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Ashutosh Thakur

Ashutosh's portrait

Ashutosh Thakur

2018 McKinnon Fellowship Recipient
Stanford Center on Global Poverty and Development

About

Ashutosh Thakur is a third year PhD student in the Political Economics group at the Stanford Graduate School of Business. His main interests lie in using market design and matching theory to study institutional design in development, labor, finance, and politics.

Fellowship research abstract

Matching Problem of Civil Service

This project applies matching theory to study the lifelong assignment of elite Indian civil servants to states. Thakur analyzes the extent to which existing and alternative Indian Civil Service state assignment mechanisms can yield balance across three dimensions of interest: quality, embeddedness, and quota. Global balance in quality across state cadres is a unique constraint which arises when applying matching to political economy settings, as the mechanism designer is a paternalistic central planner. He finds that the most recent change in the matching mechanism in 2008 has systematically skewed assignments by assigning relatively poor quality, outsider bureaucrats to 'bad' state cadres: regions with external foreign conflict, states with internal political strife, and newly-formed states. There has been a remarkable upswing in regional homophily amongst Northern and Southern states and civil servants are assigned much closer to their home state. He shows that this imbalance in quality, also translates to deterioration in state capacity as bad state cadres are able to collect less tax revenues. And these bad state cadres are also consistently assigned fewer exam toppers and older candidates, which leads to lower perceived bureaucratic effectiveness and increased political interference in bureaucracy through politicized transfers and promotions, as existing literature shows. This paper analyzes the causes of these imbalances, assesses the impact of this mechanism change on state capacity, development outcomes, and bureaucratic performance, and highlights tradeoffs in implementing alternate mechanisms.