Nicolas Hardy, Dimitris Korobilis
arXiv 3 Dec 2025 · Econometrics
arXiv:2512.03763 · PDF · DOI · OpenAlex · Extracted main text
We revisit macroeconomic time-varying parameter vector autoregressions (TVP-VARs), whose persistent coefficients may adapt too slowly to large, abrupt shifts such as those during major crises. We explore the performance of an adaptively-varying parameter (AVP) VAR that incorporates deterministic adjustments driven by observable exogenous variables, replacing latent state innovations with linear combinations of macroeconomic and financial indicators. This reformulation collapses the state equation into the measurement equation, enabling simple linear estimation of the model. Simulations show that adaptive parameters are substantially more parsimonious than conventional TVPs, effectively disciplining parameter dynamics without sacrificing flexibility. Using macroeconomic datasets for both the U.S. and the euro area, we demonstrate that AVP-VAR consistently improves out-of-sample forecasts, especially during periods of heightened volatility.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Primiceri, G. E (2005) Time varying structural vector autoregressions and monetary policy | 1.000 | 6 | 4 | 100% |
| 2 | Carriero, A., Clark, T. E., Marcellino, M., and Mertens, E (2023) Addressing COVID-19 outliers in BVARs with stochastic volatility | 0.928 | 4 | 3 | 100% |
| 3 | Korobilis, D (2022) A new algorithm for structural restrictions in Bayesian vector autoregressions self | 0.843 | 3 | 3 | 100% |
| Kimetal1998 | unmatched citation key Kimetal1998 | 0.737 | 3 | 2 | 100% |
| 5 | McCracken, M. and Ng, S (2020) Fred-qd: A quarterly database for macroeconomic research | 0.737 | 3 | 2 | 100% |
| 6 | Amir-Ahmadi, P., Matthes, C., and Wang, M.-C (2020) Choosing prior hyperparameters: W ith applications to time-varying parameter models | 0.644 | 2 | 2 | 100% |
| 7 | Arias, J. E., Rubio-Ramírez, J. F., and Shin, M (2023) Macroeconomic forecasting and variable ordering in multivariate stochastic volatility models | 0.644 | 2 | 2 | 100% |
| 8 | Fischer, M. M., Hauzenberger, N., Huber, F., and Pfarrhofer, M (2023) General Bayesian time-varying parameter vector autoregressions for modeling government bond yields | 0.644 | 2 | 2 | 100% |
| 9 | Stock, J. H. and Watson, M. W (2007) Why has US inflation become harder to forecast? | 0.644 | 2 | 2 | 100% |
| ChanJeliazkov2009 | unmatched citation key ChanJeliazkov2009 | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 53 scored citations. 2 of these could not be matched to a bibliography entry, so only the citation key is shown.