Policy Impacts of Measuring Performance: Case of Local Governments in India

• In Event: Governance and Development at the State and Local Levels in South Asia

Abstract

States use information collected on citizens to both make policies and implement them. Increasingly, the output of data collection exercises is also used by upper levels of government to monitor and control the behavior of actors at lower levels. How does mandating that local governments report data to the central government impact the policy priorities of political leaders at the local level? I answer this question in the context of local government planning by village councils (gram panchayats, henceforth GPs) in rural India. Under the “Mission Antyodaya” framework, elected GP heads conduct a holistic survey of their villages and report the data collected to the central government. This data is then used by the central government to score and rank the GPs, with the best performers receiving some additional funds as performance grants. I argue that this exercise may change the policy priorities of GP heads through two channels: the incentive created by performance grants and the informational effect stemming from gathering data on performance. To examine how collection of this data affects policy priorities, I assemble a novel dataset with GP rankings, scorecards, gap reports (which highlight strengths and weaknesses of the GPs on a set of indicators), and the raw survey data across three years of the Mission Antyodaya survey for 2,67,337 GPs across India. (Preliminary) Results suggest that when funding incentives matter, GPs are more likely to invest in infrastructure at the cost of implementation of policies in order to increase their ranks. GPs that increase their ranks in a given survey year report more facilities but do not report better functioning of these facilities compared to GPs that lose in rank. This project shows how the collection of performance data by national governments is used to shape the behavior of decentralized governments.

Author

• Meghna Yadav, New York University