Panel Data Analysis on the Socio-Economic Determinants of Corruption in the D-8 Countries
Panel Data Analysis on the Socio-Economic Determinants of Corruption in the D-8 Countries
The phenomenon of corruption is a problem which has high negative externalities at the economic, sociological, and global levels. Throughout history, corruption has expressed itself differently but has been present in nearly every society. It continues to affect many developed and developing societies today. The widespread public externality caused by corruption has been studied in various scientific fields, such as economics, finance, sociology, and psychology. The majority of the literature reveals that corruption negatively affects economic growth and development. Measuring corruption, a socioeconomic problem that is illegal, is difficult because there are challenges in identifying its determinants. The aim of this study is to conduct an empirical analysis of corruption with selected determinants. In the present study, the following the determinants of corruption were used: economic freedom, GDP, human development index, tax burden, and inflation. Data was obtained from the period between 2003 and 2021 from the D-8 countries (which consist of Indonesia, Bangladesh, Iran, Egypt, Malaysia, Pakistan, Nigeria, and Turkey), before panel data analysis was conducted. In the analysis, corruption was used as the dependent variable, while general government expenditure, economic freedom, GDP, human development index, total tax revenue as a percentage of GDP, and inflation were used as explanatory variables. The results of the analysis revealed that economic freedom, human development index, and the governments total tax revenue as a percentage of GDP positively affect the corruption perception index. The rate of inflation, GDP, and government spending did not have a significant relationship with corruption.
___
- Akça, H., Ata, A. Y., & Karaca, C. (2012). Inflation and corruption relationship: Evidence from panel data in developed and developing countries. International Journal of Economics and Financial Issues, 2(3), 281-295. google scholar
- Akçay, S. (2000). Yolsuzluk, ekonomik özgürlükler ve demokrasi. Muğla Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (1), 1-15. google scholar
- Al-Marhubi, F. A. (2000). Corruption and inflation. Economics Letters, 66(2), 199-202. google scholar
- Alsarhan, A. A. (2019). Determinants of corruption in Middle East countries: Evidence from panel data. International Journal of Economic Behavior and Organization, 7(4), 57-63. http://dx.doi. org/10.11648/j.ijebo.20190704.11 google scholar
- Baltagi, B. H. (2005). Econometrics analysis of panel data (3th ed.). John Wiley & Sons. google scholar
- Banerjee, A., Mullainathan, S., & Hanna, R. (2012). Corruption (No. w17968). National Bureau of Economic Research. Working Paper 17968. google scholar
- Bayar, G. (2010). Corruption in Turkey-an econometric enalysis. Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 1(28), 105-131. google scholar
- Bitterhout, S., & Simo-Kengne, B. D. (2020). The effect of corruption on economic growth in the BRICS countries. A panel data analysis. University of Johannesburg, EDWRG Working Paper, 10-2022. google scholar
- Çelen, M. (2007). Yolsuzluk ekonomisi- kamusal bir kötülük olarak yolsuzluğun ekonomik analizi. İstanbul Serbest Muhasebeci ve Mali Müşavirler Odası Yayınları. google scholar
- Davies, A., & Lahiri, K. (1995). A new framework for testing rationality and measuring aggregate shocks using panel data. Journal of Econometrics, 68(1), 205-227. http://dx.doi.org/10.1016/0304-4076(94)01649-K. google scholar
- Farrales, M. J. (2005). What is corruption?: A history of corruption studies and the great definitions debate. (June 2005). http://dx.doi.org/10.2139/ssrn.1739962. google scholar
- Ghura, D. (1998). Tax revenue in Sub-Saharan Africa: Effects of economic policies and corruption (No. 98/135). International Monetary Fund. google scholar
- Greene, W. H. (2003). Econometric analysis. Prentice-Hall. google scholar
- Gründler, K., & Potrafke, N. (2019). Corruption and economic growth: New empirical evidence. European Journal of Political Economy, 60, 101810. google scholar
- Heritage Foundation. (2022). The heritage foundation. https://www.loc.gov/item/lcwaN0002695/. google scholar
- Hsiao, C. (2007). Panel data analysis—advantages and challenges. Test, 16(1), 1-22. http://dx.doi. org/10.1007/s11749-007-0046-x. google scholar
- Linhartova, V., & Halaskova, M. (2022). Determinants of corruption: A panel data analysis of Visegrad countries. Equilibrium. Quarterly Journal of Economics and Economic Policy, 17(1), 51-79. http://dx.doi.org/10.24136/eq.2022.003 google scholar
- Paldam, M. (1999). The Big Pattern of Corruption: Economics, Culture, and Seesaw Dynamics. Working Paper No: 11, Center for Dynamic Modelling in Economics, Department of Economics, University of Aarhus, Denmark. google scholar
- Piplica, D. (2011). Corruption and inflation in transition EU member countries. Ekonomska Misao I Praksa, 20(2), 469-506. google scholar
- Rehman, H. U., & Naveed, A. (2007). Determinants of corruption and its relation to GDP (A panel study). Journal of Political Studies, 12(2), 27-59. google scholar
- Sandu, S., & Ciocanel, B. (2014). Impact of R & D and Innovation on High-tech Export. Procedia Economics and Finance, 15, 80-90. google scholar
- Senaviratna, N. A. M. R., & Cooray, T. M. J. A. (2019). Diagnosing multicollinearity of logistic regression model. Asian Journal of Probability and Statistics, 5(2),1-9. http://dx.doi.org/10.9734/ ajpas/2019/v5i230132. google scholar
- Stephen. (1999, August 29). The Turkish quake’s secret accomplice: Corruption. New York Times, p. 3. google scholar
- Svensson, J. (2005). Eight questions about corruption. Journal of Economic Perspectives, 19(3), 19-42. google scholar
- Tanzi, V. (1998). Corruption around the world: Causes, consequences, scope, and cures. https:// www.imf.org/en/Publications/WP/Issues/2016/12/30/Corruption-Around-the-World-Causes-Consequences-Scope-and-Cures-2583 google scholar
- Topal, M. H., & Ünver, M. (2016). The determinants of corruption: A panel cointegration analysis for fragile economies. Balkan ve Yakın Doğu Sosyal Bilimler Dergisi, 2(2), 58-68. google scholar
- Tosun, U. (2003). Yolsuzluğun nedenleri üzerine ampirik bir çalışma. Akdeniz İktisadi İdari Bilimler Fakültesi Dergisi, 5, 125-146. google scholar
- Transparency International. (2019). What is corruption? https://www.transparency.org/what-is-corruption/#define (20.09. 2022). google scholar
- Transparency International. (2022a). Corruption Perceptions Index. https://www.transparency.org/ en/cpi/2021 (8.12.2022). google scholar
- Transparency International. (2022b). Corruption Perceptions Index Report 2021. CPI2021_Report_ EN-web.pdf (transparencycdn.org) (8.12.2022). google scholar
- UNODC. (2022). UNODC’s action against corruption and economic crime. https://www.unodc.org/ unodc/en/corruption/ google scholar
- Swaleheen, M., & Stansel, D. (2007). Economic freedom, corruption and growth. Cato Journal, 27(3), 343-358. google scholar
- Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT Press. google scholar
- World Bank. (2021). Worldwide Governance Indicators. https://databank.worldbank.org/source/ worldwide-governance-indicators google scholar
- Yamak, N., Abdioğlu, Z., & Doğan, S. (2022). Determinants of corruption in the G20 countries: Panel ordered logit approach. Gazi İktisat ve İşletme Dergisi, 8(3), 501-512. google scholar