Identifying the Determinants of Corruption: An Application of Instrumental Variable Bayesian Model Averaging
Subject Areas : Labor and Demographic Economics
Safoora Kashefi
1
(
PhD student in Economics, Aras International Campus, University of Tehran, Tehran, Iran
)
Mohsen Mehrara
2
(
Professor, Department of Economics, University of Tehran, Tehran, Iran
)
Ghahraman Abdoli
3
(
Professor, Department of Economics, University of Tehran, Tehran, Iran
)
Keywords: Rule of law, D72, JEL classification: C11, Bayesian Model Averaging, D73. Keywords: Corruption, Endogeneity, Model Uncertainty,
Abstract :
AbstractPrevious studies in the corruption literature have introduced numerous variables as the determinants of corruption. This articles aims to evaluate the robustness of potential determinants of corruption by addressing the model uncertainty and endogeneitry. The results derived from an instrumental variable Bayesian model averaging analysis indicate that based on the data of 123 countries, rule of law, with a posterior inclusion probability (PIP) of 1 and posterior mean of 0.662 has the most important role in keeping corruption under control among 36 explanatory variables. Government effectiveness, with a PIP of 0.964 and posterior mean of 0.358 is another significant variable in curbing corruption. Also, with a PIP of 0.965 and posterior mean of -0.194 the Asia dummy variable tells that corruption is a serious problem in the Asia region. Further, confining the analysis to 95 developing countries reveals that rule of law with a PIP of 0.999 and posterior mean of 0.684 is the most critical variable in the fight against corruption.
¾ ادیبپور، مهدی، کرباسیزاده، سینا (1397). رانت نفتی و فساد در کشورهای منطقه خاورمیانه و شمال آفریقا (منا). فصلنامه مدلسازی اقتصادی، (44)12: 72- 47.
¾ باغچقی، اقدس، خوشنودی، عبداله، هراتی، جواد (1398). بررسی اثر متقابل دموکراسی و امنیت حقوق مالکیت بر فساد مالی در کشورهای مختلف. فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)، (3)98: 144- 109.
¾ سپهردوست، حمید، برجیسیان، عادل (1397). رابطه فساد با حقوق مالکیت، نابرابری درآمد و دموکراسی، شواهد تجربی کشورهای منتخب. دو فصلنامه جستارهای اقتصادی ایران، (29)15: 172-143.
¾ مرادی، ابراهیم، رهنما، علی، حیدریان، سمیرا (1396). تاثیر شاخصهای حکمرانی خوب بر کنترل فساد (مطالعه موردی: کشورهای خاورمیانه و جنوب شرق آسیا). فصلنامه اقتصاد مقداری، (4)14: 182- 151.
¾ مهرآرا، محسن، قبادزاده، رضا (1395). بررسی عوامل مؤثر بر تورم در ایران مبتنی بر رویکرد میانگین‌گیری بیزینی (BMA) و میانگین‌گیری حداقل مربعات (WALS). فصلنامه برنامه‌ریزی و بودجه، (1)21: 82- 57.
¾ Acemoglu, D., &Verdier, T. (1998). Property rights, corruption and the allocation of talent: A general equilibrium approach. The Economic Journal, 108(450): 1381–1403.
¾ Acemoglu, D., Johnson, S., & Robinson, J. A. (2001). The colonial origins of comparative development: An empirical investigation. American economic review, 91(5): 1369-1401.
¾ Akbari, M., Bahrami-Rad, D., & Kimbrough, E. O. (2019). Kinship, fractionalization and corruption. Journal of Economic Behavior & Organization.
¾ Alesina, A., & Angeletos, G. M. (2005). Corruption, inequality, and fairness. Journal of Monetary Economics, 52(7): 1227-1244.
¾ Alesina, A., Devleeschauwer, A., Easterly, W., Kurlat, S., & Wacziarg, R. (2003). Fractionalization. Journal of Economic Growth, 8(2): 155–194.
