Agricultural Economics and Development

Agricultural Economics and Development

Determining the Optimal Cropping Pattern with Emphasis on Income Risk: A Case study of Roshanabad Subdistrict of Gorgan County in Iran

Document Type : Original Article

Authors
M. Aminravan 1
S.M. Mojaverian 2
S.-A. Hosseini-Yekani 3
R. Joolaie 4
D. Viaggi 5
1 PhD Student in Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
2 . Associate Professor, Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
3 Associate Professor, Department of Agricultural Economics, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
4 . Associate Professor, Department of Agricultural Economics, Gorgan Agricultural Sciences and Natural Resources University, Gorgan, Iran.
5 Associate Professor, Department of Agricultural Economics, University of Bologna, Italy.
10.30490/aead.2022.329875.1150
Abstract
The changing environment of agricultural activities face farmers to a variety of risks and uncertainties that influence the decisions of production, sustainability and profitability of these activities. Income risk as a result of both price and crop yield risks is one of the most important risks for farmers. In this study, optimal cropping pattern of crops as a tool for managing income risk was determined using diversification-consistent Data Envelopment Analysis (DEA) model based on directional-distance measures. For this purpose, the expected profit and the conditional value at risk at different probability levels were used as return and risk measures. The results showed that in the optimal cropping pattern, the share of wheat decreased and the share of more profitable crops such as medium rice grain with high-quality increased; in addition, crops such as soybeans and cotton with less profit and more risk were eliminated from the optimal cropping pattern. Based on the study results, it is suggested to use tools such as income insurance, compensating payments and a revenue stabilization fund for the development of rice cultivation in the region.
Keywords
: Income Risk
Cropping Pattern
DEA Model
Gorgan (County)
  1. Agh, M., Joolaei, R., Keramatzadeh, A. and Shirani Bidabadi, F. (2016). Determining the cropping pattern with emphasis 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. (Persian)
  2. Akbari, N., Esmaeilpour, A. and Sarkhoshsara, A. (2013). Determination of crop pattern under risk conditions (case study of Mahabad). Second National Conference on Sustainable Agricultural Development and Healthy Environment, Hamedan, Iran. (Persian)
  3. Avazyar, M.R., Ahmadpour Borazjani, M. and Ziaee, S. (2018). Determining the optimal crop pattern with an emphasis on increasing the irrigation efficiency in lands of Mollasadra dam in Fars province. Scientific Journal Management System, 11(36): 21-32. (Persian)
  4. Badi-Barzin, H., Salarpour, M., Azimi, A. and Zamani, Z. (2014). Determination of optimal pattern of cultivation in uncertain conditions (case study of Golestan province, Fazelabad). The First International Conference on Political Epic (With an Approach to the Middle East Developments) and Economic Epic (With an Approach to Management and Accounting). Islamic Azad University, Rudehen, Iran. (Persian)
  5. Bielza, M., Conte, C.G., Dittmann, C., Gallego Pinilla, F.J. and Stroblmair, J. (2008). Agricultural insurance schemes. Publications Office of the European Union.
  6. Branda, M. (2015). Diversification-consistent data envelopment analysis based on directional-distance measures. Omega, 52: 65-76.
  7. Charnes, A., Cooper, W.W. and Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6): 429-444.
  8. Chung, Y.H., Färe, R. and Grosskopf, S. (1997). Productivity and undesirable outputs: a directional distance function approach. Journal of Environmental Management, 51(3): 229-240.
  9. Emadzadeh, M., Zahedi Keyvan, M. and Aghaei, K. (2009). Determination of cultivation optimum pattern in farms with attention to risk and uncertainly conditions: an approach of interval linear programming. Journal of Agricultural Economics and Development, 17(67): 73-92. (Persian)
  10. Fallahi, E., Khalilian, S. and Ahmadian, M. (2013). Optimizing cropping pattern with emphasis on water resource restrictions: a case study of Seidan-Farough plain, Marvdasht township. Journal of Agricultural Economics Research, 5(2): 91-115. (Persian)
