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Climate Risk and the Volatility of Agricultural Commodity Price Fluctuations: A Forecasting Experiment

Author

Listed:
  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)

Abstract

Using the Heterogeneous Autoregressive Realized Volatility (HAR-RV) model as a modeling platform, we study whether climate-risk factors help to predict out-of-sample the realized volatility of movements of agricultural commodity prices. Our main finding is that climaterisk factors improve the out-of-sample performance of the HAR-RV model mainly at longer forecast horizons (month or beyond). Our main finding is robust to estimating the HAR-RV model by the ordinary least squares technique, and to using various shrinkage estimators. We discuss the implications of our results for policymakers and investors.

Suggested Citation

  • Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risk and the Volatility of Agricultural Commodity Price Fluctuations: A Forecasting Experiment," Working Papers 202177, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202177
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    More about this item

    Keywords

    Climate risks; Realized volatility; Agricultural commodities; Forecasting;
    All these keywords.

    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
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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