بررسی روند تصادفی مشترک میان قیمت کنجاله سویا و ذرت در ایران و کشورهای طرف عمده تجاری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری اقتصاد دانشگاه ارومیه

2 دانشیار اقتصاد دانشگاه ارومیه

3 استادیار اقتصاد دانشگاه ارومیه

4 استادیار مرکز تحقیقات کشاورزی و منابع طبیعی مازندران

چکیده

وابستگی زندگی و تداوم حیات انسان به محصولات کشاورزی برای تأمین غذا و لزوم به حداقل رساندن نوسان‌های قیمت و دادن اطمینان خاطر بیشتر در مورد سطوح قیمت‌ها در آینده، تقریباً همیشه از اهداف اساسی سیاست قیمت محصولات کشاورزی بوده است. لذا هدف مطالعه حاضر بررسی روند تصادفی مشترک میان قیمت کنجاله  سویا و ذرتدر ایران و کشورهای طرف عمده تجاری با ایران بوده است. در همین راستا از اطلاعات قیمت ماهانه دو محصول ذرت و کنجاله سویا برای ایران و کشورهای طرف‌ عمده تجاری طی دوره زمانی 95-1385 و همچنین از روش گونزالو-گرنجر و الگوی جوهانسون جهت تعیین روندهای تصادفی استفاده شد. نتایج نشان داد که برای قیمت ذرت دو روند تصادفی مشترک وجود دارد و در این راستا سه کشور ایران، برزیل و آرژانتین می‌توانند به‌عنوان رهبر تعیین‌کننده قیمت باشند. همچنین برای قیمت کنجاله سویا سه روند تصادفی مشترک بین ایران و طرف‌های تجاری وجود دارد، ولی هیچ‌ یک از کشورها رهبر   تعیین کننده قیمت نخواهند بود. بر این اساس لازم است که به منظور اجتناب از بروز نوسان زیاد در قیمت های داخلی، شرایط بازار جهانی به طور مستمر نظارت شده و با اتخاذ تدابیر حمایتی لازم به ویژه در زمینه سیاست های تجاری، از حساسیت زیاد قیمت‌های داخلی به نوسان قیمت‌های جهانی کاسته شود.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating the Common Stochastic Trend of Corn and Soybean Meal Prices in Iran and Its Main Trading Partners

نویسندگان [English]

  • Madadali -Rostami Navan 1
  • K. Shahbazi 2
  • S.J. Mohseni Zonouzi 3
  • Hasan asadpour 4
1 Ph.D. Student of Economics, Urmia University, Urmia, Iran
2 Associate Professor of Economics, Urmia University, Urmia, Iran
3 Assistant Professor of Economics, Urmia University, Urmia, Iran
4 Assistant Professor of Agricultural and Natural Resources Research Center of Mazandaran
چکیده [English]

Dependence of life and its continuity on agricultural products for providing food and necessity to minimize price volatility and reassuring the price levels in the future have been almost always one of the essential objectives of agricultural product price policy. The aim of the present study was to investigate the common stochastic trend between selected agricultural product prices in Iran and its trading partners. For this purpose, monthly price data of corn and soybean meal for Iran and Iran's main trading partner countries over the period 2006-2016 were used. Gonzalo-Granger and Johansen methods were used to determine common stochastic trends. The results showed that there are two common stochastic trends for the price of corn and in this regard, Iran, Brazil, and Argentina could be decisive leaders. Also, there are three common stochastic trends for the price of soybean meal, but none of the countries will be the price policy leader. Accordingly, in order to avoid fluctuations in domestic prices, it is necessary that the conditions of global market were monitored continuously and also the sensitivity of domestic prices to international price fluctuations by adopting appropriate support measures, particularly in the area of trade policy was reduced. 

کلیدواژه‌ها [English]

