Research on World Agricultural Economy

Coupling Coordination Analysis between Total Factor Productivity and Digital Economy in China’s Agriculture

Shuang Gao

United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, Tokyo 183‑8509, Japan

Masaaki Yamada

Institute of Agriculture, Tokyo University of Agriculture and Technology, Tokyo 183‑8509, Japan

Dawei Gao

College of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou 450002, China

Haisong Nie

Institute of Agriculture, Tokyo University of Agriculture and Technology, Tokyo 183‑8509, Japan

DOI: https://doi.org/10.36956/rwae.v6i1.1425

Received: 25 October 2024 | Revised: 11 November 2024 | Accepted: 13 November 2024 | Published Online: 17 December 2024

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Abstract

This study aims to systematically analyze the coupling and coordinated development between the digital economy (DE) and total factor productivity (TFP) in China’s agricultural sector, focusing on their impact on regional agricultural advancement. Using a comprehensive dataset from 31 Chinese provinces covering the period from 2014 to 2021, we apply the EBM model, entropy weight method, and coupling coordination degree model to assess TFP-DE interactions. To capture spatial-temporal dynamics and regional disparities, we employ kernel density estimation, Moran’s I index, the Dagum Gini coefficient, and an obstacle degree model. The findings reveal an initial phase of “multipolarization” in TFP-DE coordination, which gradually stabilizes towards preliminary coordination levels. Despite this progress, significant regional imbalances persist, particularly in central and western provinces where “low-low” clusters dominate, in contrast to the “high-high” clusters in eastern regions. While disparities in coordination have narrowed in eastern areas, they continue to widen across central and western regions. The primary obstacles have shifted from foundational infrastructure to challenges directly associated with DE and TFP. This study underscores the necessity of region-specific policies to address these disparities, particularly in underdeveloped areas, to enhance agricultural productivity through digital integration. The findings provide a strategic foundation for policymakers to foster balanced and sustainable growth, contributing to China’s broader goals for agricultural modernization.

Keywords: Agricultural productivity improvement; Digital transformation; Spatial-temporal disparities; Sustainable agriculture; Agricultural policy

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References

[1] Leng, X., Tong, G., 2022. The digital economy empowers sustainable development of agriculture-related industries in China. Sustainability. 14(17), 10967. DOI: https://doi.org/10.3390/su141710967

[2] Bukht, R., Heeks, R., 2017. Defining, conceptualising and measuring the digital economy. Development Informatics Working Paper no. 68, 3 August 2017. DOI: http://dx.doi.org/10.2139/ssrn.3431732

[3] Kholiavko, N., Popelo, O., Bazhenkov, I., et al., 2021. Information and communication technologies as a tool of strategy for ensuring the higher education adaptability to the digital economy challenges. International Journal of Computer Science & Network Security. 21(8), 187–195. DOI: https://doi.org/10.22937/IJCSNS.2021.21.8.25

[4] Sarjana, S., Najib, M.A.A., Khayati, N., 2021. Bibliometric analysis to encourage the development of digital economy scientific studies. Proceedings of the Conference Towards ASEAN Chairmanship 2023; Online, Indonesia, 13–15 December 2021. pp. 14–21. DOI: https://doi.org/10.2991/aebmr.k.211207.002

[5] Organisation for Economic Cooperation and Development, 2015. Measuring the digital economy: A new perspective, 1st ed. (Translated by Zhang, X.). Science Press, Shanghai Far East Publishing House: Shanghai, China. pp. 28–47.

[6] Shi, Y., 2022. Digital economy: Development and future. Bulletin of Chinese Academy of Sciences. 37(1), 78–87. DOI: https://doi.org/10.16418/j.issn.1000-3045.20211217002

[7] Wang, Z., Gao, T., Wang, R., 2022. Research on the impact of digital innovationon the development of digital economy: A literature review. 40(5), 90–97. DOI: https://doi.org/10.19445/j.cnki.15-1103/g3.2022.05.012

[8] Li, J., 2019. An analysis of the role of the digital economy in promoting agricultural economic development: A review of “The driving force of transformation: China's agricultural supply-side structural reform”. China's Agricultural Resources and Regional Planning. 11, 94+102. Available from: http://www.cnki.net

[9] Wen, Y., Sun, Z., 2023. The impact of the digital economy on high-quality development of agriculture: A Chinese case study. Sustainability. 15, 5745. DOI: https://doi.org/10.3390/su15075745

