Agricultural commodity price dynamics and their determinants: A comprehensive econometric approach

Crespo-Cuaresma, Jesús; Hlouskova, JaroslavaORCID: and Obersteiner, Michael (2021) Agricultural commodity price dynamics and their determinants: A comprehensive econometric approach. Journal of Forecasting, 40 (7), pp. 1245-1273.

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We present a comprehensive modelling framework aimed at quantifying the response of agricultural commodity prices to changes in their potential determinants. The problem of model uncertainty is assessed explicitly by concentrating on specification selection based on the quality of short-term out-of-sample forecasts (1 to 12 months ahead) for the price of wheat, soybeans and corn. Univariate and multivariate autoregressive models (autoregressive [AR], vector autoregressive [VAR] and vector error correction [VEC] specifications, estimated using frequentist and Bayesian methods), specifications with heteroskedastic errors (AR conditional heteroskedastic [ARCH] and generalized AR conditional heteroskedastic [GARCH] models) and combinations of these are entertained, including information about market fundamentals, macroeconomic and financial developments, and climatic variables. In addition, we assess potential non-linearities in the commodity price dynamics along the business cycle. Our results indicate that variables measuring market fundamentals and macroeconomic developments (and, to a lesser extent, financial developments) contain systematic predictive information for out-of-sample forecasting of commodity prices and that agricultural commodity prices react robustly to shocks in international competitiveness, as measured by changes in the real exchange rate.

Item Type: Article in Academic Journal
Keywords: commodity prices, forecast averaging, forecasting, model uncertainty, vector autoregressive model
Funders: European Union, H2020 Food
Research Units: Current Research Groups > Macroeconomics and Business Cycles
Date Deposited: 06 Oct 2021 09:44
Last Modified: 13 Dec 2023 12:45
DOI: 10.1002/for.2768
ISSN: 0277-6693

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