Investigating The Role of Risk Grouping in Analyzing The Effects of Government Policies on The Cultivation Pattern of Nahavand And Bahar in Hamedan Province

Document Type : Research Paper

Authors

1 MSc. Student, Department of Agricultural Economics, Faculty of Agricultural Economics and Development, University of Tehran. Karaj. Iran

2 Assistant Professor, Department of Agricultural Economics and Development, University of Tehran, Karaj, Iran

3 Department of Agricultural Economics, Faculty of Agricultural Economics and Development,University of Tehran, Karaj. Iran

Abstract

Due to problems such as high risk, water resources constraints, environmental problems and low technology levels in the agricultural sector, policy-making in this sector requires major revision. according to this, accordingly the main purpose of this research is to analyze the impact of policies and factors such as reducing water resources, reducing the use of fertilizer and developing mechanization on the farming model of Hamedan province, taking into account risk conditions and using a positive math planning approach. Based on the coefficient of variation of the cities, Nahavand and Bahar were selected as the Low risk and riskiest city. According to the results, with decreasing of water resources, barley cultivation in Nahavand and alfalfa remained constant in the Bahar city and wheat and corn in Bahar city and alfalfa in Nahavand were eliminated from the crop pattern. Water sensitivity analysis showed that by saving 55 percent of water consumption, the production level, and current profit could be reached. Due to the policy of reducing fertilizer use in the Bahar city, the level of fixed hay and wheat, maize and barley are eliminated from the cultivar model, but in Nahvand it does not change the cultivar pattern, which showed that the sensitivity analysis of fertilizer limits showed a decrease of 40% The use of fertilizer, the pattern of cultivation will not change. In the Bahar, with the policy of mechanization development, the level of cultivation of wheat and maize, the increase in barley and alfalfa and potatoes is constant, but in Nahavand, alfalfa, wheat, and barley, maize is increasing, and potatoes remain constant like Bahar city. Also, by applying this scenario, the total profit in the Bahar city has increased and declined in the city of Nahavand. Therefore, the Nahavand area needs less mechanization development. The results of this study showed that the high risk of production in each region leads to risk of policy implementation. This means that significant changes in yield and, consequently, greater risk will make farmers more sensitive to changing the current situation and imposing constraints and implementing the policies expressed.

