A service provided by the WU Library and the WU IT-Services

Should I Stay or Should I Go? Bayesian Inference in the Threshold Time Varying Parameter (TTVP) Model

Huber, Florian and Kastner, Gregor and Feldkircher, Martin (2016) Should I Stay or Should I Go? Bayesian Inference in the Threshold Time Varying Parameter (TTVP) Model. Research Report Series / Department of Statistics and Mathematics, 130. WU Vienna University of Economics and Business, Vienna.

Download (636Kb) | Preview


We provide a flexible means of estimating time-varying parameter models in a Bayesian framework. By specifying the state innovations to be characterized trough a threshold process that is driven by the absolute size of parameter changes, our model detects at each point in time whether a given regression coefficient is con stant or time-varying. Moreover, our framework accounts for model uncertainty in a data-based fashion through Bayesian shrinkage priors on the initial values of the states. In a simulation, we show that our model reliably identifies regime shifts in cases where the data generating processes display high, moderate, and low numbers of movements in the regression parameters. Finally, we illustrate the merits of our approach by means of two applications. In the first application we forecast the US equity premium and in the second application we investigate the macroeconomic effects of a US monetary policy shock.

Item Type: Paper
Keywords: Change point model / Threshold mixture innovations / Structural breaks / Shrink- age / Bayesian statistics / Monetary policy
Classification Codes: JEL C11, C32, C52, E42
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Gregor Kastner
Date Deposited: 19 Sep 2016 09:13
Last Modified: 25 Jan 2019 09:23
FIDES Link: https://bach.wu.ac.at/d/research/results/87252/
URI: http://epub.wu.ac.at/id/eprint/5173


View Item