Corruption's effect on BRICS countries' economic growth: a panel data analysis

• Autores: Simo-Kengne, Beatrice D., Bitterhout, Siphiwo
• Formato: artículo
• Fecha de Publicación: 2023
• Institución: Universidad ESAN
• Repositorio: ESAN-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.esan.edu.pe:20.500.12640/3678
• Enlace del recurso: https://hdl.handle.net/20.500.12640/3678; https://doi.org/10.1108/JEFAS-04-2021-0041
• Nivel de acceso: acceso abierto
• Materia: Corruption; Economic growth; Panel data; Corrupción; Crecimiento económico; Datos de panel; https://purl.org/pe-repo/ocde/ford#5.02.04

Purpose: The theoretical debate of corruption's impact on economic growth remains unsettled, making it an empirical question. This study aims to investigate corruption's effect on BRICS countries' economic growth. Design/methodology/approach: A panel dataset on BRICS countries spanning 1996 to 2020 was used. Bias-corrected estimators in small dynamic panels were employed to estimate a growth model as a linear-quadratic function of corruption that accounts for cross-sectional dependence, endogeneity and unobserved heterogeneity due to country and time-specific characteristics. Findings: The results indicate that corruption is detrimental to economic growth in BRICS countries; the quadratic relationship implies corruption is less prevalent in some countries than others. Thus, governments of BRICS countries are encouraged to embark on anti-corruption policies to boost their economic performance. Originality/value: An important limitation of corruption studies is the difficulty in measuring real corruption experiences due to the secretive nature of corruption and the fact that corruption is known not to leave a paper trail. For the uncertainty of the index estimates, the analysis used a continuous corruption composite score measuring the standard deviation of the extent to which public power is exercised for public gain. Furthermore, estimation and inference are robust to small dynamic panels with a general form of cross-sectional dependence.