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2010-2014

Food Price Spikes in a Warming World

KenyaMaizeExpt-Burke.jpg

Photo credit: 
Marshall Burke

Researchers

Principal Investigator
Senior Fellow
  • Associate Professor, Earth System Science
  • William Wrigley Fellow at the Freeman Spogli Institute for International Studies and Stanford Woods Institute for the Environment

There are reasons to expect more frequent price spikes, given that it will be more common to see conditions that are considered extreme. Other factors could dampen rises, however, including responses such as raising grain storage or changing trade policies. - David Lobell

In this project, we seek to improve quantitative understanding of price spikes in general and the potential effects of climate change on these spikes in particular. The project is divided into five steps. Part A will consider the relationship between weather outcomes and yields for the four major staple crops: corn, soybeans, wheat and rice. Part B establishes how weather distributions are predicted to change in various general circulation models.

Part C combines the crop yield response function of part A with the predicted changes in weather outcomes to derive a distribution of yield outcomes. Specifically, we will consider how (1) yield variability increases with higher average temperatures because of the nonlinear response of yield to temperature; (2) yield variability increases with potential increased climate variability and frequency of extreme weather events; (3) bad weather events could become more or less correlated between key regions and thereby affect the extent to which idiosyncratic weather shocks may no longer average out, influencing aggregate yield variability; (4) production could become more or less concentrated in particular regions and thus again influence the variability of aggregate yield outcomes.

Part D considers estimation of fundamental demand, supply and storage elasticities of agricultural commodities using random exogenous yield shocks as an instrument. These elasticities are required to translate yield distributions from part C into price distributions. Part E will use results from parts C and D to simulate the effects of changing climatic conditions on food prices. We will examine how the increased supply variability will affect optimal storage behavior.

More frequent price spikes give an added incentive to accumulate inventories, thereby dampening the predicted increase in price spikes. Similarly, continued expansion of irrigated agriculture can make yields less variable. On the other hand, some government policies, like export restrictions have the potential to increase price variability, and may also affect storage behavior.

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