This paper aims to investigate the social, economic, and cultural factors that impact satisfaction with life (SWL) in 63 countries. The intent is to determine empirically the extent to which self‐reported SWL truly reflects well‐being.
A cross‐sectional data set of 63 countries in the 1990s is used to develop a model that explains SWL using social, economic, and cultural variables. The regression errors indicate that some countries are inexplicably happy or unhappy. If behavioral variables in these countries, such as suicide and fertility rates, are better explained by the model's fitted values than actual SWL, then cross country comparisons of subjective SWL surveys are invalid.
Social and economic factors explain about 66 percent of the variation in self‐reported happiness across countries. Respondents in former socialist‐bloc countries report surprisingly low levels of SWL given their circumstances while Latin Americans report higher‐than‐expected levels of happiness. These two geographic anomalies are attributed to cultural factors and dummy variables for each region are highly significant. People living in these two geographic regions are shown to behave in accordance with their reported levels of happiness, more so than their predicted levels, with regard to suicide and fertility rates. Even mean blood pressure in these countries is better predicted with reported levels of satisfaction than predicted levels. All this supports the notion that surveys of SWL are good measures of well‐being.
The results are obtained using cross‐country macro‐level data. The degree of aggregation, sample size, and presence of multicollinearity may hinder the identification of appropriate predictors of well‐being. On the other hand, these results corroborate those from larger, pooled, and individual‐level data sets.
The findings support the view that aggregated surveys of life satisfaction contain important information concerning the well‐being of citizens in a given country. Survey data can compete with other macroeconomic and sociological data to monitor progress and explain behavior at the national level.
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