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Electoral Rules and Corruption

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  • Persson, Torsten
  • Tabellini, Guido
  • Trebbi, Francesco

Abstract

Is corruption systematically related to electoral rules? A number of studies have tried to uncover economic and social determinants of corruption but, as far as we know, nobody has yet empirically investigated how electoral systems influence corruption. We try to address this lacuna in the literature, by relating corruption to different features of the electoral system in a sample from the late nineties encompassing more than 80 (developed and developing) democracies. Our empirical results are based on traditional regression methods, as well as non-parametric estimators. The evidence is consistent with the theoretical models reviewed in the Paper. Holding constant a variety of economic and social variables, we find that 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. Altogether, proportional elections are associated with more corruption, since voting over party lists is the dominant effect, while the district magnitude effect is less robust.

Suggested Citation

  • Persson, Torsten & Tabellini, Guido & Trebbi, Francesco, 2001. "Electoral Rules and Corruption," CEPR Discussion Papers 2741, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:2741
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    2. 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.
    3. John Ferejohn, 1986. "Incumbent performance and electoral control," Public Choice, Springer, vol. 50(1), pages 5-25, January.
    4. Rafael Di Tella & Alberto Ades, 1999. "Rents, Competition, and Corruption," American Economic Review, American Economic Association, vol. 89(4), pages 982-993, September.
    5. 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.
    6. 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.
    7. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," Review of Economic Studies, Oxford University Press, vol. 65(2), pages 261-294.
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    More about this item

    Keywords

    Comparative Politics; Corruption; Political Economies;
    All these keywords.

    JEL classification:

    • H0 - Public Economics - - General
    • I0 - Health, Education, and Welfare - - General

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