IDEAS home Printed from https://ideas.repec.org/a/vrs/mtrbid/v45y2023i4p453-466n5.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://doi.org/10.15544/mts.2023.44
    Download Restriction: no
    File URL: https://libkey.io/10.15544/mts.2023.44?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. Matthess, Marcel & Kunkel, Stefanie, 2020. "Structural change and digitalization in developing countries: Conceptually linking the two transformations," Technology in Society, Elsevier, vol. 63(C).
    3. Fernando Rios-Avila, 2020. "Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition," Stata Journal, StataCorp LP, vol. 20(1), pages 51-94, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francis,David C. & Kubinec ,Robert, 2022. "Beyond Political Connections : A Measurement Model Approach to Estimating Firm-levelPolitical Influence in 41 Economies," Policy Research Working Paper Series 10119, The World Bank.
    2. Ma, Wanglin & Vatsa, Puneet & Zheng, Hongyun, 2022. "Cooking fuel choices and subjective well-being in rural China: Implications for a complete energy transition," Energy Policy, Elsevier, vol. 165(C).
    3. Boris Hirsch & Philipp Lentge, 2021. "Non-Base Compensation and the Gender Pay Gap," Working Paper Series in Economics 404, University of Lüneburg, Institute of Economics.
    4. Njangang, Henri & Beleck, Alim & Tadadjeu, Sosson & Kamguia, Brice, 2022. "Do ICTs drive wealth inequality? Evidence from a dynamic panel analysis," Telecommunications Policy, Elsevier, vol. 46(2).
    5. Umakrishnan Kollamparambil, 2021. "Socio-Economic Inequality of Wellbeing: A Comparison of Switzerland and South Africa," Journal of Happiness Studies, Springer, vol. 22(2), pages 555-574, February.
    6. Melanie Jones & Ezgi Kaya, 2024. "Performance‐related pay and the UK gender pay gap," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 63(4), pages 512-529, October.
    7. Medet Sartbayev & Leila Tussupova & Irina Selezneva & Tamara Mukhamedyarova-Levina & Elmira Yeralina, 2023. "Strategic investment management in the digital transformation of the economy of the Republic of Kazakhstan," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 0(1 suppl.), pages 295-311.
    8. Bekhzod Djalilov & Islomjon Kobiljonov & Raufhon Salahodjaev, 2023. "Can Digital Human Capital Mitigate CO2 Emissions? Empirical Test for Post-Communist Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(4), pages 383-388, July.
    9. Ira N. Gang & Rajesh Raj Natarajan & Kunal Sen & Myeong-Su Yun, 2021. "The gender productivity gap: Evidence from the Indian informal sector," WIDER Working Paper Series wp-2021-183, World Institute for Development Economic Research (UNU-WIDER).
    10. Leite, Higor & Hodgkinson, Ian R. & Lachowski Volochtchuk, Ana Vitória & Cavalcante Nascimento, Thiago, 2024. "‘It's not the boogeyman’: How voice assistant technology is bridging the digital divide for older people," Technovation, Elsevier, vol. 136(C).
    11. Carlos J Gil-Hernández & Guillem Vidal & Sergio Torrejón Perez, 2024. "Technological Change, Tasks and Class Inequality in Europe," Work, Employment & Society, British Sociological Association, vol. 38(3), pages 826-851, June.
    12. Hirsch, Boris & Lentge, Philipp, 2021. "Non-Base Compensation and the Gender Pay Gap," IZA Discussion Papers 14551, Institute of Labor Economics (IZA).
    13. Canavire Bacarreza,Gustavo Javier & Rios Avila,Fernando & Sacco Capurro,Flavia Giannina, 2022. "Recovering Income Distribution in the Presence of Interval-Censored Data," Policy Research Working Paper Series 10147, The World Bank.
    14. Himaz, Rozana & Aturupane, Harsha, 2021. "Why are boys falling behind? Explaining gender gaps in school attainment in Sri Lanka," World Development, Elsevier, vol. 142(C).
    15. Boris Hirsch & Philipp Lentge & Claus Schnabel, 2022. "Uncovered workers in plants covered by collective bargaining: Who are they and how do they fare?," British Journal of Industrial Relations, London School of Economics, vol. 60(4), pages 929-945, December.
    16. Harkness, Susan, 2022. "Single mothers’ income in twelve rich nations: differences in disadvantage across the distribution," ISER Working Paper Series 2022-06, Institute for Social and Economic Research.
    17. Singh, Shiwangi & Sharma, Meenakshi & Dhir, Sanjay, 2021. "Modeling the effects of digital transformation in Indian manufacturing industry," Technology in Society, Elsevier, vol. 67(C).
    18. Cheng, Zhiming, 2021. "Education and consumption: Evidence from migrants in Chinese cities," Journal of Business Research, Elsevier, vol. 127(C), pages 206-215.
    19. Ben Jann, 2021. "Relative distribution analysis in Stata," Stata Journal, StataCorp LP, vol. 21(4), pages 885-951, December.
    20. Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2024. "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," ILR Review, Cornell University, ILR School, vol. 77(4), pages 562-597, August.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:mtrbid:v:45:y:2023:i:4:p:453-466:n:5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.