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Forecasting seasonal UK consumption components

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Clements, Michael P. and Smith, Jeremy (Jeremy P.) (1997) Forecasting seasonal UK consumption components. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.487).

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Abstract

Periodic models for seasonal data allow the parameters of the model to vary across the different seasons. This paper uses the components of UK consumption to see whether the periodic autoregressive (PAR) model yields more accurate forecasts than non-periodic models, such as the airline model of Box and Jenkins (1970), and autoregressive models that pre-test for (seasonal) unit roots. We analyse possible explanations for the relatively poor forecast performance of the periodic models that we find, notwithstanding the apparent support such models receive from the data in-sample.

Item Type:

Working or Discussion Paper (Working Paper)

Subjects:

H Social Sciences > HB Economic Theory
D History General and Old World > DA Great Britain

Divisions:

Faculty of Social Sciences > Economics

Library of Congress Subject Headings (LCSH):

Consumption (Economics) -- Great Britain, Consumption (Economics) -- Mathematical models, Seasonal variations (Economics) -- Great Britain, Economic forecasting, Periodic functions

Series Name:

Warwick economic research papers

Publisher:

University of Warwick, Department of Economics

Place of Publication:

Coventry

Official Date:

12 June 1997

Dates:

Date	Event
12 June 1997	Published

Number:

No.487

Number of Pages:

Status:

Not Peer Reviewed

Access rights to Published version:

Open Access

Funder:

Economic and Social Research Council (Great Britain) (ESRC)

Grant number:

L116251015 (ESRC)

References:

Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61, 821–856.
Boswijk, H. P., and Franses, P. H. (1996). Unit roots in periodic autoregressions. Journal of Time Series Analysis, 17, 221–245.
Box, G. E. P., and Jenkins, G.M. (1970). Time Series Analysis, Forecasting and Control. San Francisco: Holden-Day.
Clements,M. P., andHendry, D. F. (1996). Intercept corrections and structural change. Journal of Applied
Econometrics, 11, 475–494.
Clements, M. P., and Hendry, D. F. (1997a). An empirical study of seasonal unit roots in forecasting. International Journal of Forecasting. Forthcoming.
Clements, M. P., and Hendry, D. F. (1997b). Forecasting economic processes. International Journal of Forecasting. Forthcoming.
Diebold, F. X., and Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business and Economic Statistics, 13, 253–263.
Engle, R. F. (1982). Autoregressive conditional heteroscedasticity, with estimates of the variance of
United Kingdom inflations. Econometrica, 50, 987–1007.
Fildes, R., and Makridakis, S. (1995). The impact of empirical accuracy studies on time series analysis and forecasting. International Statistical Review, 63, 289–308.
Franses, P. H. (1996). Periodicity and Stochastic Trends in Economic Time Series. Oxford: Oxford University Press.
Franses, P. H., and Koehler, A. B. (1994). Model selection strategies for time series with increasing seasonal variation. revised version of Econometric Institute Report 9308, Erasmus University Rotterdam.
Franses, P. H., and McAleer, M. (1995). Testing nested and non-nested periodically integrated autoregressive models. Center for Economic Research Discussion Paper No. 9510, Tilburg University.
Franses, P. H., and Paap, R. (1994). Model selection in periodic autoregressions. Oxford Bulletin of Economics and Statistics, 56, 421–439.
Franses, P. H., and Vogelsang, T. J. (1995). Testing for seasonal unit roots in the presence of changing seasonal means. Econometric Institute Report 9532, Erasmus University Rotterdam.
Godfrey, L. G. (1978). Testing for higher order serial correlation in regression equations when the regressors
include lagged dependent variables. Econometrica, 46, 1303–1313.
Hylleberg, S., Engle, R. F., Granger, C. W. J., and Yoo, B. S. (1990). Seasonal integration and cointegration. Journal of Econometrics, 44, 215–238.
Hylleberg, S., Jørgensen, C., and Sørensen, N. K. (1993). Seasonality in macroeconomic time series. Empirical Economics, 18, 321–325.
Jarque, C. M., and Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence
of regression residuals. Economics Letters, 6, 255–259.
Osborn, D. R. (1988). Seasonality and habit persistence in a life cycle model of consumption. Journal of Applied Econometrics, 3, 255–266.
Osborn, D. R. (1990). A survey of seasonality in UK macroeconomic variables. International Journal of Forecasting, 6, 327–336.
Osborn, D. R., and Smith, J. P. (1989). The performance of periodic autoregressive models in forecasting seasonal UK consumption. Journal of Business and Economic Statistics, 7, 117–127.
Perron, P. (1989). The great crash, the oil price shock and the unit root hypothesis. Econometrica, 57, 1361–1401.
Perron, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics, 8, 153–162.
Proietti, T. (1996). Spurious periodic autoregressions. Mimeo, Dipartimento di Scienze Statistiche, Universit`
a di Perugia.
Ramsey, J. B. (1969). Tests for specification errors in classical linear least squares regression analysis.
Journal of the Royal Statistical Society B, 31, 350–371.
Schwartz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 462–464.
Smith, J., and Otero, J. (1997). Structural breaks and seasonal integration. Economic Letters. Forthcoming.
Taylor, A. M. R. (1997). On the practical problems of computing seasonal unit root tests. International Journal of Forecasting. Forthcoming.
Tiao, G. C., and Grupe, M. R. (1980). Hidden periodic autoregressive-moving average models in time series data. Biometrika, 67, 365–373.