[10] Zhang, Y.F, Ji, M.X., Zheng, X.Z., 2023. Digital economy, agricultural technology innovation, and agricultural green TFP. SAGE Open. 13, 215. DOI: https://doi.org/10.1177/21582440231194388

[11] Gao, D, Lyu, X., 2023. Agricultural TFP, digital economy, and high-quality agricultural development. Plos One. 18(10), 1–15. DOI: https://doi.org/10.1371/journal.pone.0292001

[12] Li, H., Zhang, Y., Li, Y., 2024. Impact of the digital economy on the TFP of manufacturing firms: Empirical evidence from China. Technological Forecasting and Social Change. 207, 123604. DOI: https://doi.org/10.1016/j.techfore.2024.123604

[13] Hua, J., Yu, J., Song, Y., et al., 2024. The enabling effect of the digital economy on high-quality agricultural development evidence from China. Sustainability. 16(9), 3859. DOI: https://doi.org/10.3390/su16093859

[14] Litvinenko, V.S., 2020. Digital economy as a factor in the technological development of the mineral sector. Natural Resources Research. 29(3), 1521–1541. DOI: https://doi.org/10.1007/s11053-019-09568-4

[15] Sridhar, A., Balakrishnan, A., Jacob, M.M., et al., 2023. Global impact of COVID-19 on agriculture: The role of sustainable agriculture and digital farming. Environmental Science and Pollution Research. 30(15), 42509–42525. DOI: https://doi.org/10.1007/s11356-022-19358-w

[16] Guzueva, E.R., Vezirov, T.G., Beybalaeva, D.K., et al., 2020. Impact of agriculture automation on the digital economy. IOP Conference Series: Earth and Environmental Science. 421(2), 022047. DOI: https://doi.org/10.1088/1755-1315/421/2/022047

[17] Carolan, M., 2017. Publicising food: Big data, precision agriculture, and co-experimental techniques of addition. Sociologia Ruralis. 57(2), 135–154. DOI: https://doi.org/10.1111/soru.12120

[18] Wang, Y., Wu, L., Su, F., 2022. Research on the dynamic change of agricultural energy efficiency in China's main grain-producing areas based on the super-efficiency EBM and global-malmquist index model. Resource Development & Market. 38(6), 641–649. DOI: https://doi.org/10.3969/j.issn.1005-8141.2022.06.001

[19] Zhou, P., Ang, B.W., Wang, H., 2012. Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach. European Journal of Operational Research. 221(3), 625–635. DOI: https://doi.org/10.1016/j.ejor.2012.04.022

[20] Tone, K., 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research. 130(3), 498–509. DOI: https://doi.org/10.1016/S0377-2217(99)00407-5

[21] Tone, K., Tsutsui, M., 2010. An epsilon-based measure of efficiency in DEA: A third pole of technical efficiency. European Journal of Operational Research. 207(3), 1554–1563. DOI: https://doi.org/10.1016/j.ejor.2010.07.014

[22] Coelli, T.J., Rao, D.P., 2005. Total factor productivity growth in agriculture: A Malmquist index analysis of 93 countries, 1980–2000. Agricultural Economics. 32, 115–134. DOI: https://doi.org/10.1111/j.0169-5150.2004.00018.x

[23] Li, J., Wang, Y., Cheng, P., 2023. Spatio-temporal evolution differences and endogenous composition of China's agricultural total factor productivity. Journal of China Agricultural University. 28(02), 240–252. DOI: https://doi.org/10.11841/j.issn.1007-4333.2023.02.21

[24] Avila, A.F.D., Evenson, R.E., 2010. Total factor productivity growth in agriculture: The role of technological capital. Handbook of Agricultural Economics. 4, 3769–3822. DOI: https://doi.org/10.1016/S1574-0072(09)04072-9

[25] Temoso, O., Villano, R.A., Hadley, D., 2015. Agricultural productivity, efficiency and growth in a semi-arid country: A case study of Botswana, African Journal of Agricultural and Resource Economics. 10(3), 192–206. DOI: https://doi.org/10.22004/ag.econ.211667

[26] Effendy, S., 2018. Changes of technical efficiency and total factor productivity of cocoa farming in Indonesia, Bulgarian Journal of Agricultural Science. 24(4), 566–573. Avalable from: https://scholar.google.com

