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Agricultural Commodity Price Dynamics: Evidence from BVAR Models

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  • Olga Bondarenko

    (National Bank of Ukraine)

Abstract

Agricultural commodity markets have experienced bouts of significant volatility in recent years, drawing the attention of policymakers all over the world. This paper studies the dynamics of wheat and corn prices since 1999 through the lens of standard BVAR models in the spirit of Kilian (2009) and Kilian and Murphy (2014). I use monthly revisions of the WASDE supply projections to overcome the problem of limited availability of high-frequency data and develop an indicator of aggregate demand for grains, following Baumeister et al. (2020). The estimated elasticities are generally consistent with theory and earlier studies and produce reasonable historical decompositions. Models are helpful in forecasting exercises, including conditional forecasts and alternative scenarios while they perform no better than the random walk in short-term unconditional forecasting.

Suggested Citation

  • Olga Bondarenko, 2023. "Agricultural Commodity Price Dynamics: Evidence from BVAR Models," Working Papers 03/2023, National Bank of Ukraine.
    • Handle: RePEc:ukb:wpaper:03/2023
    as

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    References listed on IDEAS

    as
    1. McPhail, Lihong Lu & Du, Xiaodong & Muhammad, Andrew, 2012. "Disentangling Corn Price Volatility: The Role of Global Demand, Speculation, and Energy," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(3), pages 401-410, August.
    2. Michael J. Roberts & Wolfram Schlenker, 2013. "Identifying Supply and Demand Elasticities of Agricultural Commodities: Implications for the US Ethanol Mandate," American Economic Review, American Economic Association, vol. 103(6), pages 2265-2295, October.
    3. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    4. Eugenio Bobenrieth & Brian Wright & Di Zeng, 2013. "Stocks-to-use ratios and prices as indicators of vulnerability to spikes in global cereal markets," Agricultural Economics, International Association of Agricultural Economists, vol. 44(s1), pages 43-52, November.
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    More about this item

    Keywords

    commodity prices; corn; wheat; BVAR models; demand elasticity; supply elasticity; historical decomposition; USDA supply forecasts; WASDE;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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