Religions seem to defy the law-of-demand, which suggests that all else equal, an increase in the cost of an activity will induce individuals to decrease the resources they spend on that activity. Rather than weakening religious organizations, evidence shows that the sacrifices exacted by religious practices are positively associated with the success of those organizations. We present the first strong evidence that this association is neither spurious nor endogenous. We use a natural experiment that rests on a peculiar time-shifting feature of Ramadan that makes the fasting duration—our measure of sacrifice—vary not just by latitude but from year-to-year. We find that a half-hour increase in fasting time during the median Ramadan day increases the vote shares of Islamist political parties by 11 percent in Turkey’s parliamentary elections between 1973 and 2018, and results in one additional attendee per 1,000 inhabitants for voluntary Quran courses. We further investigate two mechanisms, screening and commitment, that could explain the effects we find. By testing their divergent implications, we infer that commitment is the mechanism triggered by sacrifice, which drives up the intensity of religious beliefs and participation that in turn bolster the success of religious organizations.

How does armed conflict influence tropical forest loss? For Colombia, both enhancing and reducing effect estimates have been reported. However, a lack of causal methodology has prevented establishing clear causal links between these two variables. In this work, we propose a class of causal models for spatio-temporal stochastic processes which allows us to formally define and quantify the causal effect of a vector of covariates X on a real-valued response Y. We introduce a procedure for estimating causal effects and a nonparametric hypothesis test for these effects being zero. Our application is based on geospatial information on conflict events and remote-sensing-based data on forest loss between 2000 and 2018 in Colombia. Across the entire country, we estimate the effect to be slightly negative (conflict reduces forest loss) but insignificant (P = 0.578), while at the provincial level, we find both positive effects (e.g., La Guajira, P = 0.047) and negative effects (e.g., Magdalena, P = 0.004). The proposed methods do not make strong distributional assumptions, and allow for arbitrarily many latent confounders, given that these confounders do not vary across time. Our theoretical findings are supported by simulations, and code is available online.