Keywords

References

  1. Aghapour Sabbaghi, M., Yazdani, S., Salami, H., & Peykani, Gh. (2012). Model of Optimal and Sustainable use of Water Resources in Agricultural Sector (case study of Hamedan- Kabodarahang Plain). Iranian Journal of Agricultural Economics and Development. 42(2), 313-322.
  2. Agh, M., Julayi, R., Karamatzadeh, A., & Shirani Beid Abadi, F. (2016). Determination of cropping pattern with emphasis on fertilizer and water use reduction policy in Mazandaran province (Case study: Behshahr city). Soil management and sustainable production. 5(3), 247-259
  3. Agricultural Organization of Hamedan Province. (2016).  http://hamedan.agri-jahad.ir.
  4. Arjmandi, A., & Mehrabi Bashrabadi, H. (2014). Consideration of changes in the pattern of cultivation of crops in Iran during the period 1983-84 to 2009-2010. Agricultural Economics. 7(4), 87-104.
  5. Bagheri, N. Mo'azen,  A.(2008). Optimization Strategy of Agricultural Mechanization Development in Iran. 5th National Congress of Agricultural Machinery and Mechanization.
  6. Bakhshi, M., & Peykani, Gh. 2012. Simulation of direct support policy in the subsection of agriculture (application of the Positive Planning Approach and Maximum Entropy). Iranian Journal of Agricultural Economics and Development. 42(2), 501-511.
  7. Bakhshude, M., & Akbari, A. (2014). Production economy and its application in agriculture. (4th ed.). University of Bahonar Kerman Publications. Kerman. Iran
  8. Bani Asadi, M., & Varmazyari, H. (2015). Investigating factors affecting labor productivity, income distribution and poverty in rural areas of Iran. Quarterly Journal of Village and Development, Institute for Planning Research, Agricultural Economics and Rural Development, Ministry of Jihad-e-Agriculture, 17 (4), 1-23.
  9. Cortignani, R., & Severini, S. (2009). Modeling farm-level adoption of deficit irrigation
  10. 10. Cui, T., Zhang ,D., Yang, L., & Gao, N. (2012). Design and experiment of collocated-copying and semi-low-height planting-unit for corn precision seeder. Transactions of the Chinese Society of Agricultural Engineering. 28(1),18-23.
  11. 11. Das, P.S., & Kar, A .(1995). Decision making under uncertainty: Bayesian approach: A case study of Aman paddy in Midnapore district” , Indian Journal of Agricultural Economics, 50(1), 59-68.
  12. 12. Eskandari Dameneh, H., Nowruzi, H ., Khosravi, H ., Rafiee, H ., & Taheri, A. (2014).Feasibility study of low crop plan implementation in order to revive Jazz Morian wetland, case study of Jiroft city. Journal of Rural Development Strategies.2(3), 287-298.        
  13. 13. Frankfurter, G.M., Philips. H.E., & Seagle, J.P. (1971). Portfolio selection: The effect of uncertainty means, variances, and covariances. Journal of Financial and Quantilative Analisis, 6: 1251-62.
  14. 14. 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.
  15. 15. Howitt,  R.E.,  Medellin-Azuara,  J., MacEwan,  D., & Lund,  R. (2012). Calibrating disaggregate economic models of agricultural production and water management. Science of the Environmental Modeling and Software, 38(2), 244-258.
  16. 16. Howitt R.E. (2005). PMP based production models- development and integration. The future of rural Europe in the global agriculture food system, Denmark, 23-21.
  17. 17. Howitt,  R.E., Medellin-Azuara, J., & MacEwan, D. (2009). Estimating the economic impacts of agricultural yield related changes for California. Final Paper, a Paper from California Climate Change Center, 29P
  18. 18. Jamshidi, A., Timuri, M., Hazeri, M., & Rusta, M. (2010). Effective Factors on Participation of Farmers in Implementation of Land Consolidation Plan in Ilam Province: A Case Study of Shirvan and Chardavol, Rural Development Quarterly, 12 (1), 109-127.
  19. 19. Kasnakoglu, H., & Bauer, S. (1998). Concept and Application of an Agricultural Sector Model for Policy Analysis in Turkey. In: Agricultural Sector Modeling. S. Bauer and W.Henrichsmeyer (Eds), Vauk Verlag: Kiel.
  20. 20. Kim, C. (2001). Developing Policies for Agriculture and the Environment, Korea Rurul
  21. Economic Institute, Working Paper.
  22. 21. Lin, W., Dean, G., & Moore, C. (1974). An empirical test of utility versus profit maximization in agricultural production American Journal of Agricultural Economics, 56(3), 497-508.
  23. 22. Parham, H., Jafarzadeh, N., Dehghan, s., & Kian Ersi, F. (2008). Changes in nitrogen and phosphorus concentration and some physical parameters of soil and chemical in the lake behind the Karkhe dam and determination of its biolan. Journal of Science, Shahid Chamran University, 17 (2): 117-125.
  24. 23. Parhizkari, A., & Sabouhi, M. (2014). Economic Analysis of the Effects of Technology Development and Mechanization on Agricultural Production in Qazvin Province. Agricultural Economics Research. 5(4), 1-23.
  25. 24. Parikh, A. (1966) State-wise Growth Rate in Agricultural Output: An Econometric Analysis. Artha Vijnana, 8(1): 1-52
  26. 25. Paris, Quirino. (1979). Revenue and cost uncertainty, generalized mean-variance, and linear complementarity problem .Am. Agr. Econ., 61(2), 268-275.
  27. 26. Pishbahar, E., & Khodabakhshi, S. (2015). Effects of eliminating subsidies on agricultural inputs on cropping pattern in Hamadan province.Iranian Journal of Agriculture Economics and Development Research, 46(3), 551-558.
  28. 27. Shini Dashtghel, A., Noori, M., & Minaei,S.  (2013). Study of transmission and distribution efficiencies and providing solutions to reduce water losses in the irrigation network of Dez (Case study of Sabili channels and (E (4)), The fourth national conference on irrigation networks management and Drainage, Ahvaz, Shahid Chamran University of Ahvaz.
  29. 28. Timmer, C.P. (1997) Farmers and Markets: The Political Economy of New Paradigms. American Journal of Agricultural Economics, 79(1), 621-627.
  30. 29. Torkamani, J. (1996). Decision criteria in risk analysis: An application of stochastic dominance with respect to a function. 1-18.
  31. using Positive Mathematical Programming. Agricultural Water Management, 96(2), 1785-1791.
  32. 30. Weersink, A., Livernois, J.,& Shogren, J.F., & Shortle, J.S. (1998). Economic Instruments and Environmental Policy in agriculture. J. Can. Public Policy. 24(3), 309-327.
  33. 31. Yang, S.L., Milliman, J.D.,  Li, P., & Xu, K. (2011). 50000 dams later: erosion of the Yangtze River and its delta. Glob Planet Change, 75, 14–20.
Iranian Journal of Agricultural Economics and Development Research
Volume 49, Issue 4
November 2018
Pages 607-619

Files

Share

How to cite

Statistics