Optimal Forecasts from Markov Switching Models

48 Pages Posted: 16 Dec 2014

See all articles by Tom Boot

Tom Boot

Erasmus University Rotterdam (EUR)

Andreas Pick

Erasmus University Rotterdam (EUR) - Department of Econometrics; De Nederlandsche Bank

Date Written: December 15, 2014

Abstract

We derive optimal weights for Markov switching models by weighting observations such that forecasts are optimal in the MSFE sense. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the effect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substantially when the construction of optimal weights takes uncertainty around states into account. Performance of the optimal weights is shown through simulations and an application to US GNP, where using optimal weights leads to significant reductions in MSFE.

Keywords: Markov switching models, forecasting, optimal weights, GNP forecasting

JEL Classification: C25, C53, E37

Suggested Citation

Boot, Tom and Pick, Andreas, Optimal Forecasts from Markov Switching Models (December 15, 2014). De Nederlandsche Bank Working Paper No. 452, Available at SSRN: https://ssrn.com/abstract=2538507 or http://dx.doi.org/10.2139/ssrn.2538507

Tom Boot (Contact Author)

Erasmus University Rotterdam (EUR) ( email )

Burgemeester Oudlaan 50
3000 DR Rotterdam, Zuid-Holland 3062PA
Netherlands

Andreas Pick

Erasmus University Rotterdam (EUR) - Department of Econometrics ( email )

P.O. Box 1738
3000 DR Rotterdam
Netherlands

De Nederlandsche Bank ( email )

PO Box 98
1000 AB Amsterdam
Amsterdam, 1000 AB
Netherlands

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