The Relationship Between Agroeconomic Expansion and Ecosystem Quality Based on a Regression Model
Downloads
Objective: To reveal the intrinsic relationship between agricultural economic growth and ecological environment quality in the northwest region, the study took Shaanxi, Qinghai, and Gansu as the research areas and conducted an empirical analysis of the panel data of the three provinces from 2020 to 2023. Method: This study utilizes the Autoregressive Integrated Moving Average model to analyze the dynamic trends of the agricultural economy, handles the cross-sectional heterogeneity of the data through the bidirectional fixed effects model, and addresses spatial dependence using the Spatial Durbin model. Result: The development of the agricultural economy in the northwest region has a positive effect on the quality of the ecological environment, and the degree of this effect is influenced by factors such as time and geographic location. However, the extensive economic development model will instead reduce the quality of the ecological environment. Innovativeness: By focusing precisely on the characteristics of arid and semi-arid regions, the reliability of the conclusion has been enhanced through the collaborative analysis of multiple models. This has verified the bidirectional influence relationship between agricultural economic development and ecological environment quality in the northwest region, providing empirical evidence for the coordinated development of the ecological economy in this type of region.
Downloads
[1] Eyitayo Raji, Tochukwu Ignatius Ijomah, & Osemeike Gloria Eyieyien. (2024). Integrating technology, market strategies, and strategic management in agricultural economics for enhanced productivity. International Journal of Management & Entrepreneurship Research, 6(7), 2112–2124. doi:10.51594/ijmer.v6i7.1260.
[2] Olawale Adisa, Bamidele Segun Ilugbusi, Odunayo Adewunmi Adelekan, Onyeka Franca Asuzu, & Ndubuisi Leonard Ndubuisi. (2024). A comprehensive review of redefining agricultural economics for sustainable development: Overcoming challenges and seizing opportunities in a changing world. World Journal of Advanced Research and Reviews, 21(1), 2329–1241. doi:10.30574/wjarr.2024.21.1.0322.
[3] Wuepper, D., Wiebecke, I., Meier, L., Vogelsanger, S., Bramato, S., Fürholz, A., & Finger, R. (2024). Agri-environmental policies from 1960 to 2022. Nature Food, 5(4), 323–331. doi:10.1038/s43016-024-00945-8.
[4] Wang, Y., Liu, Y., Feng, W., & Zeng, S. (2023). Waste Haven Transfer and Poverty-Environment Trap: Evidence from EU. Green and Low-Carbon Economy, 1(1), 41–49. doi:10.47852/bonviewglce3202668.
[5] Fatima, S., Abbas, S., Rebi, A., & Ying, Z. (2024). Sustainable forestry and environmental impacts: Assessing the economic, environmental, and social benefits of adopting sustainable agricultural practices. Ecological Frontiers, 44(6), 1119–1127. doi:10.1016/j.ecofro.2024.05.009.
[6] Wu, G., Riaz, N., & Dong, R. (2023). China’s agricultural ecological efficiency and spatial spillover effect. Environment, Development and Sustainability, 25(4), 3073–3098. doi:10.1007/s10668-022-02169-x.
[7] Wang, J., Zhou, F., Xie, A., & Shi, J. (2024). Impacts of the integral development of agriculture and tourism on agricultural eco-efficiency: a case study of two river basins in China. Environment, Development and Sustainability, 26(1), 1701–1730. doi:10.1007/s10668-022-02781-x.
[8] Sun, W., Yu, Q., Xu, C., Zhao, J., Wang, Y., & Miao, Y. (2024). Construction and optimization of ecological spatial network in typical mining cities of the Yellow River Basin: the case study of Shenmu City, Shaanxi. Ecological Processes, 13(1), 60–78. doi:10.1186/s13717-024-00539-z.
[9] Li, Y., Cheng, W., Zuo, W., & Zhang, L. (2023). Agricultural Vulnerability to Drought in China’s Agro-pastoral Ecotone: A Case Study of Yulin City, Shaanxi Province. Chinese Geographical Science, 33(5), 934–945. doi:10.1007/s11769-023-1386-5.
[10] Wang, X., Xu, Y., Wang, H., Kang, M., Hua, J., & Wang, F. Y. (2024). Region-Farm Crop Planning Through Double Deep Q-Learning Toward Sustainable Agriculture. IEEE Transactions on Computational Social Systems, 11(6), 7608–7617. doi:10.1109/TCSS.2024.3441543.
[11] Arumugam, U., & Manida, M. (2023). Agripreneurship for Sustainable Economic Development in India. ComFin Research, 11(4), 15–23. doi:10.34293/commerce.v11i4.6662.
[12] Silvestri, C., Silvestri, L., Piccarozzi, M., & Ruggieri, A. (2024). Toward a framework for selecting indicators of measuring sustainability and circular economy in the agri-food sector: a systematic literature review. International Journal of Life Cycle Assessment, 29(8), 1446–1484. doi:10.1007/s11367-022-02032-1.
[13] Maulidar, P., Fitriyani, F., Sasmita, N. R., Hardi, I., & Idroes, G. M. (2024). Exploring Indonesia’s CO2 Emissions: The Impact of Agriculture, Economic Growth, Capital and Labor. Grimsa Journal of Business and Economics Studies, 1(1), 43–55. doi:10.61975/gjbes.v1i1.22.
