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.

ORCID iDs

Chan, Joshua C.C., Koop, Gary

, Leon-Gonzalez, Roberto and Strachan, Rodney W.;

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Item metadata

Item type:	Monograph(Discussion paper)
ID code:	67934
Dates:	Date Event 11 May 2011 Published
Notes:	Discussion paper.
Keywords:	time varying parameter, TVP, time varying dimension, TVD, bayesian inference, Economic Theory, Economics, Econometrics and Finance (miscellaneous)
Subjects:	Social Sciences > Economic Theory
Department:	Strathclyde Business School > Economics
Depositing user:	Pure Administrator
Date deposited:	21 May 2019 14:50
Last modified:	14 Jul 2021 01:05
URI:	https://strathprints.strath.ac.uk/id/eprint/67934

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