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Does Corruption Pay in Indonesia? If So, Who are Benefited the Most?

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  • Pradiptyo, Rimawan

Abstract

This paper aims to assess the discrepancies in sentencing corruptors by judges in Indonesia’s judicial system. The data are based on the Supreme Court’s decisions during the period of 2001-2009 which available in public domain in www.putusan.mahkamahagung.go.id. The data comprise of 549 cases, which involved 831 defendants. The defendants have been classified into five groups depending on their alleged scales of corruptions (i.e. petty, small, medium, large and grand scale of corruptions). The explicit cost of corruption during the period of 2001-2009 was Rp73.1 trillion (about US $7.86 billion). In this paper, total financial punishment was estimated as the summation of the value of fines, seizure of assets (monetary only), and the compensation order sentenced by judges. The total financial punishment sentenced by the supreme judges during the period of 2001-2009 was Rp5.33 trillion (about US$573.12 million), therefore Rp67.77 trillion (US$7.28 billion) gap between the explicit cost of corruption and total financial punishment sentenced shall be borne by the tax payers. Logistic and Tobin’s logistic (TOBIT) regressions have been used to analyse both the likelihood and the intensity of sentencing offenders, respectively, with particular punishments (i.e. imprisonment, fines, compensation order, etc.). The results show that the probability and the intensity of sentencing across various types of punishment do not correspond to the scale of corruptions. Offenders who committed petty and small scales corruption tend to be punished more severely than their medium, large and grand corruptors.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 41384.

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Date of creation: 17 Sep 2012
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Handle: RePEc:pra:mprapa:41384

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Related research

Keywords: Corruption; Court Decisions; Probability of Sentencing; Intensity of Sentencing; Logistic Regression; Tobin’s Logistic (TOBIT) Regression;

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  1. A. Mitchell Polinsky & Steven Shavell, 1999. "The Economic Theory of Public Enforcement of Law," NBER Working Papers 6993, National Bureau of Economic Research, Inc.
  2. Rasmusen, Eric, 1996. "Stigma and Self-Fulfilling Expectations of Criminality," Journal of Law and Economics, University of Chicago Press, University of Chicago Press, vol. 39(2), pages 519-43, October.
  3. Nuno Garoupa & Daniel Klerman, 2002. "Optimal Law Enforcement with a Rent-Seeking Government," American Law and Economics Review, Oxford University Press, Oxford University Press, vol. 4(1), pages 116-140, January.
  4. Gary S. Becker, 1968. "Crime and Punishment: An Economic Approach," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 76, pages 169.
  5. Garoupa, Nuno & Klerman, Daniel, 2004. "Corruption and the optimal use of nonmonetary sanctions," International Review of Law and Economics, Elsevier, Elsevier, vol. 24(2), pages 219-225, June.
  6. S. Illeris & G. Akehurst, 2001. "Introduction," The Service Industries Journal, Taylor & Francis Journals, Taylor & Francis Journals, vol. 21(1), pages 1-4, January.
  7. Garoupa, Nuno, 1997. " The Theory of Optimal Law Enforcement," Journal of Economic Surveys, Wiley Blackwell, Wiley Blackwell, vol. 11(3), pages 267-95, September.
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