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Labour share and income inequalities in the European Union, taking into account the level of development of economies

Abstract

Research background: The relationship between labour share and income inequality is a complex and multifaceted problem. Despite ongoing discussions among economists, there is still no consensus on the direction of the relationship between labour share and income inequality.

Purpose of the article: The article aims to assess the impact of labour share on income inequality, which is measured in three ways: the Gini index of gross income, the Gini index of market incomes, and the Gini index of household disposable income.

Methods: Dynamic panel data models were applied to estimate the relationship between Gini coefficients and socio-economic indicators. The study investigated 25 European Union countries over the 2011–2021 period.

Findings & value added: Despite the long convergence process of the EU economies, there is still great diversity in the labour share, social inequalities, and the interplay between these factors. The added value of this research is the indication of labour share impact on three Gini measures covering a diverse income spectrum (from labour and capital). Based on the research findings, hypothesis 1, claiming that the more developed the national economy, the lower the share of employment income, favouring capital gains, is confirmed. Hypothesis 2  (as the share of income from work increases, the Gini coefficient of gross incomes decreases) must be rejected. There is no significant relationship between labour share and the studied Gini measures in 'old' EU countries. In 'new' EU members, there is a reverse relationship than assumed in hypothesis 2. The growth of the Gini coefficient was influenced by the rise in labour share, which can be attributed to the diversity in economic structures.

