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Digital Rural Construction and Farmers’ Income Growth: Theoretical Mechanism and Micro Experience Based on Data from China

Author

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  • Wei Chen

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Quanzhong Wang

    (College of Economics and Management, Anqing Normal University, Anqing 246011, China)

  • Hong Zhou

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

This study analyzes the effect of digital rural construction on farmers’ income growth and the underlying mechanism using a 2SLS instrumental variable approach based on the county digital village index developed by Peking University and AliResearch, as well as micro-survey data of farmers in China. After fully correcting for endogeneity and verifying the robustness of the models, we found that digital rural construction has a significant positive impact on farmers’ total household income, wage income, and property income, while also inhibiting the growth of net agricultural income. Furthermore, we found that digital rural construction increases farmers’ income mainly by promoting non-agricultural employment and asset transformation. In terms of heterogeneity analysis, digital rural construction has a greater effect on increasing farmers’ income with high physical and human capital, but it is not beneficial to farmers with moderate social capital. It also has a greater effect on increasing farmers’ income in villages with better infrastructure. In addition, digital rural construction more significantly increases farmers’ income in the eastern, central, and southern regions of China compared with the western and northern regions. These findings provide new empirical evidence of the effect of digital rural construction on farmers’ income growth in China and other developing countries.

Suggested Citation

  • Wei Chen & Quanzhong Wang & Hong Zhou, 2022. "Digital Rural Construction and Farmers’ Income Growth: Theoretical Mechanism and Micro Experience Based on Data from China," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11679-:d:917382
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