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Addressing Rural–Urban Income Gap in China through Farmers’ Education and Agricultural Productivity Growth via Mediation and Interaction Effects

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  • Jianxu Liu

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Xiaoqing Li

    (School of Economics, Shandong University of Finance and Economics, Jinan 250014, China)

  • Shutong Liu

    (Faculty of Economics, Nankai University, Tianjin 300071, China)

  • Sanzidur Rahman

    (School of Agriculture, Policy and Development (SAPD), University of Reading, Reading RG6 6UR, UK)

  • Songsak Sriboonchitta

    (Faculty of Economics, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

Narrowing the rural–urban income gap is an important challenge in achieving sustained and stable economic and social development in China. The present study investigates the role of farmers’ education and agricultural productivity growth in influencing the rural–urban income gap by applying mediation, interaction, and quantile regression models to provincial panel data of China from 2003 to 2017. Results show that, first of all, China’s agricultural productivity (TFP) continues to improve, and it is mainly driven by technical change (TC), with no significant role of technical efficiency change (TEC) or stable scale change (SC). Improving farmers’ education not only directly narrows the rural–urban income gap but also indirectly improves agricultural productivity to further narrow the rural–urban income gap. Due to differences in income sources of farmers, the corresponding impacts of farmers’ education and agricultural productivity growth on the rural–urban income gap also differ. Policy recommendations include continued investments in farmers’ education and training as well as modernization of agricultural for higher productivity growth.

