The economics of happiness is an approach to assessing welfare that combines the techniques typically used by economists with those more commonly used by psychologists.
While psychologists have long used surveys of reported well-being to study happiness, economists only recently ventured into this arena. Early economists and philosophers, ranging from Aristotle (384–322 BCE) to Adam Smith (1723–1790), Jeremy Bentham (1748–1832), and John Stuart Mill (1806–1873), incorporated the pursuit of happiness in their work. Yet, as economics grew more rigorous and quantitative, more parsimonious definitions of welfare took hold. Utility was taken to depend only on income as mediated by individual choices or preferences within a rational individual’s budget constraint.
The study of happiness or subjective well-being is part of a more general move in economics that challenges these narrow assumptions. The introduction of bounded rationality and the establishment of behavioral economics opened new lines of research. Happiness economics —which represents one new direction—relies on more expansive notions of utility and welfare, including interdependent utility functions, procedural utility, and the interaction between rational and nonrational influences.
Richard Easterlin was the first modern economist to revisit the concept of happiness, beginning in the early 1970s. More generalized interest took hold in the late 1990s (see, among others, Easterlin 1974, 2003; Blanchflower and Oswald 2004; Clark and Oswald 1994; Frey and Stutzer 2002a; Graham and Pettinato 2002; and Layard 2005).
The approach does not purport to replace income-based measures of welfare but instead to complement them with broader measures. These measures are based on the results of large-scale surveys, across countries and over time, of hundreds of thousands of individuals. The surveys provide information about the importance of a range of factors that affect well-being, including income but also others, such as health, marital and employment status, and civic trust.
The approach, which relies on expressed preferences rather than on revealed choices, is particularly well suited to answering questions in areas where a revealed-preferences approach provides limited information. Indeed, it often uncovers discrepancies between expressed and revealed preferences. Revealed preferences cannot fully gauge the welfare effects of particular policies or institutional arrangements that individuals are powerless to change. Examples of these include the welfare effects of inequality, environmental degradation, and macroeconomic policies. Amartya Sen’s (1995) capabilities-based approach to poverty, for example, highlights the lack of capacity of the poor to make choices or to take certain actions. Another area where a choice approach is limited is the welfare effects of addictive behaviors such as smoking and drug abuse.
Happiness surveys are based on questions in which the individual is asked, “Generally speaking, how happy are you with your life?” or “How satisfied are you with your life?” with possible answers on a four- to seven-point scale. The answers to happiness and life satisfaction questions correlate closely—ranging between .56 and .50 (Blanchflower and Oswald 2004; Graham and Pettinato 2002).
This approach presents several methodological challenges (Bertrand and Mullainathan 2001; Frey and Stutzer 2002b). To minimize order bias, happiness questions must be placed at the beginning of surveys. As with all economic measurements, the answer of any specific individual may be biased by idiosyncratic, unobserved events. Bias in answers to happiness surveys can also result from unobserved personality traits and correlated measurement errors (which can be corrected via individual fixed effects if and when panel data are available).
Despite the potential pitfalls, cross sections of large samples across countries and over time find remarkably consistent patterns in the determinants of happiness. Many errors are uncorrelated with the observed variables, and do not systematically bias the results. Psychologists also find validation in the way that people answer these surveys based in physiological measures of happiness, such as the number of “genuine”—Duchenne—smiles (Diener and Seligman 2004).
Microeconometric happiness equations have the standard form: W it = α + β x it + є it, where W is the reported well-being of individual i at time t, and X is a vector of known variables including sociodemographic and socioeconomic characteristics. Unobserved characteristics and measurement errors are captured in the error term. Because the answers to happiness surveys are ordinal rather than cardinal, they are best analyzed via ordered logit or probit equations. These regressions typically yield lower R-squares than economists are used to, reflecting the extent to which emotions and other components of true well-being are driving the results, as opposed to the variables that we are able to measure, such as income, education, and marital and employment status.
The availability of panel data in some instances, as well as advances in econometric techniques, are increasingly allowing for sounder analysis (van Praag and Ferrer-i-Carbonell 2004). The coefficients produced from ordered probit or logistic regressions are remarkably similar to those from OLS regressions based on the same equations. While it is impossible to measure the precise effects of independent variables on true well-being, happiness researchers have used the OLS coefficients as a basis for assigning relative weights to them. They can estimate how much income a typical individual in the United States or Britain would need to produce the same change in stated happiness that comes from the well-being loss resulting from, for example, divorce ($100,000) or job loss ($60,000) (Blanchflower and Oswald 2004).
