Investigating the Impact of Input Price Shocks in Iranian Egg Market

Document Type : Original Article

Authors

1 Corresponding Author and PhD Student in Agricultural Economics, Faculty of Agriculture and Natural Resources, University of Tehran, Tehran, Iran (adalatsalim@ut.ac.ir).

2 PhD Student in Agricultural Economics, Faculty of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.

3 Assistant Professor of Agricultural Economics, Faculty of Agriculture and Natural Resources, University of Tehran, Tehran, Iran.

Abstract

Eggs are one of the most important protein products with a special place in the food basket of Iranian households. The large changes in the price of this product can have a great impact on buyers and producers. A large share of the cost of egg production is related to the consumption of two inputs, soy and corn; therefore, the final price and fluctuations in the price of eggs are highly dependent on the prices of these two inputs and their fluctuations. In this research, by using bounds-testing, the long-term and short-term relationships between egg prices and soybean and corn prices were explored, as well as the effect of the price shocks of these inputs in the egg market. This test was carried out in the form of Autoregressive Distributed Lag (ARDL) and the presence of cointegration relationship between the variables in different modes was investigated. Since the lack of long-term relationship between the variables was rejected in all three studied modes, the Vector Error Correction Model (VECM) was found to be suitable for investigating the shocks on the egg market. The study results showed that the shocks on soybean prices had the greatest effect on the fluctuation of egg prices in the short term, and in the long term, the leadership of the egg price (increase or decrease in the price of eggs) was done by the shocks on the corn market. Therefore, it is suggested that in the short term, the policy-maker should prevent the transfer of shocks from the soy market to eggs by adopting suitable tariff policies (variable tariff appropriate to fluctuations in global input prices); in addition, with the development of corn cultivation in areas susceptible to cultivation, the need to import this product would be minimized, because with self-sufficiency in corn production, the impact of global shocks on the market of this product and the egg market will be reduced, and it will be easier to control domestic shocks than the global shocks.

Keywords

Main Subjects

References

  • Abbasiyan, M., & Karbasi, A. (2003). Application of quantitative methods in predicting economic variables (Case Ssudy: egg production and wholesale price). Paper presented at the Proceedings of the Fourth Biennial Conference on Agricultural Economics of Iran, Faculty of Agriculture, University of Tehran. (in Persian)
  • Azizi J., & Torkmani, J. (2001). Estimation of meat demand functions in Iran. Quarterly Journal of Agricultural Economics and Development, 217-234. (in Persian)
  • Baz Mohhamadi, H. (2001). Relationship between producer price index, consumer price and welfare index. Central Bank of the Islamic Republic of Iran, Office of Investment and Policy. Department of Economic Studies. (in Persian)
  • Belloumi, M. (2014). The relationship between trade, FDI and economic growth in tunisia: an application of the autoregressive Ddistributed lag model. Economic systems, 38(2), 269-287.
  • Belloumi, M., & Alshehry, A. S. (2015). Sustainable energy development in Saudi Arabia. Sustainability, 7(5), 5153-5170.
  • Bhattacharya, P. S., & Thomakos, D. D. (2008). Forecasting industry-level CPI and PPI inflation: does exchange rate pass-through matter? International Journal of Forecasting, 24(1), 134-150.
  • Dashti, A., & Mohhamadi, H. (2010). Predicting meat and egg prices using artificial neural networks in Iran. Quarterly Journal of Economic Research and Policy. (in Persian)
  • Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: Journal of the Econometric Society, 251-276.
  • Fakhri, M. (2004). Determine The inflation rate with a three-step regression user. Central Bank of The Islamic Republic Of Iran, Office of Investment And Policy, Department of Economic Studies. (in Persian)
  • Fetri, M., & Torkamani, M. (2011). Mechanism of price transfer of producer index to consumer. jornal of agricultral economic. (in Persian)
  • Ghazali, M. F., Yee, O. A., & Muhammad, M. Z. (2008). Do producer prices cause consumer prices? Some empirical evidence. International Journal of Business and Management, 3(11), 78-82.
  • Ghorbani, M., & Motallebi, M. (2009). Application Pesaran and Shin method for estimating Irans import demand function. Journal of Applied Sciences, 9.
  • Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in gaussian vector autoregressive models. Econometrica: journal of the Econometric Society, 1551-1580.
  • Khemili, H., & Belloumi, M. (2018). Cointegration relationship between growth, inequality and poverty in Tunisia. International Journal of Applied Economics, Finance and Accounting, 2(1), 8-18.
  • kohansal, M., permeh, z., esmaelipoor, e., & ghasemi, a. (2012). Egg price prediction using arima, artificial nerual network and Holt-Winters smothing. Quarterly Journal of Business Research, 49-72. (in Persian)
  • Liping, H., Gang, F., & Jiani, H. (2008). CPI vs. PPI: Which drives which? Economic Research Journal, 11, 16-26.
  • Narayan, P. (2005). The saving and investment nexus For China: evidence from cointegration tests. Applied Economics, 37(17): 1979–1990.
  • Park, J. (1990). Testing for unit roots by variable ddition. advances in econometrics: cointegration, spurious regressions and unit roots, eds. TB Fomby and RF Rhodes, JAI Press, Greenwich.
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of applied econometrics, 16(3), 289-326.
  • Shahbaz, M., Awan, R. U., & Nasir, N. M. (2009). Producer & consumer prices nexus: ARDL bounds testing approach. International Journal of Marketing Studies, 1(2), 78.
  • Shahbaz, M., Wahid, A. N., & Haider, A. (2010). Empirical psychology between wholesale price and consumer price indices: the case of pakistan. The Singapore Economic Review, 55(03), 537-551.
  • Shin, Y. (1994). A residual-based test of the null of cointegration against the alternative of no cointegration. Econometric theory, 10(1), 91-115.
  • Sidaoui, J., Capistrán, C., Chiquiar, D., & Ramos-Francia, M. (2009). A note on the predictive content of PPI over CPI tnflation: the case of Mexico. Retrieved From
  • Stock, J. H., & Watson, M. W. (1988). Testing for common trends. Journal of the American statistical Association, 83(404), 1097-1107.
  • Tavakoli, A., & Karimi, F. (2010). Determining the factors affectingi nflation using autoregressive vector model. Paper Presented at the Ninth Conference on Monetary Policy and Foreign Exchange Rates. (in Persian)
  • Tayebi, K., Azerbaijani, K., & Biyari, L. (2009). Egg price forecaste in Iran: comparayion of arch method and artificiial networks. Journal of Agricultural Economics and Development. (Persian)
  • Yazdani, s., & Shajari, s. (2009). The impact of macro econonic indicators on agricultral trade balance Of Iran. american jornal of applied sciences, 1473.1477.

Files

Share

How to cite

Statistics