Suggested Citation

  • Jianxu Liu & Xiaoqing Li & Shutong Liu & Sanzidur Rahman & Songsak Sriboonchitta, 2022. "Addressing Rural–Urban Income Gap in China through Farmers’ Education and Agricultural Productivity Growth via Mediation and Interaction Effects," Agriculture, MDPI, vol. 12(11), pages 1-23, November.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:11:p:1920-:d:973336
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    as
    1. Chu, Lan Khanh & Hoang, Dung Phuong, 2020. "How does economic complexity influence income inequality? New evidence from international data," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 44-57.
    2. Wang, Xiang & Shao, Shuai & Li, Ling, 2019. "Agricultural inputs, urbanization, and urban-rural income disparity: Evidence from China," China Economic Review, Elsevier, vol. 55(C), pages 67-84.
    3. Yu Sheng & Xiaohui Tian & Weiqing Qiao & Chao Peng, 2020. "Measuring agricultural total factor productivity in China: pattern and drivers over the period of 1978‐2016," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 64(1), pages 82-103, January.
    4. Hu, Yue & Liu, Chang & Peng, Jiangang, 2021. "Financial inclusion and agricultural total factor productivity growth in China," Economic Modelling, Elsevier, vol. 96(C), pages 68-82.
    5. Lu, Ding, 2002. "Rural-urban income disparity: impact of growth, allocative efficiency, and local growth welfare," China Economic Review, Elsevier, vol. 13(4), pages 419-429, December.
    6. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    7. Andreas Savvides & Marios Zachariadis, 2005. "International Technology Diffusion and the Growth of TFP in the Manufacturing Sector of Developing Economies," Review of Development Economics, Wiley Blackwell, vol. 9(4), pages 482-501, November.
    8. Biwei Su & Almas Heshmati, 2013. "Analysis Of The Determinants Of Income And Income Gap Between Urban And Rural China," China Economic Policy Review (CEPR), World Scientific Publishing Co. Pte. Ltd., vol. 2(01), pages 1-29.
    9. Wang, Sun Ling & Huang, Jikun & Wang, Xiaobing & Tuan, Francis, 2019. "Are China’s regional agricultural productivities converging: How and why?," Food Policy, Elsevier, vol. 86(C), pages 1-1.
    10. Gradín, Carlos & Wu, Binbin, 2020. "Income and consumption inequality in China: A comparative approach with India," China Economic Review, Elsevier, vol. 62(C).
    11. Wang, Siliang & Tan, Shukui & Yang, Shengfu & Lin, Qiaowen & Zhang, Lu, 2019. "Urban-biased land development policy and the urban-rural income gap: Evidence from Hubei Province, China," Land Use Policy, Elsevier, vol. 87(C).
    12. Qiang Li & Xiaohang Wu & Yi Zhang & Yafei Wang, 2020. "The Effect of Agricultural Environmental Total Factor Productivity on Urban-Rural Income Gap: Integrated View from China," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    13. Jianxu Liu & Sanzidur Rahman & Songsak Sriboonchitta & Aree Wiboonpongse, 2017. "Enhancing Productivity and Resource Conservation by Eliminating Inefficiency of Thai Rice Farmers: A Zero Inefficiency Stochastic Frontier Approach," Sustainability, MDPI, vol. 9(5), pages 1-18, May.
    14. Anlimachie, Moses Ackah & Avoada, Cynthia, 2020. "Socio-economic impact of closing the rural-urban gap in pre-tertiary education in Ghana: context and strategies," International Journal of Educational Development, Elsevier, vol. 77(C).
    15. 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.
    16. Chi‐Wei Su & Yu Song & Ye‐Ting Ma & Ran Tao, 2019. "Is financial development narrowing the urban–rural income gap? A cross‐regional study of China," Papers in Regional Science, Wiley Blackwell, vol. 98(4), pages 1779-1800, August.
    17. Zhiqiang Zhou & Wenyan Liu & Huilin Wang & Jingyu Yang, 2022. "The Impact of Environmental Regulation on Agricultural Productivity: From the Perspective of Digital Transformation," IJERPH, MDPI, vol. 19(17), pages 1-19, August.
    18. Lessmann, Christian & Seidel, André, 2017. "Regional inequality, convergence, and its determinants – A view from outer space," European Economic Review, Elsevier, vol. 92(C), pages 110-132.
    19. Laureti, Tiziana & Benedetti, Ilaria & Branca, Giacomo, 2021. "Water use efficiency and public goods conservation: A spatial stochastic frontier model applied to irrigation in Southern Italy," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    20. Shen, Zhiyang & Baležentis, Tomas & Ferrier, Gary D., 2019. "Agricultural productivity evolution in China: A generalized decomposition of the Luenberger-Hicks-Moorsteen productivity indicator," China Economic Review, Elsevier, vol. 57(C).
    21. Alves, Luiz G.A. & Andrade, José S. & Hanley, Quentin S. & Ribeiro, Haroldo V., 2019. "The hidden traits of endemic illiteracy in cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 566-574.
    22. Sanzidur Rahman & Ruhul Salim, 2013. "Six Decades of Total Factor Productivity Change and Sources of Growth in Bangladesh Agriculture (1948–2008)," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(2), pages 275-294, June.
    23. Dong, Xiao-Ying & Hao, Yu, 2018. "Would income inequality affect electricity consumption? Evidence from China," Energy, Elsevier, vol. 142(C), pages 215-227.
    24. Ma, Yong & Chen, Diandian, 2020. "Openness, rural-urban inequality, and happiness in China," Economic Systems, Elsevier, vol. 44(4).
    25. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    26. Berisha, Edmond & Meszaros, John, 2020. "Macroeconomic determinants of wealth inequality dynamics," Economic Modelling, Elsevier, vol. 89(C), pages 153-165.
    27. Wang, Can & Deng, Mengzhi & Deng, Junfeng, 2020. "Factor reallocation and structural transformation implications of grain subsidies in China," Journal of Asian Economics, Elsevier, vol. 71(C).
    28. Rada, Nicholas & Helfand, Steven & Magalhães, Marcelo, 2019. "Agricultural productivity growth in Brazil: Large and small farms excel," Food Policy, Elsevier, vol. 84(C), pages 176-185.
    29. Luo, Chuliang & Li, Shi & Sicular, Terry, 2020. "The long-term evolution of national income inequality and rural poverty in China," China Economic Review, Elsevier, vol. 62(C).
    30. Mittal, Amit & Garg, Ajay Kumar, 2021. "Bank stocks inform higher growth—A System GMM analysis of ten emerging markets in Asia," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 210-220.
    31. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    32. Tang, Jianjun & Gong, Jiaowei & Ma, Wanglin & Rahut, Dil Bahadur, 2022. "Narrowing urban–rural income gap in China: The role of the targeted poverty alleviation program," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 74-90.
    33. Mou Wang & Wenmei Kang & Ruiying Zhang, 2020. "The Gap between Urban and Rural Development Levels Narrowed," Complexity, Hindawi, vol. 2020, pages 1-10, September.
    34. Zhang, Huafeng, 2017. "Opportunity or new poverty trap: Rural-urban education disparity and internal migration in China," China Economic Review, Elsevier, vol. 44(C), pages 112-124.
    35. Gao, Yanyan & Zang, Leizhen & Sun, Jun, 2018. "Does computer penetration increase farmers’ income? An empirical study from China," Telecommunications Policy, Elsevier, vol. 42(5), pages 345-360.
    36. Jianxu Liu & Mengjiao Wang & Li Yang & Sanzidur Rahman & Songsak Sriboonchitta, 2020. "Agricultural Productivity Growth and Its Determinants in South and Southeast Asian Countries," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    37. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    38. Yiguo Chen & Peng Luo & Tsangyao Chang, 2020. "Urbanization and the Urban–Rural Income Gap in China: A Continuous Wavelet Coherency Analysis," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
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