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The Impact of Digital Technology on Land Rent-Out Behavior: Information Sharing or Exclusion?

Author

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  • Xiaofan Zuo

    (College of Humanities and Development Studies, China Agricultural University, Beijing 100193, China)

  • Zhisheng Hong

    (Institute of Science and Development, Chinese Academy of Sciences, Beijing 100190, China)

Abstract

In the digital age, it is critical to understand the nexus between digital technology (DT) and land rent-out behavior (LRB). It has implications for reducing the rate of land abandonment to achieve sustainable agricultural development. A large dataset ( n = 5233) dating from 2016 and coming from the China Family Panel Studies (CFPS) is used to explore the impact of DT on LRB by applying several econometric models, also including the “Recursive Bivariate Probit (RBP) model” and “Chain Multiple Mediation effect (CMM) model”. We provide empirical evidence that the DT’s information sharing effect positively impacted LRB, while an opposite effect is observed by the “digital divide (DT_GAP)” i.e., information exclusion that negatively impacted LRB. We further test the effect of two other variables, namely “digital information dependence” and “non-farm jobs” supposed as mediating factors of DT and DT_GAP in influencing LRB, respectively in a positive and negative way. In particular, the variable “nonfarm jobs” plays a mediating role conditional on the variable “digital information dependence” as a mediating variable at the first level. In addition, statistical tests reveal that the impact of DT and the DT_GAP on LRB is not significant in terms of regional preferences but is significant in terms of age of householder and household income level.

Suggested Citation

  • Xiaofan Zuo & Zhisheng Hong, 2022. "The Impact of Digital Technology on Land Rent-Out Behavior: Information Sharing or Exclusion?," Agriculture, MDPI, vol. 12(7), pages 1-19, July.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:7:p:1046-:d:865937
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    References listed on IDEAS

    as
    1. Marcin Relich, 2017. "The impact of ICT on labor productivity in the EU," Information Technology for Development, Taylor & Francis Journals, vol. 23(4), pages 706-722, October.
    2. Zhang, Yuanxia & Halder, Pradipta & Zhang, Xiaoning & Qu, Mei, 2020. "Analyzing the deviation between farmers' Land transfer intention and behavior in China's impoverished mountainous Area: A Logistic-ISM model approach," Land Use Policy, Elsevier, vol. 94(C).
    3. Tewathia, Nidhi & Kamath, Anant & Ilavarasan, P. Vigneswara, 2020. "Social inequalities, fundamental inequities, and recurring of the digital divide: Insights from India," Technology in Society, Elsevier, vol. 61(C).
    4. Tasso Adamopoulos & Diego Restuccia, 2020. "Land Reform and Productivity: A Quantitative Analysis with Micro Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(3), pages 1-39, July.
    5. Paunov, Caroline & Rollo, Valentina, 2016. "Has the Internet Fostered Inclusive Innovation in the Developing World?," World Development, Elsevier, vol. 78(C), pages 587-609.
    6. Rogers, Sarah & Wilmsen, Brooke & Han, Xiao & Wang, Zoe Ju-Han & Duan, Yuefang & He, Jun & Li, Jie & Lin, Wanlong & Wong, Christine, 2021. "Scaling up agriculture? The dynamics of land transfer in inland China," World Development, Elsevier, vol. 146(C).
    7. Stark, Oded & Taylor, J Edward, 1991. "Migration Incentives, Migration Types: The Role of Relative Deprivation," Economic Journal, Royal Economic Society, vol. 101(408), pages 1163-1178, September.
    8. Fei, Rilong & Lin, Ziyi & Chunga, Joseph, 2021. "How land transfer affects agricultural land use efficiency: Evidence from China’s agricultural sector," Land Use Policy, Elsevier, vol. 103(C).
    9. Jianying Wang & Yumei Xu & Lilin Zou & Ying Wang, 2021. "Does Culture Affect Farmer Willingness to Transfer Rural Land? Evidence from Southern Fujian, China," Land, MDPI, vol. 10(6), pages 1-19, June.
    10. Douglas Staiger & James H. Stock & Mark W. Watson, 1997. "The NAIRU, Unemployment and Monetary Policy," Journal of Economic Perspectives, American Economic Association, vol. 11(1), pages 33-49, Winter.
    11. Jenny C. Aker & Isaac M. Mbiti, 2010. "Mobile Phones and Economic Development in Africa," Journal of Economic Perspectives, American Economic Association, vol. 24(3), pages 207-232, Summer.
    12. Aparajita Goyal, 2010. "Information, Direct Access to Farmers, and Rural Market Performance in Central India," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 22-45, July.
    13. Yan, Jinming & Yang, Yumeng & Xia, Fangzhou, 2021. "Subjective land ownership and the endowment effect in land markets: A case study of the farmland “three rights separation” reform in China," Land Use Policy, Elsevier, vol. 101(C).
    14. Gao, Jia & Song, Ge & Sun, Xueqing, 2020. "Does labor migration affect rural land transfer? Evidence from China," Land Use Policy, Elsevier, vol. 99(C).
    15. Uwe Deichmann & Aparajita Goyal & Deepak Mishra, 2016. "Will digital technologies transform agriculture in developing countries?," Agricultural Economics, International Association of Agricultural Economists, vol. 47(S1), pages 21-33, November.
    16. Eduardo Nakasone & Maximo Torero & Bart Minten, 2014. "The Power of Information: The ICT Revolution in Agricultural Development," Annual Review of Resource Economics, Annual Reviews, vol. 6(1), pages 533-550, October.
    17. Deng, Xin & Xu, Dingde & Zeng, Miao & Qi, Yanbin, 2019. "Does early-life famine experience impact rural land transfer? Evidence from China," Land Use Policy, Elsevier, vol. 81(C), pages 58-67.
    18. Deng, Xin & Xu, Dingde & Zeng, Miao & Qi, Yanbin, 2019. "Does Internet use help reduce rural cropland abandonment? Evidence from China," Land Use Policy, Elsevier, vol. 89(C).
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