Premium
OPTIMAL FORECAST COMBINATION UNDER REGIME SWITCHING*
Author(s) -
Elliott Graham,
Timmermann Allan
Publication year - 2005
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/j.1468-2354.2005.00361.x
Subject(s) - variable (mathematics) , computer science , monte carlo method , range (aeronautics) , markov chain , series (stratigraphy) , markov chain monte carlo , econometrics , latent variable , variety (cybernetics) , process (computing) , mathematics , artificial intelligence , statistics , machine learning , engineering , mathematical analysis , paleontology , biology , aerospace engineering , operating system
This article proposes a new forecast combination method that lets the combination weights be driven by regime switching in a latent state variable. An empirical application that combines forecasts from survey data and time series models finds that the proposed regime switching combination scheme performs well for a variety of macroeconomic variables. Monte Carlo simulations shed light on the type of data‐generating processes for which the proposed combination method can be expected to perform better than a range of alternative combination schemes. Finally, we show how time variations in the combination weights arise when the target variable and the predictors share a common factor structure driven by a hidden Markov process.