Vol. 8 No. 4 (2020): Business & Management Studies: An International Journal


Mehmet Ali POLAT
Asisst. Prof. Dr., Malatya Turgut Özal University

Published 2020-12-10


  • Transfer Payments Income Distribution Panel Data Analysis Method GINI Coefficient
  • Transfer Ödemeleri, Gelir Dağılımı, Panel Veri Analizi Yöntemi, GINI Katsayısı

How to Cite

POLAT, M. A. . (2020). THE IMPACTS OF TRANSFER PAYMENTS FOR SOCIAL PURPOSES ON INCOME DISTRIBUTION: PANEL DATA ANALYSIS FOR OECD COUNTRIES. Business & Management Studies: An International Journal, 8(4), 764–796. https://doi.org/10.15295/bmij.v8i4.1577




In this study, the effect of transfer payments on income distribution was examined by panel data analysis method, using data from 36 OECD countries for 1996-2018 period. In the study; GINI coefficient was used as the dependent variable, and the data for the ratio of household transfer payments to national income was as the independent variable. As a result of the panel regression analysis; it was determined that in OECD countries, transfer payments to households and economic growth reduced income inequality in 1996-2018 period.

Based on the findings of Gustafsson and Johansson (1999), Li et al. (2000), Keane and Prasad (2002), Sylwester (2002), Schwabish et al. (2004), Huber et al. (2004), Afonso et al. (2010), Niehues (2010), Hazman (2011), Holzner (2011), Caminada et al. (2012), Wang et al. (2012), Woo et al. (2013), Martínez-Vázquez et al. (2014), İlgün (2015), D’Agostino et al. (2016), Cimoli et al. (2017), Eroğlu et al.  (2017), Ürper (2018), Kozuharov and Petkovski (2018), Yardımcıoğlu and Yayla (2020); It can be stated that the transfer payments made by countries to their citizens have a decreasing effect on the income distribution imbalance. Therefore, it would be beneficial for countries to continue such aids within their means.


The study aimed to examine the effect of social transfer expenditures on income distribution. The result that the transfer payments to households reduce income distribution inequality has made the study necessary in terms of guiding government policies.


It is thought that the study using data from 36 OECD countries will make a significant contribution to the literature by the finding that transfer payments to households will reduce income inequality.



This study is a research paper, and a quantitative research design was adopted in the study.


In this study, the effect of transfer payments on income distribution was examined by panel data analysis method, using data from 36 OECD countries for 1996-2018 period.


The GINI coefficients are obtained from The Standardized World Income Inequality Database Version 8 prepared by Frederick (2019), which is in the Harvard University Data Bank. Transfer payments were gathered from OECD (2020b), economic growth and population data were from the World Bank (2020a, 2020b).


In this study, the effect of transfer payments on income distribution was examined by panel data analysis method, using data from 36 OECD countries for 1996-2018 period. In the study; GINI coefficient was used as the dependent variable, and the data for the ratio of household transfer payments to national income was as the independent variable. Also, economic growth rate, population growth rate, dummy variables representing the 2008 global economic crisis were included in the analysis. LLC tested the stationarity of the series included in the study, IPS, Fisher ADF and Fisher PP panel unit root tests and it was found that the series were stationary at level values.

Since the countries in the analysis are spread over vast geography, and they do not have standard policies affecting the balance of income distribution, it is not expected that there will be cross-section dependencies between countries. Therefore, first-generation panel data analysis methods were preferred in the study. In this context, the stationarity of the series was tested by Levin, Lin and Chu (2002, LLC), Im, Pesaran and Shin (2003, IPS), Maddala and Wu (1999), Fisher ADF and Fisher PP panel unit root tests. The method to be used in the panel regression analysis was decided by the Hausman (1978) test. Causality relationships between the series were examined by Dumitrescu and Hurlin (2012) panel causality test.



