UK Macroeconomic Forecasting with Many Predictors : Which Models Forecast Best and When Do They Do So?
Koop, Gary and Korobilis, Dimitris (2009) UK Macroeconomic Forecasting with Many Predictors : Which Models Forecast Best and When Do They Do So? Discussion paper. University of Strathclyde, Glasgow.
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Abstract
Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting models as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output growth and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.
ORCID iDs
Koop, Gary ORCID: https://orcid.org/0000-0002-6091-378X and Korobilis, Dimitris;-
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Item type: Monograph(Discussion paper) ID code: 67798 Dates: DateEvent2009PublishedNotes: Published as a paper within the Discussion Papers in Economics, No. 09-17 (2009) Subjects: Social Sciences > Economic Theory Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 14 May 2019 10:31 Last modified: 20 Sep 2024 00:46 URI: https://strathprints.strath.ac.uk/id/eprint/67798