Abstract
Using the provincial panel data from 1978 to 2020 as the research object, this study employs the fixed effect SFA-Malmquist model to measure the agricultural total factor productivity of each province and city, and the spatial correlation of China’s agricultural total factor productivity is determined by Moran’s I. On this basis, three weights (adjacency, economy, geography) are included as spatial factors in three spatial β-convergence models (SAR, SEM and SDM), and the spatial convergence characteristics of China’s agricultural total factor productivity are analyzed in different time periods and different regions. The study found that: First, China’s agricultural total factor productivity shows a growing trend, but as time goes on, its growth rate gradually slows down, and the growth rate in the eastern region is higher than that in the central and western regions. Second, China’s agricultural total factor productivity has significant spatial correlation and spatial convergence characteristics. The differences in agricultural total factor productivity in various regions are shrinking over time, and the spatial spillover effect significantly shortens the convergence process. Due to spatial convergence, while carrying out agricultural production, all regions should thoroughly consider the advantages of agricultural resources in neighboring regions and strengthen cooperation and exchanges between regions.
References
Caves, D., Christensen, L., & Diewert, W. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica: Journal of the Econometric Society, 1393–1414.
Chen, P., Yu, M., Chang, C., & Hsu, S. (2008). Total factor productivity growth in China’s agricultural sector. China Economic Review, 19(4), 580–593. https://doi.org/10.1016/j.chieco.2008.07.001
Fan, L., & Li, G. (2012). Total factor productivity and its research progress in the field of agriculture. Modern Economic Science, 34(1), 109–119+128.
Gao, F. (2015). Evolution trend and internal mechanism of regional total factor productivity in Chinese agriculture. The Journal of Quantitative & Technical Economics, 32(5), 3–19+53. https://doi.org/10.13653/j.cnki.jqte.2015.05.001
Gao, M., & Song, H. (2014). The spatial convergence of grain production technical efficiency and the difference of functional areas also on the spatial ripple effect of technology diffusion. Management World (7), 83–92. https://doi.org/10.19744/j.cnki.11-1235/f.2014.07.010
Gao, M., Song, H., & Carter, M. (2016). The impact of grain direct subsidies on wheat productivity of farmers with different scales of operation based on data of rural households in fixed observation points nationwide. Chinese Rural Economy (8), 56–69.
Gong, B. (2018a). Agricultural reforms and production in China: Changes in provincial production function and productivity in 1978–2015. Journal of Development Economics, 132, 18–31. https://doi.org/10.1016/j.jdeveco.2017.12.005
Gong, B. (2018b). The contribution of inputs and productivity to agricultural growth in China. Journal of Agrotechnical Economics (6), 4–18. https://doi.org/10.13246/j.cnki.jae.2018.06.001
Greene, W. (2005). Reconsidering heterogeneity in panel data estimators of the stochastic frontier model. Journal of Econometrics, 126(2), 269-303. https://doi.org/10.1016/j.jeconom.2004.05.003
Hou, M., & Yao, S. (2018). Spatial-temporal evolution and trend prediction of agricultural eco-efficiency in China: 1978–2016. Acta Geographica Sinica, 73(11), 2168–2183. https://doi.org/10.11821/dlxb201811009
Huo, Z., Wu, Y., & Zhou, Z. (2011). Evaluation of agricultural productivity China based on input-output. Economic Geography, 31(6), 999–1002.
Jia, L., & Xia, Y. (2017). Scale efficiency of grain production and influencing factors based on survey data from Heilongjiang, Henan and Sichuan. Resources Science, 39(5), 924–933. https://doi.org/10.18402/resci.2017.05.12
Kuang, Y. (2012). Technology efficiency, technology progress, factor accumulation and China’s agricultural economic growth. The Journal of Quantitative & Technical Economics, 29(1), 3–18. https://doi.org/10.13653/j.cnki.jqte.2012.01.009
Kumbhakar, S. (1990). Production frontiers, panel data, and time-varying technical inefficiency. Journal of Econometrics, 46(1–2), 201–211. https://doi.org/10.1016/0304-4076(90)90055-X
Li, G. (2014). The green productivity revolution of agriculture in China from 1978 to 2008. China Economic Quarterly, 13(2), 537–558. https://doi.org/10.13821/j.cnki.ceq.2014.02.011
Li, S., & Yin, X. (2017). Analysis of the impact of rural labor transfer on agricultural total factor productivity in China. Journal of Agrotechnical Economics (9), 4–13. https://doi.org/10.13246/j.cnki.jae.2017.09.001
Lin, J. (1992). Rural reforms and agricultural growth in China. The American Economic Review, 34–51.
