TAILIEUCHUNG - Fixing Market Failures or Fixing Elections? Agricultural Credit in India

The guidance of Lawrence Haddad and Sudhir Wanmali in providing an enabling research environment deserves special recognition. We thank John Pender, the IFPRI internal reviewer, and two anonymous external reviewers for their critical but very constructive comments, which helped us significantly improve the analysis in and presentation of the report. Particular sections of this report have also benefited from the comments of Alain de Janvry, Andrew Foster, Lawrence Had- dad, Soren Hauge, Hanan Jacoby, Manohar Sharma, John Strauss, and participants in the Bunda/IFPRI workshop on rural finance held in October 1996 at Bunda, in seminars at IFPRI, and in various conferences at which papers emanating from this research were. | 09-001 Fixing Market Failures or Fixing Elections Agricultural Credit in India Shawn A. Cole Copyright 2008 by Shawn A. Cole Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author. Fixing Market Failures or Fixing Elections Agricultural Credit in India Shawn Cole July 5 2008 Abstract This paper integrates theories of political budget cycles with theories of tactical electoral redistribution to test for political capture in a novel way. Studying banks in India I find that government-owned bank lending tracks the electoral cycle with agricultural credit increasing by 5-10 percentage points in an election year. There is significant cross-sectional targeting with large increases in districts in which the election is particularly close. This targeting does not occur in non-election years or in private bank lending. I show capture is costly elections affect loan repayment and election year credit booms do not measurably affect agricultural output. Finance Unit Harvard Business School. 25 Harvard Way Boston MA 02163 scole@. I thank Abhijit Banerjee Esther Duflo and Sendhil Mullainathan for guidance and Abhiman Das . Barman and especially the Reserve Bank of India for substantial support and assistance. I also thank Abhiman Das for performing calculations on disaggregated data at the Reserve Bank of India. In addition I thank Victor Chernozhukov Ivan Fernandez-Val Francesco Franco Andrew Healy Andrei Levchenko Rema Hanna Petia Topalova and participants various seminars and workshops the editor Thomas Lemieux and two referees for comments. Gautam Bastian and Samantha Bastian provided excellent research assistance. I am grateful for financial support from a National Science Foundation Graduate Research Fellowship and Harvard Business School s Division of Research and Faculty .

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