EconPapers    
Economics at your fingertips  
 

Should I stay or should I go? A latent threshold approach to large‐scale mixture innovation models

Florian Huber, Gregor Kastner and Martin Feldkircher

Journal of Applied Econometrics, 2019, vol. 34, issue 5, 621-640

Abstract: We propose a straightforward algorithm to estimate large Bayesian time‐varying parameter vector autoregressions with mixture innovation components for each coefficient in the system. The computational burden becomes manageable by approximating the mixture indicators driving the time‐variation in the coefficients with a latent threshold process that depends on the absolute size of the shocks. Two applications illustrate the merits of our approach. First, we forecast the US term structure of interest rates and demonstrate forecast gains relative to benchmark models. Second, we apply our approach to US macroeconomic data and find significant evidence for time‐varying effects of a monetary policy tightening.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
https://doi.org/10.1002/jae.2680

Related works:
Working Paper: Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models (2018) Downloads
Working Paper: Should I stay or should I go? A latent threshold approach to large-scale mixture innovation models (2018) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:japmet:v:34:y:2019:i:5:p:621-640

Ordering information: This journal article can be ordered from
http://www3.intersci ... e.jsp?issn=0883-7252

Access Statistics for this article

Journal of Applied Econometrics is currently edited by M. Hashem Pesaran

More articles in Journal of Applied Econometrics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

 
Page updated 2025-03-22
Handle: RePEc:wly:japmet:v:34:y:2019:i:5:p:621-640