The existence and direction of causality relationships between series were examined by Dumitrescu and Hurlin (2012) panel causality test. As a result of this test; the mutual causality relationship was found between transfer payments and income distribution inequality in OECD countries. This relationship implies that when the income distribution imbalance in countries increases/decreases, transfer payments also increase/decrease. As a matter of fact, in the Covid-19 period, developed countries, especially the USA and Canada, gave unrequited money (made transfer payments) to their citizens whose monthly income was below a certain level. Two-way causality relationship between income inequality and population growth rate supports the premise that countries with high population growth rates also have high imbalances in income distribution. The mutual causality relationship between population growth rate and transfer payments also reminds the type of state aid of payments per child, especially in developed countries. The causality relationship from economic growth to transfer payments indicates that countries with higher income can provide more assistance to their citizens. The causality relationship from income inequality to economic growth suggests that when the income distribution imbalances in countries decreases, individuals get the return of their labor more quickly and, thus, they work more efficiently and contribute positively to the economic growth of their countries.


4.1. RESULTS of the PAPER

According to the findings obtained at the end of the study; in OECD countries, transfer payments to households in the 1996-2018 period reduced income inequality. This result is significant on the main question that our study focuses on. In that case; it would be beneficial for countries to continue to increase their transfer payments so that they can reduce the income imbalance among their citizens. Increases in economic growth have also reduced income inequality. This suggests that the income generated is shared equitably. Population growth, in addition to these, increased the income distribution imbalance. However, in the fixed effects model, it is seen that this effect is in the decreasing direction. For this reason, no decision could be reached on the effects of population growth. It has been determined that the 2008 Global Economic Crisis has a decreasing effect on the income distribution imbalance in the pooled model but at a statistically insignificant level.


Based on the findings obtained from this paper, it can be stated that the transfer payments made by countries to their citizens have a decreasing effect on the income distribution imbalance; therefore it would be beneficial for countries to continue such aids within their means. However, at this point, the necessity of preventing some citizens from getting used to living with granted state aid without working and the importance of “teaching people how to fish instead of giving fish” and transforming them into working and producing individuals should not be overlooked. It should not be forgotten that such social assistance is always open to abuse, that people who are not really in need may try to benefit from these aids and this case may put the economy in a difficult situation as in Greece, and the public should take the necessary measures. It is of paramount importance that the income generated by economic growth is distributed equitably among all citizens. At this point, it is essential that states effectively fulfil their functions of regulating and controlling the salary and other personal rights of people working in the private sector. The abnormal increase in the population of the country with imbalanced immigration can reduce the welfare of the residents in the country. For this reason, it is beneficial for states to maintain their immigration policies in line with their economic strength and the number of people they can employ.


Download data is not yet available.


