Drivers and triggers of international food price spikes and volatility

By Getaw Tadesse, Bernardina Algieri, Matthias Kalkuhl, Joachim von Braun. 2014

381 citations recorded by the source corpus.

The objective of this study is to explore empirical evidence about the quantitative importance of supply, demand, and market shocks for price changes in international food commodity markets. To this end, it distinguishes between root, conditional, and internal drivers of price changes using three empirical models: (1) a price spike model in which monthly food price returns (spikes) are estimated against oil prices, supply and demand shocks, and excessive speculative activity; (2) a volatility model in which annualized monthly variability of food prices is estimated against the same set of variables plus a financial crisis index; and (3) a trigger model that estimates extreme values of price spikes and volatility using quantile regressions. The results point to increasing linkages between food, energy, and financial markets. This explains much of the observed food price spikes and volatility. While financial speculation amplifies short-term price spikes, oil price volatility intensifies medium-term price volatility.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/27525a0d1ecfb0376ede8dc7a49f71844533471c

How researchers see this paper

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In Economics and Econometrics

1. Maximo Torero
2. Matthias Kalkuhl
3. Joachim von Braun

Citations in the corpus

• Worldwide Acreage and Yield Response to International Price Change and Volatility: A Dynamic Panel Data Analysis for Wheat, Rice, Corn, and Soybeans (2015, neutral): “Besides the traditional causes of price fluctuations, agricultural commodities are increasingly connected to energy and financial markets, with potentially destabilizing impacts on prices (Tadesse et al. 2014).”
• Food Price Volatility and Its Implications for Food Security and Policy (2016, methodology): “If we accept the argument that both the variability of a trend and the variability around the trend need to be considered, then it is crucial to identify methods of decomposing price movements into trend variability (explained by long-term factors), variability around the trend (partially related to”