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Explaining the standard errors of corruption perception indices

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  • Qu, Guangjun
  • Slagter, Bob
  • Sylwester, Kevin
  • Doiron, Kyle

Abstract

This paper examines the standard errors of two popular indices of corruption perceptions: the Worldwide Governance Indicators’ Control of Corruption (WGI-CC) and Transparency International's Corruption Perception Index (TI-CPI). The standard errors of these indexes stem from the degree of variation across the sources upon which these two aggregate indices are based. In general, standard errors are not associated with country characteristics; this supports the common assumption that differences across surveys are random. There are two exceptions, however. They involve the degree of media freedom in a country and the country's past corruption scores, possibly indicating the use of cognitive heuristics by the assessors who do the ratings. No evidence exists that more diverse countries have greater variation across corruption scores. In comparing the two aggregate measures, we find that the standard errors for TI-CPI are associated with country characteristics in fewer cases than are those for WGI-CC. Finally, our findings raise concerns about the applicability of the WGI-CC's use of the unobserved components model for extracting signals from noise.

Suggested Citation

  • Qu, Guangjun & Slagter, Bob & Sylwester, Kevin & Doiron, Kyle, 2019. "Explaining the standard errors of corruption perception indices," Journal of Comparative Economics, Elsevier, vol. 47(4), pages 907-920.
  • Handle: RePEc:eee:jcecon:v:47:y:2019:i:4:p:907-920
    DOI: 10.1016/j.jce.2019.07.003
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    References listed on IDEAS

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    1. 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.
    2. Andrei Shleifer, 2012. "Psychologists at the Gate: A Review of Daniel Kahneman's Thinking, Fast and Slow," Journal of Economic Literature, American Economic Association, vol. 50(4), pages 1080-1091, December.
    3. Daniel Kaufmann & Aart Kraay, 2008. "Governance Indicators: Where Are We, Where Should We Be Going?," The World Bank Research Observer, World Bank, vol. 23(1), pages 1-30, January.
    4. La Porta, Rafael & Lopez-de-Silanes, Florencio & Shleifer, Andrei & Vishny, Robert, 1999. "The Quality of Government," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 15(1), pages 222-279, April.
    5. Jakob Svensson, 2005. "Eight Questions about Corruption," Journal of Economic Perspectives, American Economic Association, vol. 19(3), pages 19-42, Summer.
    6. Givens, David, 2013. "Defining governance matters: A factor analytic assessment of governance institutions," Journal of Comparative Economics, Elsevier, vol. 41(4), pages 1026-1053.
    7. Glaeser, Edward L. & Saks, Raven E., 2006. "Corruption in America," Journal of Public Economics, Elsevier, vol. 90(6-7), pages 1053-1072, August.
    8. Shleifer, Andrei, 2012. "Psychologists at the Gate: Review of Daniel Kahneman’s Thinking, Fast and Slow," Scholarly Articles 10735580, Harvard University Department of Economics.
    9. Treisman, Daniel, 2000. "The causes of corruption: a cross-national study," Journal of Public Economics, Elsevier, vol. 76(3), pages 399-457, June.
    10. Knack, Stephen, 2007. "Measuring Corruption: A Critique of Indicators in Eastern Europe and Central Asia," Journal of Public Policy, Cambridge University Press, vol. 27(3), pages 255-291, December.
    11. Egger, Peter & Winner, Hannes, 2006. "How Corruption Influences Foreign Direct Investment: A Panel Data Study," Economic Development and Cultural Change, University of Chicago Press, vol. 54(2), pages 459-486, January.
    12. Olken, Benjamin A., 2009. "Corruption perceptions vs. corruption reality," Journal of Public Economics, Elsevier, vol. 93(7-8), pages 950-964, August.
    13. Charles P. Oman & Christiane Arndt, 2006. "Governance Indicators for Development," OECD Development Centre Policy Insights 33, OECD Publishing.
    14. Hannu Tanninen, 1999. "Income inequality, government expenditures and growth," Applied Economics, Taylor & Francis Journals, vol. 31(9), pages 1109-1117.
    15. repec:dau:papers:123456789/4352 is not listed on IDEAS
    16. Razafindrakoto, Mireille & Roubaud, François, 2010. "Are International Databases on Corruption Reliable? A Comparison of Expert Opinion Surveys and Household Surveys in Sub-Saharan Africa," World Development, Elsevier, vol. 38(8), pages 1057-1069, August.
    17. Dilyan Donchev & Gergely Ujhelyi, 2014. "What Do Corruption Indices Measure?," Economics and Politics, Wiley Blackwell, vol. 26(2), pages 309-331, July.
    18. Paolo Mauro, 1995. "Corruption and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 681-712.
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    Cited by:

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    2. Gründler, Klaus & Potrafke, Niklas, 2019. "Corruption and economic growth: New empirical evidence," European Journal of Political Economy, Elsevier, vol. 60(C).
    3. Wen, Jun & Yin, Hua-Tang & Jang, Chyi-Lu & Uchida, Hideaki & Chang, Chun-Ping, 2023. "Does corruption hurt green innovation? Yes – Global evidence from cross-validation," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    4. Gutmann, Jerg & Padovano, Fabio & Voigt, Stefan, 2020. "Perception vs. experience: Explaining differences in corruption measures using microdata," European Journal of Political Economy, Elsevier, vol. 65(C).
    5. Samuele Murtinu & Giulio Piccirilli & Agnese Sacchi, 2022. "Rational inattention and politics: how parties use fiscal policies to manipulate voters," Public Choice, Springer, vol. 190(3), pages 365-386, March.
    6. Yang Li & Hu WenXiu & Su ZhenXing, 2023. "Impact of Local Official Corruption on Local Government Debt in China: The Mediating Role of Government Investment Efficiency," SAGE Open, , vol. 13(3), pages 21582440231, July.
    7. Kanat Abdulla, 2021. "Corrosive effects of corruption on human capital and aggregate productivity," Kyklos, Wiley Blackwell, vol. 74(4), pages 445-462, November.
    8. Yemin Ding & Lee Chin & Fangyan Li & Peidong Deng, 2022. "How Does Government Efficiency Affect Health Outcomes? The Empirical Evidence from 156 Countries," IJERPH, MDPI, vol. 19(15), pages 1-18, August.

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    More about this item

    Keywords

    Corruption perception index; Transparency international; Worldwide governance indicators; Standard error; Heuristic; Statistical aggregation; Comparative country studies;
    All these keywords.

    JEL classification:

    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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