Crossref] 320. Fabio D’Orlando. 2011. The Demand for Pornography. Journal of Happiness Studies 12:1, 51-75. [Crossref] 321. Alfred Barth, Leopold Sögner, Timo Gnambs, Michael Kundi, Andreas Reiner, Robert Winker. 2011. Socioeconomic Factors and

Suicide. Journal of Occupational and Environmental Medicine 53:3, 313-317. [Crossref] 322. Olga Stavrova, Thomas Schlösser, Detlef Fetchenhauer. 2011. Are the unemployed equally unhappy all around the world? The role of

the social norms to work and welfare state provision in 28 OECD countries. Journal of Economic Psychology 32:1, 159-171. [Crossref] 323. Leonardo Becchetti, Giovanni Trovato, David Andres Londono Bedoya. 2011. Income, relational goods and happiness. Applied

Economics 43:3, 273-290. [Crossref]

324. David G. Blanchflower, Andrew J. Oswald. 2011. International Happiness: A New View on the Measure of Performance. Academy of Management Perspectives 25:1, 6-22. [Crossref]

325. Eiji Yamamura. 2011. The Influence of Government Size on Economic Growth and Life Satisfaction. Japanese Economy 38:4, 28-64. [Crossref]

326. Franz H. Heukamp, Miguel A. Ariño. 2011. Does Country Matter for Subjective Well-Being?. Social Indicators Research 100:1, 155-170. [Crossref]

327. Yang Yang. Aging, Cohorts, and Methods 17-30. [Crossref] 328. H. Welsch. 2011. The magic triangle of macroeconomics: how do European countries score?. Oxford Economic Papers 63:1, 71-93.

[Crossref] 329. Peter H. van der Meer, Rudi Wielers. 2011. What makes workers happy?. Applied Economics 45:3, 357-368. [Crossref] 330. Mike Slade. 2010. Mental illness and well-being: the central importance of positive psychology and recovery approaches. BMC Health

Services Research 10:1. . [Crossref] 331. Yang Yang, Muhammad Waliji. 2010. Increment–Decrement Life Table Estimates of Happy Life Expectancy for the U.S. Population.

Population Research and Policy Review 29:6, 775-795. [Crossref] 332. Rafael Di Tella, John Haisken-De New, Robert MacCulloch. 2010. Happiness adaptation to income and to status in an individual

panel. Journal of Economic Behavior & Organization 76:3, 834-852. [Crossref] 333. Tim Krieger, Daniel Meierrieks. 2010. Terrorism in the Worlds of Welfare Capitalism. Journal of Conflict Resolution 54:6, 902-939.

[Crossref] 334. Liam Graham, Andrew J. Oswald. 2010. Hedonic capital, adaptation and resilience. Journal of Economic Behavior & Organization 76:2,

372-384. [Crossref] 335. Daniel M. Hausman. 2010. HEDONISM AND WELFARE ECONOMICS. Economics and Philosophy 26:03, 321-344. [Crossref] 336. Fredrik Carlsson, Olof Johansson-Stenman. 2010. Why Do You Vote and Vote as You Do?. Kyklos 63:4, 495-516. [Crossref] 337. Yasuharu Tokuda, Seiji Fujii, Takashi Inoguchi. 2010. Individual and Country-Level Effects of Social Trust on Happiness: The Asia

Barometer Survey. Journal of Applied Social Psychology 40:10, 2574-2593. [Crossref] 338. Luca Stanca. 2010. The Geography of Economics and Happiness: Spatial Patterns in the Effects of Economic Conditions on Well-

Being. Social Indicators Research 99:1, 115-133. [Crossref] 339. Bruno S. Frey, Alois Stutzer. 2010. Happiness and public choice. Public Choice 144:3-4, 557-573. [Crossref] 340. Lan Nguyen Chaplin, Wilson Bastos, Tina M. Lowrey. 2010. Beyond brands: Happy adolescents see the good in people. The Journal

of Positive Psychology 5:5, 342-354. [Crossref] 341. Andrea Salvatori. 2010. Labour contract regulations and workers’ wellbeing: International longitudinal evidence. Labour Economics

17:4, 667-678. [Crossref] 342. Zohal Hessami. 2010. The Size and Composition of Government Spending in Europe and Its Impact on Well-Being. Kyklos 63:3,

