The Economic Significance of Work Experience for Elderly Employment in Thailand

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Kritsada Wattanasaovaluk


A rapid demographic change to the aging and aged population in Thailand has led to a reduction in the labor force, and an increasing concern about the economic potential of the country. Therefore, a study of older adults who are capable of working, and an analysis of the significance of their work experience is vital for public policy. An analysis of the data from the 2018 Labor Force Survey in Thailand demonstrates that older adults in the age groups of 60-64 and 65-69 who are capable of working constitute 24.2% and 21.2% of the population, respectively. Among these older adults are retirees, who have the highest potential because they are well educated and highly experienced. Multinomial logistic regression was applied to correct the selectivity bias in the analysis of the return on work experience. The results indicate that the marginal return on work experience is 2.75% for high-skilled occupations. There are similar results for semi-skilled and low-skilled occupations (1.99% and 1.73%), however, diminishes more rapidly in the latter than in the former. These findings indicate that the value of experience increases with occupations that require skills, and diminishes significantly in jobs that mainly require physical strength (i.e., low-skilled occupations). This study suggests that older adults with the potential to do so should be encouraged to remain active in the labor market, and that labor demand is enhanced by emphasizing the value of their experience.


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Wattanasaovaluk, K. (2020). The Economic Significance of Work Experience for Elderly Employment in Thailand. Journal of Population and Social Studies [JPSS], 29(-), 82 - 99. Retrieved from
Author Biography

Kritsada Wattanasaovaluk, School of Development Economics, National Institute of Development Administration, Thailand

