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Is internet penetration narrowing the rural–urban income inequality? A cross-regional study of China

Author

Listed:
  • Lei-Ju Qiu

    (Central University of Finance and Economics)

  • Shun-Bin Zhong

    (Central University of Finance and Economics)

  • Bao-Wen Sun

    (Central University of Finance and Economics)

  • Yu Song

    (University of Finance and Economics)

  • Xiao-Hua Chen

    (Central University of Finance and Economics)

Abstract

Internet penetration (NET) brings new opportunities as well as challenges to countries all over the world. It can narrow the rural–urban income inequality (RUI), because it increases the connections of rural areas to the urban areas from both the production side and consumption side. It can also enlarge the RUI, because the internet may be skill-biased. Meanwhile, income level and the RUI may lead to different local internet development. However, the relationship between NET and RUI remains unclarified. This study applies the method of bootstrap panel Granger causality to explore the causal relationship between NET and RUI. The estimation results show that the causal relationship between NET and RUI varies across different provinces and regions, which is in line with the hypothesis of the inverted U-shaped technological Kuznets curve (TKC). Specifically, the NET does Granger-cause RUI in two-fifths of China’s provinces, primarily in North China and East China, while RUI does not Granger-cause NET in China since the NET itself is largely dependent on government policies. Therefore, policymakers should develop fair internet development policies targeting the improvement of rural and urban income distribution.

Suggested Citation

  • Lei-Ju Qiu & Shun-Bin Zhong & Bao-Wen Sun & Yu Song & Xiao-Hua Chen, 2021. "Is internet penetration narrowing the rural–urban income inequality? A cross-regional study of China," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(5), pages 1795-1814, October.
  • Handle: RePEc:spr:qualqt:v:55:y:2021:i:5:d:10.1007_s11135-020-01081-8
    DOI: 10.1007/s11135-020-01081-8
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    as
    1. Liu, Chun & Jayakar, Krishna, 2012. "The evolution of telecommunications policy-making: Comparative analysis of China and India," Telecommunications Policy, Elsevier, vol. 36(1), pages 13-28.
    2. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    3. Menzie D. Chinn & Robert W. Fairlie, 2007. "The determinants of the global digital divide: a cross-country analysis of computer and internet penetration," Oxford Economic Papers, Oxford University Press, vol. 59(1), pages 16-44, January.
    4. Nelson C. Mark & Masao Ogaki & Donggyu Sul, 2005. "Dynamic Seemingly Unrelated Cointegrating Regressions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 797-820.
    5. Olena Ivus & Matthew Boland, 2015. "The employment and wage impact of broadband deployment in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1803-1830, December.
    6. 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.
    7. Rudra P. Pradhan & Mak B. Arvin & Neville R. Norman & Sara E. Bennett, 2016. "Financial depth, internet penetration rates and economic growth: country-panel evidence," Applied Economics, Taylor & Francis Journals, vol. 48(4), pages 331-343, January.
    8. Rudra P. Pradhan & Mak B. Arvin & Mahendhiran Nair & Sara E. Bennett & John H. Hall, 2019. "The information revolution, innovation diffusion and economic growth: an examination of causal links in European countries," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1529-1563, May.
    9. Sudeshna Ghosh, 2020. "Impact of economic growth volatility on income inequality: ASEAN experience," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(3), pages 807-850, June.
    10. Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2012. "Testing for Granger non-causality in heterogeneous panels," Economic Modelling, Elsevier, vol. 29(4), pages 1450-1460.
    11. M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, March.
    12. M. Hashem Pesaran, 2021. "General diagnostic tests for cross-sectional dependence in panels," Empirical Economics, Springer, vol. 60(1), pages 13-50, January.
    13. Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
    14. Vasilis Sarafidis & Donald Robertson, 2009. "On the impact of error cross-sectional dependence in short dynamic panel estimation," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 62-81, March.
    15. Chris Forman & Avi Goldfarb & Shane Greenstein, 2012. "The Internet and Local Wages: A Puzzle," American Economic Review, American Economic Association, vol. 102(1), pages 556-575, February.
    16. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    17. Briglauer, Wolfgang & Dürr, Niklas S. & Falck, Oliver & Hüschelrath, Kai, 2019. "Does state aid for broadband deployment in rural areas close the digital and economic divide?," Information Economics and Policy, Elsevier, vol. 46(C), pages 68-85.
    18. Zhang, Xiaoqun, 2013. "Income disparity and digital divide: The Internet Consumption Model and cross-country empirical research," Telecommunications Policy, Elsevier, vol. 37(6), pages 515-529.
    19. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-323, March.
    20. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    21. Granger, Clive W. J., 2003. "Some aspects of causal relationships," Journal of Econometrics, Elsevier, vol. 112(1), pages 69-71, January.
    22. Qiu, Leiju & Zhao, Daxuan, 2019. "Urban inclusiveness and income inequality in China," Regional Science and Urban Economics, Elsevier, vol. 74(C), pages 57-64.
    23. Li, Raymond & Shiu, Alice, 2012. "Internet diffusion in China: A dynamic panel data analysis," Telecommunications Policy, Elsevier, vol. 36(10), pages 872-887.
    24. Gourieroux, Christian & Holly, Alberto & Monfort, Alain, 1982. "Likelihood Ratio Test, Wald Test, and Kuhn-Tucker Test in Linear Models with Inequality Constraints on the Regression Parameters," Econometrica, Econometric Society, vol. 50(1), pages 63-80, January.
    25. Bauer, Johannes M., 2018. "The Internet and income inequality: Socio-economic challenges in a hyperconnected society," Telecommunications Policy, Elsevier, vol. 42(4), pages 333-343.
    26. Rudra P. Pradhan & Samadhan Bele & Shashikant Pandey, 2013. "Internet-growth nexus: evidence from cross-country panel data," Applied Economics Letters, Taylor & Francis Journals, vol. 20(16), pages 1511-1515, November.
    27. Gao, Yanyan & Zang, Leizhen & Sun, Jun, 2018. "Does computer penetration increase farmers’ income? An empirical study from China," Telecommunications Policy, Elsevier, vol. 42(5), pages 345-360.
    28. Briglauer, Wolfgang & Dürr, Niklas S. & Falck, Oliver & Hüschelrath, Kai, 2019. "Does state aid for broadband deployment in rural areas close the digital and economic divide?," Information Economics and Policy, Elsevier, vol. 46(C), pages 68-85.
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    2. Shunbin Zhong & Mengding Li & Yihui Liu & Yun Bai, 2023. "Do Internet Development and Urbanization Foster Regional Economic Growth: Evidence from China’s Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(12), pages 1-14, June.
    3. Haoyun Meng & Peidong Deng & Jinbo Zhang, 2022. "Nonlinear Impact of Circulation-Industry Intelligentization on the Urban–Rural Income Gap: Evidence from China," Sustainability, MDPI, vol. 14(15), pages 1-26, August.
    4. Xiaofan Zuo & Zhisheng Hong, 2022. "The Impact of Internet Use on Perception of the Poor–Rich Gap: Empirical Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    5. Zhengxin Li & Chengjun Liu & Xihui Chen, 2022. "Power of Digital Economy to Drive Urban-Rural Integration: Intrinsic Mechanism and Spatial Effect, from Perspective of Multidimensional Integration," IJERPH, MDPI, vol. 19(23), pages 1-20, November.

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    More about this item

    Keywords

    Internet penetration; Rural–urban income inequality; Technological kuznets curve; Bootstrap panel granger causality;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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