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Forecasting with Dynamic Models using Shrinkage-based Estimation

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Author Info
Andrea Carriero () (Queen Mary, University of London)
George Kapetanios () (Queen Mary, University of London)
Massimiliano Marcellino () (Bocconi University and EUI)

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Abstract

The paper provides a proof of consistency of the ridge estimator for regressions where the number of regressors tends to infinity. Such result is obtained without assuming a factor structure. A Monte Carlo study suggests that shrinkage autoregressive models can lead to very substantial advantages compared to standard autoregressive models. An empirical application focusing on forecasting inflation and GDP growth in a panel of countries confirms this finding.

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File URL: http://www.econ.qmul.ac.uk/papers/doc/wp635.pdf
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Publisher Info
Paper provided by Queen Mary, University of London, Department of Economics in its series Working Papers with number 635.

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Date of creation: Oct 2008
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Handle: RePEc:qmw:qmwecw:wp635

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Related research
Keywords: Shrinkage; Forecasting;

Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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