Bayesian model selection and prediction with empirical applications: comments

Article Abstract:

A recent study by Peter C.B. Phillips proposes the use of the posterior information criterium (PIC) to select economic forecasting models. The application of PIC, which had earlier been established by Phillips and Werner Ploberger, to macro-economic time series for the US economy revealed that they perform better than the fixed-format AR(93) model with linear trend for the selection of forecasting models. However, further research is needed before PIC can be established as better than other model selection criteria such as the posterior odds criterium and time-varying parameter.

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Bayesian prediction: a response

Article Abstract:

Comments on a recent study on the use of posterior information criterium (PIC) in the selection of economic forecasting models have largely been favorable. The few points raised against the study include its allegation that PIC is better than the posterior odds criterium (POC) in forecasting model selection. However, closer study revealed that PIC is indeed better than POC in model selection.

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Trending time series and macroeconomic activity: Some present and future challenges

Article Abstract:

Some challenges for econometric research on trending time series are discussed in relation to some perceived needs of macroeconomics and macroeconomic policy making. [C] 2001 Elsevier Science S.A. All rights reserved. JEL classification: C32; C53; E10 Keywords: Breaks; Growth; Policy intervention; Productivity; Trend mechanisms; Unit roots

United States, Economics, Research and Development in the Social Sciences and Humanities, Research, Economic research

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