Long-Run Effects of Religious Institutions on Development

Abstract

How do religious institutions affect long-run development? Most studies examining this relationship study its impact on human capital formation. I frame religious institutions as decentralized religious institutions and those that served in the imperial center. Drawing on medieval Muslim religious institutions in India, I argue that differences in the market dependency and coordination mechanisms anchored by the religious institution type durably affect development and democratic outcomes in opposing ways today. The decentralized religious institution, dependent on the market, incentivized market participation, reflected in the higher village-level marketplaces and participation in an increasingly industrializing economy today. It also coordinated local collective action, which constitutes civic engagement today that increases accountability in constituency services, such as more public goods provision, through higher electoral competition. In contrast, the religious institution that served the imperial courts and bureaucracy—a source of employment unavailable today—does not have a legacy coordinating collective action locally, and hence, neither enables civic engagement nor affects democratic performance locally. Instead, it competes with centralized institutions to conserve the application of its religious expertise in policy and legislation. I provide empirical evidence from India, where the medieval religious institutions of Sufi Khanaqah and Madrasa Dar-ul-Uloom evolved from the 13th century onwards. I construct a novel dataset of Khanaqah and Madrasa locations for all villages of India. The dataset is integrated with census-level data for the years 1991, 2001, and 2011, road upgradation data for 2000-2015, and pooled assembly election results for 1974-2018. I find that the presence of Khanaqah leads to better development and democratic performance today. The reverse is observed for Madrasa. Multiple placebo tests and instrumental variable analysis corroborate causality in the hypothesized relationships.