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On The Determinants Of Educational Corruption: The Case Of Ukraine

Author

Listed:
  • Philip Shaw
  • Marina-Selini Katsaiti
  • Brandon Pecoraro

Abstract

type="main" xml:id="coep12097-abs-0001"> This article utilizes a unique data set to examine the relationship between a group of potential explanatory variables and educational corruption in Ukraine. Our corruption controls include bribing on exams, on term papers, for credit, and for university admission. We use a robust nonparametric approach in order to estimate the probability of bribing across the four different categories. This approach is shown to be robust to a variety of different types of endogeneity often encountered under commonly assumed parametric specifications. Our main findings indicate that corruption perceptions, past bribing behavior, and the perceived criminality of bribery are significant factors for all four categories of bribery. From a policy perspective, we argue that when bribe control enforcement is difficult, anti-corruption education programs targeting social perceptions of corruption could be appropriate . ( JEL K42, J16, C14)

Suggested Citation

  • Philip Shaw & Marina-Selini Katsaiti & Brandon Pecoraro, 2015. "On The Determinants Of Educational Corruption: The Case Of Ukraine," Contemporary Economic Policy, Western Economic Association International, vol. 33(4), pages 698-713, October.
    • Handle: RePEc:bla:coecpo:v:33:y:2015:i:4:p:698-713
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    File URL: http://hdl.handle.net/10.1111/coep.2015.33.issue-4
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    Citations

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    Cited by:

    1. Shaw, Philip & Mauro, Joseph A., 2023. "The macroeconomic implications of corruption in the choice to educate," Economic Systems, Elsevier, vol. 47(2).
    2. Zeena Mardawi & Guillermina Tormo‐Carbó & Elies Seguí‐Mas & Saed Al‐Koni, 2023. "Does corruption rule the auditor's soul? Examining the auditors' attitude toward accepting corruption behaviors," Economics and Politics, Wiley Blackwell, vol. 35(3), pages 1070-1098, November.
    3. Obbey Elamin & Len Gill & Martyn Andrews, 2020. "Insights from kernel conditional-probability estimates into female labour force participation decision in the UK," Empirical Economics, Springer, vol. 58(6), pages 2981-3006, June.
    4. Vasylyeva, Anna & Merkle, Ortrun, 2018. "Combatting corruption in higher education in Ukraine," MERIT Working Papers 2018-021, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Denisova-Schmidt, Elena & Huber, Martin & Leontyeva, Elvira, 2016. "On the development of students’ attitudes towards corruption and cheating in Russian universities," FSES Working Papers 467, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    6. Robson Fernandes Soares & Edson Ronaldo Guarido Filho, 2021. "Anti-Corruption Enforcement and Organizations: A Narrative Review," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 25(6), pages 190149-1901.
    7. Asif Reza Anik & Siegfried Bauer, 2014. "Household Income and Relationships with Different Power Entities as Determinants of Corruption," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 8(3), September.

    More about this item

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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