[27] Adom, P.K., Amoani, S., 2021. The role of climate adaptation readiness in economic growth and climate change relationship: An analysis of the output/income and productivity/institution channels. Journal of Environmental Management. 293, 112923. DOI: https://doi.org/https://doi.org/10.1016/j.jenvman.2021.112923

[28] Song, Y., Zhang, B., Wang, J., et al., 2022. The impact of climate change on China's agricultural green total factor productivity. Technological Forecasting and Social Change. 185, 122054. DOI: https://doi.org/10.1016/j.techfore.2022.122054

[29] Song, M., Wu, Q., Zhu, H., 2024. Could the aging of the rural population boost green agricultural total factor productivity? Evidence from China. Sustainability. 16(14), 6117. DOI: https://doi.org/10.3390/su16146117

[30] Medennikov, V.I., Butrova., E.V., Sklyarov, A.E., 2021. An approach to estimate the economic effect of using ERS data to solve agricultural issues. IOP Conference Series: Earth and Environmental Science. IOP Publishing. 666, 062084. Available from: https://iopscience.iop.org/article/10.1088/1755-1315/666/6/062084/pdf

[31] Wang, F., Sun, S., Liu, T., 2023. Has the development of digital economy promoted changes in agricultural production methods? Evidence from prefectures in the Yellow River Basin. China Rural Economy. 9, 122–143. DOI: https://doi.org/10.20077/j.cnki.11-1262/f.2023.09.007

[32] Yuan, L., Ruan, J., 2023. Digital economy empowers chinese agricultural and rural modernization theoretical logic and empirical evidence. Economic Issues. 8, 25–32. DOI: https://doi.org/10.16011/j.cnki.jjwt.2023.08.015

[33] Gong, R., Xie, L., Wang, Y., 2020. Interactive mechanism and empirical test of agricultural high-quality development and new urbanization. Reform. 7, 145–159. Available from: http://www.reform.net.cn

[34] Hou, G., You, S., 2023. To calculate China's plant-climate productive potentialities by “Chikuzo model”. Journal of Natural Resources. 5(1), 60–65. DOI: https://doi.org/10.11849/zrzyxb.1990.01.007

[35] Li, Z., Wang, Y., 2006. Analysis of the evolution of climate productivity on the Loess Plateau. Journal of Shanxi University (Natural Science Edition). 29(1), 96–101. DOI: https://doi.org/10.13451/j.cnki.shanxi.univ(nat.sci.).2006.01.027

[36] Hou, X., 2008. The temporal and spatial dynamics of climate production potential in China from 1951 to 2000. Geography of Arid Regions. 31(5), 723–730. Available from: http://ir.yic.ac.cn/handle/133337/4217

[37] Liu, D., Li, H., 2013. Climatic potential productivity change in Altay region during 1961–2011. Desert and Oasis Meteorology. 7(2), 25–28. Available from: https://www.cnki.net

[38] Lieth, H., 1973. Primary production: Terrestrial ecosystem. Human Ecology. 1, 303–332. Available from: https://link.springer.com/content/pdf/10.1007/BF01536729.pdf

[39] Lieth, H., Whittaker, R.H., 1985. Primary productivity of the biosphere (Translated by Wang, Y.Q.). Science Press: Beijing, China. pp. 217–236. Available from: https://baike.baidu.com/item/%E7%94%9F%E7%89%A9%E5%9C%88%E7%9A%84%E7%AC%AC%E4%B8%80%E6%80%A7%E7%94%9F%E4%BA%A7%E5%8A%9B/52948595?fr=ge_ala

[40] Zhou, J., Fan, F., Du, X., et al., 2020. Agricultural climate production potential in Shijiazhuang: Change analysis. Chinese Agriculture Science Bulletin. 36(3), 100–103. Available from: https://www.cnki.net

[41] Xu, Y., Yu, L., Zhou, B., et al., 2019. Temporal-spatio dynamic pattern of climatic potential production under the background of climate change in the future in China. Journal of Arid Land Resources and Environment. 33(09), 72–80. DOI: https://doi.org/10.13448/j.cnki.jalre.2019.268

[42] Zhang, L., Tan, X., Xiao, Q., et al., 2023. Agricultural eco-efficiency measurement and regional difference in China based on the climate resource input. Economic Geography. 43(04), 154–163. DOI: https://doi.org/10.15957/j.cnki.jjdl.2023.04.016

[43] Liu, L., Zou, J., 2023. Temporal and spatial evolution of the coupling coordination of economy, technology, and ecosystem in Hubei Province. Journal of South-Central University for Nationalities (Humanities and Social Sciences Edition). (11), 132–140+186–187. DOI: https://doi.org/10.19898/j.cnki.42-1704/c.20231102.01.

