Are people who are more satisfied with their lives more likely to participate in politics? Although the literature on political participation in the United States is one of the most theoretically and methodologically developed in political science, little research has sought to incorporate subjective life satisfaction into models of political participation. Instead, life satisfaction has been studied nearly exclusively as a dependent variable. By turning to life satisfaction as an independent variable, we contribute to the literatures on both political participation and life satisfaction. Using survey data, we find that individuals who are more satisfied with their lives are more likely to turn out to vote and participate in the political process through other avenues, and that the magnitude of this relationship rivals that of education. We also find that the relationship between life satisfaction and political participation is confined to “non-conflictual” forms of participation, and exhibits no relationship with the decision to engage in political protest.
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In two related studies, Hiskey and Bowler (2005) find that Mexican citizens are more likely to participate in politics if they are satisfied with government and view the political process as fair. Vowles (2002) suggests that low voter turnout in New Zealand is due, in part, to decreased levels of satisfaction with democracy there. So, there is some evidence that political participation is linked to satisfaction with government and the political process. We extend this research program and ask whether political participation is linked to an individual’s satisfaction with their life more generally.
A large literature assesses the validity and reliability of self-reported measures of subjective well-being in general and life satisfaction in particular. Myers and Diener (1995) find that self-reports are consistent with external evaluations, display stability over time, and are not particularly troubled by social desirability bias (also see Ehrhardt et al. 2000).
This problem arises because the ANES offers respondents only three response categories. Respondents are less likely to place themselves in the middle category as the number of categories increases. Moreover, some surveys that measure life satisfaction avoid this problem altogether by not offering a middle category (for example, the World Values Survey asks respondents to place themselves on a 1–10 scale).
We use an additive scale rather than factor analysis to ease interpretation of our findings. When we factor the six participation items into a single composite score and instead use that as our dependent variable, the results are substantively identical to the results we report in Table 3 using the additive scale.
The six participation items have a Cronbach's alpha scale reliability coefficient of 0.50.
We include a term for age and age squared because of our expectation that the relationship between age and participation is curvilinear (i.e. propensity to vote increases with age to a point and then declines).
The presidential competitiveness measure is coded such that states with closer election margins have larger values. Because survey respondents are nested within states, all models report standard errors that are clustered by state.
The internal political efficacy factor score was derived from a respondent’s responses to these four items: (1) “I feel that I have a pretty good understanding of the important political issues facing our country,” (2) “I consider myself well-qualified to participate in politics,” (3) “I feel that I could do as good a job in public office as most other people,” and (4) “I think that I am better informed about politics and government than most people.” The eigenvalue of the lone retained factor was 1.96. The loadings for the items were 0.68, 0.75, 61, and 0.75, respectively.
The external political efficacy factor score was derived from a respondent’s responses to these two items: (1)“Public officials don't care much what people like me think” and (2) “People like me don't have any say about what the government does.” The eigenvalue of the lone retained factor was 0.85. The loadings for the items were 0.65 and 0.65, respectively.
The eigenvalue of the lone retained factor was 1.27. The loadings for the items were 0.66, 0.68, and 0.61.
Descriptive statistics for each variable used in the analysis are reported in the Appendix in Table 5.
To isolate that it is the addition of new control variables that is altering the coefficient and standard error for life satisfaction and not simply the loss of some respondents who did not answer all of the items in the model, we dropped all respondents who had missing values on any of our independent variables before conducting our analysis for each table. The slightly lower number of observations for the models reported in Table 3 compared to Tables 1 and 4 is because a handful of respondents did not provide a response to all six items that make up our participation index.
We generate these predicted values using CLARIFY (Tomz et al. 2003).
Given the lower costs associated with voting compared to the other five items that compose the political participation index, there is some concern that voting alone may be driving any link we find between life satisfaction and citizens’ participation. To account for this possibility, we repeated the analysis we present in Table 3, excluding voting from the participation index. Doing so does not alter the results. We also consider the fact that the participation index is essentially a count variable (of the number of participatory acts a respondent engages in) that is roughly but not perfectly normally distributed. To account for this concern, we use the same model specifications as Table 3 and run both a Poisson and negative binomial regression. The results from these estimations are substantively identical, so we report OLS coefficients in Table 3 for ease of interpretation.
Because only 3.1% of respondents report engaging in political protest in the ANES data, it can be considered a “rare event” (i.e. the outcomes are unbalanced) where a probit estimator is not ideal. To account for this concern, we ran the same model specifications reported in Table 4 again using a rare events logit estimator (Tomz et al. 1999). The results we obtain are substantively identical: all of the coefficients for life satisfaction are negative but not statistically different from zero.
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See Table 5.
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Flavin, P., Keane, M.J. Life Satisfaction and Political Participation: Evidence from the United States. J Happiness Stud 13, 63–78 (2012). https://doi.org/10.1007/s10902-011-9250-1
- Political science
- Effects of life satisfaction