Time Varying Dimension Models
Chan, Joshua C.C. and Koop, Gary and Leon-Gonzalez, Roberto and Strachan, Rodney W. (2011) Time Varying Dimension Models. Discussion paper. University of Strathclyde, Glasgow.
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Abstract
Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomics. However, TVP models are parameter-rich and risk over-fitting unless the dimension of the model is small. Motivated by this worry, this paper proposes several Time Varying dimension (TVD) models where the dimension of the model can change over time, allowing for the model to automatically choose a more parsimonious TVP representation, or to switch between different parsimonious representations. Our TVD models all fall in the category of dynamic mixture models. We discuss the properties of these models and present methods for Bayesian inference. An application involving US inflation forecasting illustrates and compares the different TVD models. We find our TVD approaches exhibit better forecasting performance than several standard benchmarks and shrink towards parsimonious specifications.
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Item type: Monograph(Discussion paper) ID code: 67934 Dates: DateEvent11 May 2011PublishedNotes: Discussion paper. Subjects: Social Sciences > Economic Theory Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 21 May 2019 14:50 Last modified: 04 Jun 2024 00:59 URI: https://strathprints.strath.ac.uk/id/eprint/67934