Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T08:51:30.808Z Has data issue: false hasContentIssue false
  • English
  • Français

Modeling Pork Supply Response and Price Volatility: The Case of Greece

Published online by Cambridge University Press:  26 January 2015

Anthony N. Rezitis  and
Konstantinos S. Stavropoulos
Anthony N. Rezitis
Affiliation:
Department of Business Administration of Food and Agricultural Enterprises, School of Natural Resources and Enterprise Management, University of Ioannina, Agrinio, Greece
Konstantinos S. Stavropoulos
Affiliation:
Department of Business Administration of Food and Agricultural Enterprises, School of Natural Resources and Enterprise Management, University of Ioannina, Agrinio, Greece
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper examines the supply response of the Greek pork market. A GARCH process is used to estimate expected price and price volatility, while price and supply equations are estimated jointly. In addition to the standard GARCH model, several different symmetric, asymmetric, and nonlinear GARCH models are estimated. The empirical results indicate that among the estimated GARCH models, the quadratic NAGARCH model seems to better describe producers' price volatility, which was found to be an important risk factor of the supply response function of the Greek pork market. Furthermore, the empirical findings show that feed price is an important cost factor of the supply response function and that high uncertainty restricts the expansion of the Greek pork sector. Finally, the model provides forecasts for quantity supplied, producers' price, and price volatility.

