Document Type: Original Article

Authors

1 Assistant Professor, Department of Agricultural Economics, Faculty of Agricultural Sciences, University of Guilan

2 MSc of Commercial Management, Islamic Azad University, Rasht branch.

Abstract

Rice plays an especial role in Iranian households' nutrition basket. The volatilities of its price during recent years caused consumers' dissatisfaction. This paper investigates spillover effects of price volatilities (at the wholesale and retail levels) in the Guilan Province rice market. The Generalized Autoregressive Conditional Hetroscedasitic (GARCH) model was used for the monthly time period of 1999 to 2013. As the results of the unit root tests showed, the monthly time series of Sadri-Momtaz variety wholesale price and Sadri-Momtaz variety retail price have unit roots in zero frequency or they are I(1). Considering the amounts of trace and maximum eigen values statistics, there is a long-run relationship between Sadri-Momtaz variety wholesale and retail monthly price time series.  Coefficients  of  normalized cointegration  vector  showed  that,  with  one  percent  increase  (decrease)  in  retail  price,  it  would be likely  that  wholesale  price  could increase  (decrease)  by 0.99  percent. Results of GRACH model revealed that spillover effects exist from the retail price to the wholesale price and vice versa. In addition, price volatility in retail and wholesale levels had positive and significant effects on its own level price volatility. Accordingly, providing proper policy packages in both supply and demand sides were advised.

Graphical Abstract

Highlights

Monthly time series of Sadri-Momtaz rice wholesale and retail price have unit roots in zero frequency.

There is a long-run relationship between Sadri-Momtaz rice wholesale and retail price.

The volatility spillover coefficients in GARCH are positive and statistically significant.

Spillover effects exist from retail price to wholesale price and vice versa in Guilan Province rice market.

Keywords

Main Subjects

Alom, F., Ward, D., & Hu, B. (2010). Cross country mean and colatility spillover effects of food prices: Evidence for Asia and Pacific. International Review of Business Research Papers, 6(5), 334-355.

Apergis, N., & Rezitis, A. (2003). Food price volatility and macroeconomic factor volatility: Heat wave or meteor showers? Applied Economics Letters, 10(1), 155-160.

Bergmann, D., O'Connor, D., & Thummel, A. (2016). An analysis of price and volatility transmission in butter, palm oil and crude oil markets. Agricultural and Food Economics, 1(4), 1-23.

Buguk, C., Hudson, D., & Hanson, T. (2003). Price volatility spillover in agricultural markets: An examination of U.S. catfish markets. Journal of Agricultural Economics, 28(1), 86-99.

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 8(3), 307–327.

Enders, W. (2004). Applied Econometric Time Series. Wiley Press, Hoboken.

Engle, R.F., & Boller-Slev, T. (1982). Modeling the persistence of conditional variances. Econometric Review, 5(1), 1–50.

Engle, R.F., Ito, T., & Lin, W. (1990). Meteor showers or heat waves? Heteroskedastic intra-daily volatility in the foreign exchange market. Econometrica, 15(2), 525–542.

Goodwin, B.K., & Holt, M.T. (1999). Price transmission and asymmetric adjustment in the U.S. beef sector. American Journal of Agricultural Economics, 21(1), 630–637.

Gujarati, N.D. (2003). Basic Econometrics. McGraw-/hill/Irwin Press, New York, USA.

 

Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210.

Kaltalioglu, M., & Soytas, U. (2011). Volatility spillover from oil to food and agricultural raw material markets. Modern Economy, 1(2), 71-76.

Kavoosi-Kalashami, M., Khaligh-Khiyavi, P., & 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.

Kwiatkowski, D., Philips, P.C.B., Schmidt, P., & Shin, Y. (1992). Testing the null hypothesis of stationary against the alternative of a unit root. Journal of Econometrics, 14(2), 159-178.

Lahiani, A., Nguyen, D.K., & Vo, T. (2013). Understanding return and volatility spillovers among major agricultural commodities. The Journal of Applied Business Research, 29(6), 1781-1790.

Ling, S., & McAleer, M. (2003). Asymptotic theory for a vector ARMA-GARCH Model. Econometric Theory, 5(3), 278–308.

Mensi, W., Beljid, M., Boubaker, A., & Managi, S. (2013). Correlations and volatility spillovers across commodity and stock markets: Linking energies, food and gold. Economic Modelling, 7(4), 15-22.

Natcher, W.C., & Weaver R.D. (1999). The transmission of price volatility in the beef markets: A multivariate approach. Presented at the Annual Meeting of the American Agricultural Association, August 8-11, - Nashville, Tennessee, USA.

Rezitis, A. (2003). Volatility spillover effect in Greece consumer meat prices. Agricultural Economics Review, 4(1), 29-36.

Saha, A., & Delgado, C. (1989). The nature and implications for market interventions of seasonal food price variability. In D. Sahn (ed.), Seasonal Variability in Third World Agriculture: the Consequences for Food Security. Baltimore, MD: Johns Hopkins University Press.

Shuang-Ying, W., & Dong, L. (2011). The spillover effects on petrochemical industrial concentration of international oil price. Energy Procedia, 5 (2011), 2444–2448.

Sims, C. (1980). Macroeconomics and reality. Econometrica, 48, 1–48.

Trujillo-Barrera, A., Mallory, M., & Garcia, P. (2011). Volatility spillovers in the U.S. crude oil, corn, and ethanol markets. Paper presented at the NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management St.  Louis, Missouri, April 18-19, USA.

Tsay, R. (1987). Conditional heteroskedastic time series models. Journal of the American Statistical Association, 41(2), 590–604.

Zhou, Z., Dong, H., & Wang, S. (2014). Intraday volatility spillovers between index futures and spot market:  Evidence from China.  2nd  International  Conference  on  Information Technology  and  Quantitative  Management,  Procedia  Computer  Science, 31 (2014), 721–730.