Hierarchical Shrinkage in Time-varying Parameter Models
Belmonte, Miguel and Koop, Gary and Korobilis, Dimitris (2011) Hierarchical Shrinkage in Time-varying Parameter Models. Discussion paper. University of Strathclyde, Glasgow.
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Abstract
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.
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Item type: Monograph(Discussion paper) ID code: 68009 Dates: DateEvent30 June 2011PublishedNotes: Discussion paper. Subjects: Social Sciences > Economic Theory Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 23 May 2019 10:59 Last modified: 02 Jun 2024 06:12 URI: https://strathprints.strath.ac.uk/id/eprint/68009