Climate Risks and Forecastability of the Weekly State-Level Economic Conditions of the United States

Oguzhan Cepni, Rangan Gupta, Wenting Liao (liaowenting@ruc.edu.cn) and Jun Ma (ju.ma@northeastern.edu)
Additional contact information
Wenting Liao: School of Finance, Renmin University of China, Beijing, People's Republic of China
Jun Ma: Department of Economics, Northeastern University, 301 Lake Hall, Boston, Massachusetts, 02115, United States

No 202251, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we first utilize a Dynamic Factor Model with Stochastic Volatility (DFM-SV) to filter out the national factor from the local components of weekly state-level economic conditions indexes of the United States (US) over the period of April 1987 to August 2021. In the second step, we forecast the state-level factors in a panel data set-up based on the information content of corresponding state-level climate risks, as proxied by changes in temperature and its SV. The forecasting experiment depicts statistically significant evidence of out-of-sample predictability over a one-month- to one-year-ahead horizon, with stronger forecasting gains derived for states that do not believe that climate change is happening and are Republican. We also find evidence of national climate risks in accurately forecasting the national factor of economic conditions. Our analyses have important policy implications from a regional perspective.

Keywords: State-Level Economic Conditions; Climate Risks; Dynamic Factor Model with Stochastic Volatility; Panel Predictive Regression; Forecasting (search for similar items in EconPapers)
JEL-codes: C31 C32 C53 E32 E66 Q54 (search for similar items in EconPapers)
Pages: 14 pages
Date: 2022-10
New Economics Papers: this item is included in nep-env and nep-for
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Journal Article: Climate risks and forecastability of the weekly state‐level economic conditions of the United States (2024)
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