Koop, Gary and Strachan, Rodney and Leon-Gonzalez, Roberto and Chan, Joshua (2012) Time varying dimension models. Journal of Business and Economic Statistics. ISSN 0735-0015 (In Press)
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.
|Keywords:||Bayesian models, time varying parameter model, Economic Theory, Economics and Econometrics, Social Sciences (miscellaneous), Statistics and Probability, Statistics, Probability and Uncertainty|
|Subjects:||Social Sciences > Economic Theory|
|Department:||Strathclyde Business School > Economics|
|Depositing user:||Pure Administrator|
|Date Deposited:||08 Jun 2012 13:24|
|Last modified:||19 Jan 2017 06:20|