346-382. [Crossref] 343. Matthew D. Rablen. 2010. Performance targets, effort and risk-taking. Journal of Economic Psychology 31:4, 687-697. [Crossref] 344. H. Meulemann. 2010. Self-Concern, Self-Transcendence, and Well-Being. European Sociological Review 26:4, 385-399. [Crossref] 345. Luis Angeles. 2010. Children and Life Satisfaction. Journal of Happiness Studies 11:4, 523-538. [Crossref] 346. David H. Wolpert. 2010. Why income comparison is rational. Games and Economic Behavior 69:2, 458-474. [Crossref] 347. Tommy Ferrarini, Ola Sjöberg. 2010. Social policy and health: transition countries in a comparative perspective. International Journal

of Social Welfare 19, S60-S88. [Crossref] 348. Ángel Álvarez-Díaz, Lucas González, Benjamin Radcliff. 2010. The Politics of Happiness: On the Political Determinants of Quality

of Life in the American States. The Journal of Politics 72:3, 894-905. [Crossref] 349. Paul Whiteley, Harold D. Clarke, David Sanders, Marianne C. Stewart. 2010. Government Performance and Life Satisfaction in

Contemporary Britain. The Journal of Politics 72:3, 733-746. [Crossref] 350. Michael McBride. 2010. Money, happiness, and aspirations: An experimental study. Journal of Economic Behavior & Organization

74:3, 262-276. [Crossref] 351. Xiangmin Liu, Scott Thomas, Liang Zhang. 2010. College Quality, Earnings, and Job Satisfaction: Evidence from Recent College

Graduates. Journal of Labor Research 31:2, 183-201. [Crossref] 352. Hilke Brockmann. 2010. Why are Middle-Aged People so Depressed? Evidence from West Germany. Social Indicators Research 97:1,

23-42. [Crossref]

353. Andrew E. Clark, Claudia Senik. 2010. Who Compares to Whom? The Anatomy of Income Comparisons in Europe*. The Economic Journal 120:544, 573-594. [Crossref]

354. Meike Bartels, Viatcheslav Saviouk, Marleen H. M. de Moor, Gonneke Willemsen, Toos C. E. M. van Beijsterveldt, Jouke-Jan Hottenga, Eco J. C. de Geus, Dorret I. Boomsma. 2010. Heritability and Genome-Wide Linkage Scan of Subjective Happiness. Twin Research and Human Genetics 13:02, 135-142. [Crossref]

355. M. Grazia Pittau, Roberto Zelli, Andrew Gelman. 2010. Economic Disparities and Life Satisfaction in European Regions. Social Indicators Research 96:2, 339-361. [Crossref]

356. Georgios Kavetsos, Stefan Szymanski. 2010. National well-being and international sports events. Journal of Economic Psychology 31:2, 158-171. [Crossref]

357. Fabio D’Orlando. 2010. Swinger economics. The Journal of Socio-Economics 39:2, 295-305. [Crossref] 358. Sonali Bhattacharya. 2010. Relationship between Three Indices of Happiness. Journal of Human Values 16:1, 87-125. [Crossref] 359. T. Hinks. 2010. Job Satisfaction and Employment Equity in South Africa. Journal of African Economies 19:2, 237-255. [Crossref] 360. INGEBJØRG KRISTOFFERSEN. 2010. The Metrics of Subjective Wellbeing: Cardinality, Neutrality and Additivity. Economic

Record 86:272, 98-123. [Crossref] 361. Christian Bjørnskov. 2010. How Comparable are the Gallup World Poll Life Satisfaction Data?. Journal of Happiness Studies 11:1,

41-60. [Crossref] 362. Leonardo Becchetti, Stefano Castriota, Giovanni Osea Giuntella. 2010. The effects of age and job protection on the welfare costs of

inflation and unemployment. European Journal of Political Economy 26:1, 137-146. [Crossref] 363. R. Layard. 2010. Measuring Subjective Well-Being. Science 327:5965, 534-535. [Crossref] 364. Irena Grosfeld, Claudia Senik. 2010. The emerging aversion to inequality. Economics of Transition 18:1, 1-26. [Crossref] 365. Lena Malesevic Perovic, Sivia Golem. 2010. Investigating Macroeconomic Determinants of Happiness in Transition Countries. Eastern

