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 logoORCID: https://orcid.org/0000-0002-6091-378X and Korobilis, Dimitris;
  • Item type:Monograph(Discussion paper)
    ID code:67798
    Dates:
    Date
    Event
    20 August 2009
    Published
    Notes: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:11 Nov 2024 16:04
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/67798
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