Liu, Y., & Meng, L. (2002). SFA method for measuring Malmquist productivity index. Journal of Beijing Institute of Technology (Social Sciences Edition) (S1), 42–44.
Nin Pratt, A., Yu, B., & Fan, S. (2008). The total factor productivity in China and India: New measures and approaches. China Agricultural Economic Review, 1(1), 9–22. https://doi.org/10.1108/17561370910915339
Pan, D., & Ying, R. (2012). Spatial-temporal differences of agricultural total factor productivity: Restudy of previous literatures. Economic Geography, 32(7), 113–117+128. https://doi.org/10.15957/j.cnki.jjdl.2012.07.018
Quan, J. (2009). Empirical analysis of China’s agricultural total factor productivity growth: 1978 ~ 2007-Based on Stochastic Frontier Analysis (SFA) method. Chinese Rural Economy (9), 36–47.
Shi, C., Zhu, J., & Jie, C. (2016). Regional differences and convergence analysis of agricultural total factor productivity growth in China-based on fixed effect SFA model and panel unit root method. Inquiry Into Economic Issues (4), 134–141.
Tobler, W. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240.
Wang, B., & Zhang, W. (2018). Cross-provincial differences in determinants of agricultural eco-efficiency in China: An analysis based on panel data from 31 provinces in 1996-2015. Chinese Rural Economy (1), 46–62.
Wang, S., Tuan, F., Gale, F., Somwaru, A., & Hansen, J. (2013). China’s regional agricultural productivity growth in 1985-2007: A multilateral comparison. Agricultural Economics, 44(2), 241–251. https://doi.org/10.1111/agec.12008
Wang, Y., Song, W., & Han, X. (2010). Spatial econometric analysis of agricultural total factor productivity and its influencing factors in China-Based on provincial spatial panel data from 1992 to 2007. Chinese Rural Economy (8), 24–35.
Wu, S., Walker, D., Devadoss, S., & Lu, Y. (2001). Productivity growth and its components in Chinese agriculture after reforms. Review of Development Economics, 5(3), 375–391. https://doi.org/10.1111/1467-9361.00130
Wu, Y. (2010). An estimation of output elasticity of regional agricultural production factors in China—An empirical study with spatial econometric models. Chinese Rural Economy (6), 25-37+48.
Xu, Q., Yin, R., & Zhang, H. (2011). Economies of scale, returns to scale and the problem of optimum-scale farm management: An empirical study based on grain production in China. Economic Research Journal, 46(3), 59–71+94.
Xu, Y. (1999). Agricultural productivity in China. China Economic Review, 10(2), 108–121.
Yang, G., & Yang, M. (2013). The spatial correlation effect of agricultural total factor productivity in China—An empirical study based on static and dynamic spatial panel models. Economic Geography, 33(11), 122–129.
Yang, Y., Lin, W., & Zhang, L. (2017). Agricultural technology progress, technical efficiency and grain production—An empirical analysis based on provincial panel data in China. Journal of Agrotechnical Economics (5), 46–56. https://doi.org/10.13246/j.cnki.jae.2017.05.005
Yu, Y. (2015). Research on the dynamic spatial convergence of provincial total factor productivity in China. The Journal of World Economy, 38(10), 30–55. https://doi.org/10.19985/j.cnki.cassjwe.2015.10.003
Zeng, Y., Lv, Y., & Wang, X. (2018). Multidimensional analysis of the impact of farmland transfer on the technical efficiency of grain production—An empirical study based on stochastic frontier production function. Journal of Huazhong Agricultural Uni-versity (Social Sciences Edition) (1), 13–21+156–157. https://doi.org/10.13300/j.cnki.hnwkxb.2018.01.002
Zhang, L., & Cao, J. (2013). China’s agricultural total factor productivity growth: The introduction of allocative efficiency change—An empirical analysis based on stochastic frontier production function method. Chinese Rural Economy (3), 4–15.
Zhang, L., & Chen, S. (2015). Empirical Analysis on spatial-temporal evolution and driving forces of per capita grain possession in China. Economic Geography, 35(3), 171–177. https://doi.org/10.15957/j.cnki.jjdl.2015.03.025
Zhang, Z., Xue, B., Chen, X., & Li, Y. (2015). Convergence in spatial difference of industrial environmental efficiency in China. China Population Resources and Environment, 25(2), 30–38. https://doi.org/10.3969/j.issn.1002-2104.2015.02.005
Zhou, L., & Zhang, H. (2013). Productivity growth in China’s agriculture during 1985-2010. Journal of Integrative Agriculture, 12(10), 1896–1904. https://doi.org/10.1016/S2095-3119(13)60598-5
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2023 Chaozhu Li, Xiaoliao Li