Forecasting the Adoption of Future Market by Rice Farmers: A Case Study of the Sari City

مجله اقتصاد و توسعه کشاورزی

Article 2, Volume 33, Issue 1 - Serial Number 43, April 2019, Pages 15-24   

Document Type: Research Article

DOI: 10.22067/jead2.v0i0.67858

Authors

K. Sam Daliri¹; S.A. Hosseini Yekani^{* 2}; S.M. Mojaverian²

¹Sari University of Agricultural Science and Natural Resources.

²Sari University of Agricultural Science and Natural Resources

Abstract

Introduction: Agricultural products market in Iran is facing structural problems with non-competitive and inefficient conditions for trade of agricultural products, which leads to high price fluctuations for these products. Future markets as one of the risk sharing strategies would shift price risk to brokers and intermediaries. So, future markets are considered as one of the best tools for reducing agricultural risk. Designing and implementing future contracts is time-consuming and costly. Therefore, in order to succeed in setting up such contracts, it is essential to pay attention to several main issues consisting selecting the correct commodity for exchange, determining the optimal specification of the future contracts of agricultural products, and the way of decision making and preferences of market participants.
Materials and Methods: Despite the precise design of future contracts, future markets may fail after commencing due to lack of access for farmers, to use these tools. The purpose of this study is to predict future market acceptance by rice farmers in Sari.
To achieve this goal, the positive Mathematical Programming Model (PMP) is used in the simulation of the traditional and future market within the framework of the GAMS software. All required data were derived from statistics provided by the Ministry of Agriculture and Statistical Center of Iran during 2000 to 2015. The objective function of the model was a calibrated objective function which maximizes the actual quantities of farmers' production. But it should be noted that in solving this model, it was assumed that when the future market is launched the decision of the producers regarding the amount of production is not affected and only a part of their product will be offered in the future market, rather than in the traditional market, with the aim of reducing the price risk. Since this assumption does not validate   in the actual operating conditions and it is expected that the producers' decision-making process would also be affected after entering the futures market and trading in this market.
Results and Discussion: The results of simulation of the traditional market showed that the real average of the production, consumption, and net exports respectively were about 1.1663*10+5, 24074.390 and 1.4071*10+5 tone and the total profit of the producers of these products was about 3.7928*10+8 million Rials..
Based on the results of simulation of future market, the real average of the production, Consumption and Net exports equals about 1.4349*10+5, 26199.05 and 1.1729*10+5 tone respectively and the total profit of the producers of these products is about 3.7958*10+8 million Rials. Thus it is expected that after commencing future market for agricultural products, 44% of all rice farmers would sell their product using future contracts.
Therefore producers' decisions are not affected by the level of production and only a part of their product would be offered in the future market instead of the traditional market with the aim of reducing the price risk. In addition to comparing this market to the traditional market, the launch of the future market will increase the production, consumption and net exports about 1.9, 8.8 and 5.6 percent respectively.
Conclusion: Due to the strategic condition of the rice product and the suitability of this product to enter the future market, it should be noted that in the process of optimal design of future contracts, without paying attention to all dimensions for launching the upcoming market, this market will not be successful. Therefore, in this study determination of the amount of participation by rice farmers before launching a successful future market for rice crops has been considered. The first stage were simulating conditions before the launch of the future market, named traditional market conditions of rice, and the average real values of production, consumption, net exports and total profit of the producers of this product were estimated in Sari city. Subsequently, with the goal of reducing the price risk, the conditions after launch of the future market were simulated that represent about half of rice producers will be participanting in the upcoming market. Base on the results of this study, it is suggested that the launch of futures markets and transfering process to the Agricultural Commodity Exchange would need cultural and extension courses to understand the benefits of entering this market.

Keywords

Future Market؛ Participation؛; Price Risk؛ Rice؛ simulation

References

1- Abdollahi Ezat Abadi M., and Najafi B. 2007. Check the possibility the Particiipation of the farmers and Traders in the Futures Markets and Trading of Agricultural Products in Iran: A case Study of Pstacgio. 57:105-130. (In Persian)

2- Ahmdi Kliji S., and Amjadi A. 2015. Agricultural commodity exchange in support of the agricultural sector.

3- Ai D. 2012. Hedging effectiveness of constant and time varying hedge ratios using futures heteroshedasticity. Journal of Economics 31: 307-327.

