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Social Indicators Research

Erschienen in:

01.12.2011

The Heterogeneous Effects of Income Changes on Happiness

verfasst von: Leonardo Becchetti, Luisa Corrado, Fiammetta Rossetti

Erschienen in: Social Indicators Research | Ausgabe 3/2011

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Abstract

We investigate the relationship between money and happiness across the waves of the British Household Panel Study by using a latent class approach which accounts for slope heterogeneity. Our findings reveal the presence of a vast majority of “Easterlin-type” individuals with positive but very weak relationship between changes in income and changes in happiness and a small minority (2 percent) of “frustrated achievers” with negative relationship. Such share is much below descriptive evidence on frustrated achievement (17.5 percent). The probability of belonging to such group is shown to be positively related with divorced status and negatively related to education and relative (personal to reference group) income. Our interpretation of these results is that the standard concave money-happiness relationship provides a partial and incomplete picture of the complex nexus between happiness and income as it does not take into account two important phenomena: the role of peers and of reference group income and that of the dynamics between realisations and expectations.

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Utility and happiness are not exactly the same concept. But, by definition, something is useful if it enhances our wellbeing and life satisfaction. Therefore, a straightforward link between utility and happiness may be easily established and such link is conventionally assumed in most of the happiness literature.

This is the case for instance of first order stochastic dominance.

By focusing on this last group of people and analyzing the determinants of frustrated achievement we may provide evidence which sheds light on the problematic side of the income-happiness relationship. More specifically, with the latent class approach, we may discover that the aggregate weak impact of income on happiness (obtained under the assumption of slope homogeneity) found in many papers may depend not only on the above mentioned dampening effects and concurring factors, but also on the existence and growth of a group of “frustrated achievers”. The identification of such group and the analysis of the factors affecting their attitude as well as that of the alternative group of “satisfied achievers” may provide useful policy advices to policymakers which are sometime surprised by the lack of positive reaction in terms of electoral consensus of good economic performances.

Consider however that racial differences within the UK may be a factor of heterogeneity as serious as that existing in intercountry comparisons. This does not allow us to overcome completely the problem.

The BHPS is an annual survey consisting of a nationally representative sample of about 5,500 households recruited in 1991, containing a total of approximately 10,000 interviewed individuals. The sample is a stratified clustered design drawn from the Postcode Address File and all residents present at those addresses at the first wave of the survey were designated as panel members. These same individuals are re-interviewed each successive year and, if they split-off from original households to form new households, they are followed and all adult members of these households are also interviewed.

The survey covers both individual and households in the UK. The main topics covered are: (1) Individual details—core subjects include neighborhood and individual demographics, current employment, labor and non-labour income, health and caring , employment history, values and opinions. Continuous measures of income and employment histories over the life of the survey; (2) Household details—core subjects include size and condition of dwelling, ownership, housing costs, consumer durable. Rotating core (cyclical every two waves—individual questionnaire. (3) Health and caring—attitude towards cost/payments for health care. Distribution of wealth—social justice, government’s roles and responsibilities, environment, management of household expenditures.

Summary statistics of database variables used in our empirical analysis are presented in Table 2.

However, several authors come in support of the plausibility of interpersonal cardinal comparability by arguing that individuals are able to recognize or predict self declared happiness of others (Ferrer-i-Carbonell 2005; Ferrer-i-Carbonell and Frijters 2004; Diener et al. 1999a) and translate verbal labels moreless into the same numerical values.

For the estimation we use the package Generalised Linear and Latent Mixed Models (GLLAMM), see http://www.gllamm.org. We carried the estimations in this section using Stata 9.2. The family link in the estimation is gaussian.

We control for household member effects by introducing the number of children and family status among regressors in the group membership equation. We prefer this approach to the use of a household equivalised income since it is more flexible and does not impose arbitrary structure to our variables. A robustness check using real personal income is also performed with results which are not substantially different from those shown here.

The table shows that, when the number of groups is above two, the probability of inclusion in some of the groups is almost nil.

As it is common in this literature, we assume that our dependent variable has enough variation to be approximated by a continuous one and therefore we estimate a model in which the link is gaussian.

We use the them “Easterlin types” because our estimate provides indirect evidence that the impact of income change on happiness is relatively small, consistently with the well known empirical evidence of the “Easterlin paradox” showing that the share of very happy US citizens has remained constant and slightly declined in the postwar period, notwithstanding the sustained increase in per capita income

Such elasticity is different from the total coefficient of the estimate presented in Table 6 since the latter is drawn from a linear-logarithmic estimate.

Actually the sign of the relationship also implies cases in which reductions of income reduce the probability of a negative change in happiness and therefore individuals of this group are both “frustrated achievers” and “satisfied losers”. We keep on defining them as frustrated achievers for simplicity.

Consider that it is much easier to find many individual-year cases in which we observe both positive changes in happiness and negative changes in income than situations in which, for a given individual, a regression of changes in income on changes in happiness across the overall sample period exhibits a significant and negative coefficient. In the first case we may have a spurious temporary negative association between the two variables, in the second case we have a non spurious relationship (random components in the mixture approach capture effects of omitted variables) which is calculated over a long time period.

We introduce both socio-economic status and income in the same equation as they are mildly correlated (−0.24 with real household income and −0.30 with real personal income).

Another criteria uses location to identify reference-groups. Blanchflower and Oswald (2004) use GSS data over the 1972–1998 period, and use average income by US State as reference group income. Aslam and Corrado (2007) use regions as reference group income. Luttmer (2005) follows a geographic approach as well, and calculates average income by local area identified in several waves of the US National Survey of Families and Households. The author finds a negative slope with life satisfaction, conditional on the respondent individual income.

The regression approach of calculating the income of “people like me” is also used by Clark and Oswald (1996) on the first wave of the British Household Panel Survey (BHPS) data. The estimated coefficients on household and reference group income in a job satisfaction equation are statistically equal and opposite, which is consistent with a “fully relative” utility function. To paraphrase Easterlin (1995), these results document that “increasing the income of all increases the happiness of no-one”.

Wave 3 (2006) of the European Social Survey has introduced a survey question where individuals are first asked “How important is it to you to compare your income with other people’s incomes?” They are then asked “Whose income would you be most likely to compare your own with?”, with responses on a showcard of Work colleagues, Family members, Friends, and Others.

In Models II and III, following Di Tella et al. (2007), we also introduce in the estimation additional controls for relative income and changes in relative income.

An alternative approach is that of obtaining ratios for each of the seven different life satisfaction categories. This approach leads to seven different ratios (obtained by calculating compensating amounts needed to remain on each of the seven different categories) and is of more difficult interpretation. This is why in the literature the assumption of continuity is generally preferred. In this respect Van Praag and Ferrer-i-Carbonell (2004, 2006) show that the simple linear models are as good as the ordered probit and logit method, but computationally much easier.

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Titel: The Heterogeneous Effects of Income Changes on Happiness
verfasst von: Leonardo Becchetti
Luisa Corrado
Fiammetta Rossetti
Publikationsdatum: 01.12.2011
Verlag: Springer Netherlands
Erschienen in: Social Indicators Research / Ausgabe 3/2011
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI: https://doi.org/10.1007/s11205-010-9750-0

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