Keywords

labour share, income inequalities, panel models, European Union

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References

  1. Afonso, A., Schuknecht, L., & Tanzi, V. (2008). Income distribution determinants and public spending efficiency. European Central Bank, Working Paper Series, 861. DOI: https://doi.org/10.2139/ssrn.1083986
    View in Google Scholar
  2. Autor, D., Dorn, D., Katz, L. F., Patterson, Ch., & Van Reenen, J. (2020). The rise of superstar firms and the fall of the labor share. Quarterly Journal of Economics, 135(2), 645–709. DOI: https://doi.org/10.1093/qje/qjaa004
    View in Google Scholar
  3. Autor, D., Van Reenen, J. V., & Patterson, Ch. (2023). Local and national concentration trends in jobs and sales: The role of structural transformation. SSRN. DOI: https://doi.org/10.3386/w31130
    View in Google Scholar
  4. Arellano, M., & Bond, S. R. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58, 277–297. DOI: https://doi.org/10.2307/2297968
    View in Google Scholar
  5. Arpaia, A., Pérezaand, E., & Pichelmann, K. (2009). Understanding labour income share dynamics in Europe. Economic Papers, 379.
    View in Google Scholar
  6. Atkinson, A. B., & Jenkins, S. P. (2019). A different perspective on the evolution of UK income inequality. Review of Income and Wealth, 66(2), 253–266, DOI: https://doi.org/10.1111/roiw.12412
    View in Google Scholar
  7. Atkinson, A. B. (2009). Factor shares: The principal problem of political economy?, Oxford Review of Economic Policy, 25, 3–16, DOI: https://doi.org/10.1093/oxrep/grp007
    View in Google Scholar
  8. Atkinson, A. B. (2015). Inequality. Cambridge: Harvard University Press. DOI: https://doi.org/10.4159/9780674287013
    View in Google Scholar
  9. Atkinson, A. B., Piketty, T., & Saez, E. (2011). Top incomes in the long run of history. Journal of Economic Literature, 49(1), 3–71. DOI: https://doi.org/10.1257/jel.49.1.3
    View in Google Scholar
  10. Ayala, L., Martin-Roman, J., & Vicente, J. (2019). The contribution of the spatial dimension to inequality: A counterfactual analysis for OECD countries. Papers in Regional Science, 99(3), 447–477. DOI: https://doi.org/10.1111/pirs.12503
    View in Google Scholar
  11. Balcerzak, A. P., & Rogalska, E. (2016). Non-Keynesian effects of fiscal consolidations in Central Europe in the Years 2000-2013. In M. H. Bilgin & H. Danis (Eds.). Entrepreneurship, business and economics - Vol. 2. Proceedings of the 15th Eurasia Business and Economics Society (pp. 271–282). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-27573-4_18
    View in Google Scholar
  12. Balcerzak, A. P., Pietrzak, M. B., & Rogalska, E. (2016). Fiscal contractions in Eurozone in the years 1995-2012: Can non-Keynesian effects be helpful in future deleverage process? In M. H. Bilgin, H. Danis & E. Demir, U. Can (Eds.). Business challenges in the changing economic landscape - Vol. 1. Proceedings of the 14th Eurasia Business and Economics Society (pp. 483–496). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-22596-8_35
    View in Google Scholar
  13. Baltagi, B. (2008). Econometric analysis of panel data. Chichester: West Sussex: Wiley.
    View in Google Scholar
  14. Baymul, C., & Sen K. (2020). Was Kuznets right? New evidence on the relationship between structural transformation and inequality. Journal of Development Studies, 56(9), 1643–1662. DOI: https://doi.org/10.1080/00220388.2019.1702161
    View in Google Scholar
  15. Bentolila, S., & Saint-Paul, G. (2003). Explaining movements in the labor share. B.E. Journal of Macroeconomics, 3(1), 1–33. DOI: https://doi.org/10.2202/1534-6005.1103
    View in Google Scholar
  16. Bond, S., Hoeffner, A., & Temple, J. (2001). GMM estimation of empirical growth models. Economics Papers, Economics Group, Nuffield College, University of Oxford, 2001‑W21.
    View in Google Scholar
  17. Brussevich, M., Liu, S., & Papageorgiou, Ch. (2022). Income convergence or divergence in the aftermath of the COVID-19 shock? IMF Working Papers, WPIEA2022121. DOI: https://doi.org/10.2139/ssrn.4239464
    View in Google Scholar
  18. Buechel, B., Gangl, S., & Huber, M. (2023). How residence permits affect the labor market attachment of foreign workers: Evidence from a migration lottery in Liechtenstein. European Economic Review, 152, 104377, DOI: https://doi.org/10.1016/j.euroecorev.2023.104377
    View in Google Scholar
  19. Checchi, D., & García-Peñalosa, C. (2010). Labour market institutions and the personal distribution of income in the OECD. Economica, 77(307), 413–450, DOI: https://doi.org/10.1111/j.1468-0335.2009.00776.x
    View in Google Scholar
  20. Chinoracký, R., & Čorejová, T. (2019). Impact of digital technologies on labor market and the transport sector. Transportation Research Procedia, 40, 994–1001. DOI: https://doi.org/10.1016/j.trpro.2019.07.139
    View in Google Scholar
  21. Chong, A., Gradstein, M., & Calderon, C. (2009). Can foreign aid reduce income inequality and poverty? Public Choice, 140(1/2), 59–84. DOI: https://doi.org/10.1007/s11127-009-9412-4
    View in Google Scholar
