How meteorological disasters affect the labor market? The moderating effect of government emergency response policy

Abstract

Natural disasters and climate change impose a severe threat to the sustainable development of economy and human society. This paper studies the economic consequences of meteorological disasters specifically to the wages income and unemployment. Using panel data from 31 provinces in China from 2010 to 2018 as a sample, it examines the relationship between meteorological disasters and labor market, and then verifies the moderating effect of government emergency response policy which is obtained through big data crawler technology. The results show that meteorological disasters will increase the level of unemployment, and at the same time increase the wage income of urban and rural people; while government emergency response policy only plays a moderating role between meteorological disasters and urban wage income. Although this paper focuses on China geographically, the overall conclusions presented in this article have strong policy implications for other regions in developing countries facing the challenge of meteorological disasters.

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Acknowledgements

This research was funded by the Humanity and Social Science Youth Foundation of Ministry of Education in China (Grant Number 19YJC630240) and Graduate Cultivation Innovation Project of Jiangsu Province and Postgraduate Training Unit (SJCX20_0284).

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Correspondence to Xiaodong Zhu.

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The authors declare that there is no conflict of financial interests or personal relationships that could have appeared to influence the work reported in this paper. The data are available to public and will be provided through writing to the corresponding author.

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Zhu, X., Jin, Z., Managi, S. et al. How meteorological disasters affect the labor market? The moderating effect of government emergency response policy. Nat Hazards (2021). https://doi.org/10.1007/s11069-021-04526-x

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Keywords

  • Meteorological disaster
  • Labor market
  • Emergency response policy
  • Big data