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Common factors and the dynamics of cereal prices. A forecasting perspective

Author

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  • Marek Kwas
  • Alessia Paccagnini
  • Michal Rubaszek
Abstract
This article investigates what determines the price dynamics of the main cereals: barley, maize, rice and wheat. Using an extensive dataset of monthly time series covering the years 1980 - 2019, we extract four different common factors explaining the dynamics of commodity prices, exchange rates, financial and macroeconomic indicators. Next, we examine whether these factors are useful in explaining the movements of cereal prices. We show that models incorporating all four factors outperform significantly the naive random walk model in out-of-sample forecasting competition, especially for longer horizons. However, they have only marginally better performance than a simpler model based on the commodity factor alone.

Suggested Citation

  • Marek Kwas & Alessia Paccagnini & Michal Rubaszek, 2020. "Common factors and the dynamics of cereal prices. A forecasting perspective," CAMA Working Papers 2020-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2020-47
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    Cited by:

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    2. Marek Kwas & Michał Rubaszek, 2021. "Forecasting Commodity Prices: Looking for a Benchmark," Forecasting, MDPI, vol. 3(2), pages 1-13, June.

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    More about this item

    Keywords

    Cereal prices; Forecasting; Factor models; Autoregressive models.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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