Analysis of Asymmetric Price Transmission in the Poultry Market of Mazandaran Province
Keywords:
Asymmetric price transmission, poultry market, TAR model, agricultural marketAbstract
This study aims to analyze asymmetric price transmission behavior in the poultry market of Mazandaran Province and to examine the intensity and speed of price transmission across different price regimes. This applied and descriptive–analytical study used annual time-series data on the poultry price index in Mazandaran Province from 1991 to 2024 (constant prices of 2021). Data were obtained from the Central Bank of Iran and the Statistical Center of Iran. After testing for stationarity using the Augmented Dickey–Fuller (ADF) test, the Threshold Autoregression (TAR) model was estimated following the Enders and Siklos (2001) approach. The optimal lag length was selected using the Akaike and Schwarz criteria, and the price threshold was determined using Chan’s (1993) method. The ADF results confirmed that the poultry price index is I(1). The TAR model showed good fit (R²=0.67; DW=2.04), with the optimal threshold estimated at 1.415 and one lag selected. The estimated coefficients were 1.005 in the low-price regime and 1.117 in the high-price regime, both significant at the 0.01 level. These findings indicate that price transmission occurs faster and more intensely when prices rise than when they fall, confirming asymmetric price adjustment. The results confirm the existence of asymmetric price transmission in Mazandaran’s poultry market. Price increases are transmitted more quickly to consumers than price decreases, reflecting market concentration, adjustment costs, and intermediary power. Policymakers should enhance transparency in pricing, limit monopolistic practices, and promote long-term contracts between producers and retailers to improve market stability and consumer welfare.
Downloads
References
Arbabi, F., Mirahmadi, M., & Lashgarara, F. (2015). Marketing Challenges of Agricultural Products from the Perspective of Rural Cooperatives in Qom Province. Int. J. Rev. Life. Sci., 5(2), 59-62.
Bahrami, J., Mohammadi, T., & Bozorg, S. (2014). Asymmetric Transmission of Exchange Rate to Domestic Price Indices with an SVAR Approach. Iranian Economic Research Quarterly, 40, 37-65.
Batten, J. A., Kinateder, H., Szilagyi, P. G., & Wagner, N. F. (2018). Liquidity, surprise volume and return premia in the oil market. Eneeco. https://doi.org/10.1016/j.eneco.2018.06.016
Chen, S. S. (2012). Revisiting the empirical linkages between stock returns and trading volume. Journal of Banking & Finance, 36, 1781-1788. https://doi.org/10.1016/j.jbankfin.2012.02.003
Cristea, A. D., & Nguyen, D. X. (2016). Transfer pricing by multinational firms: New evidence from foreign firm ownerships. American Economic Journal: Economic Policy, 8(3), 170-202. https://doi.org/10.1257/pol.20130407
Davies, R. B., Martin, J., Parenti, M., & Toubal, F. (2018). Knocking on tax haven's door: Multinational firms and transfer pricing. Review of Economics and Statistics, 100(1), 120-134. https://doi.org/10.1162/REST_a_00673
de Gavelle, E., Davidenko, O., Fouillet, H., Delarue, J., Darcel, N., Huneau, J. F., & Mariotti, F. (2019). Self-declared attitudes and beliefs regarding protein sources are a good prediction of the degree of transition to a low-meat diet in France. Appetite, 142. https://doi.org/10.1016/j.appet.2019.104345
Ebrahimi, M., & Hozhabr Kiani, K. (2020). Investigating the Asymmetric Effects of Oil Price and Interest Rate Changes on the Unemployment Rate in Iran: The NARDL Approach. Scientific-Research Quarterly of Economic Strategy, 9(34), 41-69.
Eyshi Ravandi, M., Moeinaddin, M., Taftiyan, A., & Rostami Bashmani, M. (2024). Investigating the Impact of Investor Sentiment and Liquidity on Stock Returns of the Iranian Stock Exchange. Dynamic Management and Business Analysis, 3(1), 40-52. https://doi.org/10.22034/dmbaj.2024.2038046.1068
Fousekis, P., & Tzaferi, D. (2019). Price returns and trading volume changes in agricultural futures markets: An empirical analysis with quantile regressions. The Journal of Economic Asymmetries, 19. https://doi.org/10.1016/j.jeca.2019.e00116
Hosseini, S. S., & Saraei Shad, Z. (2009). Price Transmission in the Farmed Rainbow Trout Market in Fars Province. Agricultural Research Journal, 1(4), 121-181.
