Role of Efficiency in Transferring Climate and Price Shocks on Farmers (Case Study: Razan Township)
Subject Areas : Agricultural Economics ResearchH. Haji Mirza 1 , Reza Shakeri 2 *
1 - Master of Agricultural Economics, University of Tehran.
2 - Ph.D. Student in Agricultural Economics, University of Tehran
Keywords: Efficiency, Data Envelopment Analysis, Positive Mathematical Programming,
Abstract :
The purpose of this study was to investigate the role of efficiency in the transmission of climate and price shocks on farmers' behavior. The hypothesis of this study is that efficient farmers in the agricultural sector are more resilient and less vulnerable to climate and price shocks. In order to test this hypothesis, data envelopment analysis approach and positive math planning model were used. Data needed for this purpose were collected from the Agricultural Jihad questionnaires in Razan township, north of Hamedan province. The findings indicate that, due to the effects of climate change, farmers' groups are less effective than inefficient farmers and have more resistance. Also, farmers are less effective than price changes, which reflect the stable situation of this group of farmers in relation to these shocks. Therefore, it can be inferred that moving towards a productive boundary can be a means to reduce the impact of climatic hazards, markets and fluctuations in agricultural production in the studied area.
Agh, M. Joolaie, R. Keramatzade, A. & Shirani Bidabadi, F. (2016). Determining the cropping pattern with emphesize on reducing fertilizer and water consumption policies in Mazandaran province (Case study: Behshahr county). Journal of Soil Management and Sustainable Production, 5(3), 247-259. (In Persian).
- Alene, A.D. & Zeller, M. (2005). Technology adoption and farmer efficiency in multiple crops production in eastern Ethiopia: a comparison of parametric and nonparametric distance functions. Agricultural Economics, 6, 5–17.
- Asadi Zarch, M. (2017). Analyzing climate change effects on drought occurrence in Yazd province, Iran. Desert Management, 5(9), 74-90. (In Persian).
- Asadi Zarch, M. A. Sivakumar, B. & Sharma, A. (2015). Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI). Journal of Hydrology, 526, 183–195.
- Bakhshi, M., Peykani, G. (2012). Simulation of Direct Payment Policy in Agronomy Subsector (Application of PMP & ME Techniques). Iranian Journal of Agricultural Economics and Development Research, 42-2(4), 501-511. (In Persian).
- Charnes, A. Cooper, W.W. & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research. 2, 429–444.
- Cortignani, R. & Dono, G. (2015). Simulation of the impact of greening measures in an agricultural area of the southern Italy. Land Use Policy, 48,525-533.
- Cortignani, R. & Severini, S. (2009). Modeling farm-level adoption of deficit irrigation using Positive Mathematical Programming. Agricultural Water Management, 96(12), 1785-1791.
- Fragoso, R. Marques, C. Lucas, M.R. Martins, M.D.B. & Jorge, R. (2011). The economic effects of common agricultural policy on Mediterranean montado/dehesa ecosystem. Journal of Policy Modeling, 33(2), pp.311-327.
- Gillis, M. Perkins, D. H. Roemer, M. & Snodgrass, D. R. (1996). Economics of Development. New York: W, W.
- Haji Mirza, H. (2018). Determining the pattern of optimal economic cultivation for Damavand agricultural subdivision Master's thesis. Faculty of Economics and Agricultural Development, University of Tehran. (In Persian).
- Henry de Frahan, B. Buysse, J. Polomé, P. Fernagut, B. Harmignie, O. Lauwers, L. Van Huylenbroeck, G. & Van Meensel, J. (2005). Positive Mathematical Programming for Agricultural and Environmental Policy Analysis: Review and Practice. In: A. Weintraub, T. Bjorndal, R. Epstein and C. Romero (Eds.), Management of Natural Resources: A Handbook of Operations Research Models, Algorithms and Implementations.
- Hosseinpour Talebi, S. (2017). Economic study of rice cultivation pattern in Mazandaran province with emphasis on the development of ratoon cultivation, application of positive mathematical planning model (case study of Amol city). Master Thesis in Agricultural Economics. Campus of Agriculture and Natural Resources, University of Tehran. (In Persian).
