Abstract
Though there has been a recent outpouring of studies on the determinants of individual happiness, there remains a paucity of research on the influence of specific sub-national government policies. Additionally, theoretical expectations about how fiscal variables influence happiness are unclear, making further empirical research imperative. Combining survey data and aggregate information about state and local government revenue and expenditures within the United States, we draw inferences about whether or not such activities affect individual happiness. We find no indication that the overall level of state or local fiscal activity affects life satisfaction. However, we offer evidence that personal happiness could be increased with an increase in the percentage of sub-national expenditure devoted to public safety. We also find that there are notable differences across ideological groups (conservatives, moderates, and liberals) with respect to how much public safety influences happiness, as well as how some other fiscal variables influence happiness. We conclude that ideology mediates the impact of fiscal variables on life satisfaction.
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Notes
For example, a recent study by the Australian Centre on Quality of Life (2008) indicates that happiness rises only marginally beyond a gross household income of about A$100,000 (about US$96,000), and after A$150,000 (about US$143,000) there is no further reliable increase.
For a recent survey of happiness research by psychologists, see Dolan and White (2007).
Helliwell (2006) highlights the discussion on whether national differences in average personality or mood make subjective cross-country data unreliable measures of life satisfaction. We chose to avoid this discussion by sampling from two periods and including a specific set of dummy variables for urban areas in the sample.
Alesina et al. (2004) may have taken a partial step in this direction, since their measure of inequality in the United States is a state level variable. However, their focus is not on the states per se, and they discuss state differences only in passing.
A PSU consists of a single county, group of counties, or the various configurations of a metropolitan statistical area as defined by the United States Census.
The dependent variable measuring happiness contained 4,175 valid observations. The explanatory variables with missing observations measuring African American, age, foreign born, and family income respectively had 5,464, 5,579, 5,573, and 4,965 valid observations. We tried running all regressions for only a given year’s observation and found no substantial differences from the conclusions drawn from the full sample, only the lack of statistical significance for some explanatory variables found significant in the pooled sample. This is likely due to the smaller degrees of freedom found in the 1-year samples.
The simple correlation coefficient between local revenue per capita and state revenue per capita is 0.81. The correlation between local expenditure per capita and state expenditure per capita is 0.91.
Note that the explanatory variable Underlying Political Ideology in State of Residence was not included in the three sub-sample regressions for respondents holding a liberal, moderate, or conservative political because the regression results would not converge for either the liberal or moderate samples when this explanatory variable was included. The results did converge for both the ordered probit and linear regression models for the conservative sample, and statewide political ideology did not exert a statistically significant effect on the this group, nor did the significance or sign of sub-national fiscal measures change. Accordingly, we opted to exclude the ideology measure from these sub-sample regressions.
Clark (2007) discusses why happiness is U-shaped in relation to age.
To classify respondents we draw from the seven-point, self-identification scale of political ideology commonly used by political scientists and available from the GSS data. With respect to combining categories within the scale, there has been considerable controversy about whether people who label themselves independents but “lean” toward one or another party are better classified with that party or with “pure” independents who do not express such a leaning. We follow the lead of many political scientists who combine “leaners” with the appropriate acknowledged partisans, based on the voting behavior and other inclinations of the former group (see especially Keith et al. 1992).
On the importance of partisanship as a source of self-identify analogous to religious identification, see especially Green et al. (2002).
A third possible reason for the insignificance of our finding that sub-national government activity exerts no significant influence on individual happiness is a line of thought that began with Roback’s (1982) model of households moving between cities (and states) to obtain the highest level of utility (happiness) possible. The long-run equilibrium in such a model is that individual utility levels are equal across all locations. If people move among primary statistical units due to the overall level of sub-national fiscal activity occurring there, then the results derived here are the expected ones. Nevertheless, the assumption necessary for this to be the theoretical reason for our finding—a sample of jurisdictions that match everyone’s taste for sub-national public expenditure per capita—is not likely to be the case.
We focus on divisions based on ideology rather than partisanship, because the distinctions among groups were more striking for the ideological groupings, and prior studies were as likely to emphasize the importance of ideology as partisanship per se.
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Wassmer, R.W., Lascher, E.L. & Kroll, S. Sub-national Fiscal Activity as a Determinant of Individual Happiness: Ideology Matters. J Happiness Stud 10, 563–582 (2009). https://doi.org/10.1007/s10902-008-9109-2
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DOI: https://doi.org/10.1007/s10902-008-9109-2