Huiming, Z., Xianfang, S., Yawei, G., & Yinghua, R. (2016). The Asymmetric Effects of Oil Price Shocks on the Chinese Stock Market: Evidence from a Quantile Impulse Response Perspective. Sustainability, 8(8), 1-19. https://doi.org/10.3390/su8080766
Khaleel, M. I., Jabbar, A. Y., Kalai, M., Aloulou, R., & Helali, K. (2024). An applied study of the symmetric and asymmetric impact of oil prices and international financial markets on economic growth in Iraq. International Journal of Energy Economics and Policy, 14(4), 66-80. https://doi.org/10.32479/ijeep.16123
Kumar, S. (2017). Revisiting the price-volume relationship: A cross-currency evidence. International Journal of Managerial Finance, 13(1), 91-104. https://doi.org/10.1108/IJMF-11-2015-0197
Li, H. S., Hu, C. P., Lu, Z., Li, M., & Guo, X. (2021). African swine fever and meat prices fluctuation: An empirical study in China based on TVP-VAR model. Journal of Integrative Agriculture, 20(8), 2289-2301. https://doi.org/10.1016/S2095-3119(20)63307-X
Mashayekhi, S., & Hajizadeh Fallah, M. (2011). Investigating the Factors Affecting the Chicken Meat Market in Iran (Application of the Vector Autoregression Model). Economic Research Journal, 11(1), 131-154.
Memarzadeh, A. (2024). Investigating the Asymmetric Effects of Geopolitical Risks on Iran's Crude Oil Prices: New Evidence from the Econometric Modeling Approach. Quarterly Journal of Econometric Modeling, 9(1).
Nusair, S. A., & Al-Khasawneh, J. A. (2023). Changes in oil price and economic policy uncertainty and the G7 stock returns: evidence from asymmetric quantile regression analysis. Economic Change and Restructuring, 56(3), 1849-1893. https://doi.org/10.1007/s10644-023-09494-9
Pishbahar, E., Ferdowsi, R., & Asadollahpour, F. (2019). Price Transmission in Iran's Chicken Meat Market: Application of the Markov Switching Autoregressive (MSAR) Model. Iranian Journal of Agricultural Economics and Development Research, 2(1), 1-17.
Rathke, A., Rezende, A., & Watrin, C. (2020). Classification of transfer pricing systems across countries. International Economics, 164, 151-167. https://doi.org/10.1016/j.inteco.2020.08.002
Sanjari Kenarsandal, N., Elyas Pour, B., & Nikou Ghadam, M. (2022). The Asymmetric Impact of Oil Price, Oil Price Uncertainty, and Interest Rate on Unemployment in Iran. Iranian Economic Issues, 9(1), 269-296.
Sarker, P. K., Bouri, E., & Marco, C. K. L. (2023). Asymmetric effects of climate policy uncertainty, geopolitical risk, and crude oil prices on clean energy prices. Environmental Science and Pollution Research, 30(6), 15797-15807. https://doi.org/10.1007/s11356-022-23020-w
Shavvalpour Arani, S., Mohseni, R., & Kordtabar Firoozjaei, H. a.-D. (2024). An Asymmetric Analysis of the Impact of Oil Price, Exchange Rate, and Their Uncertainties on Unemployment in Oil-Exporting Countries. Macroeconomic Research Journal, 19(2), 37-70.
Zheng, Y., & Ma, J. (2018). The analysis of the dynamic impacts of avian influenza on livestock and poultry prices: Based on the TVP-VAR mode. Research of Agricultural Modernization, 39, 751-760.
Downloads
Published
Submitted
Revised
Accepted
Issue
Section
License
Copyright (c) 2024 Boromand Alizadeh Seyed Zeynolabedini (Corresponding author); Mostafa Goodarzi, Ghasem Norouzi (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
