taheri reykandeh, E., Rafiee, H. (2024). Modeling Return and Volatility Spillovers between Inputs Market of Livestock and Poultry Industry in Iran. , 31(4), 19-47. doi: 10.30490/aead.2024.356654.1396
emran taheri reykandeh; Hamed Rafiee. "Modeling Return and Volatility Spillovers between Inputs Market of Livestock and Poultry Industry in Iran". , 31, 4, 2024, 19-47. doi: 10.30490/aead.2024.356654.1396
taheri reykandeh, E., Rafiee, H. (2024). 'Modeling Return and Volatility Spillovers between Inputs Market of Livestock and Poultry Industry in Iran', , 31(4), pp. 19-47. doi: 10.30490/aead.2024.356654.1396
taheri reykandeh, E., Rafiee, H. Modeling Return and Volatility Spillovers between Inputs Market of Livestock and Poultry Industry in Iran. , 2024; 31(4): 19-47. doi: 10.30490/aead.2024.356654.1396

Modeling Return and Volatility Spillovers between Inputs Market of Livestock and Poultry Industry in Iran

اقتصاد کشاورزی و توسعه
Article 2, Volume 31, Issue 4 - Serial Number 124, March 2024, Pages 19-47    PDF (472.38 K)
Document Type: Original Article
DOI: 10.30490/aead.2024.356654.1396
Authors
emran taheri reykandeh1; Hamed Rafiee* 2
1PhD Students, Department of Agricultural Economics, Faculty of Agricultural Economics and Development, University of Tehran, Karaj, Iran
2Assistant Professor of Agricultural Economics, University of Tehran, Tehran, Iran
Abstract
Introduction: The occurrence of wide fluctuations in commodity markets poses numerous challenges to producers and consumers. Examining the link between markets can make it possible to predict the future behavior of commodity prices. Accordingly, the present study intended to explain return and volatility spillovers of the market of three necessary inputs of Iran's livestock and poultry industry, including corn, soybean meal, and barley.
Materials and Methods: In this study, for modelling the relationships between the price fluctuations of the livestock and poultry inputs market, using the monthly data of 2001:04-2021:3, the Vector Autoregressive (VAR)- Baba, Engle, Kraft, and Kroner (BEKK)- Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MVGARCH) model known as VAR-BEKK-MVGARCH model was estimated.
Results and Discussion: The results showed a positive and significant return spillover from the soybean meal market to the corn market, and conversely, while the barley market returns spillover to the corn market was insignificant, and the soybean meal market was negative and significant. In addition, the market return of soybean meal had a positive and significant effect on the market return of barley, and the spread of the barley market from the corn market was not accepted. Also, the current market volatility was asymmetrically affected by positive and negative shocks, and the existence of a unidirectional asymmetric cross-market spillover from corn and barley markets to soybean meal market and from corn market to barley market was confirmed.
Conclusions: Based on the results obtained in this study, it is suggested that policymakers consider these effects in the management of price movements. Furthermore, it is suggested that the government prevent the spread of various negative news items, such as reducing the supply of currency required for the import of inputs.
References
  • Abdallah, M. B., Farkas, M. F., & Lakner, Z. (2020). Analysis of meat price volatility and volatility spillovers in Finland. Agricultural Economics, 66(2), 84-91.
  • Alaei Borujeni, P., Farnam, A., Abdoli, M., Hamidpour Zare, S., Tolouei, Z., Khosravi, K., Azami, A., Varmazyari, H., & Razani, B. (2020). About leap in production (2) its requirements in the fields of agriculture, housing, transportation and rural development. Deputy of Infrastructure and Production Affairs Research. Islamic Parliament Research Center (IPRC), 17127. [In Persian]
  • Bergmann, D., O’Connor, D., & Thümmel, A. (2016). An analysis of price and volatility transmission in butter, palm oil and crude oil markets. Agricultural and Food Economics, 4(1), 1-23.
  • Beykzadeh, S., Ghahremanzadeh, M., & Mahmoodi, A. (2020). The evaluation of price volatility of beef and chicken and livestock’s major inputs in Iran. Journal of Animal Science Research, 30(3), 85-103. [In Persian]
  • Chen, Y., Zheng, B., & Qu, F. (2020). Modeling the nexus of crude oil, new energy and rare earth in China: an asymmetric VAR-BEKK (DCC)-GARCH approach. Resources Policy, 65, 101545.
  • Díaz-Bonilla, E. (2016). Volatile volatility: conceptual and measurement issues related to price trends and volatility. Springer, Cham.
  • Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66.
  • Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122-150.
  • Fasanya, I. O., & Odudu, T. F. (2020). Modeling return and volatility spillovers among food prices in Nigeria. Journal of Agriculture and Food Research, 2, 100029.
  • FAO (2010). Price volatility in agricultural markets: evidence, impact on food security and policy responses. Economic and Social Perspective, Policy Brief 12. FAO, Economic and Social Development Department.
