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Perceptions of Corruption: An Empirical Study Controlling for Survey Bias

Author

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  • Klaus S. Friesenbichler
  • Eva Selenko
  • George Clarke

Abstract

Survey data on corruption are widely used to construct corruption indices, but are hardly questioned. How do individual experiences shape perceptions of corruption? Do more work-engaged respondents perceive corruption as a bigger obstacle to business operations than others? What role does answer bias play in corruption surveys? This article brings together several strands of literature to discuss these questions, and tests them empirically with survey data from Bangladesh and Sri Lanka. We find that individuals who are more work engaged report corruption as a bigger obstacle. So did respondents who were previously exposed to corruption. We control for possible answer bias by implementing a randomized response technique, and find that corruption tends to be under-reported. The effects of work engagement and prior exposure to corruption are more pronounced when the bias indicator is considered, and again become stronger once we control for answer bias affecting past experiences with corruption. JEL: C83, D03, D73, O12

Suggested Citation

  • Klaus S. Friesenbichler & Eva Selenko & George Clarke, 2018. "Perceptions of Corruption: An Empirical Study Controlling for Survey Bias," Journal of Interdisciplinary Economics, , vol. 30(1), pages 55-77, January.
    • Handle: RePEc:sae:jinter:v:30:y:2018:i:1:p:55-77
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    Citations

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    Cited by:

    1. 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.
    2. Era Dabla-Norris & Mark Gradstein & Fedor Miryugin & Florian Misch, 2019. "Productivity and Tax Evasion," CESifo Working Paper Series 8002, CESifo.

    More about this item

    Keywords

    Corruption; work engagement; survey reticence; random response; Bangladesh; Sri Lanka;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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