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A Gaussian smooth transition vector autoregressive model: An application to the macroeconomic effects of severe weather shocks

Markku Lanne, Savi Virolainen

arXiv 21 Mar 2024 · Econometrics · publishedJournal of Economic Dynamics and Control (2025) · 2 citations (OpenAlex)

arXiv:2403.14216 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We introduce a new smooth transition vector autoregressive model with a Gaussian conditional distribution and transition weights that, for a $p$th order model, depend on the full distribution of the preceding $p$ observations. Specifically, the transition weight of each regime increases in its relative weighted likelihood. This data-driven approach facilitates capturing complex switching dynamics, enhancing the identification of gradual regime shifts. In an empirical application to the macroeconomic effects of a severe weather shock, we find that in monthly U.S. data from 1961:1 to 2022:3, the shock has stronger impact in the regime prevailing in the early part of the sample and in certain crisis periods than in the regime dominating the latter part of the sample. This suggests overall adaptation of the U.S. economy to severe weather over time.

Citation extraction

29
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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Kim H., Matthess C., Phan T. (in press) Severe weather and the macroeconomy0.97715493%
2Virolainen S (2025) sstvars: Toolkit for reduced form and structural smooth transition vector autoregressive models0.9285580%
3Kilian L., Lütkepohl H (2017) Structural vector autoregressive analysis0.9285380%
4Kalliovirta L., Meitz M., Saikkonen P (2016) Gaussian mixture vector autoregression0.9209778%
5Virolainen S (2022) A mixture autoregressive model based on Gaussian and Student's $t$-distributions0.81142100%
6Kheifets I., Saikkonen P (2020) Stationarity and ergodicity of vector STAR models0.79414350%
7Anderson H., Vahid F (1998) Testing multiple equation systems for common nonlinear components0.7373367%
8Koop G., Pesaran M., Potter S (1996) Impulse response analysis in nonlinear multivariate models0.7373367%
9Virolainen S (2025) A statistically identified structural vector autoregression with endogeneously switching volatility regime0.73732100%
10Saikkonen P (2008) Stability of regime switching error correction models under linear cointegration0.6597329%

Showing the top 10 of 30 scored citations.