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Misunderestimating Corruption

Author

Listed:
  • Aart Kraay

    (The World Bank)

  • Peter Murrell

    (University of Maryland)

Abstract

Corruption estimates rely largely on self-reports of affected individuals and officials. Yet survey respondents are often reticent to tell the truth about sensitive subjects, leading to downward biases in surveybased corruption estimates. This paper develops a method to estimate the prevalence of reticent behavior and reticence-adjusted rates of corruption using survey responses to sensitive questions. A statistical model captures how respondents answer a combination of conventional and randomresponse questions, allowing identification of the effect of reticence. GMM and maximum likelihood estimates are obtained for ten countries. Adjusting for reticence dramatically alters the perceptions of the extent of corruption.

Suggested Citation

  • Aart Kraay & Peter Murrell, 2016. "Misunderestimating Corruption," The Review of Economics and Statistics, MIT Press, vol. 98(3), pages 455-466, July.
    • Handle: RePEc:tpr:restat:v:98:y:2016:i:3:p:455-466
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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00536
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    Cited by:

    1. Bernard GAUTHIER & Frédéric LESNÉ, 2018. "Reported Corruption vs. Experience of Corruption in Public Procurement Contracts," Working Papers P242, FERDI.
    2. Roberto Iorio & Maria Luigia Segnana, 2022. "Is paying bribes worthwhile? Corruption and innovation in middle-income countries," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 475-504, September.
    3. Van Ha, Le, 2024. "Unveiling a novel approach to corruption measurement: Leveraging household survey data on income and expenditure through forensic analysis," Economic Modelling, Elsevier, vol. 136(C).
    4. Bernard GAUTHIER & Frédéric LESNÉ, 2017. "Measuring corruption in presence of reticent respondents: Theory and Application," Working Papers P207, FERDI.
    5. Francis,David C. & Kubinec ,Robert, 2022. "Beyond Political Connections : A Measurement Model Approach to Estimating Firm-levelPolitical Influence in 41 Economies," Policy Research Working Paper Series 10119, The World Bank.
    6. Hongli Feng & Tong Wang & David A. Hennessy & Gaurav Arora, 2022. "Over-Perception about Land Use Changes: Assessing Empirical Evidence and Linkage with Decisions and Motivated Beliefs," Land Economics, University of Wisconsin Press, vol. 98(2), pages 254-273.
    7. Olivia Bertelli & Thomas Calvo & Emmanuelle Lavallée & Marion Mercier & Sandrine Mesplé-Somps, 2023. "Measuring insecurity-related experiences and preferences in a fragile state : a list experiment in Mali," Working Papers hal-04891546, HAL.
    8. Laarni Escresa & Lucio Picci, 2020. "The determinants of cross-border corruption," Public Choice, Springer, vol. 184(3), pages 351-378, September.
    9. Gauthier, Bernard & Goyette, Jonathan & Kouamé, Wilfried A.K., 2021. "Why do firms pay bribes? Evidence on the demand and supply sides of corruption in developing countries," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 463-479.
    10. Chaoyi Chen & Mehmet Pinar & Thanasis Stengos, 2024. "Bribery, regulation and firm performance: evidence from a threshold model," Empirical Economics, Springer, vol. 66(1), pages 405-430, January.
    11. Kim, Sahrok & Praveen Parboteeah, K. & Cullen, John B. & Jeong, Nara, 2022. "Social institutions approach to women’s firm ownership and firm bribery activity: A study of small-sized firms in emerging markets," Journal of Business Research, Elsevier, vol. 144(C), pages 1333-1349.
    12. Anderson, James & Baidya, Akanksha, 2025. "Which Data Do Economists Use to Study Corruption ? A Cross-Section of Corruption Research," Policy Research Working Paper Series 11091, The World Bank.
    13. Tomasi, Chiara & Le, Quoc Thai & Nguyen, Thi Ngoc Lan, 2025. "Greasing or Grinding? Regulatory context and the productivity effects of corruption: Evidence from Vietnamese SMEs," European Journal of Political Economy, Elsevier, vol. 89(C).
    14. Spyridon Boikos & Mehmet Pinar & Thanasis Stengos, 2023. "Bribery, on-the-job training, and firm performance," Small Business Economics, Springer, vol. 60(1), pages 37-58, January.

    More about this item

    Keywords

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    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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