In his original study, Richard Easterlin revealed a paradox that sparked interest in the topic but is as yet unresolved. While most happiness studies find that within countries wealthier people are, on average, happier than poor ones, studies across countries and over time find very little, if any, relationship between increases in per capita income and average happiness levels. On average, wealthier countries (as a group) are happier than poor ones (as a group); happiness seems to rise with income up to a point, but not beyond it. Yet even among the less happy, poorer countries, there is not a clear relationship between average income and average happiness levels, suggesting that many other factors—including cultural traits—are at play (see Figure 1).
Within countries, income matters to happiness (Oswald 1997; Diener et al. 2003). Deprivation and abject poverty in particular are very bad for happiness. Yet after basic needs are met, other factors such as rising aspirations, relative income differences, and the security of gains become increasingly important in addition to
income. James Duesenberry (1949) noted the impact of changing aspirations on income satisfaction and its potential effects on consumption and savings rates. A number of happiness studies have since confirmed the effects of rising aspirations, and their potential role in driving excessive consumption and other perverse economic behaviors (Frank 1999).
A common interpretation of the Easterlin paradox is that humans are on a “hedonic treadmill”: aspirations increase along with income and, after basic needs are met, relative levels of income matter to well-being. Psychologists’ “set point” theory of happiness, in which every individual is presumed to have a happiness level that he or she goes back to over time, even after major events such as winning the lottery or getting divorced (Easterlin 2003), provides a complementary interpretation.
Individuals are remarkably adaptable and in the end can get used to most things, and in particular to income gains (Kahneman et al. 1999). Easterlin argues that individuals adapt more in the pecuniary arena than in the nonpecuniary arena. Yet, because most policy is based on pecuniary factors, measures of well-being underestimate the effects of non-income factors, such as health, family, and stable employment.
There is no consensus about which interpretation is most accurate. Yet numerous studies demonstrate that happiness levels can change significantly in response to a variety of factors. Even under the rubric of set point theory, happiness levels can fall significantly in the aftermath of events like illness or unemployment. Even if levels eventually adapt upward to a longer-term equilibrium, mitigating or preventing the unhappiness and disruption that individuals experience for months, or even years, in the interim certainly seems a worthwhile objective for policy.
Happiness research has been applied to a range of issues. These include the relationship between income and happiness, the relationship between inequality and poverty, the effects of macropolicies on individual welfare, and the effects of public policies aimed at controlling addictive substances.
Some studies have attempted to separate the effects of income from those of other endogenous factors, such as satisfaction in the workplace. Studies of unexpected lottery gains find that these isolated gains have positive effects on happiness, although it is not clear that they are of a lasting nature (Gardner and Oswald 2001). Other studies have explored the reverse direction of causality, and find that people with higher happiness levels tend to perform better in the labor market and to earn more income (Diener et al. 2003; Graham, Eggers, and Sukhtankar 2004).
A related question is how income inequality affects individual welfare. Most studies of OECD (Organization for Economic Cooperation and Development) countries find that inequality has modest or insignificant effects on happiness. The mixed results may reflect the fact that inequality can be a signal of future opportunity and mobility as much as it can be a sign of injustice (Alesina et al. 2004). In contrast, recent research on Latin America finds that inequality is negative for the well-being of the poor and positive for the rich. In a region with high inequality and weak public institutions and labor markets, inequality signals persistent disadvantage or advantage rather than future opportunity (Graham and Felton 2005).
Happiness surveys also facilitate the measurement of the effects of non-income components of inequality, such as race, gender, and status, all of which seem to be highly significant (Graham and Felton 2005). Relative social standing, meanwhile, has significant effects on health outcomes (Marmot 2004).
Happiness research can deepen our understanding of poverty. The set point theory suggests that a destitute peasant can be very happy. While this contradicts a standard finding in the literature—namely, that poor people are less happy than wealthier people within countries—it is suggestive of the role that low expectations play in explaining persistent poverty in some cases.
Perceptions of poverty vary. People who are high up the income ladder can identify themselves as poor, while many of those who are below the objective poverty line do not, because of different expectations (Rojas 2004). In addition, the well-being of those who have escaped poverty is often undermined by insecurity, and their reported well-being is often lower than that of the poor (Graham and Pettinato 2002).
