Methodological errors in corruption research: Recommendations for future research

Andrew Delios (), Edmund J. Malesky (), Shu Yu () and Griffin Riddler ()
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Andrew Delios: National University of Singapore
Edmund J. Malesky: Duke University
Shu Yu: Suzhou Industrial Park Monash Research Institute of Science and Technology
Griffin Riddler: Duke University

Journal of International Business Studies, 2024, vol. 55, issue 2, No 7, 235-251

Abstract: Abstract The secretive, illegal, multidimensional, and ubiquitous nature of corruption leads to formidable difficulties in research design and measurement. When research fails to account for these challenges, it can lead to an empirical misalignment with concepts and theories of corruption, with inferential errors commensurately emerging. We define, measure, and track four common measurement errors and two common research design errors for papers on corruption published in international business/management and political economy journals in the 2000–2021 period. Our data marks a substantial opportunity to tighten the fit between theory and methods. We offer recommendations to accelerate improvements in empirical research on corruption, and indeed for other phenomena that are characterized by legal, moral, and social desirability concerns. These empirical recommendations contribute to more robust theory building.

Keywords: corruption; ethics; bribery; measurement error; research design; list experiments; political economy (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1057/s41267-023-00637-8

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