FORECASTING US INFLATION USING DYNAMIC GENERAL‐TO‐SPECIFIC MODEL SELECTION |
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| Authors: | George Bagdatoglou Alexandros Kontonikas Mark E Wohar |
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| Affiliation: | 1. Deloitte Economic Consulting, London, UK;2. Adam Smith Business School, University of Glasgow, UK;3. Department of Economics, University of Nebraska–Omaha, USA |
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| 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. |
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| Keywords: | dynamic general‐to‐specific inflation forecasting C22 C52 E31 E37 |
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