A linear demand system within a seemingly unrelated time series equations framework
AbstractWe consider a Seemingly Unrelated Time Series Equations framework for the linear Almost Ideal Demand system. The framework is applied to a consumer demand system covering nine non-durable commodities. We test for demand homogeneity within a specification where the static linear Almost Ideal Demand system is augmented by three stochastic trends and three stochastic seasonal variables. The homogeneity restriction is rejected for about half of the commodities and in the system as a whole using conventional significance levels. However, when comparing the out-of-sample predictions from a homogeneous and non-homogeneous model, we do not find that the non-homogenous model performs better than the homogeneous one. Moreover, the income and price elasticities calculated under homogeneity restrictions are all of the right sign and have reasonable magnitudes.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Springer in its journal Empirical Economics.
Volume (Year): 32 (2007)
Issue (Month): 1 (April)
Contact details of provider:
Postal: Stumpergasse 56, A-1060 Vienna
Phone: ++43 - (0)1 - 599 91 - 0
Fax: ++43 - (0)1 - 599 91 - 555
Web page: http://link.springer.de/link/service/journals/00181/index.htm
More information through EDIRC
Other versions of this item:
- Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2003. "A linear demand system within a Seemingly Unrelated Time Series Equation framework," Discussion Papers 345, Research Department of Statistics Norway.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Pesaran,H.M. & Shin,Y., 1995.
"Long-Run Structural Modelling,"
Cambridge Working Papers in Economics
9419, Faculty of Economics, University of Cambridge.
- Anderson, G J & Blundell, R W, 1982. "Estimation and Hypothesis Testing in Dynamic Singular Equation Systems," Econometrica, Econometric Society, vol. 50(6), pages 1559-71, November.
- Frank Asche & Cathy R. Wessells, 1997. "On Price Indices in the Almost Ideal Demand System," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1182-1185.
- Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
- Keuzenkamp, Hugo A. & Barten, Anton P., 1995. "Rejection without falsification on the history of testing the homogeneity condition in the theory of consumer demand," Journal of Econometrics, Elsevier, vol. 67(1), pages 103-127, May.
- Anderson, Gordon & Blundell, Richard, 1983. "Testing Restrictions in a Flexible Dynamic Demand System: An Application to Consumers' Expenditure in Canada," Review of Economic Studies, Wiley Blackwell, vol. 50(3), pages 397-410, July.
- Chalfant, James A, 1987. "A Globally Flexible, Almost Ideal Demand System," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(2), pages 233-42, April.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Phillips, P C B, 1991.
"Optimal Inference in Cointegrated Systems,"
Econometric Society, vol. 59(2), pages 283-306, March.
- Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-89, October.
- I. A. Moosa & J. L. Baxter, 2002. "Modelling the trend and seasonals within an AIDS model of the demand for alcoholic beverages in the United Kingdom," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 95-106.
- Anderson, G. J., 1980. "The structure of simultaneous equations estimators : A comment," Journal of Econometrics, Elsevier, vol. 14(2), pages 271-276, October.
- L. Fanelli & M. Mazzocchi, 2002. "A cointegrated VECM demand system for meat in Italy," Applied Economics, Taylor & Francis Journals, vol. 34(13), pages 1593-1605.
- Håvard Hungnes, 2008.
"A Demand System for Input Factors when there are Technological Changes in Production,"
556, Research Department of Statistics Norway.
- Håvard Hungnes, 2011. "A demand system for input factors when there are technological changes in production," Empirical Economics, Springer, vol. 40(3), pages 581-600, May.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Guenther Eichhorn) or (Christopher F Baum).
If references are entirely missing, you can add them using this form.