[14] Dong, J., Zhang, Z., Liu, B., & Zhang, X. (2023). Geographical exploration of the spatial differentiation mechanism of eco-environmental quality in northwest China from the perspective of “production-living-ecological” space. Arid Land Geography, 46(4), 515–526. doi:10.12118/j.issn.1000-6060.2022.242.
[15] Xue, B., Han, B., Li, H., Gou, X., Yang, H., Thomas, H., & Stückrad, S. (2023). Understanding ecological civilization in China: From political context to science. Ambio, 52(12), 1895–1909. doi:10.1007/s13280-023-01897-2.
[16] Liu, C., Huang, H., Melack, J. M., Tian, Y., Jiang, J., Fu, X., Cao, Z., & Wang, S. (2024). Assessing Land Degradation and Restoration in Eastern China Grasslands from 1985 to 2018 Using Multitemporal Landsat Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 19328–19342. doi:10.1109/JSTARS.2024.3483992.
[17] Li, X., Hou, B., Zhang, R., & Liu, Y. (2023). A Review of RGB Image-Based Internet of Things in Smart Agriculture. IEEE Sensors Journal, 23(20), 24107–24122. doi:10.1109/JSEN.2023.3309774.
[18] Duguma, A. L., & Bai, X. (2025). How the internet of things technology improves agricultural efficiency. Artificial Intelligence Review, 58(2), 63–88. doi:10.1007/s10462-024-11046-0.
[19] Bai, M., Li, Z., Huo, P., Wang, J., & Li, Z. (2023). Propagation characteristics from meteorological drought to agricultural drought over the Heihe River Basin, Northwest China. Journal of Arid Land, 15(5), 523–544. doi:10.1007/s40333-023-0059-7.
[20] Zhu, C. (2024). Spatial Distribution Characteristics and Influencing Factors of Geographical Indication Agricultural Products in Shaanxi Province. International Journal of Global Economics and Management, 3(1), 448–457. doi:10.62051/ijgem.v3n1.56.
[21] Qiu, Y., Liu, C., Du, L., Jiang, X., & Yuan, D. (2024). Study on the safety of recycled water irrigation in arid, semiarid and underdeveloped areas: a case study in Qinghai Province. Irrigation Science, 42(4), 769–783. doi:10.1007/s00271-024-00918-6.
[22] Liang, X., Li, J., Guo, G., Li, S., & Gong, Q. (2023). Urban water resource utilization efficiency based on SBM-undesirable–Gini coefficient–kernel density in Gansu Province, China. Environment, Development and Sustainability, 25(11), 13015–13034. doi:10.1007/s10668-022-02601-2.
[23] El-Afifi, M. I., Eladl, A. A., Sedhom, B. E., & Hassan, M. A. (2025). Enhancing EV Charging Station Integration: A Hybrid ARIMA-LSTM Forecasting and Optimization Framework. IEEE Transactions on Industry Applications, 61(3), 4924–4935. doi:10.1109/TIA.2025.3540788.
[24] Nasir, J., Aamir, M., Haq, Z. U., Khan, S., Amin, M. Y., & Naeem, M. (2023). A New Approach for Forecasting Crude Oil Prices Based on Stochastic and Deterministic Influences of LMD Using ARIMA and LSTM Models. IEEE Access, 11, 14322–14339. doi:10.1109/ACCESS.2023.3243232.
[25] Arkhangelsky, D., Imbens, G. W., Lei, L., & Luo, X. (2024). Design‐robust two‐way‐fixed‐effects regression for panel data. Quantitative Economics, 15(4), 999–1034. doi:10.3982/qe1962.
[26] Raihan, A., Tanchangya, T., Rahman, J., & Ridwan, M. (2024). The Influence of Agriculture, Renewable Energy, International Trade, and Economic Growth on India’s Environmental Sustainability. Journal of Environmental and Energy Economics, 3(1), 37–53. doi:10.56946/jeee.v3i1.324.
[27] Hardi, I., Idroes, G. M., Zulham, T., Suriani, S., & Saputra, J. (2023). Economic Growth, Agriculture, Capital Formation and Greenhouse Gas Emissions in Indonesia: FMOLS, DOLS and CCR Applications. Ekonomikalia Journal of Economics, 1(2), 82–91. doi:10.60084/eje.v1i2.109.
[28] Chandio, A. A., Gokmenoglu, K. K., Dash, D. P., Khan, I., Ahmad, F., & Jiang, Y. (2025). Exploring the energy-climate-agriculture (ECA) nexus: a roadmap toward agricultural sustainability in Asian countries. Environment, Development and Sustainability, 27(6), 12769–12795. doi:10.1007/s10668-023-04418-z.
[29] Kazungu, F. K., Muindi, E. M., & Mulinge, J. M. (2023). Overview of Sorghum (Sorghum bicolor. L), its Economic Importance, Ecological Requirements and Production Constraints in Kenya. International Journal of Plant & Soil Science, 35(1), 62–71. doi:10.9734/ijpss/2023/v35i12744.
[30] Zafeiriou, E., Azam, M., & Garefalakis, A. (2023). Exploring environmental – economic performance linkages in EU agriculture: evidence from a panel cointegration framework. Management of Environmental Quality: An International Journal, 34(2), 469–491. doi:10.1108/MEQ-06-2022-0174.
- This work (including HTML and PDF Files) is licensed under a Creative Commons Attribution 4.0 International License.