  1. Afonso, A., Schuknecht, L. ve Tanzi, V. (2010). Income Distribution Determinants and Public Spending Efficiency. Journal of Economic Inequality, 8(3), 367-389.
  2. Alesina, A. ve Rodrik, D. (1994). Distributive Politics and Economic Growth, Quarterly Journal of Economics, Vol. 109, No. 2 (May, 1994), s. 465-490.
  3. Baltagi, B. H. (1995). Econometric Analysis of Panel Data, John Wiley&Sons Ltd. England.
  4. Bastagli, F., Coady, D. ve Gupta, S. (2012). Income inequality and fiscal policy, International Monetary Fund Staff Discussion Note, No. SDN/12/08R.
  5. Caminada, K., Goudswaard, K. ve Wang, C. (2012). Disentangling Income Inequality and the Redistributive Effect of Taxes and Transfers in 20 LIS Countries Over Time, LIS Working Paper Series, No: 581, s.s. 1-47.
  6. Chu, K., Davoodi, H. ve Gupta, S. (2000). Income Distribution and Tax, and Government Social Spending Policies in Developing Countries. (No. 214), World Institute for Development Economics Research (UNU-WIDER), Erişim Adresi https://www.wider.unu.edu/sites/default/files/wp214.pdf.
  7. Cimoli, M., Neto, A. M., Porcile, G. ve Sossdorf, F. (2017). Productivity, Social Expenditure and Income Distribution in Latin America, Brazilian Journal of Political Economy, 37(4), s. 660-679.
  8. Çalışkan, Ş. (2010). Türkiye’de Gelir Eşitsizliği ve Yoksulluk, Sosyal Siyaset Konferansları Dergisi, (59), s. 89-132.
  9. D’Agostino, G., Pieroni, L. ve Procidano, I. (2016). Revisiting the Relationship Between Welfare Spending and Income Inequality in OECD Countries. Munich Personal RePEc Archive, s. 1-27.
  10. DPT (2020). Gelir Dağılımı ve Politikaları 7.BYKP, Erişim Adresi http://ekutup.dpt.gov.tr/plan/plan7.pdf.
  11. Dumitrescu, E. I. ve Hurlin, C. (2012). Testing for Granger Non-Causality in Heterogeneous Panels. Economic Modelling, 29(4), s. 1450-1460.
  12. Engle, F. E. ve Granger C. W. J. (1987). Co-integration and Error Correction: Representation and Testing. Econometrica, (55), s. 251-276.
  13. Eroğlu, N., Altaş, D., Turgut, Ü. N. ve Ulu, M. İ. (2017). OECD Ülkelerinde Sosyal Yardım Harcamalarının Gelir Dağılımına Etkisi: Panel Veri Analizi, Uluslararası Ekonomik Araştırmalar Dergisi, 3(3), s. 335-354.
  14. Frederick, S. (2019). The Standardized World Income Inequality Database, Erişim Adresihttps://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/LM4OWF.
  15. Granger, C. W. J. ve Newbold, P. (1974). Spurious Regressions in Econometrics. Journal of Econometrics, 2(2), s. 111-120.
  16. Greene, W. H. (2002). Econometric Analysis. (Fifth Edition). Prentice Hall, New Jersey.
  17. Gujarati, D. N. ve Porter, D. C. (2012). Temel Ekonometri (Beşinci Basımdan Çeviri), Çevirenler: Ümit Şenesen ve Gülay Güllük Şenesen. Literatür Yayınevi, İstanbul.
  18. Gustafsson, B. ve Johansson, M. (1999). In search of smoking guns: What makes income inequality vary over time in different countries?. American Sociological Review, 64 (4): 585-605.
  19. Hazman, G. G. (2011). Türkiye’de Gelir Dağılımında Adalet ve Sosyal Güvenlik Harcamaları Arasındaki Nedensellik İlişkisi, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(1), s. 205-216.
  20. Heald, D. ve McLeod, A. (2002). Constitutional Law, The Laws of Scotland: Stair Memorial Encyclopaedia, Edinburgh: Butterworths.
  21. Holzner, M. (2011). Inequality, Growth and Public Spending in Central, East and Southeast Europe, ECINEQ WP, s. 1-25.
  22. Huber, E., Pribble, J. ve Stephens, J. D. (2004). ‘’Social Spending and Inequality in Latin America and the Caribbean’’ In Paper Delivered at The Meetings of The Society for The Advancement of Socio-Economics, Washington. DC. July.
  23. Im, K. S., Pesaran, M. H. ve Shin, Y. (2003). Testing for Unit Roots in Heterogenous Panels. Journal of Econometrics, 115, 53-74.
  24. IMF (2001). A Manual on Government Finance Statistics, ErişimAdresi www.imf.org/external/pubs/ft/gfs/manual/pdf/all.pdf.
  25. İlgün, M. F. (2015). Kamu Sosyal Harcamalarının Gelir Dağılımı Üzerindeki Etkisi: OECD Ülkelerine Yönelik Panel Veri Analizi, Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 17(4), s. 493-516.