Most studies find that inflation and unemployment have negative effects on happiness. The effects of unemployment are stronger than those of inflation, and hold above and beyond those of forgone income (Di Tella et al. 2001). The standard “misery index,” which assigns equal weight to inflation and unemployment, may be underestimating the effects of the latter (Frey and Stutzer 2002b).
Political arrangements also matter. Both trust and freedom have positive effects on happiness (Helliwell 2003; Layard 2005). Research based on voting across cantons in Switzerland finds that there are positive effects from participating in direct democracy (Frey and Stutzer 2002b). Research in Latin America finds a strong positive correlation between happiness and preference for democracy (Graham and Sukhtankar 2004).
Happiness surveys can also be utilized to gauge the welfare effects of various public policies. How does a tax on addictive substances, such as tobacco and alcohol, for example, affect well-being? A recent study on cigarette taxes suggests that the negative financial effects may be outweighed by positive self-control effects (Gruber and Mullainathan 2002).
Richard Layard (2005) makes a bold statement about the potential of happiness research to improve people’s lives directly via changes in public policy. He highlights the extent to which people’s happiness is affected by status— resulting in a rat race approach to work and to income gains, which in the end reduces well-being. He also notes the strong positive role of security in the workplace and in the home, and of the quality of social relationships and trust. He identifies direct implications for fiscal and labor market policy—in the form of taxation on excessive income gains and via reevaluating the merits of performance-based pay.
While not all agree with Layard’s specific recommendations, there is nascent consensus that happiness surveys can serve as an important complementary tool for public policy. Scholars such as Ed Diener and Martin Seligman (2004) and Daniel Kahneman and his colleagues (2004) advocate the creation of national well-being accounts to complement income accounts.
Still, a sound note of caution is necessary in directly applying the findings of happiness research to policy, both because of the potential biases in survey data and because of the difficulties associated with analyzing this kind of data in the absence of controls for unobservable personality traits. In addition, happiness surveys at times yield anomalous results that provide novel insights into human psychology—such as adaptation and coping during economic crises—but do not translate into viable policy recommendations. One example is the finding that unemployed respondents are happier (or less unhappy) in contexts with higher unemployment rates. The positive effect that reduced stigma has on the well-being of the unemployed outweighs the negative effects of a lower probability of future employment (Clark and Oswald 1994; Stutzer and Lalive 2004; and Eggers et al. 2006). One interpretation of these results for policy—raising unemployment rates—would obviously be a mistake. At the same time, the research suggests a new focus on the effects of stigma on the welfare of the unemployed. Happiness economics also opens a field of research questions that still need to be addressed, including the implications of well-being findings for national indicators and economic growth patterns; the effects of happiness on behavior such as work effort, consumption, and investment; and the effects on political behavior.
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"Happiness." International Encyclopedia of the Social Sciences. . Encyclopedia.com. (November 18, 2017). http://www.encyclopedia.com/social-sciences/applied-and-social-sciences-magazines/happiness
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See also 28. ATTITUDES ; 279. MOODS
- a state of tranquility free from anxiety and emotional disturbance. —ataractic, ataraxic, adj.
- an inability to be happy. —athedonic, adj.
- an extreme love for gaiety.
- an abnormal fear of gaiety.
- eudemonics, eudaemonics
- 1. an art or means of acquiring happiness; eudemonism.
- 2. the theory of happiness. —eudemonia, n. —eudemonic, eudemonical, adj.
- eudemonism, eudaemonism
- Ethics. a moral system based upon the performance of right actions to achieve happiness. —eudemonist, eudaemonist, n.
- euphoria, euphory
- 1. a state of happiness and well-being.
- 2. Psychiatry. an exaggerated state of happiness, with no foundation in truth or reality. —euphoric, adj.
- the quality or condition of being merry or cheerful. —jocund, adj.
- Obsolete, a person who leads a merry life.
- 1. the quality or state of being merry or jovial.
- 2. festivity.
- Obsolete. the condition or act of being pleasant.
- the practice of making others happy through praise and felicitation. —macarize, v.
"Happiness." -Ologies and -Isms. . Encyclopedia.com. (November 18, 2017). http://www.encyclopedia.com/education/dictionaries-thesauruses-pictures-and-press-releases/happiness
"Happiness." -Ologies and -Isms. . Retrieved November 18, 2017 from Encyclopedia.com: http://www.encyclopedia.com/education/dictionaries-thesauruses-pictures-and-press-releases/happiness