  11. Filippi, C., Mansini, R. and Stevanato, E. (2017). Mixed integer linear programming models for optimal crop selection. Journal of Computers and Operations Research, 81: 26-39.
  12. Ghorbanian, E., Zibaei, M., Ghorbani, M. and Kohansal, M.R. (2013). Determining the optimal cropping pattern due to limited groundwater resources in Kavar plain. Journal of Agricultural Economics and Development, 27(1): 1-7. (Persian)
  13. Hao, L., Su, X. and Singh, V.P. (2018). Cropping pattern optimization considering uncertainty of water availability and water saving potential. International Journal of Agricultural and Biological Engineering, 11(1): 178-186.
  14. Hazell, P.B.R. (1982). Application of risk preference estimates in firm-household and agricultural sector models. American Journal of Agricultural Economics, 64(2): 384-390.
  15. Heydari Kamalabadi, R., Hosseini Yekani, S.A., Mojaverian, M. and Nikouei, A. (2017). Measuring the future risk of crops yield using CVaR method in Zayanderud agricultural system. Journal of Agricultural Economics and Development, 31(3): 252-266. (Persian)
  16. Joolaei, R., Mirkarimi, S., Hasanvand, M. and Shirani Bidabadi, F. (2016). Management of optimum cropping pattern of crops in Mazandaran province using goal programming. Journal of Agricultural Economics and Development, 24(94): 71-94. (Persian)
  17. Kashiri Kolaei, F., Hosseini Yekani, S.A. and Karkaboodi, F. (2017). Effect of agricultural crop insurance on the optimal cropping pattern in Mazandaran province (application of Conditional Value at Risk model). Journal of Agricultural Economics, 11(1): 111-132. (Persian)
  18. Kashiri Kolaei, F. and Hosseini Yekani, S.A. (2016). Determination of optimal cropping pattern in Mazandaran province in the context of conditional risk value model. 10th Biennial Conference of Iran’s Agricultural Economics, Kerman, Iran. (Persian)
  19. Lamb, J.D. and Tee, K.H. (2012). Data envelopment analysis models of investment funds. European Journal of Operational Research, 216(3): 687-696.
  20. MAJ (2017). Agricultural statistics. Tehran: Ministry of Agriculture-Jahad (MAJ). (Persian)
  21. Markowitz, H.M. (1952). Portfolio Selection. The Journal of Finance, 7(1): 77-91.
  22. Mirkarimi, S., Joolaei, R., Eshraghi, F. and Shirani Bidabadi, F. (2018). Application of fuzzy goal programming approach in determining optimal cropping pattern to achieve sustainable rural development goals: subsector of farming, Amol county of Iran. Journal of Village and Development, 18(3): 109-129. (Persian)
  23. Mirzaei, A., Layani, G., Azarm, H. and Jamshidi, S. (2018). Determination of optimal crop pattern in central district of Sirjan county based on sustainability of water resources and environment. Journal of Agricultural Economics Research, 9(36): 283-304. (Persian)
  24. Mohammadi, H., Ahmadpour Borazjani, M., Ziaee, S., Fakheri, B.A. and Ramrodi, M. (2013). Optimal cropping pattern of sugar beet growers with emphasis on price and yield risk: the case of Fasa district. Journal of Sugar Beet, 29(2): 229-240. (Persian)
  25. Osama, S., Elkholy, M. and Kansoh, R.M. (2017). Optimization of the cropping pattern in Egypt. Alexandria Engineering Journal, 56(4): 557-566.
  26. Pishbahar, E. and Abedi, S. (2017). Measuring portfolio Value at Risk: the application of Copula approach. Scientific Journal of Management System, 8(30): 55-73. (Persian)
  27. Silva Portela, M.C.A., Thanassoulis, E. and Simpson, G. (2004). Negative data in DEA: a directional distance approach applied to bank branches. Journal of the Operational Research Society, 55(10): 1111-1121.
  28. Tahamipour, M., Salami, H., Yazdani, S. and Chizari, A.H. (2013). Determining spatial dependency of systematic risk of dryland wheat yield in Iran: application of spatial autoregressive models. Iranian Journal of Agricultural Economics and Development Research, 44(3): 343-356. (Persian)
  29. Tanaka, D.L., Krupinsky, J.M., Liebig, M.A., Merrill, S.D., Ries, R.E., Hendrickson, J.R., Johnson, H.A. and Hanson, J.D. (2002). Dynamic cropping systems. Agronomy Journal, 94(5): 957-961.
  30. Zhong, H., Sun, L., Fischer, G., Tian, Z. and Liang, Z. (2019). Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain. Journal of Agricultural Systems, 173: 94-106.