European Economics 48:4, 59-75. [Crossref] 366. Leonardo Becchetti, Fiammetta Rossetti, Stefano Castriota. 2010. Real household income and attitude toward immigrants: an empirical

analysis. The Journal of Socio-Economics 39:1, 81-88. [Crossref] 367. Therese Jefferson, J. E. King. 2010. Can Post Keynesians make better use of behavioral economics?. Journal of Post Keynesian Economics

33:2, 211-234. [Crossref] 368. Emyr Williams, Leslie Francis, Andrew Village. 2010. Marriage, religion and human flourishing: how sustainable is the classic

Durkheim thesis in contemporary Europe?. Mental Health, Religion & Culture 13:1, 93-104. [Crossref] 369. Hans-Jürgen Engelbrecht. 2009. Natural capital, subjective well-being, and the new welfare economics of sustainability: Some evidence

from cross-country regressions. Ecological Economics 69:2, 380-388. [Crossref] 370. Y.H. Farzin. 2009. The effect of non-pecuniary motivations on labor supply. The Quarterly Review of Economics and Finance 49:4,

1236-1259. [Crossref] 371. Meike Bartels, Dorret I. Boomsma. 2009. Born to be Happy? The Etiology of Subjective Well-Being. Behavior Genetics 39:6, 605-615.

[Crossref] 372. Michael W. M. Roos. 2009. Die deutsche Fiskalpolitik w��hrend der Wirtschaftskrise 2008/2009. Perspektiven der Wirtschaftspolitik

10:4, 389-412. [Crossref] 373. Claudia Senik. 2009. Direct evidence on income comparisons and their welfare effects. Journal of Economic Behavior & Organization

72:1, 408-424. [Crossref] 374. Yujun Dong, Peng Yin. Research on Chinese Citizens’ Happiness Based on B-P Neural Networks 1-4. [Crossref] 375. Maurizio Pugno. 2009. The Easterlin paradox and the decline of social capital: An integrated explanation. The Journal of Socio-

Economics 38:4, 590-600. [Crossref] 376. Björn Frank, Takao Enkawa. 2009. Does economic growth enhance life satisfaction? The case of Germany. International Journal of

Sociology and Social Policy 29:7/8, 313-329. [Crossref] 377. Wen‐Chun Chang. 2009. Social capital and subjective happiness in Taiwan. International Journal of Social Economics 36:8, 844-868.

[Crossref] 378. James Copestake, Monica Guillen-Royo, Wan-Jung Chou, Tim Hinks, Jackeline Velazco. 2009. The Relationship Between Economic

and Subjective Wellbeing Indicators in Peru. Applied Research in Quality of Life 4:2, 155-177. [Crossref] 379. Tony Dolphin. 2009. Progress and well-being. Public Policy Research 16:2, 127-132. [Crossref] 380. Christopher K Hsee, Yang Yang, Naihe Li, Luxi Shen. 2009. Wealth, Warmth, and Well-Being: Whether Happiness Is Relative

or Absolute Depends on Whether It Is About Money, Acquisition, or Consumption. Journal of Marketing Research 46:3, 396-409. [Crossref]

381. Andrew Clark, Fabien Postel-Vinay. 2009. Job security and job protection. Oxford Economic Papers 61:2, 207-239. [Crossref] 382. Bert G. M Van Landeghem. 2009. The Course of Subjective Well-Being over the Life Cycle. Schmollers Jahrbuch 129:2, 261-267.

[Crossref] 383. Michael A. Shields, Stephen Wheatley Price, Mark Wooden. 2009. Life satisfaction and the economic and social characteristics of

neighbourhoods. Journal of Population Economics 22:2, 421-443. [Crossref] 384. Björn Frank, Takao Enkawa. 2009. Economic drivers of dwelling satisfaction. International Journal of Housing Markets and Analysis

2:1, 6-20. [Crossref] 385. Mark Wooden, Diana Warren, Robert Drago. 2009. Working Time Mismatch and Subjective Well-being. British Journal of Industrial

Relations 47:1, 147-179. [Crossref] 386. Hung-Lin Tao, Shih-Yung Chiu. 2009. The Effects of Relative Income and Absolute Income on Happiness. Review of Development

