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Research Article

Will advances in digital technology reduce the rural-urban income gap?

ORCID Icon &
Article: 2194954 | Received 15 Sep 2022, Accepted 17 Mar 2023, Published online: 21 Aug 2023

References

  • Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. The Quarterly Journal of Economics, 118(4), 1279–1333. https://doi.org/10.1162/003355303322552801
  • Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716
  • Brynjolfsson, E., & McAfee, A. (2016). The second machine age: Work, progress, and prosperity in a time of brilliant technologies (Reprint edition). W. W. Norton & Company.
  • Cai, F. (2019). How can economics meet the new technological revolution? Research in Labor Economics, 7(2), 3–20.
  • Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2002). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Routledge. https://doi.org/10.4324/9780203774441
  • Chen, B., Pengfei, Z., & Rudai, Y. (2010). Government education investment, human capital investment and urban-rural income gap in China. Management World, (1), 36–43.
  • Cheng, K. M., & Li, J. C. (2007). Mechanism of action and dynamic analysis of urban bias, urbanization and urban-rural income gap. Research on Quantitative Economics and Technology Economics, 2007(7), 116–125.
  • Cheng, M. W., & Zhang, J. P. (2019). Internet penetration and urban-rural income gap:theory and empirical evidence. China Rural Economy, 2019(2), 19–41.
  • Cheng, M. W., & Zhang, J. P. (2019). Internet development and consumption gap between urban and rural residents in the context of the new era[J]. Research on Quantitative Economics and Technology Economics, 36(7), 22–41.
  • Cohen, S. S. (1988). Manufacturing matters: The myth of the post-industrial economy (Reprint ed.). Basic Books.
  • Chen, X., Long, T., & Yuehwan, T. (2021). Can rural e-commerce policies help reduce the urban-rural income gap–based on the perspective of factor mobility and expenditure structure. Agricultural Technology Economics, 335(03), 89–103.
  • Duro, J. A. (2008). Cross-country inequalities in welfare and its decomposition by Sen factors: The virtues of the Theil index. Applied Economics Letters, 15(13), 1041–1045. https://doi.org/10.1080/13504850600993507
  • Guo, F., Wang, J. I., & Wang, F. (2020). Measuring the development of digital inclusive finance in China: index development and spatial characteristics. Econometrics (Quarterly), 19(4), 1401–1418.
  • Guo, K., & Xiang, F. (2021). Artificial intelligence technology and wage income gap. Industrial Economics Review, 47(6), 82–100.
  • Hoselitz, B. F. (1952). Non-economic barriers to economic development. Economic Development and Cultural Change, 1(1), 8–21. https://doi.org/10.1086/449605
  • Katz, L. F., & Murphy, K. M. (1992). Changes in relative wages, 1963-1987: Supply and demand factors. The Quarterly Journal of Economics, 107(1), 35–78. https://doi.org/10.2307/2118323
  • Luo, C., Shi, L., & Ximing, Y. (2021). Analysis of the change of income disparity in China (2013-2018). China Social Science, 301(1), 33–54.
  • Li, C., Tao, S., & Shuo, W. (2021). Demographic dividend, fiscal expenditure bias and urban-rural income gap in China. Dynamics of Economics, 719(1), 105–124.
  • Li, D. S., & Li, Q. (2007). Mechanisms and empirical study of the impact of agricultural technology progress on the income gap of farm households. Agricultural Technology Economics, 161(3), 23–27.
  • Li, D., & Pei, Y. (2013). Research on the impact of urban-rural public service gap on urban-rural income gap. Financial and Economic Research, 45(4), 111–123.
  • Lister, F. (2013). The national system of political economy (1st ed.). Huaxia Press Ltd.
  • Liu, H. (2020). How industrial intelligence affects the urban-rural income gap-an explanation from the perspective of employment of agricultural transfer labor. China Rural Economy, (5), 55–75.
