Open Access Journal Article

Inverted U-shaped relationship between non-labor income and labor hours, with wage rates as the threshold variable

by Qi Wang a,*
a
School of Public Administration, Shandong Technology and Business University, Yantai, China
*
Author to whom correspondence should be addressed.
REA  2024 3(1):24; https://doi.org/10.58567/rea03010002
Received: 13 October 2023 / Accepted: 16 February 2024 / Published Online: 20 February 2024
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Abstract

Non-labor income is a crucial factor influencing time allocation, and prior studies have primarily concentrated on the linear association between non-labor income and labor hours. Utilizing micro-survey data from the CFPS in 2018 and 2020 and employing the panel threshold model, this paper empirically identifies a double threshold with the wage rate as the threshold variable. This finding reveals a non-linear relationship between non-labor income and labor hours. The two thresholds categorize the relationship into three intervals. In the first interval, non-labor income significantly promotes labor hours, while in the second and third intervals, non-labor income significantly decreases labor hours, exhibiting slightly varying degrees of influence. In general, the relationship between non-labor income and labor hours demonstrates an irregular inverted U-shaped pattern. Upon dividing the workers in the sample into three groups based on the two thresholds, it is observed that wage rates exhibit a positive correlation with non-labor income.

Keywords: Non-labor income; Threshold model; Inverted U-shaped;
Copyright: © 2024 by Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Wang, Q. Inverted U-shaped relationship between non-labor income and labor hours, with wage rates as the threshold variable. Review of Economic Assessment, 2024, 3, 24. https://doi.org/10.58567/rea03010002
AMA Style
Wang Q. Inverted U-shaped relationship between non-labor income and labor hours, with wage rates as the threshold variable. Review of Economic Assessment; 2024, 3(1):24. https://doi.org/10.58567/rea03010002
Chicago/Turabian Style
Wang, Qi 2024. "Inverted U-shaped relationship between non-labor income and labor hours, with wage rates as the threshold variable" Review of Economic Assessment 3, no.1:24. https://doi.org/10.58567/rea03010002
APA style
Wang, Q. (2024). Inverted U-shaped relationship between non-labor income and labor hours, with wage rates as the threshold variable. Review of Economic Assessment, 3(1), 24. https://doi.org/10.58567/rea03010002

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References

  1. Alenezi, M., & Walden, M. L. (2004). A new look at husbands' and wives' time allocation. Journal of Consumer Affairs, 38(1), 81-106. https://doi.org/10.1111/j.1745-6606.2004.tb00466.x
  2. Becker, G. S. (1965). A Theory of the Allocation of Time. The economic journal, 75(299), 493-517. https://doi.org/10.2307/2228949
  3. Black, D. A., Hayes, K. J., & Slottje, D. J. (1989). Demographic Change and Inequality in the Size Distributions of Labor and Nonlabor Income. Review of Income and Wealth, 35(3), 283-296. https://doi.org/10.1111/j.1475-4991.1989.tb00594.x
  4. Block, M. K., & Heineke, J. M. (1973). The allocation of effort under uncertainty: the case of risk-averse behavior. Journal of Political Economy, 81(2, Part 1), 376-385. https://doi.org/10.1086/260033
  5. Chang, H., MacPhail, F., & Dong, X. Y. (2011). The feminization of labor and the time-use gender gap in rural China. Feminist Economics, 17(4), 93-124. https://doi.org/10.1080/13545701.2011.604621
  6. Cheng-Liang Y. (2018). Delayed Retirement, Intergenerational Parenting and the Birth Rate. World Economy, 41(6): 152-172.
  7. Chiu, W. H., & Eeckhoudt, L. (2010). The effects of stochastic wages and non-labor income on labor supply: update and extensions. Journal of Economics 100, 69-83. https://doi.org/10.1007/s00712-010-0119-2
  8. Chang, H., Dong, X., and Fiona, M. (2009). The impact of economic development on gender patterns of household time allocation in rural China. China Rural Economy, 12:72-89.
  9. Devereux, P. J. (2004). Changes in relative wages and family labor supply. Journal of Human Resources, 39(3), 698-722. https://doi.org/10.3368/jhr.XXXIX.3.698
  10. Ding, J., Liu, B., Wang, J., Qiao, P., & Zhu, Z. (2023). Digitalization of the business environment and innovation efficiency of Chinese ICT firms. Journal of Organizational and End User Computing (JOEUC), 35(3), 1-25. https://doi.org/10.4018/JOEUC.327365
  11. Duesenberry, J. S. (1949). Income, Saving and the Theory of Consumer Behavior. Review of Economics and Statistics, 33(3):111.
  12. Fang, C. (2010). Demographic transition, demographic dividend and Lewis turning point. Economic Research, 45(04):4-13.
  13. Fei, C and Song, K. (2005). Protection of Legal Income - Both Legal Labor Income and Legal Non-Labor Income Should be Protected. Jiangsu Business Review.
  14. Jin, Q. (2004). Legitimate Non-Labor Income: A Multi-Level Definition under the Market Economy System. Economist. (05):4-10.
  15. Hu, J. (2011). The impact of non-labor income on household time allocation-a comparative study based on job heterogeneity. China Industrial Economy.07:86-96.
  16. Na, L. (2013). Time welfare of non-labor income - Empirical evidence based on Chinese micro data. World Economic Letters, 04:98-120.
  17. Schultz, T. P. (1990). Testing the neoclassical model of family labor supply and fertility. Journal of Human resources, 599-634. https://doi.org/10.2307/145669
  18. Tiefenthaler, J. (1999). The sectoral labor supply of married couples in Brazil: Testing the unitary model of household behavior. Journal of Population Economics, 12, 591-606. https://doi.org/10.1007/s001480050115
  19. Tiefenthaler, J. (1994). A multisector model of female labor force participation: empirical evidence from Cebu Island, Philippines. Economic Development and Cultural Change, 42(4), 719-742. https://doi.org/10.1086/452117
  20. Tan, X., Hu, J., & Cha, Z. (2004). "Getting something for nothing" and "non-labor income". Productivity Research.
  21. Wang, S., & Qu, C. (2023). Digital literacy and farm household property income-Based on China Rural Revitalization Comprehensive Survey (CRRS) data. Review of Economic Assessment, 2(3), 56-87. https://doi.org/10.58567/rea02030004
  22. Wei, X. & Chu, X. (2021). Can Non-Labor Income Relieve China's Labor Supply Tension?. Journal of China Institute of Labor Relations. 35(03):102-116.
  23. Yuan, W., & Yuan, Y. (2003). Protecting legitimate non-labor income is a new development of socialist political economy. Financial Science. 01:1-3.
  24. Yiran, X. (2010). Labor supply model of urban migrant workers under low wage level. China Population Science, 03:57-66.
  25. Zhang, Z. (2022). Research on the Impact of Digital Finance on China's Urban-Rural Income Gap. Review of Economic Assessment, 1(1):63-75. https://doi.org/10.58567/rea02030004
  26. Wang, Z., & Gao, F. (2016). Research on the Impact of Income on Time Allocation of Urban Dual-Wage Families. Journal of Beijing University of Chemical Technology.03:24-29.
  27. Zhong, Y., Li, Y., Ding, J., & Liao, Y. (2021). Risk management: Exploring emerging Human Resource issues during the COVID-19 pandemic. Journal of Risk and Financial Management, 14(5), 228. https://doi.org/10.3390/jrfm14050228