Economics 13:1, 164-174. [Crossref] 387. Fabio D’Orlando, Francesco Ferrante. 2009. The demand for job protection. The Journal of Socio-Economics 38:1, 104-114. [Crossref] 388. Leonardo Becchetti, Fiammetta Rossetti. 2009. When money does not buy happiness: The case of “frustrated achievers”. The Journal

of Socio-Economics 38:1, 159-167. [Crossref] 389. Yasuharu Tokuda, Masamine Jimba, Haruo Yanai, Seiji Fujii, Takashi Inoguchi. 2008. Interpersonal Trust and Quality-of-Life: A

Cross-Sectional Study in Japan. PLoS ONE 3:12, e3985. [Crossref] 390. Olof Johansson-Stenman. 2008. Who are the trustworthy, we think?. Journal of Economic Behavior & Organization 68:3-4, 456-465.

[Crossref] 391. Yang Yang. 2008. Long and happy living: Trends and patterns of happy life expectancy in the U.S., 1970–2000. Social Science Research

37:4, 1235-1252. [Crossref] 392. Martin Hiermeyer. 2008. The trade-off between a high and an equal biological standard of living—Evidence from Germany. Economics

& Human Biology 6:3, 431-445. [Crossref] 393. Monica Guillen-Royo. 2008. Consumption and Subjective Wellbeing: Exploring Basic Needs, Social Comparison, Social Integration

and Hedonism in Peru. Social Indicators Research 89:3, 535-555. [Crossref] 394. KAISA KOTAKORPI, JANI-PETRI LAAMANEN. 2008. Welfare State and Life Satisfaction: Evidence from Public Health Care.

Economica . [Crossref] 395. Yasuharu Tokuda, Takashi Inoguchi. 2008. Interpersonal Mistrust and Unhappiness Among Japanese People. Social Indicators Research

89:2, 349-360. [Crossref] 396. Tim Hinks, Simon Davies. 2008. Life satisfaction in Malawi and the importance of relative consumption, polygamy and religion.

Journal of International Development 20:7, 888-904. [Crossref] 397. Alexander C. Pacek, Benjamin Radcliff. 2008. Welfare Policy and Subjective Well-Being Across Nations: An Individual-Level

Assessment. Social Indicators Research 89:1, 179-191. [Crossref] 398. Yelena Kalyuzhnova, Uma Kambhampati. 2008. The determinants of individual happiness in Kazakhstan. Economic Systems 32:3,

285-299. [Crossref] 399. Sibel Selim. 2008. Life Satisfaction and Happiness in Turkey. Social Indicators Research 88:3, 531-562. [Crossref] 400. Nattavudh Powdthavee. 2008. Putting a price tag on friends, relatives, and neighbours: Using surveys of life satisfaction to value social

relationships. The Journal of Socio-Economics 37:4, 1459-1480. [Crossref] 401. Alan B. Krueger, David A. Schkade. 2008. The reliability of subjective well-being measures. Journal of Public Economics 92:8-9,

1833-1845. [Crossref] 402. R. Layard, G. Mayraz, S. Nickell. 2008. The marginal utility of income. Journal of Public Economics 92:8-9, 1846-1857. [Crossref] 403. CLAUDIA SENIK. 2008. Ambition and Jealousy: Income Interactions in the âOldâ Europe versus the âNewâ Europe and the United

States. Economica 75:299, 495-513. [Crossref] 404. PAUL DOLAN, ROBERT METCALFE, VICKI MUNRO, MICHAEL C. CHRISTENSEN. 2008. Valuing lives and life years:

anomalies, implications, and an alternative. Health Economics, Policy and Law 3:03. . [Crossref] 405. Heinz Welsch. 2008. The welfare costs of corruption. Applied Economics 40:14, 1839-1849. [Crossref] 406. Petra Böhnke. 2008. Does Society Matter? Life Satisfaction in the Enlarged Europe. Social Indicators Research 87:2, 189-210. [Crossref] 407. Andrew J. Oswald, Nattavudh Powdthavee. 2008. Does happiness adapt? A longitudinal study of disability with implications for

economists and judges. Journal of Public Economics 92:5-6, 1061-1077. [Crossref] 408. AYDOGAN ULKER. 2008. MENTAL HEALTH AND LIFE SATISFACTION OF YOUNG AUSTRALIANS: THE ROLE OF

