EconPapers    
Economics at your fingertips  
 

Real‐Time Forecasting Using Mixed‐Frequency VARs With Time‐Varying Parameters

Markus Heinrich and Magnus Reif

Journal of Forecasting, 2025, vol. 44, issue 7, 2055-2066

Abstract: This paper provides a detailed assessment of the real‐time forecast accuracy of a wide range of vector autoregressive models that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed‐frequency time‐varying parameter vector autoregressive model with stochastic volatility. Monte Carlo simulation shows that the novel model is well‐suited to estimate missing monthly observations in an environment that is subject to parameter instability. In a real‐time forecast exercise, the model delivers accurate now‐ and forecasts and, on average, outperforms its competitors. Particularly, inflation and unemployment rate forecasts are more precise.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/for.3276

Related works:
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:jforec:v:44:y:2025:i:7:p:2055-2066

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

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

 
Page updated 2025-10-03
Handle: RePEc:wly:jforec:v:44:y:2025:i:7:p:2055-2066