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Electoral Rules and Corruption

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Author Info
Torsten Persson (Stockholm University)
Guido Tabellini (Bocconi University)
Francesco Trebbi (Harvard University)

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Abstract

Is corruption systematically related to electoral rules? Recent theoretical work suggests a positive answer. But little is known about the data. We try to address this lacuna by relating corruption to different features of the electoral system in a sample of about eighty democ-racies in the 1990s. We exploit the cross-country variation in the data, as well as the time variation arising from recent episodes of electoral reform. The evidence is consistent with the theoretical priors. Larger voting districts-and thus lower barriers to entry-are associated with less corruption, whereas larger shares of candidates elected from party lists-and thus less individual accountability-are associated with more corruption. Individual accountability appears to be most strongly tied to personal ballots in plurality-rule elections, even though open party lists also seem to have some effect. Because different aspects roughly offset each other, a switch from strictly proportional to strictly majoritarian elections only has a small negative effect on corruption. (JEL: E62, H3) Copyright (c) 2003 The European Economic Association.

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Publisher Info
Article provided by MIT Press in its journal Journal of the European Economic Association.

Volume (Year): 1 (2003)
Issue (Month): 4 (06)
Pages: 958-989
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Handle: RePEc:tpr:jeurec:v:1:y:2003:i:4:p:958-989

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Alberto Ades & Rafael Di Tella, 1999. "Rents, Competition, and Corruption," American Economic Review, American Economic Association, vol. 89(4), pages 982-993, September. [Downloadable!] (restricted)
  2. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
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  3. Richard Blundell & Monica Costa Dias, 2000. "Evaluation methods for non-experimental data," Fiscal Studies, Institute for Fiscal Studies, vol. 21(4), pages 427-468, January. [Downloadable!]
  4. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Blackwell Publishing, vol. 65(2), pages 261-94, April. [Downloadable!] (restricted)
  5. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Blackwell Publishing, vol. 64(4), pages 605-54, October. [Downloadable!] (restricted)
  6. Rajeev H. Dehejia & Sadek Wahba, 1998. "Causal Effects in Non-Experimental Studies: Re-Evaluating the Evaluation of Training Programs," NBER Working Papers 6586, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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