[44] Yao, C., Hong, X., Xiao, G., et al., 2023. Regional differences and dynamic evolution of the distribution of high-quality social security development in China. Economic and Management Review. 39(06), 30–42. DOI: https://doi.org/10.13962/j.cnki.37-1486/f.2023.06.003

[45] Tian, Y., Lu, Y., 2023. Coupling coordination between new-type urbanization and agricultural carbon emission efficiency in China's provinces. Journal of Huazhong Agricultural University (Social Sciences Edition). 4, 33–46. DOI: https://doi.org/10.13300/j.cnki.hnwkxb.2023.04.005

[46] Zhang, H., Lv, J., 2019. Regional disparities and dynamic evolution of food safety risks: An empirical study based on Dagum Gini coefficient decomposition and nonparametric estimation. Journal of Public Management. 16(01), 77–88. DOI: https://doi.org/10.16149/j.cnki.23-1523.20181114.005

[47] Wen, T., Chen, Y., 2020. Research on the integration of the digital economy with agriculture and the rural economy: Practice patterns, realistic obstacles, and breakthrough paths. Agricultural Economic Issues. 7, 118–129. DOI: https://doi.org/10.13246/j.cnki.iae.2020.07.011

[48] Chen, H., Liu, H., Huang, X., et al., 2023. Research on the evaluation of high-quality agricultural development level under the background of digital economy. Guangdong Agricultural Sciences. 50(4), 142–155. DOI: https://doi.org/10.16768/j.issn.1004-874X.2023.04.017

[49] Zeng, X., Li, J., Zeng, X., 2021. Factor endowment and the sustainable development of digital economy in the middle and west of China: Based on machine learning methods. Journal of Hunan University of Science & Technology (Social Science Edition). 24(6), 80–89. DOI: https://doi.org/10.13582/j.cnki.1672-7835.2021.06.015

[50] Li, F., 2023. Measurement of digital agriculture level and spatial location distribution in the context of Chinese-style modernization. Feed Research. 46(19), 186–192. DOI: https://doi.org/10.13557/j.cnki.issn1002-2813.2023.19.037

[51] Qiu, Z., Zhou, Y., 2021. Development of digital economy and regional total factor productivity: An analysis based on national big data comprehensive pilot zone. Journal of Finance and Economics. 47(7), 4–17. DOI: https://doi.org/10.16538/j.cnki.jfe.20210119.103

[52] Tang, H., Chen, X., Zhang, J., 2021. Digital economy, circulation efficiency and industrial structure upgrading. Journal of Business Economics. 11, 5–20. DOI: https://doi.org/10.14134/j.cnki.cn33-1336/f.2021.11.001

[53] Zhang, X., Chen, S., Liao, C., et al., 2016. Spatial spillover effects of regional economic growth in Beijing-Tianjin-Hebei region. Geographical Research. 35(9), 1754–1766. DOI: https://doi.org/10.11821/dlyj201609013

[54] Zhang, Y., Gao, A., Chen, H., et al., 2023. Digital agriculture application platform based on blockchain technology. Agricultural Engineering. 13(11), 37–40. DOI: https://doi.org/10.19998/j.cnki.2095-1795.2023.11.006

[55] Fang, J., Shao, Z., Li, J., et al., 2023. Preliminary research on the construction of the scientific research demonstration base of smart agriculture (digital rice)—A case study of Hejiashan Foundation Seed Farm in Hunan Province. China Rice. 29(3), 69–73.

[56] Xu, J., Guo, X., Cui, K., 2023. The level measurement and regional difference of high-quality agricultural development enabled by digital innovation. China Business and Market. 8, 54–64. DOI: https://doi.org/10.14089/j.cnki.cn11-3664/f.2023.08.005

[57] Zhu, Q., Bai, J., Peng, C., et al., 2019. Do information communication technologies improve agricultural productivity?. China's Rural Economy. 4, 22–40. Available from: http://www.cnki.net

[58] Weng, W., 2016. Research on agricultural product making mode based on one commerce plarform—Taking Chongqing as an example. Chinese Journal of Agricultural Resources and Regional Planning. 7, 206–210.

