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Has the digital economy improved the consumption of poor and subsistence households?

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  • Zhang, Yun
  • Qu, Yuxuan

Abstract

Using Chinese Family Panel Studies (CFPS) database from 2012 to 2018, this paper examines the impacts and transmission mechanisms of the digital economic growth on the consumption of the poor and subsistence households. The results show that the digital economy negatively affects the consumption of the poor and subsistence households, with a more prominent effect on the poor families. Mechanism analysis indicates that digital economic development reduces the consumption of poor and subsistence households mainly by exacerbating the uncertainties they face in labor market (higher unemployment risk and expected income uncertainty) and the inequality of wealth distribution (higher deprivation of income and wealth). Further analyses reveal that the digital economy has greater negative impacts on households with less material, human and social capital endowments, and leads no significant improvements in the consumption environment for the disadvantaged households.

Suggested Citation

  • Zhang, Yun & Qu, Yuxuan, 2024. "Has the digital economy improved the consumption of poor and subsistence households?," China Economic Review, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:chieco:v:83:y:2024:i:c:s1043951x23001682
    DOI: 10.1016/j.chieco.2023.102083
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    as
    1. Anders Akerman & Ingvil Gaarder & Magne Mogstad, 2015. "The Skill Complementarity of Broadband Internet," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1781-1824.
    2. Mark Kazarosian, 1997. "Precautionary Savings-A Panel Study," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 241-247, May.
    3. Brent Neiman, 2014. "The Global Decline of the Labor Share," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(1), pages 61-103.
    4. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    5. Christopher D. Carroll & Jiri Slacalek & Martin Sommer, 2011. "International Evidence on Sticky Consumption Growth," The Review of Economics and Statistics, MIT Press, vol. 93(4), pages 1135-1145, November.
    6. Erik Hurst & Annamaria Lusardi, 2004. "Liquidity Constraints, Household Wealth, and Entrepreneurship," Journal of Political Economy, University of Chicago Press, vol. 112(2), pages 319-347, April.
    7. Christopher D. Carroll & Edmund Crawley & Jiri Slacalek & Kiichi Tokuoka & Matthew N. White, 2020. "Sticky Expectations and Consumption Dynamics," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(3), pages 40-76, July.
    8. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    9. Meng, Xin, 2003. "Unemployment, consumption smoothing, and precautionary saving in urban China," Journal of Comparative Economics, Elsevier, vol. 31(3), pages 465-485, September.
    10. Anton Korinek & Joseph E. Stiglitz, 2018. "Artificial Intelligence and Its Implications for Income Distribution and Unemployment," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 349-390, National Bureau of Economic Research, Inc.
    11. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    12. Banerjee, Abhijit & Duflo, Esther & Qian, Nancy, 2020. "On the road: Access to transportation infrastructure and economic growth in China," Journal of Development Economics, Elsevier, vol. 145(C).
    13. Alexandra Spitz-Oener, 2006. "Technical Change, Job Tasks, and Rising Educational Demands: Looking outside the Wage Structure," Journal of Labor Economics, University of Chicago Press, vol. 24(2), pages 235-270, April.
    14. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    15. B. K. Atrostic & Sang V. Nguyen, 2005. "It and Productivity in U.S. Manufacturing: Do Computer Networks Matter?," Economic Inquiry, Western Economic Association International, vol. 43(3), pages 493-506, July.
    16. Hamid Boustanifar & Everett Grant & Ariell Reshef, 2018. "Wages and Human Capital in Finance: International Evidence, 1970–2011 [Financial reform: what shakes it? What shapes it?]," Review of Finance, European Finance Association, vol. 22(2), pages 699-745.
    17. Jonas Hjort & Jonas Poulsen, 2019. "The Arrival of Fast Internet and Employment in Africa," American Economic Review, American Economic Association, vol. 109(3), pages 1032-1079, March.
    18. Karen E. Dynan & Jonathan Skinner & Stephen P. Zeldes, 2004. "Do the Rich Save More?," Journal of Political Economy, University of Chicago Press, vol. 112(2), pages 397-444, April.
    19. Shlomo Yitzhaki, 1979. "Relative Deprivation and the Gini Coefficient," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 93(2), pages 321-324.
    20. Erik Brynjolfsson & Lorin M. Hitt, 2003. "Computing Productivity: Firm-Level Evidence," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 793-808, November.
    21. Ajay Agrawal & Joshua S. Gans & Avi Goldfarb, 2019. "Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 31-50, Spring.
    22. Daron Acemoglu & Pascual Restrepo, 2022. "Demographics and Automation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 1-44.
    23. Mark Armstrong, 2006. "Competition in two‐sided markets," RAND Journal of Economics, RAND Corporation, vol. 37(3), pages 668-691, September.
    24. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    25. Dominique Guellec, 2020. "Digital Innovation and the Distribution of Income," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 323-370, National Bureau of Economic Research, Inc.
    26. Nathan Nunn & Nancy Qian, 2014. "US Food Aid and Civil Conflict," American Economic Review, American Economic Association, vol. 104(6), pages 1630-1666, June.
    27. Kolko, Jed, 2012. "Broadband and local growth," Journal of Urban Economics, Elsevier, vol. 71(1), pages 100-113.
    28. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    29. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2018. "Adjusting to Robots: Worker-Level Evidence," Opportunity and Inclusive Growth Institute Working Papers 13, Federal Reserve Bank of Minneapolis.
    30. James Bessen, 2019. "Automation and jobs: when technology boosts employment," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 589-626.
    31. Erik Brynjolfsson & Lorin Hitt, 1996. "Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending," Management Science, INFORMS, vol. 42(4), pages 541-558, April.
    32. Kaivan Munshi & Mark Rosenzweig, 2006. "Traditional Institutions Meet the Modern World: Caste, Gender, and Schooling Choice in a Globalizing Economy," American Economic Review, American Economic Association, vol. 96(4), pages 1225-1252, September.
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    More about this item

    Keywords

    Digital economy; Consumption; The poor households; The subsistence households;
    All these keywords.

    JEL classification:

    • F49 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Other
    • F24 - International Economics - - International Factor Movements and International Business - - - Remittances

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