The projection model of Iran’s crop production in 2025

Document Type : Research Paper

Authors

1 Professor and Graduate PhD. Candidate, Agricultural Economics, Faculty of Agriculture Economics and Development, University of Tehran, Iran

2 Assiatant Professor,University of Torbat-e- Heidarie .

Abstract

The aim of this study is to develop a model to provide projections of supply of major crops in target year 2025 in Iran. To this end, a model was constructed using positive mathematical programming (PMP) approach. The model takes into account production factors constraints in different provinces in the base year as well as in the target year, and provides forecasts of potential supply of major crops in each of the provinces as well as in national level. In addition, price levels and land productivity of the crops for target year as input to the PMP model were projected using ARIMA time series approach. Results indicate that from 2008 to 2025, total crop production will increase from 36.17 million ton to 45.5 million ton with acumulative growth rate of 25.8 percent. The rate of change differs among different crops. Cereals show the highest growth rate (%76.1) while vegetable (%2.15) and industrial crops (%20.5) reveal the lowest ones. Comparing the predicted supply with those of demands indicates that supply of wheat, potato, onion and cereals will meet the direct demand for these commodities, however, the country will experience supply shortages in the case of oilseeds, sugar beet and rice and calls for more investments in production.

Keywords

References

Britz, W. (2004). CAPRI modeling system documentation. Common Agricultural Policy Regional Impact Analysis. Bonn. 
Enders, W. (2004). Applied econometric time series. New York. Wiley
FAO. (1993). The World food model -model specifications ESC/M/93/1.  Rome, Italy.
Food and Agricultural Policy Research Institute (FAPRI). (2011). World agricultural outlook database. From http:// www . fapri . iastate . edu / tools / outlook . aspx
Freebairn, J.W. (1975). Forecasting for australian agriculture. Australian Journal of Agricultural Economics, 19(3)
Heckelei, T. (1997). Positive mathematical programming: review of the standard approach, CAPRI-Working Paper 97-03, University of Bonn.
Helming, J.F.M. (2005). A model of Dutch agriculture based on Positive Mathematical Programming with regional and environmental applications. PhD thesis, Wageningen University.
Howitt, R.E. (1995). Positive mathematical programming. American Journal of Agricultural Economics,  77(2)
Koc, A.A, Darnell B. S, Frank F, and Fabiosa, J. (1998). The Turkish agricultural policy analysis model. Technical Report 98-TR 42, Center for agricultural and rural development, Iowa State University.
Jikun, H, Rozelle, S & Rosegrant, M.W. (1997). China’s food economy to the 21st century: Supply, demand, and trade. 2020 Vision Discussion Paper No. 19. Washington, D.C.: International Food Policy Research Institute.
OECD. (2011). OECD-FAO Agricultural Outlook. From http://stats.oecd.org/
Lampe, M. (1998). The world agricultural trade simulation system (WATSIM). Discussion Paper 98-05, Institute for Agricultural Policy, University of Bonn.
Ministry of Jahad-e-Keshavarzi. (2008). Production cost of agricultural crops, statistical database. (In Farsi)
Mohanty, S. Alexandratos, N & Bruinsma, J. (1998). The long term food outlook for India. Technical report 98. Center for agricultural and rural development, Iowa State University.
 Paris, Q., & Howitt, R.E. (1998). An analysis of Ill-posed production problems using maximum entropy. American Journal of Agricultural Economics. 80(1)
 Paris, Q., & Arfini, F. (2000). Frontier cost functions, self-selection, price risk, PMP and agenda 2000. Euro tools Working Papers Series, No. 20.
Rosegrant, M.W., & Meijer. S. (2002). International model for policy analysis of agricultural commodities and trade (IMPACT), International Food Policy Research Institute, Washington, from http://www.ifpri.org/themes/impact/impactmodel.pdf.
Rosegrant, M.W, Agcaoili-Sombilla, M & Perez, N. (1995). Global Food Projections to 2020. Discussion Paper No. 5., IFPRI, Washington DC.
Statistical Center of Iran. (2008). Statistical yearbook, Households' expenditure and revenues, Statistical Center of Iran. (In Farsi)
Statistical Center of Iran. (2008). Statistical yearbook, Sell price of agricultural products agricultural in rural regions of country, Statistical Center of Iran. (In Farsi)
USDA. (1996): Long Term Projections for International Agriculture to 2005. ERS Staff Paper No. 9612, August. Washington, DC.
Wiborg, T. (1998). KRAM - A sector model of danish agriculture, background and framework development. Working paper 98-WP 193. CARD, Iowa State University, Ames, Iowa.
 
 
Iranian Journal of Agricultural Economics and Development Research
Volume 45, Issue 4 - Serial Number 4
January 2015
Pages 585-599

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