Regime transplants in GDP growth forecasting: A recipe for better predictions?
AbstractFormal testing and estimation of nonlinear relations require a substantial number of observations which are typically lacking in annual models. In this paper, a novel two-step procedure is introduced to model nonlinearities in yearly asset-price based leading indicator models for growth. In the first step, quarterly data are explored to test for the presence of regime switches, the identif ication of transition variables and estimation of the accompanying thresholds. In the second step, we implement the quarterly thresholds in the annual indicator models. Results for the US and the Netherlands show that the annual forecasts improve compared to the linear model, despite the poor out-of-sample performance of the quarterly regime switching models.
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Bibliographic InfoPaper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 106.
Date of creation: Aug 2006
Date of revision:
leading indicators; gdp growth; non-linear models.;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-09-30 (All new papers)
- NEP-ECM-2006-09-30 (Econometrics)
- NEP-ETS-2006-09-30 (Econometric Time Series)
- NEP-FOR-2006-09-30 (Forecasting)
- NEP-MAC-2006-09-30 (Macroeconomics)
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