IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_416.html

Electoral Rules and Corruption

Author

Listed:
  • Torsten Persson
  • Guido Tabellini
  • Francesco Trebbi

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

  • Torsten Persson & Guido Tabellini & Francesco Trebbi, 2001. "Electoral Rules and Corruption," CESifo Working Paper Series 416, CESifo.
    • Handle: RePEc:ces:ceswps:_416
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/cesifo_wp416.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Rafael Di Tella & Alberto Ades, 1999. "Rents, Competition, and Corruption," American Economic Review, American Economic Association, vol. 89(4), pages 982-993, September.
    2. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    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.
    4. 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.
    5. 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.
    6. John Ferejohn, 1986. "Incumbent performance and electoral control," Public Choice, Springer, vol. 50(1), pages 5-25, January.
    7. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    2. Spitz, Alexandra, 2004. "Using Methods of Treatment Evaluation to Estimate the Wage Effect of IT Usage," ZEW Discussion Papers 04-67, ZEW - Leibniz Centre for European Economic Research.
    3. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
    4. Nolan, Anne, 2006. "Evaluating the Impact of Eligibility for Free Care on the Use of GP Services in Ireland: A Difference-in-Difference Matching Approach," Papers HRBWP25, Economic and Social Research Institute (ESRI).
    5. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2000. "The Long-Term Gains from GAIN: A Re-Analysis of the Impacts of the California GAIN Program," NBER Working Papers 8007, National Bureau of Economic Research, Inc.
    6. Díaz, Juan José & Jaramillo, Miguel, 2006. "An Evaluation of the Peruvian "Youth Labor Training Program" - PROJOVEN," IDB Publications (Working Papers) 3000, Inter-American Development Bank.
    7. Eliasson, Kent, 2006. "How Robust is the Evidence on the Returns to College Choice? Results Using Swedish Administrative Data," Umeå Economic Studies 692, Umeå University, Department of Economics.
    8. Peter R. Mueser & Kenneth R. Troske & Alexey Gorislavsky, 2007. "Using State Administrative Data to Measure Program Performance," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 761-783, November.
    9. Czarnitzki, Dirk & Hanel, Petr & Rosa, Julio Miguel, 2011. "Evaluating the impact of R&D tax credits on innovation: A microeconometric study on Canadian firms," Research Policy, Elsevier, vol. 40(2), pages 217-229, March.
    10. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2006. "Moving the Goalposts: Addressing Limited Overlap in the Estimation of Average Treatment Effects by Changing the Estimand," NBER Technical Working Papers 0330, National Bureau of Economic Research, Inc.
    11. John C. Ham & Xianghong Li & Patricia B. Reagan, 2004. "Propensity Score Matching, a Distance-Based Measure of Migration, and the Wage Growth of Young Men," Working Papers 2004_3, York University, Department of Economics.
    12. Barbara Sianesi, 2001. "Differential effects of Swedish active labour market programmes for unemployed adults during the 1990s," IFS Working Papers W01/25, Institute for Fiscal Studies.
    13. Fajnzylber, Pablo & Maloney, William F. & Rojas, Gabriel V. Montes, 2006. "Releasing constraints to growth or pushing on a string ? the impact of credit, training, business associations, and taxes on the performance of Mexican micro-firms," Policy Research Working Paper Series 3807, The World Bank.
    14. Steven Lehrer & Gregory Kordas, 2013. "Matching using semiparametric propensity scores," Empirical Economics, Springer, vol. 44(1), pages 13-45, February.
    15. Barbara Sianesi, 2002. "An evaluation of the Swedish system of active labour market programmes in the 1990s," IFS Working Papers W02/01, Institute for Fiscal Studies.
    16. Hujer, Reinhard & Wellner, Marc, 2000. "The Effects of Public Sector Sponsored Training on Individual Employment Performance in East Germany," IZA Discussion Papers 141, Institute of Labor Economics (IZA).
    17. Lorraine Dearden & Barbara Sianesi, 2001. "Estimating the Returns to Education: Models, Methods and Results," CEE Discussion Papers 0016, Centre for the Economics of Education, LSE.
    18. V. Joseph Hotz & Guido W. Imbens & Jacob A. Klerman, 2000. "The Long-Term Gains from GAIN: A Re-Analysis of the Impacts of the California GAIN Program," NBER Working Papers 8007, National Bureau of Economic Research, Inc.
    19. Sangeeta Pratap & Erwan Quintin, 2001. "Are labor markets segmented in Argentina? a semiparametric approach," Center for Latin America Working Papers 0701, Federal Reserve Bank of Dallas.
    20. Maria A. Davia, 2010. "Job Mobility And Wage Growth At The Beginning Of The Professional Career In Spain," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 18(1), pages 5-34, Spring.

    More about this item

    JEL classification:

    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • H1 - Public Economics - - Structure and Scope of Government

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_416. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.