  • Corn
  • Soybean Meal
  • Common Stochastic Trend
  • Gonzalo-Granger

مراجع

  1. Baquedano, F. G. & Liefert, W. M. (2014). Market integration and price transmission in consumer markets of developing countries. Food Policy, 44: 103-114.
  2. Bolkesjø, T. F. & Buongiorno, J. (2006). Short-and long-run exchange rate effects on forest product trade: evidence from panel data. Journal of Forest Economics, 11(4): 205-221.
  3. Engle, R. F. & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society, 251-276.
  4. Engle, R.F., Hendry, D.F. & Richard, J.F. (1983). Exogeneity. Econometrica, 51: 277-304.
  5. Fang, W., Lai, Y. & Miller, S. (2009). Does exchange rate risk affect exports asymmetrically? Asian evidence. Journal of International Money and Finance, 28: 215- 239.
  6. FAO (2015). FAO prediction about the world's crop state in 2015-2016. Planning Research Institute, Tehran:   Agricultural Economics and Rural Development. (Persian)
  7. Gonzalez-Riviera, G. &  Helfand, S.M., (2001). The extent, pattern and degree of market integration: a multivariate approach for the Brazilian rice market. American Journal of Agricultural Economics, 83 (3): 576–592.
  8. Gonzalo, J. &  Granger, C.W.J. (1995). Estimation of common long memory components in cointegrated systems. Journal of Business & Economic Statistics, 13 (1): 27–35.
  9. Gotz, L., Glauben, T. & Brümmer, B. (2013). Wheat export restrictions and domestic market effects in Russia and Ukraine during the food crisis. Food Policy, 38: 214-226.
  10. Granger, C.W. (1981). Some properties of time series data and their use in econometric model specification. Journal of econometrics, 16(1): 121-130.
  11. Haile, M., Kalkuhl, M., Algieri, B. & Gebreselassié, S. (2016). Analysis of price shock transmission: case of the wheat-bread market value chain in Ethiopia (No. 50). LEI Wageningen UR.
  12. Heidari Kamalabadi, R. & Shahnoushi, N. (2012). Transfer of the price from importing institutes in poultry sector from global markets to domestic markets, Case Study: Soybean Meal and Fish Powder. Agricultural Economics  and Development, 20(79):135-154. (Persian)
  13. Hong-Bo, S., Xiao-Yan, C., Li-Ye, C., Xi-Ning, Z., Gang, W., Yong-Bing, Y. & Zan-Min, H. (2006). Investigation on the relationship of proline with wheat anti-drought under soil water deficits. Colloids and Surfaces B: Biointerfaces, 53(1): 113-119.
  14. https://epl.irica.gov.ir. (Persian)
  15. Ismaili, A.K. (2012). Investigating the effect of global markets on domestic prices. Case study: barley, alfalfa, maize and soybean meal. Agricultural Economics and Development, 20(78): 145-170. (Persian)
  16. Jain, A. & Biswal, P. C. (2015). Intraday price discovery and information sharing between stocks and single stock futures: evidence from India. International Journal of Financial Markets and Derivatives, 4(3-4): 203-212.
  17. John, A. (2013). Price relations between export and domestic rice markets in Thailand. Food Policy, 42: 48-57.
  18. Kalashami, M. K., Khiyavi, P. K. & Allahyari, M. S. (2015). Price transmission, threshold behavior and asymmetric adjustment in Iranian poultry market. Iranian Journal of Applied Animal Science, 5(2): 447-452.
  19. Mahmoudi, H. & Afrasyabi, S. (2014). Analysis of price transfer in saffron market, Case study: Razavi, North and South Khorasan provinces. Saffron Agronomy and Technology, 2(2): 71-84. (Persian)
  20. Minot, N. (2010). Transmission of world food price changes to markets in Sub-Saharan Africa. Washington: International Food Policy Research Institute.
  21. Nofarasti, M. (2008). The root and coexistence in econometrics. Rasa Cultural Services Institute, First Print. Tehran: (Persian)
  22. Jozghani, F., Moghadasi, R., Yazdani, S. & Mohammadinejad, A. (2015). Spreading price model of poultry meat and the most important business partner. Agricultural Economics Research, 7(4):99-112. (Persian)
  23. Ravallion, M. (1986). Testing market integration. American Journal of Agricultural Economics, 68(1): 102-109.
  24. Sekhar, C.S.C. (2012). Agricultural market integration in India: an analysis of select commodities. Food Policy, 37(3):309-322.
  25. Shahikitash, M.N. & Omrani, M. (2014).Transfer of prices between the domestic market and the export of selected agricultural products and the welfare effects of asymmetric transmission. Agricultural Economics and Development, 22(85)177-211. (Persian)
  26. Yavari, F., Ghahremanzadeh, M., Dashti, Q. & Phalsaphiyan, A. (2014). Threshold convergence and asymmetric transmission price: applicable for veal market in the East Azarbaijan province. Agricultral Economics, 8(2):103-119. (Persian)
  27. Yousefi Motaghaed, H. & Moghadasi, R. (2013). Investigating the transfer of global prices to the domestic market of agricultural products (wheat, barley and rice) -Use the Entropy Maximization Method. Agricultural Economics Research, 5 (1):81-99.(Persian).
  28. Ministry of Agriculture-Jahad (2016). Avalibale at: http://www.maj. ir (Persian).

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