- Jahangirpour, D. Peikani, G. Hoseini, S. & Rafee, H. (2015). Effect of Elimination of Energy Subsidies on Agricultural Crops; the Use of Positive Mathematical Programming (PMP) (Case Study; Maharlu Basin-Bakhtegan). Agricultural Economics, 9(3), 63-84. (In Persian).
- Jamshidi, O. Asadi, A. & Kalantari, K. (2018). Climate Change Adaptation Strategies for Smallholder Farmers of Hamedan Province. Iranian Agricultural Extension and Education Journal, 13(2), 109-130. (In Persian).
- Khaleghi, S. Bazazan, F. & Madani, S. (2015). The Effects of Climate Change on Agricultural Production and Iranian Economy. Agricultural Economics Research, 7(25), 113-135. (In Persian)
- Li, X. Takahashi, T. Suzuki, N. & Kaiser, H. M. (2011). The impact of climate change on maize yields in the United States and China. Agricultural Systems, 104(4), 348-353.
- Mohsen Pour, R. Zibaei, M. (2010). Assessing the Consequences of Drought at Farm Level: a Case Study of Marvdasht Region. Journal of Water and Soil Science; 14 (52) :49-62. (In Persian).
- Mohseni, A. Zibaei, M. (2009). Analysing Consequences of Increasing Acreage of Colza in Namdan Plain of Fars Province: An Application of Positive Mathematical Programming. Journal of Water and Soil Science; 13 (47) :773-784. (In Persian).
- Mousavi, S. N. Gharghani, F. (2012). Assessing Policies of Irrigation for Groundwater by Positive Mathematical Programming (PMP) Case Study: Eghlid. Quarterly Journal Economic Research. 11 (4) :65-82. (In Persian).
- Neto Luiz, E., & Lins Marcos, P.E. (2004). Neural data envelopment analysis: A simulation, International Journal of Industrial Engineering, 11(1), 14-24.
- Nouri Naeini, M. Salah Manesh, A. (1994). Determining the shadow price of resources in the agricultural sector (case study of Khorasan villages. Journal of Economic Research (Tahghighat- E- Eghtesadi), 31(48(.(In Persian).
- Paris, Q. & Howitt, R.E. (1998). An Analysis of Ill-Posed Production Problems Using Maximum Entropy. American Journal of Agricultural Economics, 80(1):124-138.
- Pishbahar, A., Khoda bakhshi, S. (2014). Effects of Elimination Subsidies of Agricultural Inputs on Cropping Pattern in Varamin Region. Agricultural Economics Research, 6(22), 53-68. (In Persian).
- Plan and Budget Organization of the Islamic Republic of Iran, Deputy for Economic Affairs and Program and Budget Coordination (Secretariat of the Resistance Economy Command Headquarters). (2018). Water and resistance economics. Eleventh Biennial Conference on Agricultural Economics of Iran. (In Persian).
- Serrat-Capdevila, A. Valdés, J. B. Pérez, J. G. Baird, K. Mata, L. J. & Maddock III, T. (2007). Modeling climate change impacts–and uncertainty–on the hydrology of a riparian system: The San Pedro Basin (Arizona/Sonora). Journal of Hydrology, 347(1-2), 48-66.
- Shirmahi, S. Peykani, G. Mortazavi, S. & Zamani, O. (2014). Evaluating the Effect of Removing of Chemical Fertilizers Subsidy on the Cropping Pattern in Rey County. Agricultural Economics Research, 6(21), 155-176. (In Persian).
- Stern, N. (2007). The economics of climate change: The stern review. Cambridge University Press: Cambridge and New York.
- Thiam, A., Bravo-Ureta, B.E., & Rivas, T.E., (2001). Technical efficiency in developing country agriculture: a Meta-analysis. Agricultural Economics. 25, 235–243.
- Wadud, A. & White, B. (2000). Farm household efficiency in Bangladesh: a comparison of stochastic frontier and DEA methods. Applied Economics, 32, 1665–1673.
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