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- Title
FORECASTING US INFLATION USING DYNAMIC GENERAL-TO-SPECIFIC MODEL SELECTION.
- Authors
Bagdatoglou, George; Kontonikas, Alexandros; Wohar, Mark E.
- Abstract
ABSTRACT We forecast US inflation using a standard set of macroeconomic predictors and a dynamic model selection and averaging methodology that allows the forecasting model to change over time. Pseudo out-of-sample forecasts are generated from models identified from a multipath general-to-specific algorithm that is applied dynamically using rolling regressions. Our results indicate that the inflation forecasts that we obtain employing a short rolling window substantially outperform those from a well-established univariate benchmark, and contrary to previous evidence, are considerably robust to alternative forecast periods.
- Subjects
UNITED States; MATHEMATICAL models; INFLATION forecasting; PRICE inflation; MACROECONOMIC models; ECONOMIC indicators; DYNAMIC models; AVERAGING method (Differential equations)
- Publication
Bulletin of Economic Research, 2016, Vol 68, Issue 2, p151
- ISSN
0307-3378
- Publication type
Article
- DOI
10.1111/boer.12041