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E-Government as an anti-corruption strategy

  • Andersen, Thomas Barnebeck

This paper estimates the impact of e-government on the "control of corruption" indicator using a panel of 149 countries with two time observations (). The first differenced estimator yields a positive and economically interesting effect. By the most conservative estimate, moving from the 10th percentile to the 90th percentile in the e-government distribution implies a reduction in corruption equivalent to moving from the 10th percentile to the 23rd percentile in the control of corruption distribution. Invoking external instruments, IV results are (statistically) similar.

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File URL: http://www.sciencedirect.com/science/article/pii/S0167-6245(09)00011-0
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Article provided by Elsevier in its journal Information Economics and Policy.

Volume (Year): 21 (2009)
Issue (Month): 3 (August)
Pages: 201-210

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Handle: RePEc:eee:iepoli:v:21:y:2009:i:3:p:201-210
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/505549

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  1. La Porta, Rafael & Florencio Lopez-de-Silanes & Andrei Shleifer & Robert W. Vishny, 1997. " Legal Determinants of External Finance," Journal of Finance, American Finance Association, vol. 52(3), pages 1131-50, July.
  2. Ferraz, Claudio & Finan, Frederico S., 2007. "Exposing Corrupt Politicians: The Effects of Brazil’s Publicly Released Audits on Electoral Outcomes," IZA Discussion Papers 2836, Institute for the Study of Labor (IZA).
  3. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 83-116.
  4. Menzie D. Chinn & Robert W. Fairlie, 2004. "The Determinants of the Global Digital Divide A Cross-Country Analysis of Computer and Internet Penetration," Working Papers 881, Economic Growth Center, Yale University.
  5. Rodrik, Dani, 2008. "The New Development Economics: We Shall Experiment, but How Shall We Learn?," Working Paper Series rwp08-055, Harvard University, John F. Kennedy School of Government.
  6. Krasker, William S. & Kuh, Edwin & Welsch, Roy E., 1983. "Estimation for dirty data and flawed models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 11, pages 651-698 Elsevier.
  7. Torsten Persson & Guido Tabellini & Francesco Trebbi, 2001. "Electoral Rules and Corruption," NBER Working Papers 8154, National Bureau of Economic Research, Inc.
  8. Robert E. Hall & Charles I. Jones, 1999. "Why Do Some Countries Produce So Much More Output per Worker than Others?," NBER Working Papers 6564, National Bureau of Economic Research, Inc.
  9. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  10. Lau, T.Y. & Aboulhoson, Mira & Lin, Carolyn & Atkin, David J., 2008. "Adoption of e-government in three Latin American countries: Argentina, Brazil and Mexico," Telecommunications Policy, Elsevier, vol. 32(2), pages 88-100, March.
  11. Brunetti, Aymo & Weder, Beatrice, 2003. "A free press is bad news for corruption," Journal of Public Economics, Elsevier, vol. 87(7-8), pages 1801-1824, August.
  12. Paolo Mauro, 1995. "Corruption and Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 110(3), pages 681-712.
  13. Reinikka, Ritva & Svensson, Jakob, 2004. "The power of information : evidence from a newspaper campaign to reduce capture," Policy Research Working Paper Series 3239, The World Bank.
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