4- Amir Nezhad H., and Smaili F. 2009. Proceedings of Reviews of economic capability cultivation of retto as second culture in mazandaran province. 6th National Conference of Agricultural Economics. (In Persian)

5- Azizi V., Mehregan N., and Yavari Gh. 2015. Test of the baalance of payments constrained growth model in Iran's agriculture sectore 8:5-20. (In Persian)

6- Bakhshi A. 2015. Check feed barley price fluctuations in the Iran Mercantile Exchange by using pattern of Arima and GARCH and harmonics. Master's thesis, University of agricultural sciences and natural resources in Sari.

7- Chizari A. 2003. The introduction of agriculture in the Iran Mercantile Exchange. Agriculture and Development 11:12-42. (In Persian)

8- Fakari B., Shahnooshi N., Mohammadi H., Mirzapour A., and Dourandish A. 2012. The Role and Performance of Iran Agricultural Mercantile Exchange in Agricultural Products 6:205-226. (In Persian)

9- Franken J.R.V., Pennings J.M.E., and Garcia P. 2012. Crop production contracts and marketing strategies: what drives their use?. Journal of Agribusiness 3: 324–340.

10- Ghadiri Moghaddam A., and Nemati A. 2012. An investigation of effective factors on participation of farmers in tomato futures market. Journal of Economics and Agricultural Development. (In Persian)

11- Heckelei T., and Britz W. 2005. Models Based on Positive Mathematical Programming: State of the Art and Further Extensions. Plenary paper presented at the 89th EAAE Seminar.

12- Hosseini Yekani S.A. 2009. Optimal Design of Agricultural of Future Contracts in Iran. Ph.D. thesis. Shiraz University.

13- Hosseini Yekani S.A., and Zibaei M. 2010. Determination of Feasible Commodities for Futures Trading (A Study of Iranian Agricultural Commodities). Journal of Economics and Agricultural Development 24: 268-278. (In Persian)

14- Hosseini Yekani S.A., and Zibaei M. 2010. Determining thr specifications of agricultural futures contracts in Iran. Journal of Agricultural Economics and Development 69:81-110.

15- Hosseini Yekani S.A., and Bakhshoodeh M. 2006. The Importance of developing Future Contracts: A case study of Iran Agricultural Commodity Exchange. Paper for presentation at the 13th annual conference Economic Research Forum (ERF), Kuwait, 16-18 December.

16- Howitt R.E. 1995. A calibration method for agricultural economic production models. Journal of Agricultural Economics 2: 147-159.

17- Howitt R.E. 1995. Positive mathematical programming. American Journal of Agricultural Economics 2: 329-342

18- Hull J. 2000. Options, Futures, and Other Derivatives. New York: Prentice Hall.

19- Kuwornu J.K. M., Kuiper W.E., Pennings J.M.E., and Meulenberg M.T.G. 2005. Time-variying hedge ratio: a principal-agent approach. Journal of Agricultural Economics 56: 417-432.

20- Lerner R.L. 2000. The Mechanics of the Commodity Futures Markets: What They Are and How.They Function, Mount Lucas Management Corporation.

21- Mofokeng M., and Vink N. 2013. Factors Affecting the Hedging Decision of Maize Farmers in Gauteng Province. The 4th International Conference of the African Association of Agricultural Economists. 22-25.

22- Nelson A.G. 1997. Teaching Agriculture Producers to Consider Risk in Decision Making. Department of Agricultural Econonics, 1-16.

23- Paris Q., and Howitt R.E. 1998. An analysis of Ill-posed production problems using maximum entropy. American Journal of Agricultural Economics 1: 124-138.

24- Pennings J.M.E., and Leuthold R.M. 2001. Commodity Futures Contract Viability: A Multidisciplinary Approach. NCR-134 Proceedings. 273-288.

25- Purcell W.D., and Koontz S.R. 2003. Agricultural Futures and Options, Principles and Strategies, Second Editions. New York: Prentice Hall.

26- Rostami F., Shaban Ali Fami H., Moohammadmadi H., and Ivarani H. 2006. Risk Management of Wheat Production in Family Utilization System (Case Study: Harsin County). 2-37:93-106. (In Persian)

27- Sakhi F., Mohammadi H., and Sabuhi M. 2016. Survey probability of participation of farmers in the futures and options markets (Case study of cotton city Gonbadkavos). Journal of Economics and Agricultural Development 3.

28- Salami H., and Tahami Pour M. 2015. Determining factores affecting price risk of corn in Iran. Agricultural Economics and Development 23: 95-114. (In Persian)

29- www.agri-jahad.ir

30- www.jkmaz.ir