How could the business cycle shape attitudes (particularly trust) towards public institutions? First, a positive relationship between income and trust can operate through changes in loss aversion. Individuals experiencing a positive (negative) shock in their standard of living may feel more (less) secure and then more (less) willing to trust others in general and institutions in general. Second, trust and positive attitudes can be understood as an assessment of the political system and its institutions. An individual observing the business cycle may perceive shocks as sufficient statistics of institutions’ performances. For instance, a good economic situation could indicate good institutional performance (regardless of whether the attribution and assessment are correct), thus boosting trust in (and satisfaction with) state and related institutions. Third, and connected to the previous point, income shocks can directly affect the resources needed for well-functioning institutions. Therefore, changes in attitudes towards institutions may reflect changes in institutional equilibrium due to initial changes on the supply side of institutions.

In this paper, I use multiple waves of two public opinion surveys (i.e., LAPOP and Latinobar ́ometro) to analyze how people’s perceptions and attitudes towards public institutions respond to the business cycle in El Salvador. To do so, I estimate several econometric models explaining respondents’ attitudes towards different institutions (e.g., trust in the president or satisfaction with democracy) as a function of municipality-specific income levels. Nonetheless, the uncovered robust statistical associations do not necessarily imply causality. Indeed, economic development within a country is not a random process in which income has been randomly assigned across municipalities over time. The process of economic development and the formation of trust and confidence towards institutions (as well as its evolution), and the factors underlying the emergence and persistence of these attitudes are complex phenomena. Furthermore, some of those factors are unobserved, which hinders the identification of the causal effect of income on the aforementioned attitudes. Nevertheless, I argue that it is unlikely that my OLS results are fully driven by omitted factors or a reverse causality from trust to income. Importantly, my econometric models include both year fixed effects, which partial out the aggregate business cycle for El Salvador, and municipality fixed effects to control for persistent cross-municipality differences. Thus, my specifications explore the relationship between attitudes and deviations of the municipality income from the country average.

The lack of subnational-level statistics for GDP or measures of household income is a common problem in developing countries, and El Salvador is not the exception where a limited set of municipalities has income measures. To expand the set of municipalities under analysis and cover periods and regions for which income data is not available, I use a proxy of income commonly exploited in the growth and development literature: density of nighttime lights (Henderson et al., 2012). I show below that this proxy indeed works well predicting household income (and even cross-sectional variation in poverty rates) in El Salvador over time when such data exist.

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