  26. Karaman, B. ve Özçalık, M. (2007). Türkiye’de gelir dağılımı eşitsizliğinin bir sonucu, Yönetim ve Ekonomi Dergisi, Cilt:14. Sayı:1. s. 25-41.
  27. Keane, M.P. ve Prasad, E.S. (2000). Inequality, Transfers and Growth: New Evidence from the Economic Transition in Poland, The Review of Economics and Statistics, 84(2), s. 324-341.
  28. Kozuharov, S., ve Petkovski, V. (2018). The Impact of Social Transfers on Inequality Measured By Gini Index : The Example of Macedonia, UTMS Journal of Economics, 9(1), s. 49-61.
  29. Levin, A., Lin, C. F. ve Chu, C. S. J. (2002). Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108, s. 1-24.
  30. Li, H., Xie, D. ve Zou, H. (2000). Dynamics of Income Distributio, Canadian Journal of Economics, Vol. 33, No. 4, 2000, s. 937-961.
  31. Maddala, G. S. ve Wu, S. (1999). A Comparative Study of UnitRoot Tests with Panel Data and a New Simple Test, Oxford Bulletin of Economics and Statistics, 61, s. 631-652.
  32. Martínez-Vazquez, J., Vulovic, V. ve Dodson, B. M. (2014). The Impact of Tax and Expenditure Policies on Income Disttribution: Evidence from a Large Panel of Countries, Hacienda Pública Española/Review of Public Economics, 200-(4/2012): s. 95-130.
  33. Niehues, J. (2010). Social Spending Generosity and Income Inequality: A Dynamic Panel Approach, Discussion Paper Series, IZA (No. 5178).
  34. OECD (2020a). Income inequality. Erişim Adresi https://data.oecd.org/inequality/income-inequality.htm.
  35. OECD (2020b). Social Expenditure-Aggregated Data. Erişim Adresi https://stats.oecd.org/Index.aspx?DataSetCode=SOCX_AGG.
  36. Öztürk, N. (2009). İktisatta bölüşüm (1.bs.), Kuram-Politika, Palme Yayıncılık, Ankara.
  37. Öztürk, N. (2017). Gelir dağılımının iktisadi analizi (1.bs.), Ekin Yayınevi, Bursa.
  38. Persson T. ve Tabellini, G. (1994). The American Economic Review, Vol. 84, No. 3 (Jun., 1994), s. 600-621.
  39. Pınar, A. (2019). Maliye Politikası Teori ve Uygulama. 10. Baskı, Ankara: Turhan Yayınevi.
  40. Samuels, P. ve Gilchrist, M. (2014). Pearson Correlation, Statsutor, Community Project. Encouraging Academics to Share Statistics Support Resources.
  41. Schwabish, J., Smeeding, T. ve Osberg, L. (2004). Income Distribution and Social Expenditures: A Crossnational Perspective, Luxemburg Income Study, (LIS) Working Papers Series. No: 350, October 2004, s. 5-23.
  42. Sylwester, K. (2002). Can Education Expenditures Reduce Income Inequality?. Economics of Education Review, Vol. 21, 2002, s. 43-52.
  43. Ulu, M. İ. (2018). The effect of government social spending on income inequality in oecd: a panel data analysis, International Journal of Economics, Politics, Humanities & Social Sciences, 1 (3), s. 184-202.
  44. Ürper, T. D. (2018). Kamu Harcamalarının Gelir Dağılımı Üzerindeki Etkisi: Türkiye Örneği, Hacettepe Üniversitesi, Sosyal Bilimler Enstitüsü, Maliye Anabilim Dalı, Yüksek Lisans Tezi.
  45. Wang, C, Caminada, K. ve Goudswaard, K. (2012). The Redistributive Effect of Social Transfer Programmes and Taxes: A Decomposition Across Countries, International Social Security Review 65(3), s. 27-48.
  46. Weede, E. (1997). Income inequality, democracy and growth reconsidered. European Journal of Political Economy, 13 (4), s. 751-764.
  47. Woo, J., Bova E., Kinda T. ve Zhang, S. (2013). Distributional Consequences of Fiscal Consolidation and The Role of Fiscal Policy: What Do The Data Say?, IMF Working Paper, No. 13-195,
  48. Wooldridge, J. M. (2013). Ekonometriye Giriş. (4. Basımdan Çeviri). (Çeviren: Ebru Çağlayan), Nobel Akademik Yayıncılık, İstanbul.
  49. World Bank (2020a). GDP growth (annual %). Erişim Adresi https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?view=chart,
  50. World Bank (2020b). Population growth (annual %). Erişim Adresi https://data.worldbank.org/indicator/SP.POP.GROW?view=chart.
  51. Yardımcıoğlu, F. ve Yayla, Y. E. (2020). Sosyal Harcamaların Gelir Dağılımı Üzerindeki Etkisi: Orta ve Doğu Avrupa Ülkeleri Örneği. Gümrük Ticaret Dergisi,7(19),s.34-48.