  22. Dao, M. C., Das, M., & Koczan, Z. (2020). Why is labour receiving a smaller share of global income? Economic Policy, 34(100), 1–70. DOI: https://doi.org/10.1093/epolic/eiaa004
    View in Google Scholar
  23. de Serres, A., Scarpetta S., & de la Maisonneuve Ch. (2002). Sectoral shifts in Europe and the United States: How they affect aggregate labour shares and the properties of wage equations. OECD Economics Department (Working Papers), 326. DOI: https://doi.org/10.2139/ssrn.307425
    View in Google Scholar
  24. Erauskin, I. (2020). The labor share and income inequality: Some empirical evidence for the period 1990-2015. Applied Economic Analysis, 28(84), 173–195. DOI: https://doi.org/10.1108/AEA-04-2020-0028
    View in Google Scholar
  25. Fields, G. (2014). Self-employment and poverty in developing countries. IZA World of Labor, 60. DOI: https://doi.org/10.15185/izawol.60
    View in Google Scholar
  26. Fontagne, L., Reshef, A., Santoni, G., & Vannelli, G. (2023). Automation, global value chains andfunctional specialization. Review of International Economics. Advance online publication. DOI: https://doi.org/10.2139/ssrn.4368210
    View in Google Scholar
  27. Fontanari, A., Taleb, N. N., & Cirillo, P. (2018). Gini estimation under infinite variance. Physica A: Statistical Mechanics and its Applications, 502, 256–269. DOI: https://doi.org/10.1016/j.physa.2018.02.102
    View in Google Scholar
  28. Gencev, M. (2019). A note on a property of the Gini coefficient. Communications in Mathematical Physics, 27, 81–88. DOI: https://doi.org/10.2478/cm-2019-0008
    View in Google Scholar
  29. Gil-Anala, L., Skare, M., & Pržiklas-Družeta, R. (2019). Measuring inequality persistence in OECD 1963–2008 using fractional integration and cointegration. Quarterly Review of Economics and Finance, 72(2), 65–72. DOI: https://doi.org/10.1016/j.qref.2018.12.006
    View in Google Scholar
  30. Gini, C. (1921). Measurement of inequality of incomes. Economic Journal, 31(121), 124–126. DOI: https://doi.org/10.2307/2223319
    View in Google Scholar
  31. Goldberg, P., & Pavcnik N. (2007). Distributional effects of globalization in developing countries. Journal of Economic Literature, 45(1), 39–82. DOI: https://doi.org/10.1257/jel.45.1.39
    View in Google Scholar
  32. Gollin, D. (2002). Getting income shares right. Journal of Political Economy, 110, 458–474. DOI: https://doi.org/10.1086/338747
    View in Google Scholar
  33. Inter-agency Task Force on Financing for Development (2019). Financing for sustainable development report 2019. New York. Retrieved from https://developmentfin ance.un.org/fsdr2019 (30.01.2023).
    View in Google Scholar
  34. Harrison, A. E. (2005). Has globalization eroded labor's share? Some cross-country Eeidence. Berkeley: University of California at Berkeley and NBER.
    View in Google Scholar
  35. Hlasny, V. C, & Verme, P. (2021). The impact of top income biases on the measurement of inequality in the United States: Oxford Bulletin of Economics and Statistics, 84(8), 749–788. DOI: https://doi.org/10.1111/obes.12472
    View in Google Scholar
  36. Jayadev, A. (2007). Capital account openness and the labour share of income. Cambridge Journal of Economics, 31, 423–433. DOI: https://doi.org/10.1093/cje/bel037
    View in Google Scholar
  37. Jianu, I., Gavril, I. A., Iacob, S. E., & Hrebenciuc, A. (2021). Income inequalities and their social determinants: An analysis over developed vs. developing EU Member States. Economic Computation and Economic Cybernetics Studies and Research, Academy of Economic Studies, 55, 125–142. DOI: https://doi.org/10.24818/18423264/55.2.21.08
    View in Google Scholar
  38. Koyo, M. (2021). The decline in the labor share: Evidence from Japanese manufacturers’ panel data. Discussion papers, Policy Research Institute, Ministry of Finance Japan, ron340.
    View in Google Scholar
  39. Kuc-Czarnecka, M., Saltelli, A., Olczyk, M., & Reinert, E. S. (2021). The opening of Central and Eastern European countries to free trade: A critical assessment. Structural Change and Economic Dynamics, 58, 23–34. DOI: https://doi.org/10.1016/j.strueco.2021.04.005
    View in Google Scholar
  40. Kuznets, S. (1955). Economic growth and income inequality. American Economic Review, 45, 1–28.
    View in Google Scholar
  41. Lau, Ch-K., Pal, S., Mahalik, M. K., & Gozgor, G. (2022). Economic globalization convergence in high and low globalized developing economies: Implications for the post Covid-19 era. Economic Analysis and Policy, 76, 1027–1039. DOI: https://doi.org/10.1016/j.eap.2022.10.013
    View in Google Scholar
  42. Lee, K. C., & Jayadev, A. (2005). The effects of capital account liberalisation on growth and the labor share of income: Reviewing and extending the cross-country evidence. In G. Esptein (Ed.). Capital flight and capital controls in developing countries (pp. 15–57). Cheltenham Edward Elgar. DOI: https://doi.org/10.4337/9781781008058.00010
    View in Google Scholar
  43. Madzinova, R. (2017). Impact of government spending on income inequality. Annals of Faculty of Economics, University of Oradea, Faculty of Economics, 1(2), 210–220.
