Forecasting with demand systems

Six systems of consumer demand equations are considered using seasonally adjusted quarterly U.K. data. The homogeneity and symmetry restrictions are tested where appropriate and are only convincingly rejected by one model. The estimated models are used to generate forecasts using fourteen post-sample observations and a simple habit formation model is found to be superior. Each system is tested for parameter constancy over the forecast period and only the dynamic models pass this test. The results highlight the importance of dynamics in demand systems but suggest that simpler structures may be more appropriate for forecasting. The use of small-sample adjusted test statistics can have a dramatic impact on inferences drawn. © 1990.