Predicting recessions with leading indicators: model averaging and selection over the business cycle
AbstractThis paper evaluates the ability of several commonly followed economic indicators to predict business cycle turning points. As a baseline, forecasts from univariate models are combined by taking averages or by weighting forecasts with model-implied posterior probabilities. These combined forecasts are compared to those from a sophisticated model selection algorithm that allows for nonlinear model speci_cations. The preferred forecasting model is one that allows for nonlinear behavior across the business cycle and combines information from the yield curve with other indicators, especially at very short and very long horizons.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Kansas City in its series Research Working Paper with number RWP 13-05.
Date of creation: 2013
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-08-05 (All new papers)
- NEP-BEC-2013-08-05 (Business Economics)
- NEP-FOR-2013-08-05 (Forecasting)
- NEP-MAC-2013-08-05 (Macroeconomics)
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