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Are Perceptions of Corruption Matching Reality? Theory and Evidence from Microdata

Author

Abstract
Some criticism has been raised on the actual capability of corruption perception-based indices to gauge the essence of concepts they aim to measure. One can argue that perceptions about corruption are not matching reality and could be the re?ection of distorted truth. Based on this evidence we provide a theoretical ground for the corruption decision-making process (objective corruption) and the corruption perception-making process (subjective corruption) which accounts for the role of media attention. From the theoretical model we are able to derive testable implications for the empirical analysis, i.e. whether socio and cultural norms can explain the gap between the two measures of corruption across Europe. We employ a generalised setting of the structural equation models to build latent indices of objective and subjective corruption from our microdata exploiting the information on various economic, geographic and socio-demographic factors that can a¤ect the perception and the experience of corruption practices. The resulting indices allow us to define country rankings for both types of corruption and draw a geopolitical picture of the phenomenon across Europe. We also show that countries where the quality of media is higher are associated with lower di¤erences between perceived and real corruption.

Suggested Citation

  • Germana Corrado & Luisa Corrado & Giuseppe De Michele & Francesco Salustri, 2017. "Are Perceptions of Corruption Matching Reality? Theory and Evidence from Microdata," CEIS Research Paper 420, Tor Vergata University, CEIS, revised 14 Dec 2017.
    • Handle: RePEc:rtv:ceisrp:420
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    References listed on IDEAS

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    1. Weber Abramo, Claudio, 2008. "How Much Do Perceptions of Corruption Really Tell Us?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 2, pages 1-56.
    2. Raymond Fisman & Edward Miguel, 2007. "Corruption, Norms, and Legal Enforcement: Evidence from Diplomatic Parking Tickets," Journal of Political Economy, University of Chicago Press, vol. 115(6), pages 1020-1048, December.
    3. Jakob Svensson, 2003. "Who Must Pay Bribes and How Much? Evidence from a Cross Section of Firms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 207-230.
    4. Naci Mocan, 2008. "What Determines Corruption? International Evidence From Microdata," Economic Inquiry, Western Economic Association International, vol. 46(4), pages 493-510, October.
    5. Habyarimana, James & Humphreys, Macartan & Posner, Daniel N. & Weinstein, Jeremy M., 2007. "Why Does Ethnic Diversity Undermine Public Goods Provision?," American Political Science Review, Cambridge University Press, vol. 101(4), pages 709-725, November.
    6. Dreher, Axel & Kotsogiannis, Christos & McCorriston, Steve, 2007. "Corruption around the world: Evidence from a structural model," Journal of Comparative Economics, Elsevier, vol. 35(3), pages 443-466, September.
    7. Axel Dreher & Friedrich Schneider, 2010. "Corruption and the shadow economy: an empirical analysis," Public Choice, Springer, vol. 144(1), pages 215-238, July.
    8. Barr, Abigail & Serra, Danila, 2010. "Corruption and culture: An experimental analysis," Journal of Public Economics, Elsevier, vol. 94(11-12), pages 862-869, December.
    9. Sequeira, Sandra & Djankov, Simeon, 2014. "Corruption and firm behavior: Evidence from African ports," Journal of International Economics, Elsevier, vol. 94(2), pages 277-294.
    10. Mwangi S. Kimenyi, 2006. "Ethnicity, Governance and the Provision of Public Goods," Journal of African Economies, Centre for the Study of African Economies, vol. 15(1), pages 62-99, April.
    11. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    12. Anders Skrondal & Sophia Rabe‐Hesketh, 2009. "Prediction in multilevel generalized linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 659-687, June.
    13. Benjamin A. Olken & Patrick Barron, 2009. "The Simple Economics of Extortion: Evidence from Trucking in Aceh," Journal of Political Economy, University of Chicago Press, vol. 117(3), pages 417-452, June.
    14. Treisman, Daniel, 2000. "The causes of corruption: a cross-national study," Journal of Public Economics, Elsevier, vol. 76(3), pages 399-457, June.
    15. Maria L. Di Tommaso & Martin Raiser & Melvyn Weeks, 2007. "Home Grown or Imported? Initial Conditions, External Anchors and the Determinants of Institutional Reform in the Transition Economies," Economic Journal, Royal Economic Society, vol. 117(520), pages 858-881, April.
    16. 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).
    17. Buccirossi, Paolo & Spagnolo, Giancarlo, 2006. "Leniency policies and illegal transactions," Journal of Public Economics, Elsevier, vol. 90(6-7), pages 1281-1297, August.
    18. Fisman, Raymond & Svensson, Jakob, 2007. "Are corruption and taxation really harmful to growth? Firm level evidence," Journal of Development Economics, Elsevier, vol. 83(1), pages 63-75, May.
    19. Nicholas Charron & Lewis Dijkstra & Victor Lapuente, 2015. "Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 315-346, June.
    20. Lucia Rizzica & Marco Tonello, 2015. "Exposure to media and corruption perceptions," Temi di discussione (Economic working papers) 1043, Bank of Italy, Economic Research and International Relations Area.
    21. Olken, Benjamin A., 2009. "Corruption perceptions vs. corruption reality," Journal of Public Economics, Elsevier, vol. 93(7-8), pages 950-964, August.
    22. Nicholas Charron & Lewis Dijkstra & Victor Lapuente, 2015. "Erratum to: Mapping the Regional Divide in Europe: A Measure for Assessing Quality of Government in 206 European Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(3), pages 1059-1059, December.
    23. Van Rijckeghem, Caroline & Weder, Beatrice, 2001. "Bureaucratic corruption and the rate of temptation: do wages in the civil service affect corruption, and by how much?," Journal of Development Economics, Elsevier, vol. 65(2), pages 307-331, August.
    24. Luisa Corrado & Giuseppe De Michele, 2016. "Mind the Gap: Identifying Latent Objective and Subjective Multi-dimensional Indices of Well-Being," CEIS Research Paper 386, Tor Vergata University, CEIS, revised 24 Jun 2016.
    25. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
    26. Jaya Krishnakumar & Florian Chávez-Juárez, 2016. "Estimating Capabilities with Structural Equation Models: How Well are We Doing in a ‘Real’ World?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(2), pages 717-737, November.
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    Cited by:

    1. Attar, Andrea & Campioni, Eloisa & Piaser, Gwenaël, 2019. "Private communication in competing mechanism games," Journal of Economic Theory, Elsevier, vol. 183(C), pages 258-283.
    2. Tommaso Proietti & Niels Haldrup & Oskar Knapik, 2017. "Spikes and memory in (Nord Pool) electricity price spot prices," CEIS Research Paper 422, Tor Vergata University, CEIS, revised 18 Dec 2017.
    3. Lorenzo Ferrari & Francesco Salustri, 2020. "The relationship between corruption and chronic diseases: evidence from Europeans aged 50 years and older," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 65(3), pages 345-355, April.

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    More about this item

    Keywords

    Perceived and experienced corruption; Latent variables; Latent multi-dimensional index; Multiple indicators multiple causes models; Generalized SEM MIMIC.;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • H11 - Public Economics - - Structure and Scope of Government - - - Structure and Scope of Government
    • R50 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - General

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