FAMILY BACKGROUND. Australian Economic Papers 47:2, 199-218. [Crossref]

409. Alexander Pacek, Benjamin Radcliff. 2008. Assessing the Welfare State: The Politics of Happiness. Perspectives on Politics 6:02. . [Crossref]

410. Heinz Welsch, Udo Bonn. 2008. Economic convergence and life satisfaction in the European Union. The Journal of Socio-Economics 37:3, 1153-1167. [Crossref]

411. Claude S. Fischer. 2008. What wealth-happiness paradox? A short note on the American case. Journal of Happiness Studies 9:2, 219-226. [Crossref]

412. Paul Dolan, Tessa Peasgood. 2008. Measuring Well‐Being for Public Policy: Preferences or Experiences?. The Journal of Legal Studies 37:S2, S5-S31. [Crossref]

413. Andrew J. Oswald, Nattavudh Powdthavee. 2008. Death, Happiness, and the Calculation of Compensatory Damages. The Journal of Legal Studies 37:S2, S217-S251. [Crossref]

414. Christopher K. Hsee, Fei Xu, Ningyu Tang. 2008. Two Recommendations on the Pursuit of Happiness. The Journal of Legal Studies 37:S2, S115-S132. [Crossref]

415. David G. Blanchflower, Andrew J. Oswald. 2008. Is well-being U-shaped over the life cycle?. Social Science & Medicine 66:8, 1733-1749. [Crossref]

416. Rafael Di Tella, Robert MacCulloch. 2008. Gross national happiness as an answer to the Easterlin Paradox?. Journal of Development Economics 86:1, 22-42. [Crossref]

417. Yang Yang. 2008. Social Inequalities in Happiness in the United States, 1972 to 2004: An Age-Period-Cohort Analysis. American Sociological Review 73:2, 204-226. [Crossref]

418. David G. Blanchflower, Andrew J. Oswald. 2008. Hypertension and happiness across nations. Journal of Health Economics 27:2, 218-233. [Crossref]

419. Andrew E Clark, Paul Frijters, Michael A Shields. 2008. Relative Income, Happiness, and Utility: An Explanation for the Easterlin Paradox and Other Puzzles. Journal of Economic Literature 46:1, 95-144. [Crossref]

420. Paul Dolan, Tessa Peasgood, Mathew White. 2008. Do we really know what makes us happy? A review of the economic literature on the factors associated with subjective well-being. Journal of Economic Psychology 29:1, 94-122. [Crossref]

421. Katrin Rehdanz, David Maddison. 2008. Local environmental quality and life-satisfaction in Germany. Ecological Economics 64:4, 787-797. [Crossref]

422. Camelia Minoiu, Antonio Rodríguez Andrés. 2008. The effect of public spending on suicide: Evidence from U.S. state data. The Journal of Socio-Economics 37:1, 237-261. [Crossref]

423. Lars Osberg. Leisure 1-6. [Crossref] 424. Bernard M. S. van Praag, Ada Ferrer-i-Carbonell. A Multidimensional Approach to Subjective Poverty 135-154. [Crossref] 425. Yasuharu Tokuda, Takashi Inoguchi. 2008. Trust in the Mass Media and the Healthcare System, Interpersonal Trust and Self-Rated

Health: A Population-Based Study in Japan. Asian Journal of Epidemiology 1:1, 29-39. [Crossref] 426. Bryan Roberts. Measuring Welfare 103-138. [Crossref] 427. EMMA SAMMAN. 2007. Psychological and Subjective Well-being: A Proposal for Internationally Comparable Indicators. Oxford

Development Studies 35:4, 459-486. [Crossref] 428. Christian Bjørnskov, Axel Dreher, Justina A. V. Fischer. 2007. Cross-country determinants of life satisfaction: exploring different

determinants across groups in society. Social Choice and Welfare 30:1, 119-173. [Crossref] 429. Timothy Hinks, Carola Gruen. 2007. What is the Structure of South African Happiness Equations? Evidence from Quality of Life

