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Exploring the Effect of Internet Usage on the Urban Rural Income Gap: Empirical Evidence from China

Author

Listed:
  • Qin Mingshuai

    (PhD Student, Technical University of Ostrava, Studentská 1770/1, Poruba-Ostrava, Czech Republic)

  • Dong Hao

    (Lect. University of Southampton, Building 2, 12 University Road, Highfield, Southampton, United Kingdom)

  • Chen Hong

    (Assoc. Prof., Anhui University of Finance and Economics, #962 Caoshan Road, Bengbu City, Anhui Province, China)

  • Qin Lijian

    (Prof. Anhui University of Finance and Economics, #962 Caoshan Road, Bengbu City, Anhui Province, China)

  • Qin Wenshuai

    (Master’s student, Philippine Christian University - Manila, 1648 Taft Ave.cor Pedro Cil, Malate Manila, Republic of The Philippines)

Abstract

China has witnessed remarkable ongoing digitalization with the rapid spread and adoption of the Internet. However, this remarkable development remains uneven between urban and rural populations, and hence result in different impact on their income. Employing data China General Social Survey 2018, this study explores how internet usage affects income gap between the urban and rural China. Relying on the instrumental variables approach to regression analysis, we prove that internet usage contributes to higher increase in annual income for the urban employed compared to their rural counterparts. The RIF decomposition regression results then reveal the effects of differential urban-rural internet usage ratios, explaining the widened income gap between the urban and rural employed in various income levels. The difference in the returns to urban and rural internet usage narrowed the urban-rural income gap for low - and high- income employed, but further contributed to the urban-rural income gap for the middle-income employed.

Suggested Citation

  • Qin Mingshuai & Dong Hao & Chen Hong & Qin Lijian & Qin Wenshuai, 2023. "Exploring the Effect of Internet Usage on the Urban Rural Income Gap: Empirical Evidence from China," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, vol. 45(4), pages 453-466, December.
    • Handle: RePEc:vrs:mtrbid:v:45:y:2023:i:4:p:453-466:n:5
    DOI: 10.15544/mts.2023.44
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    References listed on IDEAS

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    1. Canh, Nguyen Phuc & Schinckus, Christophe & Thanh, Su Dinh & Hui Ling, Felicia Chong, 2020. "Effects of the internet, mobile, and land phones on income inequality and The Kuznets curve: Cross country analysis," Telecommunications Policy, Elsevier, vol. 44(10).
    2. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    3. Matthess, Marcel & Kunkel, Stefanie, 2020. "Structural change and digitalization in developing countries: Conceptually linking the two transformations," Technology in Society, Elsevier, vol. 63(C).
    4. Fernando Rios-Avila, 2020. "Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition," Stata Journal, StataCorp LLC, vol. 20(1), pages 51-94, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    China; Internet usage; RIF decomposition regression; Urban-rural income gap;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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