Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/339199 
Year of Publication: 
2025
Series/Report no.: 
Working Paper No. 16/2025
Publisher: 
Örebro University School of Business, Örebro
Abstract: 
This paper proposes a parsimonious reparametrization for time-varying parameter models that captures smooth dynamics through a low-dimensional state process combined with B-spline weights. We apply this framework to TVP-VARs, yielding Moderate TVP-VARs that retain the interpretability of standard specifications while mitigating overfitting. Monte Carlo evidence shows faster estimation, lower bias, and strong robustness to knot placement. In U.S. macroeconomic data, moderate specifications recover meaningful long-run movements, produce stable impulse responses and deliver superior density forecasts and predictive marginal likelihoods relative to conventional TVP-VARs, particularly in high-dimensional settings.
Subjects: 
Time-Varying Parameter models
High-dimensional Vector Autoregressions
Stochastic Volatility
B-splines
Macroeconomic Forecasting
JEL: 
C11
C33
C53
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.