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• Adhikari, R., Soonthorndhada, K., & Haseen, F. (2011). Labor force participation in later life: Evidence from a cross-sectional study in Thailand. BMC Geriatrics, 11(1), 15.
• Agiomirgianakis, G., Lianos, T., & Tsounis, N. (2019). Returns to Investment in Distance Learning: the Case of Greece. International Business Research, 12(3), 94-100.
• Alcan, S., & Özsoy, O. (2019). Relation between health and wages in Turkey. Panoeconomicus, 67(1), 111-126.
• Almeida, R. K., & de Faria, M. L. (2014). The wage returns to on-the-job training: evidence from matched employer-employee data. IZA Journal of Labor & Development, 8314.
• Altonji, J. G., & Williams, N. (2005). Do wages rise with job seniority? A reassessment. ILR Review, 58(3), 370-397.
• Arrow, K. J. (1971) The Economic Implications of Learning by Doing. In: Hahn F.H. (eds) Readings in the Theory of Growth. Palgrave Macmillan.
• Becker, G. S. (1962). Investment in human capital: A theoretical analysis. Journal of Political Economy, LXX(5), Part 2, 9-49.
• Börsch-Supan, A. H., & Weiss, M. (2008). Productivity and the Age Composition of Work Teams: Evidence from the Assembly Line. MEA Discussion Paper No. 148-07.
• Bound, J., Jaeger, D. A., & Baker, R. M. (1995). Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. Journal of the American Statistical Association, 90(430), 443-450.
• Bourguignon, F., Fournier, M., & Gurgand, M. (2007). Selection bias corrections based on the multinomial logit model: Monte Carlo comparisons. Journal of Economic Surveys, 21(1), 174-205.
• Chiswick, B. R., & Miller, P. W. (2003). The complementarity of language and other human capital: immigrant earnings in Canada. Economics of Education Review, 22(5), 469-480.
• Cutler, D. M., Meara, E., & Richards-Shubik, S. (2011). Healthy life expectancy: Estimates and implications for retirement age policy. NBER Working Paper, 1-39.
• Griliches, Z. (1977). Estimating the returns to schooling: Some econometric problems. Econometrica: Journal of the Econometric Society, 45(1), 1-22.
• Grogger, J. (2009). Welfare reform, returns to experience, and wages: using reservation wages to account for sample selection bias. The Review of Economics and Statistics, 91(3), 490-502.
• Hawley, J. D. (2004). Changing returns to education in times of prosperity and crisis, Thailand 1985–1998. Economics of Education Review, 23(3), 273-286.
• Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica: Journal of the Econometric Society, 47(1), 153-161.
• Hong, J., & Lee, K. (2012). The aging work force in Korea. International Archives of Occupational and Environmental Health, 85, 253-260.
• International Labour Office. (2012). International Standard Classification of Occupations: ISCO-08. Geneva: International Labour Office.
• Isaza Castro, J. G. (2014). Occupational segregation, selection effects and gender wage differences: evidence from urban Colombia. Apuntes del Cenes, 33(57), 73-116.
• Johnson, R. W. (2019). Older Workers and the Declining Rate of Return to Worker Experience. Generations, 43(3), 63-70.
• Kimura, T., Kurachi, Y., & Sugo, T. (2019). Decreasing Wage Returns to Human Capital: Analysis of Wage and Job Experience Using Micro Data of Workers. Bank of Japan Working Paper Series, 19-E-12.
• Lee, L-F. (1983). Generalized econometric models with selectivity. Econometrica: Journal of the Econometric Society, 51(2), 507-512.
• Mattos, T. (2018). Foreign Born Latina Earnings and Returns to Education and Experience in the United States. Global Business & Economics Anthology, 1, 54-62.
• Meer, J. (2007). Evidence on the returns to secondary vocational education. Economics of Education review, 26(5), 559-573.
• Mincer, J. (1958). Investment in human capital and personal income distribution. Journal of Political Economy, 66(4), 281-302.
• Mincer, J. (1962). On-the-job training: Costs, returns, and some implications. Journal of Political Economy, 70(5), Part 2, 50-79.
• Mincer, J. (1974). Schooling, experience and earnings. NBER Working Paper (0167).
• Moenjak, T., & Worswick, C. (2003). Vocational education in Thailand: a study of choice and returns. Economics of Education Review, 22(1), 99-107.
• Phijaisanit, E. (2015). How can promoting desirable elderly employment opportunities alleviate the shortfalls of Thailand’s ageing society? MPRA Paper 89824, University Library of Munich, Germany, revised 2016.
• Qadir, F., & Afzal, M. (2019). Impact of Cultural Factors on Earnings of Working Women in Khyber Pakhtunkhwa, Pakistan. European Online Journal of Natural and Social Sciences: Proceedings, 8(1)(s), 92-105.
• Rosen, S. (1972). Learning and experience in the labor market. Journal of Human Resources, 7(3), 326-342.
• Santiphop, T., & Pattaravanich, U. (2016). An Analysis of Factors to Improve the Capacity and Value of Older Persons in Thailand. Journal of Population and Social Studies [JPSS], 24(2), 66-80.
• Schwaab, K. S., Dutra, V. R., Marschner, P. F., & Ceretta, P. S. (2019). How much heavier is a “hoe” for women? wage gender discrimination in the brazilian agricultural sector. Contextus: Revista Contemporânea de Economia e Gestão, 17(2), 37-62.
• Stritch, J. M., & Villadsen, A. R. (2018). The gender wage gap and the moderating effect of education in public and private sector employment. Public Administration, 96(4), 690-706.
• Tangtipongkul, K. (2015). Rates of return to schooling in Thailand. Asian Development Review, 32(2), 38-64.
• The World Bank. (2016). Live long and prosper: Aging in East Asia and Pacific. World Bank Publications.
• Walker, A., & Maltby, T. (2012). Active ageing: A strategic policy solution to demographic ageing in the European Union. International Journal of Social Welfare, 21, S117-S130.
• Wannakrairoj, W. (2013). The effect of education and experience on wages: the case study of Thailand in 2012. Southeast Asian Journal of Economics, 1(1), 27-48.
• Warunsiri, S., & McNown, R. (2010). The returns to education in Thailand: A pseudo-panel approach. World Development, 38(11), 1616-1625.
• Wise, D. A. (2017). Social security programs and retirement around the world: The capacity to work at older ages. University of Chicago Press.
• Xia, G., & Xu, X. (2019). Research on the Wage Gap Between Urban and Rural Labor: Based on CHNS Micro Survey Data. International Journal of Economics, Finance and Management Sciences, 7(6), 197-202. 10.11648/j.ijefm.20190706.13