[59] Ming, L., 2023. Research on the relationship between agricultural industrial structure upgrading and digital economy development. Advances in Social Sciences. 12(7), 3761–3768. DOI: https://doi.org/10.12677/ass.2023.127513

[60] Zhao, C., Li, J., Feng, X., 2021. Development strategy of smart agriculture for 2035 in China. China Engineering Science. 23(4), 1–9. DOI: https://doi.org/10.15302/J-SSCAE-2021.04.001

[61] Yin, C., Gao, X., 2022. Recalculation of China's agricultural total factor productivity with climatic factors. Journal of Zhongnan University of Economics and Law. 1, 110–122. DOI: https://doi.org/10.19639/j.cnki.issn1003-5230.2022.0008

[62] Li, B., Yue, H., 2022.High-quality agricultural development enabled by digital economy: Theoretical logic and empirical test. Journal of Jiangxi University of Finance and Economics. 6, 95. DOI: https://doi.org/10.13676/j.cnki.cn36-1224/f.2022.06.004

[63] Zhao, W., Xu, X., 2023. Effect and mechanism of digital economy on the resilience of agricultural economy. Journal of South China Agricultural University: Social Science Edition. 22(2), 87–96. DOI: https://doi.org/10.7671/j.issn.1672-0202.2023.02.008

[64] Liu, Y., Chen, X., 2021. The effect of digital economy on industrial structure upgrade in China. Research on economics and management. 42(8), 15–29. DOI: https://doi.org/10.13502/j.cnki.issn1000-7636.2021.08.002

[65] Wang, Z., Allan, K.K.C., Ou, J.-F.. 2021. The mechanism and path of agricultural product circulation system influencing the fluctuation of agricultural products price—based on qualitative analysis of data from field investigation of 92 households. Chinese Journal of Management Science. 29(12), 92–103. DOI: https://doi.org/10.16381/j.cnki.issn1003-207x.2018.0329

[66] Zheng, Z., Kuang, Q., Zhang, F., 2024. The dynamic distribution and convergence trends of digital agriculture development in China. Journal of Central South University of Forestry & Technology (Social Science Edition). 2, 37–49. DOI: https://doi.org/10.14067/j.cnki.1673-9272.2024.02.005

[67] Wang, J., Yue, X., Shi, M., 2023. Research on the impact of digital economy driving agricultural modernization. Guangdong Agricultural Sciences. 50(2), 156–168. DOI: https://doi.org/10.16768/j.issn.1004-874X.2023.02.017

[68] Yin, C., Gao, X., Yang, K., 2022. Regional differences and dynamic evolution of high-quality agricultural development in China. Journal of Southwest University Natural Science Edition. 44(12), 87–100. DOI: https://doi.org/10.13718/j.cnki.xdzk.2022.12.010

[69] Zhou, S., 2024. Research on the digital transformation of agriculture in the context of rural revitalization. E-Commerce Letters. 13, 2318. DOI: https://doi.org/10.12677/ecl.2024.132284

[70] Ma, Li, Tang, M., 2024. Digital economy and agricultural green development: Theoretical mechanism and empirical test. Hubei Agricultural Sciences. 63(8), 296–302. DOI: https://doi.org/10.14088/j.cnki.issn0439-8114.2024.08.048

[71] Du, J., Zhang, Y., Liu, B., et al., 2023. Impact of digital village construction on agricultural green total factor productivity and its mechanism. China Population, Resources and Environment. 33(2), 165–175. DOI: https://doi.org/10.12062/cpre.20221013

[72] Yang, S., Li, Y., Xu, Q., 2019. Research on agricultural economic development and supply-side structural reform in Jilin Province based on grey correlation. Journal of Chinese Agricultural Mechanization. 40(8), 208–213. DOI: https://doi.org/10.13733/j.jcam.issn.2095-5553.2019.08.36.

[73] Yin, L., 2024. Analysis of the current management status and suggestions for the operation and maintenance fees of rural power grids. Public Electricity Consumption. 6, 11–13. Available from: https://www.cnki.net

[74] Zhao, M., Zhang, J., 2024. Analysis of spatio-temporal evolution of county level agricultural transformation and development and its obstacle factors in chongqing municipality. Journal of Chongqing Normal University (NaturalScience). 1, 26–36. DOI: https://doi.org/10.11721/cqnuj20240109