Forecasting National Recessions of the United States with State-Level Climate Risks: Evidence from Model Averaging in Markov-Switching Models
Oguzhan Cepni,
Christina Christou () and
Rangan Gupta
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Christina Christou: School of Economics and Management, Open University of Cyprus, 2252, Latsia, Cyprus
No 202252, Working Papers from University of Pretoria, Department of Economics
Abstract:
This paper utilizes Bayesian (static) model averaging (BMA) and dynamic model averaging (DMA) incorporated into Markov-switching (MS) models to forecast business cycle turning points of the United States (US) with state-level climate risks data, proxied by temperature changes and its (realized) volatility. We find that forecasts obtained from the DMA combination scheme provide timely updates of the US business cycles based on the information content of the metrics of state-level climate risks, particularly volatility of temperature, relative to the corresponding small-scale MS benchmarks that use national-level values of climate change-related predictors.
Keywords: Business fluctuations and cycles; Climate risks; Markov-switching models; Model averaging (search for similar items in EconPapers)
JEL-codes: C22 C53 E32 E37 Q54 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2022-10
New Economics Papers: this item is included in nep-env and nep-for
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Related works:
Journal Article: Forecasting national recessions of the United States with state-level climate risks: Evidence from model averaging in Markov-switching models (2023) 
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:202252
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