[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 17, Issue 67 (12-2017) ::
2017, 17(67): 37-69 Back to browse issues page
The Effect of Corruption on Income Distribution: A Panel Data Approach
Parvaneh Salatin
Abstract:   (1391 Views)
introduction: In economic literature, financial corruption is defined as the abuse of public resources to one’s own personal interests. Financial corruption is a multidimensional, complex phenomenon having many causes and consequences. It is demonstrated on different cultural, political and economical scale. Increased paperwork in bureaucracies paves the way to the financial corruption. High, illegal payments to the public authorities, payments made to affect regulation process, public distrust, payments made to duck away from taxes or to achieve import and export permits, utilization of the national budget for personal purposes and finally, payments by highly influential figures and monopolies made to leave other corporations deficient, are the major factors to determine the corruption index. Financial corruption creates inefficient assignments for the genius. In case financial corruption prevails, people in the society, specifically the talents, try to use illegal ways like bribery and economic rent, instead of their skills, to achieve public permits. Otherwise, these people could increase the society’s potential for technical development. Financial corruption is a widespread phenomenon that all countries, including both developed and developing countries, have to face.Several studies show that reducing the corruption in developing countries has been accompanied by increasing the income inequality. In contrast, in developed countries, reducing the corruption leads to a reduction in inequality.In this regard, the main objective of this paper is to analyze the effect of corruption on income distribution in middle-income selected countries.
Method: The purpose of this research is to investigate the nature of the method and the method of approach to the inferential problem and longitudinal secondary analysis. In terms of the method of identifying and collecting information and statistical resources, the method used is written document, electronic information and vector scanning. In this study, we refer to the statistical data available at the World Bank. Using multivariate regression and panel data and Excel and Eviews softwares, modeling the factors affecting the distribution of income with emphasis on corruption has been used. Using the panel data has advantages that make it different from other methods. Panel data has more information, greater variability, lower coherency, higher degrees of freedom, and higher efficiency over time series and cross-sectional data. Particularly, one of the ways to reduce coherence is to combine cross-sectional and temporal data into panels.
Findings: The results of estimating the model using the Fixed Effect and Generalized Method of Movement in the selected countries in the period of 1996-2013 indicate that financial corruption has a positive and significant effect on the Gini coefficient as an income distribution index in middle-income selected countries. Also, other results of the model show that with increasing unemployment in middle-income selected countries, the Gini coefficient has increased and the distribution of income has been uneven. By improving information and communication technology (ICT) and increasing real GDP, the Gini coefficient has decreased in middle-income selected countries and the distribution of income has improved. The expansion of information and communication technology improves access to free flow of information, increased production and improved distribution of income. In dynamic estimation of inflation, the positive and significant effects and the degree of openness of the economy had a negative and significant effect on the Gini coefficient as an indicator of income distribution. Increasing the general level of prices, reducing real wages and reducing the purchasing power of the labor rights will increase income inequality. Inflation and the degree of openness of the economy in the static estimation have no meaningful relation with the Gini coefficient in middle-income selected countries.
Discussion: There are two rival and contrasting theories on the effect of financial corruption on economic development. The first group are theories that consider corruption as a force that damages the efficiency of markets and in this way causes a decrease in economic development. In the other theories, corruption brings about an increase in economic development and growth by bypassing the inapt market regulations and bureaucracies. The results of this study indicate that in the group of selected countries the average income of the second group theory is true. According to the results of this study, efforts and planning to improve the business environment and reduce the volume and size of the state and create the conditions for the greater participation of the private sector, reducing the informal sector of the economy, monitoring and controlling the implementation of laws and regulations, attempting to clarify laws and regulations and removing personal perceptions of them, simplifying regulations and It is recommended to use the experience of successful countries.
Keywords: Corruption, Gini coefficient, Income distribution, Panel data, Middle-income countries
Full-Text [PDF 526 kb]   (922 Downloads)    
Type of Study: orginal |
Received: 2018/05/8 | Accepted: 2018/05/8 | Published: 2018/05/8
References
1. Ackerman, R. (1978). Corruption. A study in political economy. London/ New York: Academic Press.