Surveys. Social Indicators Research 82:2, 311-336. [Crossref] 430. Christian Bjørnskov, Axel Dreher, Justina A. V. Fischer. 2007. The bigger the better? Evidence of the effect of government size on

life satisfaction around the world. Public Choice 130:3-4, 267-292. [Crossref] 431. Nattavudh Powdthavee. 2007. Are there Geographical Variations in the Psychological Cost of Unemployment in South Africa?. Social

Indicators Research 80:3, 629-652. [Crossref] 432. Michael Kaser. East Germany’s Economic Transition in Comparative Perspective 229-239. [Crossref] 433. Kevin Daniels, Olga Tregaskis, Jonathan S. Seaton. 2007. Job control and occupational health: the moderating role of national R&D

activity. Journal of Organizational Behavior 28:1, 1-19. [Crossref] 434. Jonathan Gardner, Andrew J. Oswald. 2007. Money and mental wellbeing: A longitudinal study of medium-sized lottery wins. Journal

of Health Economics 26:1, 49-60. [Crossref] 435. Ada Ferrer-i-Carbonell, John M. Gowdy. 2007. Environmental degradation and happiness. Ecological Economics 60:3, 509-516.

[Crossref]

436. Patrick A. Imam. 2007. Effect of IMF Structural Adjustment Programson Expectations: The Case of Transition Economies. IMF Working Papers 07:261, 1. [Crossref]

437. Paul Frijters, Ingo Geishecker, John P. Haisken-DeNew, Michael A. Shields. 2006. Can the Large Swings in Russian Life Satisfaction be Explained by Ups and Downs in Real Incomes?. Scandinavian Journal of Economics 108:3, 433-458. [Crossref]

438. Carl Davidson, Steve Matusz, Doug Nelson. 2006. Fairness and the Political Economy of Trade. The World Economy 29:8, 989-1004. [Crossref]

439. Ann L. Owen, Julio Videras. 2006. Civic cooperation, pro-environment attitudes, and behavioral intentions. Ecological Economics 58:4, 814-829. [Crossref]

440. James McConvill. 2006. Executive Compensation and Corporate Governance: Rising Above the “Pay-for-Performance” Principle. American Business Law Journal 43:2, 413-438. [Crossref]

441. Claire A. Montgomery, Ted L. Helvoigt. 2006. Changes in attitudes about importance of and willingness to pay for salmon recovery in Oregon. Journal of Environmental Management 78:4, 330-340. [Crossref]

442. Rafael Di Tella, Robert MacCulloch. 2006. Some Uses of Happiness Data in Economics. Journal of Economic Perspectives 20:1, 25-46. [Crossref]

443. Claudia Senik. 2006. Journal of Economic Behavior & Organization 59:1, 147-151. [Crossref] 444. Claudia Senik. 2006. Ambition et jalousie. La perception du revenu d’autrui dans la « vieille Europe », la « nouvelle Europe » et les

États-Unis. Revue économique 57:3, 645. [Crossref] 445. David G. Blanchflower, Andrew J. Oswald. 2005. Happiness and the Human Development Index: The Paradox of Australia. The

Australian Economic Review 38:3, 307-318. [Crossref] 446. Nattavudh Powdthavee. 2005. Unhappiness and Crime: Evidence from South Africa. Economica 72:287, 531-547. [Crossref] 447. Bruno S Frey, Alois Stutzer. 2005. Happiness Research: State and Prospects. Review of Social Economy 63:2, 207-228. [Crossref] 448. Claudia Senik. 2005. Income distribution and well-being: what can we learn from subjective data?. Journal of Economic Surveys 19:1,

43-63. [Crossref] 449. Katrin Rehdanz, David Maddison. 2005. Climate and happiness. Ecological Economics 52:1, 111-125. [Crossref] 450. David G. Blanchflower, Andrew J. Oswald. 2004. Money, Sex and Happiness: An Empirical Study. Scandinavian Journal of Economics

106:3, 393-415. [Crossref] 451. Adriano Ciani, Francesco Diotallevi, Lucia Rocchi, Anna Maria Grigore, Cinzia Coduti, Elisa Belgrado. Corporate Social Responsibility

(CSR) 1500-1525. [Crossref] 452. Adriano Ciani, Francesco Diotallevi, Lucia Rocchi, Anna Maria Grigore, Cinzia Coduti, Elisa Belgrado. Corporate Social Responsibility

(CSR) 166-190. [Crossref]