Keywords

asymmetryGARCHpork supplyprice volatilityC510D200Q110
Type
Research Article
Information
Journal of Agricultural and Applied Economics , Volume 41 , Issue 1 , April 2009 , pp. 145 - 162
Copyright
Copyright © Southern Agricultural Economics Association 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Antonovitz, F., and Roe, T. “A Theoretical and Empirical Approach to the Value of Information in Risky Markets.” The Review of Economics and Statistics 68(1986):105–14.Google Scholar
Antonovitz, F., and Green, R. “Alternative Estimates of Fed Beef Supply Response to Risk.” American Journal of Agricultural Economics 72,2(1990):475–87.CrossRefGoogle Scholar
Aradhyula, S.V., and Holt, M.T. “Risk Behavior and Rational Expectations in the U.S. Broiler Market.” American Journal of Agricultural Economics 71,4(1989):892–902.CrossRefGoogle Scholar
Bhati, U.N. “Supply and Demand Responses for Poultry Meat in Australia.” Australian Journal of Agricultural Economics 31(1987):256–65.Google Scholar
Bollerslev, T. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics 31(1986):307–27.Google Scholar
Bollerslev, T., and Wooldridge, J. “Quasi-Maximum Likelihood Estimation and Inference in Dynamic Models with Time-Varying Covariances.” Econometric Reviews 11(1992):143–72.Google Scholar
Chavas, J.P. “On the Economic Rationality of Market Participants: The Case of Expectations in the U.S. Pork Market.” Journal of Agricultural and Resource Economics 24(1999):19–37.Google Scholar
Davidson, R., and MacKinnon, J.G.. Estimation and Inference in Econometrics. Oxford University Press, New York, 1993.Google Scholar
Engle, R.F., “Discussion: Stock Market Volatility and the Crash of 87.” Review of Financial Studies 3(1990):103–106.CrossRefGoogle Scholar
Engle, R.F., “Autoregressive Conditional Heteroskedasticity with Estimates of the Variances of the United Kingdom Inflation.” Econometrica 50(1982):987–1007.CrossRefGoogle Scholar
Engle, R.F., and Bollerslev, T. “Modeling the Persistence of Conditional Variances.” Econometric Reviews 5(1986):1–50.Google Scholar
Engle, R.F., Lilien, D.M., and Robins, R.P. “Estimating Time Varying Risk Premium in the Term Structure: The ARCH-M Model.” Econometrica 55(1987):391–407.CrossRefGoogle Scholar
Engle, R.F., and Ng, V. “Measuring and Testing the Impact of News in Volatility.” The Journal of Finance 48(1993):1749–78.CrossRefGoogle Scholar
Gillespie, J.M., and Fulton, J.R. “A Markov Chain Analysis of Hog Production Firms in the United States.” Agribusiness 17,4(2001):557–70.CrossRefGoogle Scholar
Gjolberg, O., and Bengtsson, B.A. “Forecasting Quarterly Hog Prices: Simple Autoregressive Models vs. Naive Predictions.” Agribusiness 13,6(1997):663–79.3.0.CO;2-1>CrossRefGoogle Scholar
Glosten, L., Jarannathan, R., and Runkle, D. “Relationship Between the Expected Value and Volatility of the Nominal Excess Return on Stocks.” The Journal of Finance 48(1993):1779–802.Google Scholar
Goodwin, T.H., and Sheffrin, S.M. “Testing the Rational Expectations Hypothesis in an Agricultural Market.” The Review of Economics and Statistics 64(1982):658–67.CrossRefGoogle Scholar
Hayenga, M.L., and Hacklander, D. “Monthly Suppy-Demand Relationships for Fed Cattle and Hogs.” American Journal of Agricultural Economics 52(1970):353–44.CrossRefGoogle Scholar
Holt, M.T., and Aradhyula, S.V. “Price Risk in Supply Equations: An Application of GARCH Time-Series Models to the U.S. Broiler Market.” Southern Economic Journal 57(1990):230–42.CrossRefGoogle Scholar
Holt, M.T., “Endogenous Risk in Rational Expectations Commodity Models: A Multivariate Generalized ARCH-M Approach.” Journal of Empirical Finance 5(1998):99–129.CrossRefGoogle Scholar
Holt, M.T., and Johnson, S.R. “Supply Dynamics in the U.S. Hog Industry.” Canadian Journal of Agricultural Economics 36(1988):313–35.Google Scholar
Holt, M.T., and Moschini, G. “Alternative Measures of Risk in Commodity Models: An Analysis of Sow Farrowing Decisions in the United States.” Journal of Agricultural and Resource Economics 17,1(1992):1–12.Google Scholar
Huntziger, R. “Market Analysis with Rational Expectations Hypothesis.” Journal of Econometrics 10(1979):265–87.Google Scholar
Just, R. “An Investigation of the Importance of Risk in Farmer's Decisions.” American Journal of Agricultural Economics 56(1974):14–25.Google Scholar
Koo, W.W., Petry, T.A., and Anderson, C. “An Econometric Analysis of Supply Response for Cattle and Hogs” Agricultural Economics Report No. 233 North Dakota State University, Department of Agribusiness and Applied Economics, 1988.Google Scholar
Kuiper, W.E., and Meulenberg, M.T.G. “Cointegration and Prediction Analysis of Market Supply in the Dutch Pig Farming Industry.” European Review of Agriculture Economics 24,2(1997):285–312.CrossRefGoogle Scholar
Mackinnon, J.G. “Model Specification Tests and Artificial Regression.” Journal of Economic Literature 30,1(1992):102–46.Google Scholar
Nelson, D. “Conditional Heteroskedasticity in Asset Returns: A New Approach.” Econometrica 59(1991):347–70.CrossRefGoogle Scholar
Nyars, L., and Vizvari, B. “On the Estimation of the Supply Function of the Hungarian Pork Market.” Journal of Central European Agriculture 4(2005):521–30.Google Scholar
Pagan, A. “Econometric Issues in the Analysis of Regressors with Generated Regressors. International.” Economic Review 3(1984):221–47.Google Scholar
Pagan, A., and Ullah, A. “The Econometric Analysis of Models with Risk Terms.” Journal of Applied Econometrics 3(1988):87–105.CrossRefGoogle Scholar
Pietola, K.S., and Wang, H.H. “The Value of Price and Quantity Fixing Contracts for Piglets in Finland.” European Review of Agriculture Economics 27,4(2000):431–37.CrossRefGoogle Scholar
Press, W.H., Flannery, B.P., Teukolsky, S.A., and Vetterling, W.T.. Numerical Recipes in C: The Art of Scientific Computing. Cambridge, UK: Cambridge University Press, 1988.Google Scholar
Rezitis, A., and Stavropoulos, K.S. “Supply Response in the Greek Broiler Industry: Application of GARCH Models under Rational Expectations.” Paper presented at the Hellenic Operational Research Society Conference, Arta, Greece, June 21-23, 2007a.Google Scholar
Rezitis, A., “Modeling Meat Supply Response under Rational Expectations and CAP Reforms: Application to the Greek Sheep Industry” Working Paper, University of Ioannina, Agrinio, Greece, 2007b.Google Scholar
Richardson, R.A., and O'Connor, J.G. “Changes in the Structure of Supply Response in the Australian Pig Industry.” Review of Marketing and Agricultural Economics 46,3(1978):220–37.Google Scholar
Schwert, G.W. “Why Does Stock Market Volatility Change Over Time?” The Journal of Finance 44(1989):1115–53.Google Scholar
Seale, J.L., and Shonkwiler, J.S. “Rationality, Price Risk and Response.” Southern Journal of Agricultural Economics 19(1987):111–18.Google Scholar
Sentana, E. “Quadratic ARCH Models.” The Review of Economic Studies 62(1995):639–61.Google Scholar
Tamini, L.D., and Gervais, J.-P. “Developing Economic Indexes for the Quebec Hog/Pork Industry.” Canadian Journal of Agricultural Economics 53(2005):1–23.Google Scholar
Taylor, S. Modelling Financial Time Series. New York: Wiley, 1986.Google Scholar
Yang, J., Hainh, M., and Leatham, D. “Agricultural Liberalization Policy and Commodity Price Volatility: A GARCH Application.” Applied Economics Letters 8(2001):593–98.Google Scholar
Zheng, Y, Kinnucan, H.W., and Thompson, H. “News and Food Price Volatility.” Applied Economics 40(2008):1629–35.Google Scholar