Abstract
What effect does government responsiveness have on political participation? Since the 1940s political scientists have used attitudinal measures of perceived efficacy to explain participation. More recent work has focused on underlying genetic factors that condition citizen engagement. The authors develop a ‘calculus of participation’ that incorporates objective efficacy, the extent to which an individual’s participation actually has an impact, and test the model against behavioral data from FixMyStreet.com (n=399,364). The authors find that a successful first experience using FixMyStreet.com (e.g., reporting a pothole and having it fixed) is associated with a 54 percent increase in the probability of an individual submitting a second report. The authors also show that the experience of government responsiveness to the first report submitted has predictive power over all future report submissions. The findings highlight the importance of government responsiveness for fostering an active citizenry, while demonstrating the value of incidentally collected data to examine participatory behavior at the individual level.
Highlights
Why do some participate in politics and others do not? It can be argued that individuals have an underlying propensity to participate, due to socialization (Tam Cho 1999) or genetic factors (Fowler, Baker, and Dawes 2008)
We make the simplifying assumption that the council’s behavior is exogenous and that problems are not fixed because of strategic political considerations. This model predicts that individual variation in objective efficacy – whether a problem gets fixed or not – will have an impact on the subjective assessment of external efficacy, and in turn have an effect on future participation
The analysis presented above consistently shows that government responsiveness is positively associated with future participation via Fix My Street in the United Kingdom
Summary
Why do some participate in politics and others do not? It can be argued that individuals have an underlying propensity to participate, due to socialization (Tam Cho 1999) or genetic factors (Fowler, Baker, and Dawes 2008). A good experience with FMS – that is, seeing a reported problem fixed – will either increase P or reinforce P, if prior beliefs about P were very high (see Figure 1) This model predicts that individual variation in objective efficacy – whether a problem gets fixed or not – will have an impact on the subjective assessment of external efficacy, and in turn have an effect on future participation.. Our estimates can be considered conservative, since a second report submitted at say day 40 and preceded by a ‘fix by others’ on day 38 is coded as a ‘no fix’ in the data This means that we are underestimating the effect due to the creation of an arbitrary cut-off that excludes all subsequent fixes. The reason here is that while the third party fixes should not be correlated with the user’s tendency to participate, these fixes will be correlated with the pool of other available users who can report fixes and their tendencies to participate
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