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Mixed frequency machine learning forecasting of the growth of real gross fixed capital formation in the United States: the role of extreme weather conditions

Author

Listed:
  • Sheng, Xin
  • Cepni, Oguzhan
  • Gupta, Rangan
  • Markovski, Minko

Abstract

We forecast the quarterly growth rate of real gross fixed capital formation of the United States using the information content of a monthly metric of extreme weather conditions, while controlling for a set of principal components derived from a large data set of economic and financial indicators. In this regard, we utilize a Mixed Frequency Machine Learning framework over the sample period of 1974:Q1 to 2022:Q1. Our results show that incorporating monthly data on severe climatic conditions, especially the information contained in relatively high (above-the-mean) extreme weather values, significantly outperforms not only the benchmark autoregressive model, but also the econometric framework that includes the macro-financial factors when forecasting the growth rate of quarterly real gross fixed capital formation.

Suggested Citation

  • Sheng, Xin & Cepni, Oguzhan & Gupta, Rangan & Markovski, Minko, 2026. "Mixed frequency machine learning forecasting of the growth of real gross fixed capital formation in the United States: the role of extreme weather conditions," Finance Research Letters, Elsevier, vol. 106(C).
    • Handle: RePEc:eee:finlet:v:106:y:2026:i:c:s1544612326007993
    DOI: 10.1016/j.frl.2026.110271
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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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