¾ Arezki, R., & Brückner, M. (2011). Oil rents, corruption, and state stability: Evidence from panel data regressions. European Economic Review, 55(7): 955–963.
¾ Arikan, G. G. (2004). Fiscal decentralization: A remedy for corruption? International Tax and Public Finance, 11(2): 175-195.
¾ Badinger, H., &Nindl, E. (2014). Globalisation and corruption, revisited. The World Economy, 37(10): 1424-1440.
¾ Bazzi, S., & Clemens, M. A. (2013). Blunt instruments: Avoiding common pitfalls in identifying the causes of economic growth. American Economic Journal: Macroeconomics, 5(2): 152–186.
¾ Brunetti, A., & Weder, B. (2003). A free press is bad news for corruption. Journal of Public economics, 87(7-8): 1801-1824.
¾ Capasso, S., & Santoro, L. (2018). Active and passive corruption: Theory and evidence. European Journal of Political Economy, 52: 103-119.
¾ d'Agostino, G., Dunne, J. P., & Pieroni, L. (2016). Corruption and growth in Africa. European Journal of Political Economy, 43: 71-88.
¾ Dell’Anno, R., & Teobaldelli, D. (2015). Keeping both corruption and the shadow economy in check: the role of decentralization. International Tax and Public Finance, 22 (1): 1-40.
¾ Dong, B., & Torgler, B. (2013). Causes of corruption: Evidence from China. China Economic Review, 26: 152-169.
¾ Dreher, A., Kotsogiannis, C., & McCorriston, S. (2009). How do institutions affect corruption and the shadow economy? International Tax and Public Finance, 16(6): 773.
¾ Egger, P., & Winner, H. (2006). How corruption influences foreign direct investment: A panel data study. Economic Development and Cultural Change, 54(2): 459–486.
¾ Eicher, T. S., Henn, C., & Papageorgiou, C. (2012). Trade creation and diversion revisited: Accounting for model uncertainty and natural trading partner effects. Journal of Applied Econometrics, 27(2): 296–321.
¾ Fan, C. S., Lin, C., & Treisman, D. (2009). Political decentralization and corruption: Evidence from around the world. Journal of Public Economics, 93(1-2): 14-34.
¾ Fernandez, C., Ley, E., & Steel, M. F. (2001). Model uncertainty in cross‐country growth regressions. Journal of applied Econometrics, 16(5): 563-576.
¾ Freille, S., Haque, M. E., & Kneller, R. (2007). A contribution to the empirics of press freedom and corruption. European Journal of Political Economy, 23(4): 838-862.
¾ Gatti, R. (2004). Explaining corruption: Are open countries less corrupt? Journal of International Development, 16(6): 851-861.
¾ Glaeser, E. L., & Saks, R. E. (2006). Corruption in America. Journal of public Economics, 90(6-7): 1053-1072.
¾ Goel, R. K., & Nelson, M. A. (2010). Causes of corruption: History, geography and government. Journal of Policy Modeling, 32(4): 433-447.
¾ Gokcekus, O., & Knörich, J. (2006). Does quality of openness affect corruption? Economics Letters, 91(2): 190-196.
¾ Grim, B. J., & Finke, R. (2006). International religion indexes: Government regulation, government favoritism, and social regulation of religion. Interdisciplinary Journal of Research on Religion, 2: 1–40.
¾ Hoeting, J. A., Madigan, D., Raftery, A. E., &Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical science: 382-401
¾ Iwasaki, I., & Suzuki, T. (2012). The determinants of corruption in transition economies. Economics Letters, 114(1): 54-60.
¾ Jha, C. K., & Sarangi, S. (2018). Women and corruption: What positions must they hold to make a difference? Journal of Economic Behavior & Organization, 151: 219-233.
¾ Karl, A., & Lenkoski, A. (2012). Instrumental variable Bayesian model averaging via conditional Bayes factors. ArXiv preprint arXiv: 1202.5846.
¾ Knack, S., &Azfar, O. (2003). Trade intensity, country size and corruption. Economics of Governance, 4(1): 1-18.
