Evaluation the technical efficiency inequality of the agriculture sector of Iran's provinces with emphasis on the role of climatic variable

Document Type : Research Paper

Authors

1 Professor, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

2 Ms student, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.

3 Professor, Department of Agricultural Economics, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.

Abstract

Introduction: Considering the importance of improving efficiency in improving the productivity of production factors, it is necessary to measure the efficiency of the agricultural sector in order to make appropriate policies in this sector, t
Materials and methods: The purpose of the present study is to measure and analyze efficiency and inequality in the agricultural sector of Iran's provinces, considering the role of climatic variables. The required data for the period of 2011-2018 related to all the provinces of the country were collected in the form of a library from the Iranian Statistics Center. For this purpose, the Super-SBM method was used under an exogenous variable for external environmental factors (rainfall).In addition, by using the Gini coefficient, regional differences in the efficiency of the agricultural sector of different provinces of Iran were investigated during the study period.
Results and discussion: The results of the research showed that the average technical efficiency of the country's provinces is 0.45. the technical efficiency of the agricultural sector is not in a favorable condition in most of the provinces of the country And there is a extreme inequality (Gini coefficient 0.41) in most regions of the country in terms of efficiency distribution between provinces. In addition, the inequality of the efficiency of the agricultural sector in the provinces of the country has been increasing during the period of 2011-2018.
Suggestion: Considering the low efficiency and its unequal distribution in different provinces and regions of the country, it is suggested to take necessary measures to improve efficiency, such as developing new technologies, expanding promotional activities, and reducing the use of harmful inputs. Also, with a more appropriate distribution of facilities and credits, the necessary ground can be provided to improve the efficiency of less privileged provinces.

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Main Subjects

References

Ahsan, F., Chandio, A. A., and Fang, W. 2020. Climate change impacts on cereal crops production in Pakistan: evidence from cointegration analysis. International Journal of Climate Change Strategies and Management. 12(2), 257-269.
Alboghdady, M., and El-Hendawy, S. E. 2016. Economic impacts of climate change and variability on agricultural production in the Middle East and North Africa region. International Journal of Climate Change Strategies and Management. 8: 463-472.
Alibakhshi, H., Dourandish, A., and Sabouhi, S. M. 2020. Investigating the effects of climate change on agricultural market in Semi-arid regions. Journal of Agricultural Economics and Development. 34: 127–48. (In Persian)
Dagum, C.1998. A new approach to the decomposition of the Gini income inequality ratio. In Income Inequality, Poverty, and Economic Welfare, Springer, 47–63.
Elasha, B. O. 2010. Mapping of climate change threats and human development impacts in the Arab region. United Nations development program, Arab human development report (AHDR), Research Paper Series, 51 pp.
Emami Meybodi, A and Mohammadi, A. 2017. Measuring efficiency and productivity in Iran’s natural gas refineries. Financial Economics 9: 61–82. (In Persian)
Guo, Y., Tong, L., and Mei, L. 2021. Evaluation and influencing factors of agricultural eco-efficiency in Jilin agricultural production zone based on Super-SBM and panel regression methods. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun. 102-130.
Huang, Y., 2021. A study on the effects of regional differences on agricultural water resource utilization efficiency using super-efficiency SBM Model. Scientific Reports 11(1): 1–11.
Intergovernmental Panel on Climate Change (IPCC). 2013. Working group 1, fifth assessment report on climate change 2013: The physical science basis. Geneva, Switzerland.
Iran Meteorological Organization. 2021. https://www.irimo.ir.
kashi, F., Ekabri Tafti, M., Mousavi Jahormi, Y., and Khosrovinejad, A. 2016. Calculating the social cost of carbon dioxide emissions by different provinces in Iran. Energy Planning and Policy Studies, 2(2):77-110. (In Persian)
Khodadadi, S., Pahlavani, M., and Hosseinzadeh, R. 2021. The effect of changing the industrial structure on carbon dioxide emissions in the provinces of Iran: Spatial econometric approach. Environmental Science Quarterly. 20(1):221-236. (In Persian)
Kuang, B., Xinhai L., Min Zh and Danling Ch. 2020. Provincial cultivated land use efficiency in China: Empirical analysis based on the SBM-DEA model with carbon cmissions considered. Technological Forecasting and Social Change 151: 119874.
Li, H., and Jin-feng Sh. 2014. Energy efficiency analysis on Chinese industrial sectors: an improved Super-SBM model with undesirable outputs. Journal of Cleaner Production, 65: 97–107.
Ministry of Energy. 2020. https://pep.moe.gov.ir.
National Climate Change Office of Iran, NCCOI. 2020. Third national communication to United Nations framework convention on climate change (UNFCCC). Department of Environment.
Peron, S., Yavari, Gh and Rezazadeh, M. 2019. Predicting the effect of climate change on vegetable production and yield in Hormozgan province (Case study: onions and tomatoes). Journal of Plant Production. 26: 177–89.
Pishbahar, E., Darparnian, S. and Ghahremanzadeh, M. 2014. The effects of climate change on grain corn yield in Iran: the application of spatial econometric approach with panel data. Agricultural Economics, 7(2): 106-83. (In Persian)
Sahoo, B., Mikulas L., and Mahlberg. B. 2011. Alternative measures of environmental technology structure in DEA: An application. European Journal of Operational Research .215(3): 750–62.
Sani, F., Dashti, Gh., Majnooni, A and Hosseinzad. J. 2020. The economic impacts of climate change and water resources management scenarios on agronomy subsector: using risk-based hydro-economic model. Journal of Agricultural Economics and Development.34: 483–501. (In Persian)
Shahraki, J., Sabouhi, M. and Yaghoubi, M. 2016. Analysis of the effects of climate change on wheat production with the stochastic production function approach. Natural Environment Hazards. 6(11): 69-84. (In Persian)
Shi, Zh. 2020. Climate change impacts on agricultural production and crop disaster area in china. International Journal of Environmental Research and Public Health. 17(13): 4792.
Statistical Centre of Iran. 2021. https://www.amar.org.ir.
Tone, Ka. 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3): 498–509.
Zarei, N., Dorandish, A., AliBakshi, H and Sabouhi, M. 2022. The effect of climate change on the yield of major cereals in Iran. Agricultural Economics, 16(2): 27-46. (In Persian)
Zhou, Y. 2013. Environmental efficiency analysis of power industry in china based on an entropy SBM model. Energy Policy.57: 68–75.
Zhu, Y., and Huo, C. 2022. The impact of agricultural production efficiency on agricultural carbon emissions in China. Energies. 15(12): 4464.  

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