Bayes Models and Forecasts of Australian Macroeconomic Time Series
This paper provides an empirical implementation of some recent work by the author and Werner Ploberger on the development of "Bayes models" for time series. The methods offer a new data-based approach to model selection, to hypothesis testing and to forecast evaluation in the analysis of time series. A particular advantage of the approach is that modelling issues such as lag order, parameter constancy, and the presence of deterministic and stochastic trends all come within the compass of the same statistical methodology, as do the evaluation of forecasts from competing models. The paper shows how to build parsimonious empirical "Bayes models" using the new approach and applies the methodology to some Australian macroeconomic data. "Bayes models" are constructed for 13 quarterly Australian macroeconomic time series over the period 1959(3)-1987(4). These models are compared with certain fixed format models (like an AR(4) + linear trend) in terms of their forecasting performance over the period 1988(1)-1991(4). The "Bayes models" are found to be superior in these forecasting exercises for 10 of the 13 series, while at the same time being more parsimonious in form.
|Date of creation:||Aug 1992|
|Publication status:||Published in Colin P. Hargreaves, ed., Nonstationary Time Series Analysis and Cointegration, 1994, pp. 53-86|
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- Phillips, Peter C.B. & Ploberger, Werner, 1994.
"Posterior Odds Testing for a Unit Root with Data-Based Model Selection,"
Cambridge University Press, vol. 10(3-4), pages 774-808, August.
- Peter C.B. Phillips & Werner Ploberger, 1992. "Posterior Odds Testing for a Unit Root with Data-Based Model Selection," Cowles Foundation Discussion Papers 1017, Cowles Foundation for Research in Economics, Yale University.
- Peter C.B. Phillips, 1991.
"Bayesian Routes and Unit Roots: de rebus prioribus semper est disputandum,"
Cowles Foundation Discussion Papers
986, Cowles Foundation for Research in Economics, Yale University.
- Phillips, P C B, 1991. "Bayesian Routes and Unit Roots: De Rebus Prioribus Semper Est Disputandum," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 435-473, Oct.-Dec..
- Peter C.B. Phillips, 1992.
"Bayesian Model Selection and Prediction with Empirical Applications,"
Cowles Foundation Discussion Papers
1023, Cowles Foundation for Research in Economics, Yale University.
- Phillips, Peter C. B., 1995. "Bayesian model selection and prediction with empirical applications," Journal of Econometrics, Elsevier, vol. 69(1), pages 289-331, September.
- Peter C.B. Phillips & Werner Ploberger, 1991. "Time Series Modelling with a Bayesian Frame of Reference: 1. Concepts and Illustrations," Cowles Foundation Discussion Papers 980, Cowles Foundation for Research in Economics, Yale University.
- Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.