Socio-Economic Determinants of Labor Productivity in Developed and Developing Countries
DOI:
https://doi.org/10.54938/ijemdss.2026.05.4.785Keywords:
Labor productivity, Human capital, Financial development, Trade openness, Income inequalityAbstract
This study empirically examines the determinants of labor productivity (GDP per worker) among a balanced panel of 24 developing and 22 developed countries over the period of 1990-2024. Adopting comprehensive panel framework, including Random Effects (GLS), Fixed Effects, cross sectional- dependence tests, second generation unit root test, Westerlund cointegration analysis, long run estimates (FMOLS/DOLS) and Dumitrescu-Hurlin causality for ensuring robustness and eliminate endogeneity. Descriptive statistics reveal significant productivity lags between developed and developing countries with a vital difference in human capital, and structural capabilities. Long run analysis reveals that Life expectancy and gross capital formation significantly positive effect on productivity in both panel groups while gross capital formation shows strong positive effect on productivity in developed countries. Financial development reveals a key role for developing countries, whereas income inequality negatively effects, particularly in developing countries. Pupil-teacher ratio statistically effects productivity for developed countries, whereas the trade openness identifies the minimal long-term effect. The findings of cointegration and causality validate a sustainable long-run relation and bidirectional and unidirectional dynamics between variables. Generally, role of productivity growth is formed by human capital, income inequality and structural changes. The study suggests that policy systems focus on the context specific: enhance financial inclusion and promoting equality in developing countries while reinforcing human capital development and capital efficiency in the developed countries.
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Acemoglu, D., & Restrepo, P. (2020). The wrong kind of AI? Artificial intelligence and the future of labor demand. Cambridge Journal of Regions, Economy and Society, 13(1), 25–35. https://doi.org/10.1093/cjres/rsaa001
Aghion, P., Antonin, C., & Bunel, S. (2021). The power of creative destruction: Economic upheaval and the wealth of nations. The Belknap Press of Harvard University Press. https://doi.org/10.4159/9780674258686
Aghion, P., Antonin, C., Bunel, S., & Jaravel, X. (2020). What are the labor and product market effects of automation? New evidence from France (CEPR Discussion Paper No. 14443). Centre for Economic Policy Research. https://cepr.org/publications/dp14443
Ahmed, S., Aleem, M. U., Mahmood, T., & Mahboob, F. (2023). The nexus of high-performance work systems and employee perceived innovation performance: Unveiling the mediating role of human capital—A study of banking industry in compliance with SDGs. Journal of Banking and Social Equity, 2(2), 63–76. https://doi.org/10.61775/jbse.v2i2.2453
Aiyar, S., Ebeke, C. H., & Shao, X. (2016). The impact of workforce aging on European productivity (IMF Working Paper No. 2016/238). International Monetary Fund. https://doi.org/10.5089/9781475559729.001
Bagali, M. M., Ganesh, S., & Jayashree, N. (2025). Perspectives on analysis regarding the impact of online teaching and higher education: Strategies and perspectives for future readiness. Pegem Journal of Education and Instruction, 15(2), 190–197. https://doi.org/10.47750/pegegog.15.02.19
Bai, C.-E., Hsieh, C.-T., & Song, Z. (2020). Special deals with Chinese characteristics. NBER Macroeconomics Annual, 34, 341–379. https://doi.org/10.1086/707189
Barro, R. J. (1991). Economic growth in a cross section of countries. The Quarterly Journal of Economics, 106(2), 407–443. https://doi.org/10.2307/2937943
Beck, T., Levine, R., & Levkov, A. (2010). Big bad banks? The winners and losers from bank deregulation in the United States. The Journal of Finance, 65(5), 1637–1667. https://doi.org/10.1111/j.1540-6261.2010.01589.x
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press.
