Research article

Impact of high-standard basic farmland construction policies on agricultural eco-efficiency: Case of China

  • Received: 12 April 2022 Revised: 19 May 2022 Accepted: 25 May 2022 Published: 16 June 2022
  • JEL Codes: Q18

  • The impact of high-standard basic farmland construction policies on agricultural eco-efficiency has been extensively considered. Using the Chinese provincial panel data from 2007–2017, we first measure the level of agricultural eco-efficiency in China by employing data envelopment analysis. Then, using difference-in-difference models, we analyze the impact of high-standard basic farmland construction policies on agricultural eco-efficiency and test whether there is heterogeneity of this impact. Finally, we further explore the specific channels through which the polices of high-standard basic farmland construction affect agricultural eco-efficiency. The empirical results indicate that 1) the implementation of high-standard farmland construction policies can significantly improve agricultural eco-efficiency, 2) the heterogeneity of the impact of high-standard farmland construction policies on agricultural eco-efficiency is manifested in both regional and efficiency aspects and 3) high-standard farmland construction policies promote agricultural eco-efficiency through the interaction between the new land scale and the replanting index.

    Citation: Jinhui Zhu, Mengxin Wang, Changhong Zhang. Impact of high-standard basic farmland construction policies on agricultural eco-efficiency: Case of China[J]. National Accounting Review, 2022, 4(2): 147-166. doi: 10.3934/NAR.2022009

    Related Papers:

  • The impact of high-standard basic farmland construction policies on agricultural eco-efficiency has been extensively considered. Using the Chinese provincial panel data from 2007–2017, we first measure the level of agricultural eco-efficiency in China by employing data envelopment analysis. Then, using difference-in-difference models, we analyze the impact of high-standard basic farmland construction policies on agricultural eco-efficiency and test whether there is heterogeneity of this impact. Finally, we further explore the specific channels through which the polices of high-standard basic farmland construction affect agricultural eco-efficiency. The empirical results indicate that 1) the implementation of high-standard farmland construction policies can significantly improve agricultural eco-efficiency, 2) the heterogeneity of the impact of high-standard farmland construction policies on agricultural eco-efficiency is manifested in both regional and efficiency aspects and 3) high-standard farmland construction policies promote agricultural eco-efficiency through the interaction between the new land scale and the replanting index.