¾ Knutsen, C. H., Kotsadam, A., Olsen, E. H., & Wig, T. (2017). Mining and local corruption in Africa. American Journal of Political Science, 61(2): 320-334.
¾ Kolstad, I., & Wiig, A. (2016). Does democracy reduce corruption? Democratization, 23(7): 1198-1215.
¾ Koop, G., Leon-Gonzalez, R., & Strachan, R. (2012). Bayesian model averaging in the instrumental variable regression model. Journal of Econometrics, 171(2): 237-250.
¾ Lima, M. S. M., &Delen, D. (2019). Predicting and explaining corruption across countries: A machine learning approach. Government Information Quarterly, 101407.
¾ Lopez-Valcarcel, B. G., Jiménez, J. L., & Perdiguero, J. (2017). Danger: local corruption is contagious! Journal of Policy Modeling, 39(5): 790-808.
¾ Magnus, J. R., Powell, O., &Prüfer, P. (2010). A comparison of two model averaging techniques with an application to growth empirics. Journal of Econometrics, 154(2): 139-153.
¾ Mocan, N. (2008). What determines corruption? International evidence from microdata. Economic Inquiry, 46(4): 493-510.
¾ Murtin, F. (2013). Long-term determinants of the demographic transition, 1870–2000. Review of Economics and Statistics, 95(2): 617–631.
¾ Musila, J. W., & Sigué, S. P. (2010). Corruption and international trade: An empirical investigation of African countries. The World Economy, 33(1): 129–146.
¾ OECD (2013). The rationale for fighting corruption. https:// www. OECD. org/ cleangovbiz/ 49693613.pdf
¾ Pellegrini, L. (2011). Causes of corruption: a survey of cross-country analyses and extended results. In Corruption, development and the environment, Springer, Dordrecht: 29-51.
¾ Pinto, P. M., & Zhu, B. (2016). Fortune or evil? The effect of inward foreign direct investment on corruption. International Studies Quarterly, 60(4): 693-705.
¾ Reed, W. R. (2015). On the practice of lagging variables to avoid simultaneity. Oxford Bulletin of Economics and Statistics, 77(6): 897–905.
¾ Serra, D. (2006). Empirical determinants of corruption: A sensitivity analysis. Public Choice, 126(1-2): 225-256.
¾ Shen, C., & Williamson, J. B. (2005). Corruption, democracy, economic freedom, and state strength: A cross-national analysis. International Journal of Comparative Sociology, 46(4): 327-345.
¾ Stanig, P. (2015). Regulation of speech and media coverage of corruption: An empirical analysis of the Mexican press. American Journal of Political Science, 59(1): 175–193.
¾ Swamy, A., Knack, S., Lee, Y., &Azfar, O. (2001). Gender and corruption. Journal of development economics, 64(1): 25-55.
¾ Teorell, J., Samanni, M., Holmberg, S., & Rothstein, B. (2011). The quality of government basic dataset made from the QoG standard dataset version 6 Apr 11. The Quality of Government Institute, University of Gothenburg.
¾ Treisman, D. (2000). The causes of corruption: A cross-national study. Journal of public economics, 76(3): 399-457.
¾ Treisman, D. (2007). What have we learned about the causes of corruption from ten years of cross-national empirical research? Annu. Rev. Polit. Sci., 10: 211-244.
¾ Uberti, L. J. (2018). Corruption in transition economies: Socialist, ottoman or structural? Economic Systems, 42(4): 533-555.
¾ World Bank (2010).https://www.worldbank.org/en/news/feature/2010/12/06/corruption-hunters-rally-for-action-against-fraud
¾ You, J., & Nie, H. (2017). Who determines Chinese firms' engagement in corruption: Themselves or neighbors? China Economic Review, 43: 29-46.
¾ Zellner, A. (1986). On assessing prior distributions and Bayesian regression analysis with g-prior distributions. Bayesian inference and decision technique.
_||_