Cervellati, M., Sunde, U., & Valmori, S. (2017). Pathogens, weather shocks and civil conflicts. The Economic Journal, 127(607), 2581–2616. https://doi.org/10.1111/ecoj.12430
Frankovic, I., Kuhn, M., & Wrzaczek, S. (2020). Medical innovation and its diffusion: Implications for economic performance and welfare. Journal of Macroeconomics, 66, 103262. https://doi.org/10.1016/j.jmacro.2020.103262
Frees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of Econometrics, 69(2), 393–414. https://doi.org/10.1016/0304-4076(94)01658-M
Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200), 675–701. https://doi.org/10.1080/01621459.1937.10503522
Fubile, F. T., & Sawe, J. (2022). The impact of pupil-teacher ratio on performance in mastering reading, writing and arithmetic competencies in Morogoro Municipality: A case study of Standard Four pupils in primary schools. East African Journal of Education Studies, 5(3), 250–258. https://doi.org/10.37284/eajes.5.3.931
Grossman, G. M., & Helpman, E. (1991). Innovation and growth in the global economy. MIT Press.
Hanushek, E. A., & Woessmann, L. (2012). Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation. Journal of Economic Growth, 17(4), 267–321. https://doi.org/10.1007/s10887-012-9081-x
Harper, S., Riddell, C. A., & King, N. B. (2021). Declining life expectancy in the United States: Missing the trees for the forest. Annual Review of Public Health, 42, 381–403. https://doi.org/10.1146/annurev-publhealth-082619-104231
Hikmat. (2024). Social inequality and access to education: A literature review on the impact of social stratification on education in developing countries. Indonesian Journal of Studies on Humanities, Social Sciences, and Education, 1(1), 59–67. https://doi.org/10.54783/by3jbn19
Jabeen, M., Jabeen, B., Aakif, Z., & Aslam, H. (2026). AI-driven economic analysis: From data to decisions. International Journal of Emerging Multidisciplinaries: Social Science, 5(3), 372–403. https://doi.org/10.54938/ijemdss.2026.05.3.765
Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. The Quarterly Journal of Economics, 107(2), 407–437. https://doi.org/10.2307/2118477
Nelson, R. R., & Phelps, E. S. (1966). Investment in humans, technological diffusion, and economic growth. The American Economic Review, 56(1/2), 69–75. https://www.jstor.org/stable/1821269
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. CESifo Working Paper Series, No. 1229. https://www.ifo.de/en/cesifo/publications/2004/working-paper/general-diagnostic-tests-cross-section-dependence-panels
Psacharopoulos, G., Collis, V., Patrinos, H. A., & Vegas, E. (2021). The COVID-19 cost of school closures in earnings and income across the world. Comparative Education Review, 65(2), 271–287. https://doi.org/10.1086/713540
Sarwar, A., Khan, M. A., Sarwar, Z., & Khan, W. (2021). Financial development, human capital and its impact on economic growth of emerging countries. Asian Journal of Economics and Banking, 5(1), 86–100. https://doi.org/10.1108/AJEB-06-2020-0015
Schultz, T. W. (1961). Investment in human capital. The American Economic Review, 51(1), 1–17.
Strulik, H., & Werner, K. (2016). 50 is the new 30—Long-run trends of schooling and retirement explained by human aging. Journal of Economic Growth, 21(2), 165–187. https://doi.org/10.1007/s10887-015-9124-1
Wilson, R. A., & Briscoe, G. (2005). The impact of human capital on economic growth: A review. In P. Descy & M. Tessaring (Eds.), Impact of education and training: Third report on vocational training research in Europe: Background report (Cedefop Reference Series No. 54, 13–61). Office for Official Publications of the European Communities.
World Bank. (2018). World development report 2018: Learning to realize education's promise. World Bank. https://doi.org/10.1596/978-1-4648-1096-1
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Copyright (c) 2026 Saima Shakeela, Sadia Ali, Muhammad Rizwan Yaseen, Muhammad Faraz Riaz

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