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The Impact of Internet Use on Income Inequality from Different Sources Among Farmers: Evidence from China

Author

Listed:
  • Xuan Zhang

    (School of Public Administration, Central South University, Changsha 410075, China
    These authors contributed equally to this work.)

  • Ming Chang

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China
    These authors contributed equally to this work.)

  • Chunrong Zhang

    (School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China)

  • Shuo Zhang

    (School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China)

  • Qingning Lin

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences, Beijing 100081, China)

Abstract

The rapid advancement of digital communication and information technologies has significantly influenced rural household income and income inequality. Based on a sample of 2216 farmers from the China Family Panel Studies (CFPS), this analysis combines Ordinary Least Squares (OLS) regression with Conditional Mixed Process (CMP) estimation to account for endogeneity, evaluating how internet adoption affects both income diversification and inequality patterns among Chinese farmers. The findings reveal three key insights: First, internet use significantly increases farmers’ household income while reducing overall income inequality. Second, the positive impact of internet use on total income is primarily driven by increases in wage and operating income, while the reduction in income inequality is associated with a more equitable distribution of these income sources. Third, human capital plays a moderating role, with high-human-capital farmers benefiting more from internet use in terms of income growth and inequality reduction. Based on these findings, this study suggests that policymakers should promote internet adoption to enhance farmers’ incomes and address income inequality, while paying attention to the varying effects across different human capital groups. These insights provide valuable policy implications for achieving common prosperity in developing countries and regions.

Suggested Citation

  • Xuan Zhang & Ming Chang & Chunrong Zhang & Shuo Zhang & Qingning Lin, 2025. "The Impact of Internet Use on Income Inequality from Different Sources Among Farmers: Evidence from China," Agriculture, MDPI, vol. 15(8), pages 1-17, April.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:8:p:818-:d:1631333
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    References listed on IDEAS

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    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. Jenny C. Aker, 2011. "Dial “A” for agriculture: a review of information and communication technologies for agricultural extension in developing countries," Agricultural Economics, International Association of Agricultural Economists, vol. 42(6), pages 631-647, November.
    3. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    4. Tarvo Vaarmets & Kristjan Liivamägi & Tõnn Talpsepp, 2019. "How Does Learning and Education Help to Overcome the Disposition Effect?," Review of Finance, European Finance Association, vol. 23(4), pages 801-830.
    5. Peter Kuhn & Hani Mansour, 2014. "Is Internet Job Search Still Ineffective?," Economic Journal, Royal Economic Society, vol. 124(581), pages 1213-1233, December.
    6. John A. DeLeon & Lawrence Murphy Smith & Rabih Zeidan, 2024. "Relationship of Internet Activity to Income Inequality and Life Satisfaction," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 25(1), pages 45-72, January.
    7. Chengyou Li & Zhouhao Sha & Tao Sun, 2023. "Rural Households’ Internet Use on Common Prosperity: Evidence from the Chinese Social Survey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 170(3), pages 797-823, December.
    8. Jakob Svensson & David Yanagizawa, 2009. "Getting Prices Right: The Impact of the Market Information Service in Uganda," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 435-445, 04-05.
    9. Xiaolan Fu & Shaheen Akter, 2016. "The Impact of Mobile Phone Technology on Agricultural Extension Services Delivery: Evidence from India," Journal of Development Studies, Taylor & Francis Journals, vol. 52(11), pages 1561-1576, November.
    10. 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.
    11. Lee, Sang-Hyop & Kim, Jonghyuk, 2004. "Has the Internet changed the wage structure too?," Labour Economics, Elsevier, vol. 11(1), pages 119-127, February.
    12. David Roodman, 2011. "Fitting fully observed recursive mixed-process models with cmp," Stata Journal, StataCorp LLC, vol. 11(2), pages 159-206, June.
    13. Mora-Rivera, Jorge & García-Mora, Fernando, 2021. "Internet access and poverty reduction: Evidence from rural and urban Mexico," Telecommunications Policy, Elsevier, vol. 45(2).
    14. Wanglin Ma & Peng Nie & Pei Zhang & Alan Renwick, 2020. "Impact of Internet use on economic well‐being of rural households: Evidence from China," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 503-523, May.
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