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    [1] Andersen P, Petersen NC (1993) A Procedure for Ranking Efficient Units in Data Envelopment Analysis. Manage Sci 39: 1261-1264.
    [2] Cai X, Lu Y, Wu M, et al. (2016) Does environmental regulation drive away inbound foreign direct investment? Evidence from a quasi-natural experiment in China. J of Dev Econ 123: 73-85. https://doi.org/10.1016/j.jdeveco.2016.08.003 doi: 10.1016/j.jdeveco.2016.08.003
    [3] Charnes A, Cooper WW, Seiford L, et al. (1982) A multiplicative model for efficiency analysis. Socio-Econ Plan Sci 16: 223-224. https://doi.org/10.1016/0038-0121(82)90029-5 doi: 10.1016/0038-0121(82)90029-5
    [4] Coderoni S, Esposti R (2014) Is There a Long-Term Relationship Between Agricultural GHG Emissions and Productivity Growth? A Dynamic Panel Data Approach. Environ Resour Econ 58: 273-302. https://doi.org/10.1007/s10640-013-9703-6 doi: 10.1007/s10640-013-9703-6
    [5] Coluccia B, Valente D, Fusco G, et al. (2020) Assessing agricultural eco-efficiency in Italian Regions. Ecol Indic 116. https://doi.org/10.1016/j.ecolind.2020.106483 doi: 10.1016/j.ecolind.2020.106483
    [6] Feng Y, Chen S, Xuan W, et al. (2021) Time-varying impact of U.S. financial conditions on China's inflation: a perspective of different types of events. Quant Financ Econ 5: 604-622. https://doi.org/10.3934/qfe.2021027 doi: 10.3934/qfe.2021027
    [7] Fresard L (2010) Financial Strength and Product Market Behavior: The Real Effects of Corporate Cash Holdings. J Financ 65: 1097-1122. https://doi.org/10.1111/j.1540-6261.2010.01562.x doi: 10.1111/j.1540-6261.2010.01562.x
    [8] Khatun MN, Mitra S, Sarker MNI (2021) Mobile banking during COVID-19 pandemic in Bangladesh: A novel mechanism to change and accelerate people's financial access. Green Financ 3: 253-267. https://doi.org/10.3934/gf.2021013 doi: 10.3934/gf.2021013
    [9] Konefal J, Hatanaka M, Constance DH (2019) Multi-stakeholder initiatives and the divergent construction and implementation of sustainable agriculture in the USA. Renew Agr Food Syst 34: 293-303. https://doi.org/10.1017/s1742170517000461 doi: 10.1017/s1742170517000461
    [10] Li T, Li X, Albitar K (2021a) Threshold effects of financialization on enterprise R & D innovation: A comparison research on heterogeneity. Quant Financ Econ 5: 496-515. https://doi.org/10.3934/qfe.2021022 doi: 10.3934/qfe.2021022
    [11] Li T, Liao G (2020) The Heterogeneous Impact of Financial Development on Green Total Factor Productivity. Front Energy Res 8. https://doi.org/10.3389/fenrg.2020.00029 doi: 10.3389/fenrg.2020.00029
    [12] Li T, Ma J (2021) Does digital finance benefit the income of rural residents? A case study on China. Quant Financ Econ 5: 664-688. https://doi.org/10.3934/qfe.2021030 doi: 10.3934/qfe.2021030
    [13] Li T, Zhong J, Huang ZM (2019a) Potential Dependence of Financial Cycles between Emerging and Developed Countries: Based on ARIMA-GARCH Copula Model. Emerg Mark Financ Tr 56: 1237-1250 https://doi.org/10.1080/1540496X.2019.1611559 doi: 10.1080/1540496X.2019.1611559
    [14] Li Z, Chen L, Dong H (2021b) What are bitcoin market reactions to its-related events? Int Rev Econ Financ 73: 1-10. https://doi.org/10.1016/j.iref.2020.12.020 doi: 10.1016/j.iref.2020.12.020
    [15] Li Z, Dong H, Floros C, et al. (2021c) Re-examining Bitcoin Volatility: A CAViaR-based Approach. Emerg Mark Financ Tr 58: 1320-1338. https://doi.org/10.1080/1540496X.2021.1873127 doi: 10.1080/1540496X.2021.1873127
    [16] Li Z, Huang Z, Dong H (2019b) The Influential Factors on Outward Foreign Direct Investment: Evidence from the "The Belt and Road". Emerg Mark Financ Tr 55: 3211-3226. https://doi.org/10.1080/1540496X.2019.1569512 doi: 10.1080/1540496X.2019.1569512
    [17] Li Z, Liao G, Albitar K (2020a) Does corporate environmental responsibility engagement affect firm value? The mediating role of corporate innovation. Bus Strateg Environ 29. https://doi.org/10.1002/bse.2416 doi: 10.1002/bse.2416
    [18] Li Z, Wang Y, Huang Z (2020b) Risk Connectedness Heterogeneity in the Cryptocurrency Markets. Front Phys 8. https://doi.org/10.3389/fphy.2020.00243 doi: 10.3389/fphy.2020.00243
    [19] Li Z, Zhong J (2019) Impact of economic policy uncertainty shocks on China's financial conditions. Physica A 521: 626-634. https://doi.org/10.1016/j.physa.2019.01.100 doi: 10.1016/j.physa.2019.01.100
    [20] Liao J, Yu C, Feng Z, et al. (2021) Spatial differentiation characteristics and driving factors of agricultural eco-efficiency in Chinese provinces from the perspective of ecosystem services. J Clean Prod 288. https://doi.org/10.1016/j.jclepro.2020.125466 doi: 10.1016/j.jclepro.2020.125466
    [21] Lin B, Li X (2011) The effect of carbon tax on per capita CO2 emissions. Energ Policy 39: 5137-5146. https://doi.org/10.1016/j.enpol.2011.05.050 doi: 10.1016/j.enpol.2011.05.050
    [22] Liu Y, Fang F, Li Y (2014) Key issues of land use in China and implications for policy making. Land Use Policy 40: 6-12. https://doi.org/10.1016/j.landusepol.2013.03.013 doi: 10.1016/j.landusepol.2013.03.013
    [23] Liu Y, Li Z, Xu M (2020a) The Influential Factors of Financial Cycle Spillover: Evidence from China. Emerg Mark Financ Tr 56: 1336-1350. https://doi.org/10.1080/1540496X.2019.1658076 doi: 10.1080/1540496X.2019.1658076
