 A Gaussian smooth transition vector autoregressive model: An application to the macroeconomic effects of severe weather shocksMarkku Lanne and Savi Virolainen Journal of Economic Dynamics and Control, 2025, vol. 178, issue C Abstract: We introduce a new smooth transition vector autoregressive model with a Gaussian conditional distribution and transition weights that, for a pth 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. While the overall evidence is somewhat mixed, this may lend some support to overall adaptation of the U.S. economy to severe weather over time. Keywords: Smooth transition VAR; Nonlinear SVAR; Structural smooth transition vector autoregression; Regime-switching (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:178:y:2025:i:c:s0165188925001289 DOI: 10.1016/j.jedc.2025.105162 Access Statistics for this article Journal of Economic Dynamics and Control is currently edited by J. Bullard, C. Chiarella, H. Dawid, C. H. Hommes, P. Klein and C. Otrok More articles in Journal of Economic Dynamics and Control from Elsevier |
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