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Study on the Relationship between Agricultural Credit, Fiscal Support, and Farmers’ Income—Empirical Analysis Based on the PVAR Model

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  • Yinan Wang

    (School of Economics & Management, Beijing Forestry University, Beijing 100083, China
    These authors contributed equally to this work.)

  • Yujie Xu

    (School of Economics & Management, Beijing Forestry University, Beijing 100083, China
    These authors contributed equally to this work.)

  • Wenhui Chen

    (School of Economics & Management, Beijing Forestry University, Beijing 100083, China)

Abstract

The growth of farmers’ income is one of the most critical issues in China’s “Three Rural Issues,” and optimizing fiscal policy support and improving credit supply are crucial to improving farmers’ income. Based on the panel data of 30 Chinese provinces from 2003 to 2020, this paper develops a PVAR model in order to explore the relationship between agricultural credit, fiscal support for agriculture, and farmers’ income from a dynamic perspective, considering regional heterogeneity. The empirical results show the following factors for farmers’ income growth: (1) From the GMM estimation, the positive correlation between fiscal support for agriculture is stronger than that of agricultural credit. (2) From the impulse-response function, in the eastern region, the positive shock of agricultural credit is positively correlated in the short run, but it will be negatively correlated as that of fiscal support for agriculture in the long run; in the central region, the positive shocks of agricultural credit and fiscal support for agriculture are persistently positively correlated; in the western region, the positive shocks of agricultural credit are persistently negatively correlated, while fiscal support for agriculture will be positively correlated in contrast. (3) From the variance decomposition, agricultural credit contributes more to famer’s income growth in the short run, while fiscal support for agriculture contributes more in the long run. The policy implications for promoting farmers’ income growth include implementing regionally differentiated agricultural credit development strategies, reasonably enhancing fiscal support for agriculture, and optimizing the structure of fiscal support for agriculture.

Suggested Citation

  • Yinan Wang & Yujie Xu & Wenhui Chen, 2023. "Study on the Relationship between Agricultural Credit, Fiscal Support, and Farmers’ Income—Empirical Analysis Based on the PVAR Model," Sustainability, MDPI, vol. 15(4), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:4:p:3173-:d:1063115
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    References listed on IDEAS

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    1. Iszan Hana Kaharudin & Mohammad Syuhaimi Ab-Rahman, 2022. "Fiscal Policy Effects on Private Expenditure for Sustainable Economic Growth: A Panel VAR Study from Selected Developing Countries," Sustainability, MDPI, vol. 14(17), pages 1-21, August.
    2. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    3. Maitra, Pushkar & Mitra, Sandip & Mookherjee, Dilip & Motta, Alberto & Visaria, Sujata, 2017. "Financing smallholder agriculture: An experiment with agent-intermediated microloans in India," Journal of Development Economics, Elsevier, vol. 127(C), pages 306-337.
    4. Greenwood, Jeremy & Jovanovic, Boyan, 1990. "Financial Development, Growth, and the Distribution of Income," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 1076-1107, October.
    5. Barro, Robert J, 1981. "Output Effects of Government Purchases," Journal of Political Economy, University of Chicago Press, vol. 89(6), pages 1086-1121, December.
    6. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    7. Shahid Iqbal & Abdul Qayyum Khan & Muhammad Yar Khan & Lamya Al-Aali, 2021. "The Dynamics of Financial Development, Government Quality, and Economic Growth in Different Groups of Economies," Sustainability, MDPI, vol. 13(14), pages 1-14, July.
    8. Fei Chen & Guotong Qiao & Na Wang & Dandan Zhang, 2022. "Study on the Influence of Population Urbanization on Agricultural Eco-Efficiency and on Agricultural Eco-Efficiency Remeasuring in China," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
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    1. Kaige An & Xiaowei Wang & Zhenning Wang & He Zhao & Yao Zhong & Jia Shen & Xiaohong Ren, 2024. "Dynamic Interactive Effects of Technological Innovation, Transportation Industry Development, and CO 2 Emissions," Sustainability, MDPI, vol. 16(19), pages 1-19, October.

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