  • Liu, J. (2017). An empirical study on the urban-rural digital divide that continues to widen the urban-rural income gap. Statistics and Decision Making, 478(10), 119–121.
  • Liu, J. L., & Chen, Y. Y. (2022). Digital technology development, spatial and temporal dynamic effects and regional carbon emissions. Scientology Research, 41(05),1–17.
  • Li, S. (2018). The current income distribution situation in China. Academia, 238(3), 5–19.
  • Li, S. (2021). Digitization and the service industry wage gap: pushing or snowing? –analysis based on CFPS and industry-matched data. Industrial Economics Research, 115(6), 1–14.
  • Lin, Y., & Pengfei, Z. (2005). Latecomer advantage, technology introduction and economic growth of lagging countries. Economics (Quarterly), 2005(4), 53–74.
  • María Sarabia, J., Jordá, V., & Remuzgo, L. (2017). The theil indices in parametric families of income distributions—A short review. Review of Income and Wealth, 63(4), 867–880. https://doi.org/10.1111/roiw.12260
  • Ma, W., & Renzhong, Z. (2022). A study on the impact effect of the breadth and depth of digital finance on narrowing the urban-rural development gap–a synergistic effect perspective based on residents’ education. Agricultural Technology Economics, 322(2), 62–76.
  • Park, P. W., & Zhang, Y. (2021). Digital economy, declining demographic dividend and the rights of low- and middle-skilled laborers. Economic Research, 56(5), 91–108.
  • Piketty, T. (2017). Capital in the twenty-first century (A. Goldhammer, Trans.; Reprint edition). Belknap Press: An Imprint of Harvard University Press.
  • Qiu, Z., & Yahong, Z. (2021). Mechanism analysis of the role of e-commerce in increasing income of rural households–a micro test based on effective matching of demand and supply. China Rural Economy, (4), 36–52.
  • Ren, Z. Z., & Deng, F. (2022). Digital technology, factor structure transformation and high-quality economic development. Soft Science, 1–10.
  • Wooldridge, J. M. (2015). Introductory econometrics: A modern approach - standalone book (6th ed.). Cengage Learning.
  • Wang, L., Shengming, H., & Zhiqing, D. (2020). Does artificial intelligence technology induce labor income inequality–model derivation and classification assessment. China Industrial Economics, 385(4), 97–115.
  • Wang, X., & Yaxiong, Z. (2020). Is there a Matthew effect of digital financial development? –Empirical comparison of poor and non-poor households. Finance Research, 481(7), 114–133.
  • Wang, Y. Q., & Dong, W. (2020). How does the rise of robots affect the Chinese labor market? –Evidence from listed manufacturing companies. Economic Research, 55(10), 159–175.
  • Xu, S. (2010). Technological progress, educational returns, and income inequality. Economic Research, 45(9), 79–92.
  • Yuan, J., & Chengsi, Z. (2009). Mandatory technological change, unbalanced growth and economic cycle model in China. Economic Research, 44(12), 17–29.
  • Yang, S., Fenfen, T., & Xu, W. (2015). A study on the inverted U relationship between urban-rural income gap and urbanization rate in China. Management Review, 27(11), 3–10.
  • Zhan, G., & Xinwen, Z. (2017). External effects of educational capital on urban-rural income gap. Finance and Trade Research, 28(6), 37–46.
  • Zhou, L., Feng, D., & Yi, X. (2020). Digital inclusive finance and urban-rural income gap: "digital dividend" or "digital divide. The Economist, 257(5), 99–108.
  • Zhu, Q., Chen, Z., & Chao, P. (2022). Can informatization promote farmers’ income increase and reduce income gap? Economics (Quarterly), 22(1), 237–256.
  • Zhang, Y. L., & Li, Q. Y. (2022). The impact of Internet use on the income of farm households in poor areas–based on the survey data of farm households in poor villages in Gansu Province. Management Review, 34(1), 130–141.