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Gender, Low-Paid Status, and Time Poverty in Urban China

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  • Liangshu Qi
  • Xiao-yuan Dong

Abstract

Using synthetic data from the 2008 China Time Use Survey (CTUS) and the 2008 China Household Income Project (CHIP), this study estimates time-poverty rates and compares the profiles of time-poor men and women workers in urban China. In line with previous research, time poverty is defined as a lack of enough time for rest and leisure. Three time-poverty measures are adopted. By all three measures, women paid workers and low-paid workers account for a disproportionate share of the time poor. Regression analysis further shows that, other things being equal, workers who are women, low-paid, married, and who live with children or the elderly in counties with higher overtime rates and lower minimum wage standards are more likely to be time poor. Simulations indicate that enforcing working time regulations and raising minimum wage standards could be effective for reducing time poverty.

Suggested Citation

  • Liangshu Qi & Xiao-yuan Dong, 2018. "Gender, Low-Paid Status, and Time Poverty in Urban China," Feminist Economics, Taylor & Francis Journals, vol. 24(2), pages 171-193, April.
    • Handle: RePEc:taf:femeco:v:24:y:2018:i:2:p:171-193
    DOI: 10.1080/13545701.2017.1404621
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    Citations

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    Cited by:

    1. Gustafsson, Björn Anders & Sai, Ding, 2023. "China's Urban Poor – Comparing Twice Poverty between Residents and Migrants in 2013 and 2018," IZA Discussion Papers 16255, Institute of Labor Economics (IZA).
    2. Jiquan Peng & Juan Chen & Liguo Zhang, 2022. "Gender-Differentiated Poverty among Migrant Workers: Aggregation and Decomposition Analysis of the Chinese Case for the Years 2012–2018," Agriculture, MDPI, vol. 12(5), pages 1-23, May.
    3. de Bruin, Anne & Liu, Na, 2020. "The urbanization-household gender inequality nexus: Evidence from time allocation in China," China Economic Review, Elsevier, vol. 60(C).
    4. Qun Gao & Mei Zhao & Hengyang Chen, 2024. "Effects of the three-child policy on the employment bias against professional women: evidence from 260 enterprises in Jiangxi province," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    5. Chakraborty, Lekha, 2022. "Covid19 and Unpaid Care Economy: Evidence on Fiscal Policy and Time Allocation in India," Working Papers 22/372, National Institute of Public Finance and Policy.
    6. Chakraborty, Lekha S, 2022. "Covid19 and Fiscal Policy for Unpaid Care Economy," MPRA Paper 111925, University Library of Munich, Germany.

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