    [24] Liu Y, Zou L, Wang Y (2020b) Spatial-temporal characteristics and influencing factors of agricultural eco-efficiency in China in recent 40 years. Land Use Policy 97. https://doi.org/10.1016/j.landusepol.2020.104794 doi: 10.1016/j.landusepol.2020.104794
    [25] Maxime D, Marcotte M, Arcand Y (2006) Development of eco-efficiency indicators for the Canadian food and beverage industry. J Clean Prod 14: 636-648. https://doi.org/10.1016/j.jclepro.2005.07.015 doi: 10.1016/j.jclepro.2005.07.015
    [26] Mueller K, Holmes A, Deurer M, et al. (2015) Eco-efficiency as a sustainability measure for kiwifruit production in New Zealand. J Clean Prod 106: 333-342. https://doi.org/10.1016/j.jclepro.2014.07.049 doi: 10.1016/j.jclepro.2014.07.049
    [27] Pan D, Ying R (2013) Agricultural eco-efficiency evaluation in China based on SBM model. J Ecol 33: 3837-3845. https://doi.org/10.5846/stxb201207080953 doi: 10.5846/stxb201207080953
    [28] Pan D (2013) A meta-regression analysis of agricultural total factor productivity in China. J Food Agric Environ 11: 1271-1276.
    [29] Pastorok RA, Akcakaya HR, Regan H, et al. (2003) Role of ecological modeling in risk assessment. Hum Ecol Risk Assess 9: 939-972. https://doi.org/10.1080/713610017 doi: 10.1080/713610017
    [30] Picazo-Tadeo AJ, Gomez-Limon JA, Reig-Martinez E (2011) Assessing farming eco-efficiency: A Data Envelopment Analysis approach. J Environ Manage 92: 1154-1164. https://doi.org/10.1016/j.jenvman.2010.11.025 doi: 10.1016/j.jenvman.2010.11.025
    [31] Place F, Barrett CB, Freeman HA, et al. (2003) Prospects for integrated soil fertility management using organic and inorganic inputs: evidence from smallholder African agricultural systems. Food Policy 28: 365-378. https://doi.org/10.1016/j.foodpol.2003.08.009 doi: 10.1016/j.foodpol.2003.08.009
    [32] Qian F, Wang W, Zhang J, et al. (2016) Research on Index System Construction of High-standard Basic Farmland. In 2016 2nd International Conference on Education, Social Science, Management and Sports, Atlantis Press, 60-63. https://doi.org/10.2991/icessms-16.2017.14
    [33] Qiao J, Wu D, He Y (2017) Confirm high standard basic farmland area: a case study in Huaihua city. Adv Eng Res 129: 702-705. https://doi.org/10.2991/iceesd-17.2017.128 doi: 10.2991/iceesd-17.2017.128
    [34] Reith CC, Guidry MJ (2003) Eco-efficiency analysis of an agricultural research complex. J Environ Manage 68: 219-229. https://doi.org/10.1016/s0301-4797(02)00161-5 doi: 10.1016/s0301-4797(02)00161-5
    [35] Simon K, Soni A, Cawley J (2017) The Impact of Health Insurance on Preventive Care and Health Behaviors: Evidence from the First Two Years of the ACA Medicaid Expansions. J Policy Anal Manage 36: 390-417. https://doi.org/10.1002/pam.21972 doi: 10.1002/pam.21972
    [36] Song W, Wu K, Zhao H, et al. (2019) Arrangement of High-standard Basic Farmland Construction Based on Village-region Cultivated Land Quality Uniformity. Chinese Geogr Sci 29: 325-340. https://doi.org/10.1007/s11769-018-1011-1 doi: 10.1007/s11769-018-1011-1
    [37] Tang X, Pan Y, Liu Y (2017) Analysis and demonstration of investment implementation model and paths for China's cultivated land consolidation. Appl Geogr 82: 24-34. https://doi.org/10.1016/j.apgeog.2017.03.002 doi: 10.1016/j.apgeog.2017.03.002
    [38] Tang X, Pan Y, Liu Y, et al. (2014) Layout and mode partition of high-standard basic farmland construction at county level based on four-quadrant method. J Agric Eng 30: 238-246.
    [39] Toma P, Miglietta PP, Zurlini G, et al. (2017) A non-parametric bootstrap-data envelopment analysis approach for environmental policy planning and management of agricultural efficiency in EU countries. Ecol Indic 83: 132-143. https://doi.org/10.1016/j.ecolind.2017.07.049 doi: 10.1016/j.ecolind.2017.07.049
    [40] Tone K (2001) A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res 130: 498-509. https://doi.org/10.1016/S0377-2217(99)00407-5 doi: 10.1016/S0377-2217(99)00407-5
    [41] Wing C, Simon K, Bello-Gomez RA (2018) Designing Difference in Difference Studies: Best Practices for Public Health Policy Research. Annu Rev Publ Health 39:453-469. https://doi.org/10.1146/annurev-publhealth-040617-013507 doi: 10.1146/annurev-publhealth-040617-013507
    [42] Zhang B, Bi J, Fan Z, et al. (2008) Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach. Ecol Econ 68: 306-316. https://doi.org/10.1016/j.ecolecon.2008.03.009 doi: 10.1016/j.ecolecon.2008.03.009
    [43] Zhong J, Li T (2020) Impact of Financial Development and Its Spatial Spillover Effect on Green Total Factor Productivity: Evidence from 30 Provinces in China. Math Probl Eng 2020. https://doi.org/10.1155/2020/5741387 doi: 10.1155/2020/5741387
    [44] Zhu J, Huang Z, Li Z, et al. (2021) The Impact of Urbanization on Energy Intensity—An Empirical Study on OECD Countries. Green Financ 3: 508-526. https://doi.org/10.3934/gf.2021024 doi: 10.3934/gf.2021024
    [45] Zou L, Liu Y, Wang Y, et al. (2020) Assessment and analysis of agricultural non-point source pollution loads in China: 1978-2017. J Environ Manage 263. https://doi.org/10.1016/j.jenvman.2020.110400 doi: 10.1016/j.jenvman.2020.110400
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