Main Article Content
Abstract
Purpose ― Most global economies are dealing with the issue of skill bias. In developing and underdeveloped countries, skill bias poses a problem by preventing the educated from participating in the economy's production function, especially in the long run. This paper expands on the skill-wage relationship and investigates this issue in the case of Iran from 1981 to 2021.
Methods- Applying Impulse Responses from VECM and the Structural VAR model separates the relationship between skill and wage into short- and long-term effects. The structural wage model was estimated using the structural vector auto-regression model.
Findings ― The results show that skill played a significant role in wage determination only for three periods in the short run, and the effect was neutral in the long run. This means that skill accumulation through advancement in graduate and postgraduate study is unlikely to increase wages in the long run.
Implication ― According to the findings, skill bias implies that education attainment in the Iranian labour market can only improve wages to a minimum extent. This also proves that factors other than education determine wage growth in the economy.
Originality ― The skill-wage relationship has not been a focus of studies in education outcome fields. Moreover, in the case of Iran, this investigation is novel, and there is a lack of studies on the relationship between compensation and skill.
Keywords
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Copyright (c) 2024 Mehdi Mohebi, Akbar Komijani
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References
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- Barro, R., & Lee, J. W. (2000). International data on educational attainment: Updates and implications (Issue 7911). https://doi.org/10.3386/w7911
- Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press.
- Blanchard, O., & Perotti, R. (2002). An empirical characterization of changes in Government spending and taxes on output. Quarterly Journal of Economics, 117(4), 1329–1368. https://doi.org/10.1162/003355302320935043
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- Hendricks, L. (2002). How important is human capital for development? Evidence from immigrant earnings. American Economic Review, 92(1), 198–219. https://doi.org/10.1257/000282802760015676
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- Hutter, C., & Weber, E. (2022). Labour market effects of wage inequality and skill-biased technical change. Applied Economics, 55(27), 3063–3084. https://doi.org/10.1080/00036846.2022.2108751
- Jones, B. F. (2014). The human capital stock: A generalized approach. American Economic Review, 104(11), 3752–3777. https://doi.org/10.1257/aer.104.11.3752
- Kalman, R. E. (2006). Time series analysis. Statistical information theory, and other special. Journal of Advanced Nursing, 2(133), 43. https://doi.org/10.1111/j.1365-2648.2006.03681.x
- Klenow, P. J., & Blis, M. (2000). Does schooling cause growth? American Economic Review, 90(5), 1160–1183. https://doi.org/10.1257/aer.90.5.1160
- Lazear, E. P., & Oyer, P. (2007). Personnel economics (Issue 13480). https://doi.org/10.3386/w13480
- 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
- Manuelli, R. E., & Seshadri, A. (2014). Human capital and the wealth of nations: Dataset. American Economic Review, 104(9), 2736. https://doi.org/10.1257/aer.104.9.2736
- Mincer, J. (1974). Progress in human capital analysis of the distribution of earnings (53; National Bureau of Economic Research Working Paper Series). https://doi.org/10.3386/w0053
- Rosen, S. (1976). A theory of life earnings. Journal of Political Economy, 84(4), 45–67.
- Sims, C. A. (1999). The role of interest rate policy in the generation and propagation of business cycles: What has changed since the 30s? Federal Reserve Bank of Boston Conference Series, 42, 121–160.
- Tassaeva, I. V. (2021). The changing education distribution and income inequality in Great Britain. Review of Income and Wealth, 67(3), 659–683. https://doi.org/10.1111/roiw.12486
References
Barro, R. J., & Lee, J. W. (2001). International data on educational attainment: Updates and implications. Oxford Economic Papers, 53(3), 541–563. https://doi.org/10.1093/oep/53.3.541
Barro, R., & Lee, J. W. (2000). International data on educational attainment: Updates and implications (Issue 7911). https://doi.org/10.3386/w7911
Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. University of Chicago Press.
Blanchard, O., & Perotti, R. (2002). An empirical characterization of changes in Government spending and taxes on output. Quarterly Journal of Economics, 117(4), 1329–1368. https://doi.org/10.1162/003355302320935043
Carbonero, F., Offermanns, C. J., & Weber, E. (2022). The fall of the labor income share: The role of technological change and hiring frictions. Review of Economic Dynamics. https://doi.org/10.1016/j.red.2022.02.004
Cunha, F., Heckman, J., & Schennach, S. (2010). Estimating the technology of cognitive and noncognitive skill formation (Issue 15664). https://ideas.repec.org/p/nbr/nberwo/15664.html
Hendricks, L. (2002). How important is human capital for development? Evidence from immigrant earnings. American Economic Review, 92(1), 198–219. https://doi.org/10.1257/000282802760015676
Herrendorf, B., & Schoellman, T. (2018). Wages, human capital, and barriers to structural transformation. American Economic Journal: Macroeconomics, 10(2), 1–23. https://doi.org/10.1257/mac.20160139
Holmstrom, B. (2017). Pay for performance and beyond. American Economic Review, 107(7), 1753–1777. https://doi.org/10.1257/aer.107.7.1753
Hutter, C., & Weber, E. (2021). Labour market miracle, productivity debacle: Measuring the effects of skill-biased and skill-neutral technical change. Economic Modelling, 102, 105584. https://doi.org/10.1016/j.econmod.2021.105584
Hutter, C., & Weber, E. (2022). Labour market effects of wage inequality and skill-biased technical change. Applied Economics, 55(27), 3063–3084. https://doi.org/10.1080/00036846.2022.2108751
Jones, B. F. (2014). The human capital stock: A generalized approach. American Economic Review, 104(11), 3752–3777. https://doi.org/10.1257/aer.104.11.3752
Kalman, R. E. (2006). Time series analysis. Statistical information theory, and other special. Journal of Advanced Nursing, 2(133), 43. https://doi.org/10.1111/j.1365-2648.2006.03681.x
Klenow, P. J., & Blis, M. (2000). Does schooling cause growth? American Economic Review, 90(5), 1160–1183. https://doi.org/10.1257/aer.90.5.1160
Lazear, E. P., & Oyer, P. (2007). Personnel economics (Issue 13480). https://doi.org/10.3386/w13480
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
Manuelli, R. E., & Seshadri, A. (2014). Human capital and the wealth of nations: Dataset. American Economic Review, 104(9), 2736. https://doi.org/10.1257/aer.104.9.2736
Mincer, J. (1974). Progress in human capital analysis of the distribution of earnings (53; National Bureau of Economic Research Working Paper Series). https://doi.org/10.3386/w0053
Rosen, S. (1976). A theory of life earnings. Journal of Political Economy, 84(4), 45–67.
Sims, C. A. (1999). The role of interest rate policy in the generation and propagation of business cycles: What has changed since the 30s? Federal Reserve Bank of Boston Conference Series, 42, 121–160.
Tassaeva, I. V. (2021). The changing education distribution and income inequality in Great Britain. Review of Income and Wealth, 67(3), 659–683. https://doi.org/10.1111/roiw.12486