Factors Affecting the Labor Force Participation and Working Hours of Thai Workers under the COVID-19 Situation

Authors

  • Anyarat Wichian -
  • Apiradee Netirangsriwatchara

Keywords:

labor force participation, working hours, COVID-19

Abstract

The purpose of this research was to study factors affecting work participation and working hours of      3 types of Thai workers such as formal workers, informal workers, and unemployed workers, under the COVID-19 situation. This is done by using secondary data from the National Statistical Office (NSO) of B.E. 2019. The data was analyzed with a Polychotomous Choice Selectivity Model, and estimate coefficient by maximum likelihood estimation. The research findings showed that the most of factors affecting work participation in COVID-19 situation will be the same as in normal situations, including factors such as education level, marital status, and head of household. However, there are some factors that affect it differently from the normal situation. For example, female workers will have more opportunities to participate in the labor force than males, elderly workers will have more opportunities to join the labor force, workers with more household members are more likely to lose their jobs, and workers living outside the municipality will have more opportunities to enter the informal sector. In addition, it was also found that age, education level, and the area of residence affected the number of working hours during the COVID-19 situation.

References

Adhikari, R., Soonthorndhada, K., & Haseen, F. (2011). Labor force participation in later life: Evidence from a cross-sectional

study in Thailand. BMC Geriatrics, 11(15), 1 – 8.

Aemkulwat, C. (2014). Labor Supply of Married Couples in the Formal and Informal Sectors in Thailand. Southeast Asian Journal

of Economics, 2(2), 77-102.

Arkornsakul, P., Puttitanun, T. & Jongadsayakul, W. (2020). Labor Supply Intention of the Elderly in Thailand. Chiang Mai

University Journal of Economics, 24(2), 1-16.

Asian Development Bank. (2021). Covid-19 and Labor Markets in Southeast Asia: Impacts on Indonesia, Malaysia, The

Philippines, Thailand, and Viet Nam. https://www.adb.org/publications/covid-19-labor-markets-southeast-asia.

Assad, R. & El- Hamidi, F. (2002). Female Labor Supply in Egypt: Participation and Hours of Work. In Ismail Sirageldin (Eds.),

Human Capital: Population Economics In The Middle East. (pp. 210- 230). The American University in Cairo Press.

Bhattarai, K. (2017). Determinants of Wages and Labour Supply in the UK. Chinese Business Review, 16(3), 126-140.

Borjas, G.J. (2016). Labor Economics. (7th ed.). McGraw-Hill Education.

Cueva, R., Del Carpio, X. & Winkler, H. (2021). The Impacts of COVID-19 on Informal Labor Markets: Evidence from Peru.

Policy Research Working Paper, No.9675. chrome-

extension://efaidnbmnnnibpcajpcglclefindmkaj/https://openknowledge.worldbank.org/server/api/core/bitstreams/e9fb0

f-8659-5463-b192-555cdb85ac80/content

Department of Employment. (2020). Research.

https://www.doe.go.th/prd/main/knowledge/param/site/1/cat/94/sub/0/pull/category/view/cover-view. (in Thai)

Department of Employment. (2021). Research.

https://www.doe.go.th/prd/main/knowledge/param/site/1/cat/94/sub/0/pull/cat egory/view/cover-view. (in Thai)

Faridi, M.Z., Chaudhry, I.S. & Basit, A.B. (2009). An Analysis of the Determinants of Male Labor Force Participation and

Employment Status in Pakistan: The Case of Bahawalpur District. Pakistan Journal of Social Sciences, 29(2), 189-

Hafeez, A & Ahmad, E. (2002). Factors Determining the Labour Force Participation Decision of Educated Married Women in a

District of Pubjab. Pakistan Economic and Social Review, 40(1), 75-88.

Horioka, C.Y., Gahramanov, E., Hayat, A. & Tang, X. (2021). The Impact of bequest motives on labor supply and retirement

behavior in Japan: A theoretical and empirical analysis. Journal of The Japanese and International Economies, 62, 1 –

Hosney, S. H. (2016). Factors influencing female labor force participation in Egypt and Germany: A comparative study.

SOEPpapers on Multidisciplinary Panel Data Research, No. 826. Deutsches Institut für Wirtschaftsforschung (DIW),

Berlin.

Hussain, M., Anwar, S. & Huang, S. (2016). Socioeconomic and Demographic Factors Affecting Labor Force Participation in

Pakistan. Journal of Sustainable Development, 9(4), 69 – 79.

Ince, M. (2010). How the education affects female labor force? Empirical evidence from Turkey. Procedia Social and Behavioral

Sciences, 2, 634 – 639.

International Labour Organization. (2020). COVID-19 employment and labour market impact in Thailand. ILO brief.

https://www.ilo.org/asia/publications/labour-markets/WCMS_747944/lang--en/index.htm.

Keiichi, O. & Akter, M. (2007). Female Labor Force Participation in Indonesia. Journal of International Cooperation Studies,

(3), 71-108.

Leangthanarerk, P. (2018). Wage and Desire of additional work among informal Workers: Empirical Evidence in Thailand. (Master

of Arts in Demography, Chulalongkorn University). (in Thai)

Lee, L. F. (1983). Generalized econometric models with selectivity. Econometrica, 51, 507 - 512.

Maddala, G.S. (1983). Limited-Dependent and Qualitative Variables in Econometrics. Econometric Society Monographs No.3.

Cambridge University Press.

National Statistical Office. (2021a). The Labor Force Survey Whole Kingdom, Quarter 4: October – December 2020.

http://www.nso.go.th/sites/2014/Pages. (in Thai)

National Statistical Office. (2021b). The Labor Force Survey Whole Kingdom, Quarter 3: July – September 2020.

http://www.nso.go.th/sites/2014/Pages. (in Thai)

Ngearndee, J. & Buddhawongsa, P. (2013). Labor Force Participation, Income, and Working Hour of Thai Labors. Journal of

Economics Chiang Mai University, 17(1), 22 – 42. (in Thai)

Penpong, M.S. (2019). Labor supply in government sector after retirement Case study: Suratthani Province. Journal of

Management Science Chiangrai Rajabhat University, 14(2), 42 – 63. (in Thai)

Shen, Z., Parker, M., Brown, D. & Fang, X. (2017). Effects of public health insurance on labor supply in rural China. China

Agricultural Economic Review, 9(4), 623 – 642.

Spissu, E., Pinjari, A. R., Pendyala, R. M. & Bhat, C. R. (2009). A copula-based joint multinomial discrete–continuousmodel of

vehicle type choice and miles of travel. Transportation, 36, 403 - 422.

Soonthornchawakan, N. (2016). Labor Economics. Thammasat Printing House. (in Thai)

Sriwichailamphan, T. (2015). Labor Economics. Chiangmai University. (in Thai)

Soonthornchawakan, N. (2022). The Elderly as Additional Workers on the Thai Labor Market. BU Academic Review, 21(2), 15 –

(in Thai)

TDRI. (2021). Impact of COVID-19 outbreak 2nd round, continuing 3rd round with Direction of the Thai labor market.

https://tdri.or.th/2021/04/covid-19-2-3-affected-thai-labor-market/. (in Thai)

Wang, C. & Sweetman, A. (2013). Gender, family status and physician labour supply. Social Science & Medicine, 94, 17 – 25.

Downloads

Published

2024-06-25