Cepni, OguzhanChristou, ChristinaGupta, Rangan2023-06-282023-06Cepni, O., Christou, C. & Gupta, R. 2023, 'Forecasting national recessions of the United States with state-level climate risks: evidence from model averaging in Markov-switching models', Economics Letters, vol. 227, art. 111121, pp. 1-6, doi : 10.1016/j.econlet.2023.111121.0165-1765 (print)1873-7374 (online)10.1016/j.econlet.2023.111121http://hdl.handle.net/2263/91233DATA AVAILABILITY: The authors do not have permission to share data.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 their (realized) volatility. We find that forecasts obtained from the DMA combination scheme provide timely updates of US business cycles based on the information content of metrics of state-level climate risks, particularly the volatility of temperature, relative to the corresponding small-scale MS benchmarks that use national-level values of climate change-related predictors.en© 2023 Elsevier B.V. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Economics Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Economics Letters, vol. 227, art. 111121, pp. 1-6, doi : 10.1016/j.econlet.2023.111121.Bayesian model averaging (BMA)Dynamic model averaging (DMA)Markov-switching modelBusiness fluctuations and cyclesClimate risksModel averagingSDG-08: Decent work and economic growthUnited States (US)Postprint Article