    View in Google Scholar
  44. Nicolau, J., Raposo, P. Z., & Rodrigues, P. M. M. (2022). Measuring wage inewuality under right censoring. Economic Inquiry, 61(2), 377–401. DOI: https://doi.org/10.1111/ecin.13119
    View in Google Scholar
  45. Nikulin, D., Wolszczak-Derlacz, J., & Parteka, A. (2021). GVC and wage dispersion. Firm-level evidence from employee? Employer database. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(2), 357–375. DOI: https://doi.org/10.24136/eq.2021.013
    View in Google Scholar
  46. Niño-Zarazúa, M., Roope, L., & Tarp F. (2014). Global interpersonal inequality: trends and measurement. Working Paper Helsinki: UNU-WIDER, 004. DOI: https://doi.org/10.35188/UNU-WIDER/2014/725-7
    View in Google Scholar
  47. OECD (2016). Income inequality remains high in the face of weak recovery. Retrieved form https://www.oecd.org/social/OECD2016-Income-Inequality-Upda te.pdf. (04.03.2022).
    View in Google Scholar
  48. OECD (2015). The labour share in G20 countries, report prepared for the G20 Employment Working Group Antalya. Retrieved from https://www.oecd.org/g20/ topics/
    View in Google Scholar
  49. Pariboni, R., & Tridico, P. (2019). Labour share decline, financialisation and structural change. Cambridge Journal of Economics, 43(4), 1073–1102, DOI: https://doi.org/10.1093/cje/bez025
    View in Google Scholar
  50. Petreski, M. (2022). Labor share in transition economies: Brief firm-level investigation. Applied Economic Letters, 30(13), 1838–1842. DOI: https://doi.org/10.1080/13504851.2022.2083551
    View in Google Scholar
  51. Piketty, T., & Zucman, G. (2014). Capital is back: Wealth-income ratios in rich countries 1700–2010. Quarterly Journal of Economics, 129(3), 1255–1310, DOI: https://doi.org/10.1093/qje/qju018
    View in Google Scholar
  52. Piketty, T. (2014). Capital in the twenty-first century. Cambridge, MA: Harvard University Press. DOI: https://doi.org/10.4159/9780674369542
    View in Google Scholar
  53. Popescu, M. E., Cristescu, A., & Paun, R.-M. (2022). The COVID-19 pandemic and main economic convergence indicators in the EU. Economic Research-Ekonomska Istraživanja, 36(2), 1–26. DOI: https://doi.org/10.1080/1331677X.2022.2142807
    View in Google Scholar
  54. Reshef, A., & Santoni, G. (2023). Are your labor shares set in Beijing? The view through the lens of global value chains. European Economic Review, 155, 104459. DOI: https://doi.org/10.1016/j.euroecorev.2023.104459
    View in Google Scholar
  55. Rodrigues, F., & Jayadev A. (2010). The declining labor share of income. Human development. New York: United Nations Development Programme.
    View in Google Scholar
  56. Rodrick, D. (2007). One Economics, many recipes. Princeton: Princeton University Press. DOI: https://doi.org/10.1515/9781400829354
    View in Google Scholar
  57. Rodrick, D. (2016). Premature deindustrialization. Journal of Economic Growth, 21(1), 1–33. DOI: https://doi.org/10.1007/s10887-015-9122-3
    View in Google Scholar
  58. Saumik, P. (2018). Structural transformation, growth incidence, and inequality: A framework. In P. Saumik (Ed). Kuznets beyond Kuznets. Structural transformation and income inequality in the era of globalization in Asia (pp. 23–41). Tokyo: Asian Development Bank Institute.
    View in Google Scholar
  59. Shu, H., & Xiong, P. (2018). The Gini coefficient structure and its application for the evaluation of regional balance development in China. Journal of Cleaner Production, 199, 668–686. DOI: https://doi.org/10.1016/j.jclepro.2018.07.224
    View in Google Scholar
  60. Stolarska, A. (2018). Non-agricultural self-employment as a factor of economic inclusion of the rural population. Ekonomia i Środowisko, 1(64), 181–190.
    View in Google Scholar
  61. Soriano Mena, P. J., (2023). The extent and causes of the declining labour share of income across the globe. Essex Student Journal, 14(1), 1–10.
    View in Google Scholar
  62. TED (2022). The Conference Board total economy database™ (Original version). Retrieved from https://www.conference-board.org
    View in Google Scholar
  63. Valdez, R. I., & García-Fernández, F. (2022). The distribution of wage inequality across municipalities in Mexico: A spatial quantile regression approach. Equilibrium. Quarterly Journal of Economics and Economic Policy, 17(3), 669–697. DOI: https://doi.org/10.24136/eq.2022.023
    View in Google Scholar
  64. Wildowicz-Szumarska, A. (2022). Is redistributive policy of EU welfare state effective in tackling income inequality? A panel data analysis. Equilibrium. Quarterly Journal of Economics and Economic Policy, 17(1), 81–101. DOI: https://doi.org/10.24136/eq.2022.004
    View in Google Scholar
  65. Zungu, L. T., Greyling, L., & Mbatha, N. (2021). Economic growth and income inequality: A non-linear econometrics analysis of the SADC region 1990–2015. African Journal of Business Management, 12(2), 285–301. DOI: https://doi.org/10.1108/AJEMS-09-2020-0465
    View in Google Scholar

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