2. Ackerman, R. (1988). The Political Economy of Corruption: Causes End Consequences. World Bank.
3. Ades, A. and Rafael D. T, (2012). Causes and consequences of corruption: a review of experimental results. Quarterly Journal of Economics, 114 (1), 83-116.
4. Alesina, A. (1998). The polical Economy of High and Low Growth. Annual world Bank confernce on Development Econmics, 1997, Washington DC world Bank.
5. Aman Ullah, A. & Ahmad, E. (2007). The Relationship Between Corruption and Income Inequality. 22nd Annual General Meeting, Pakistan Society of Development Economists, Islamabad.
6. Amin Ullah, M. & Eatzez, A. (2016). Inequality and Corruption: Evidence from Panel Data. Forman Journal of Economic Studies, 12, 1-20.
7. Anders et al. (2008). Corruption, privatization and income distribution in Latin America. Political Research Quarterly, 13 (7), 45-57.
8. Apergis, N. & Dincer, O. C. (2009). The Relationship between corruption and income inequality in U.S. states: evidence from a panel cointegration and error correction model. Public Choice, 145 (1), 125-135.
9. Blackburn, K. & Powell, J. (2011). Corruption, inflation and growth. Economics Letters, 113 (3), 225-227.
10. Chong, A. & Gradstein, M. (2004). Inequality and Institution. Research Department Working paper, No. 506, Inter- American Development Banlc: New York, NY.
11. Cipraston, A. J. & Zinal, B. (2014). The Effect of Corruption on Economic Growth. Europen Journal of Political Economy, 27 (3), 56-68.
12. Clague, C. (Ed.) (1997). Institutions and Economic Development: Growth and Governance in Less- Developed and post- Socialist countries. Baltimore and London: The John Hopkins university press.
13. Dobson, S. & Ramlogan, C. (2012). Why is Corruption Less Harmful to Income Inequality in Latin America?. World Development, 40 (8), 1534-1554.
14. El-Ayouty et al. (2003). Corruption as Anti-development in perspectives on 9/11. Greenwood publishing Group: west port, CT.
15. Feng, Y. (2003). De mocracy, Governance and Economic performance: Theory and Evidence. Cambridge: MA, MIT press.
16. Gallo, L. M. & Sagales, R. (2013). Joint Determinants of Fiscal Policy, Income Inequality and Economic Growth. Economic Modelling, 30 (1), 814-824.
17. Gupta, S., Davoodi, T. & Alonso-Terme, R. (1998). Does Corruption Affect Income Inequality and Poverty?. IMF Working Paper.
18. Habib, M. & Zurawicki, L. (2002). Corruption and Foreign Direct Investment. Journal of International Business Studies, 33 (2), 291-307.
19. Hanousek, J. & Kochanova, A. (2015). Bribery environment and firmperformance: Evidence from Central and Eastern European Countries. CEPR Discussion Paper 10499.
20. Huang, Ch. (2012). Corruption, Economic Growth, and Income Inequality: Evidence from Ten Countries in Asia. World Academy of Science, Engineering.
21. Jong, S. & Khagram, S. (2005). A comparative study of Inequality and Corruption. Amerian sociological Review, 10 (1),pp, 136-157.
22. Kaufman, D., Kraay, A. & Mastruzzi, M. (2007). The Worldwide Governance Indicators Project: Answering the Critics. World Bank Policy Research Working Paper No. 4149, Washington, D.C.
23. Kaufman, D., Kraay. A. & Mastruzzi, M. (2006). Measuring Governance Using Perceptions Data. In S. Rose-Ackrman (Ed.). Handbook of Economic Corruption. Washington, DC: World Bank : Edward Elgar.
24. Kaufmann, D., Kraay, A., Zoido-Lobaton, P. (1999), Governance matters, Development Economics Research Group, Washington, DC: World Kaufmann, D. and Kraay A. (2007), Governance Indicators: Where Are We, Where Should We Be Going? Global governance Group, Policy Research Working Papers, No 4370, Washington DC: World Bank .
25. Khan, M. (1996). A typology of corrupt transactions in developing countries. IDS Bulletin, 8 (5), pp, 12-21.
26. Knack, S. & Keefer, P. (2003). Does social capital Have an Economic Payoof: A cross country emprical investigation. In S. Knack (Ed.). Democracy Governance and Growth. Ann Arbor: The University of Michigan Press.
27. Knack, S. (Ed.) (2003). Democracy, Governance and Growth. Ann Arbor: The university of michigan press.
28. La Porto, R., Lopez-de-Silanes, F., Shleifer, A. & Vishny, R. (1998). The Quality of Govermment, Journal of Law, Economics and arganisation, 15 (1), 222-279.
29. Li, H., Squire, L. & Zou, H-F. (1998). Explaining International and Intertemporal variations in Income Inequality. The economic Journal, 108, 26-43.
30. Mandal, B. & Marjit, S. (2010). Corruption and wage inequality? International Review of Economics and Finance, 19, 166-172.
31. Mauro, P. (1995). Corruption and Growth. Quartely Journal of Economics, 110 (3), 681-712.
32. Paldum, M. (1999). The big pattern of Corruption: Economics, Culture and the Seesaw dynamics. Working paper, No.1999-11, Department of Economics, University of Aarhus.
33. Patrick, A. & Jacobs, F. (2007). Effect of Corruption on Tax revenues in the Middle East. IMF Working Paper.
34. Poirson, H. (1998). Economic security, private investment and growth in developing countries. IMF working paper, wp/9817.
35. Tanzi, V. & Davoodi, H. (1997). Corruption, public investment, and growth. IMF working paper 97/139. Washington D.C. Reprinted as chapter? In V. Tanzi (2000). Policies, Institutions and the dark side of economics. Cheltenham: Edward Elgar.
Add your comments about this article
Your username or Email:

CAPTCHA code


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Salatin P. The Effect of Corruption on Income Distribution: A Panel Data Approach. Social Welfare. 2017; 17 (67) :37-69
URL: http://refahj.uswr.ac.ir/article-1-3090-en.html


Volume 17, Issue 67 (12-2017) Back to browse issues page
فصلنامه رفاه اجتماعی Social Welfare Quarterly
Persian site map - English site map - Created in 0.07 seconds with 30 queries by YEKTAWEB 3764