  • Ferrer-Pérez, H., & Gracia-de-Rentería, P. (2020). Asymmetric price volatility transmission in the Spanish fresh wild fish supply chain. Marine Resource Economics, 35(1), 65-81.
  • Ghahremanzadeh, M., & Aref Eshgi, T. (2013). Modeling asymmetric price volatility for Tehran province's chicken market. Journal of Economics and Agricultural Development, 27(2), 134-143. [In Persian]
  • Ghahremanzadeh, M., Eshtiyaghi, M., Pishbahar, E., & Dashti, G. (2014). Price volatility spillover in the agricultural products markets: the case study of meat markets in East Azerbaijan province. Iranian Journal of Agricultural Economics (Economics and Agriculture Journal), 8(1), 1-19. [In Persian]
  • Ghahremanzadeh, M., Dashti, G., & Rasouli Beyrami, Z. (2016). Price volatility and conditional correlation of livestock and poultry vertical market levels in Iran: using constant and time varying conditional correlation models. Agricultural Economics, 10(3), 19-46. [In Persian]
  • Ghahremanzadeh, M., & Falsafian, A. (2012). Price volatility spillover effects in beef market of Tehran province. Journal of Economics and Agriculture Development, 26(1), 31-40. [In Persian]
  • Ghahremanzadeh, M., & Javdan, E. (2012). Investigation the impact of news on meat price volatility in Iran. Iranian Journal of Agricultural Economics, 6(4), 37-55. [In Persian]
  • Gilanpour, O., Kohansal, M., Permeh, Z., & Esmaeilipour, E. (2012). Investigation of government intervention in the chicken meat market. Iranian Journal of Trade Studies (IJTS), 16(63), 137-168. [In Persian]
  • Ibrahim, M. H. (2015). Oil and food prices in Malaysia: a nonlinear ARDL analysis. Agricultural and Food Economics, 3(1), 1-14.
  • Jati, K., & Premaratne, G. (2017). Analysis of staple food price behaviour: multivariate BEKK-GARCH model. Journal of Asian Finance, Economics and Business, 4(4), 27-37.
  • Kavoosi Kalashami, M., & Khaligh Khiyavi, P. (2017). Spillover effects of tea price volatilities in Iran (case study: Lahijan County). Journal of Agricultural Economics and Development, 25(98), 175-191. [In Persian]
  • Kavoosi Kalashami, M., & Khaligh Khiyavi, P. (2015). Spillover effects of meat prices volatility in Iran. Journal of Agricultural Economics Research, 7 (26), 27-41. [In Persian]
  • Kebede, D. T., & Fufa, D. D. (2020). Econometric analysis of retail prices of major agricultural food commodities in Dire Dawa City Administration, Ethiopia. World, 8(1), 6-11.
  • Kroner, K. F., & Ng, V. K. (1998). Modeling asymmetric co-movements of asset returns. The Review of Financial Studies, 11(4), 817-844.
  • Musunuru, N. (2014). Modeling price volatility linkages between corn and wheat: a multivariate GARCH estimation. International Advances in Economic Research, 20(3), 269-280.
  • Nguyen, T., Chaiechi, T., Eagle, L., & Low, D. (2020). Dynamic transmissions between main stock markets and SME stock markets: evidence from tropical economies. The Quarterly Review of Economics and Finance, 75, 308-324.
  • Piot-Lepetit, I., & M’barek, R. (2011). Methods to analyse agricultural commodity price volatility. Springer, New York, NY.
  • Pishbahar, E., Ferdowsi, R., & Assadollahpour, F. (2019). Price transmission in the market of chicken meat: Autoregressive Switching Markov Models (MSAR). Iranian Journal of Agricultural Economics and Development Research, 50(1), 1-17. [In Persian]
  • Pishbahar, E., Pakroh, P., & Ghahremanzadeh, M. (2018). Using Copula approach for modeling dependence among oil prices, exchange rate and imported inputs of livestock industry in Iran. Agricultural Economics: Iranian Journal of Agricultural Economics (Economics and Agriculture Journal), 12(2), 1-19. [In Persian]
  • Rezitis, A. N., & Pachis, D. N. (2020). Investigating the price volatility transmission mechanisms of selected fresh vegetable chains in Greece. Journal of Agribusiness in Developing and Emerging Economies, 10(5), 587-611.
  • Saghaian, S., Nemati, M., Walters, C., & Chen, B. (2018). Asymmetric price volatility transmission between US biofuel, corn, and oil markets. Journal of Agricultural and Resource Economics, 43(1), 46-60.
  • Shahbazi, H., & Amjadi, A. (2016). Assessment of consumer supporting policy effect on livestock and poultry sub-sector demand. Journal of Agricultural Economics and Development, 24(94), 213-244. [In Persian]
  • SLAL (2021). The percentage of changes in the prices of foreign grain corn/soybean meal/barley. Tehran: Ministry of Agriculture-Jahad (MAJ), State Livestock Affairs Support Logistics (SLAL) Company. Available at https://iranslal.com. [In Persian]
  • Zhang, Y. J., Fan, Y., Tsai, H. T., & Wei, Y. M. (2008). Spillover effect of US dollar exchange rate on oil prices. Journal of Policy Modeling, 30(6), 973-991.
  • Zhao, J., & Goodwin, B. K. (2011). Volatility spillovers in agricultural commodity markets: an application involving implied volatilities from options markets. Conference Paper/Presentation. Agricultural and Applied Economics Association (AAEA) Conferences, Pittsburgh, Pennsylvan

 

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