November 22, 2021
Research Highlight

Higher Sensitivity of Global Agricultural Markets to Interannual Climate Variability

Model results show that uncertainties in farmers’ expectations of market and weather conditions amplify economic variability under changing climate

Photograph of a field on a hill with one half bright green and the other half yellow and harvested

In models, agricultural producers’ imperfect expectations of market and weather conditions generated market fluctuations that then further magnified market responses to climate variability.

The Science

Climate can be thought of as an input to agricultural production, and its impacts on agriculture have been extensively studied for the past three decades. However, the ways interannual variations in biophysical shocks, changes in external factors that can affect agricultural yield, and climate are transformed and transferred to global agricultural markets have been overlooked. To address this issue, researchers refined the temporal resolution of a global economic model. They showed producers’ imperfect expectations of market and weather conditions magnify agriculture market fluctuations. They also found heterogeneity in climate variability across regions. However, international trade considerably mediates regional agricultural market variabilities.

The Impact

This is the first study to systematically examine how global agriculture responds to climate and biophysical variability. Its results illustrate that how farmers form expectations of market and weather conditions plays a key role in assessing agricultural market variability. Incorporating a new decision-making approach showed that standard assumptions in economic models could underestimate the volatility of crop prices by 55%. The new approach considerably enhanced the model’s assessment of trends and variability of climate impacts. These trends are extremely valuable for comparing climate and alternative socioeconomic scenarios. Studying interannual variability provides fundamentally new insights for measuring and understanding climate impacts on global agriculture.

Summary

Most studies assessing climate impacts on agriculture have focused on average changes in market-mediated responses (e.g., changes in land use, production, and consumption). However, the response of global agricultural markets to interannual variability in climate and biophysical shocks is poorly understood and inadequately represented in global economic models. In this study, researchers demonstrated a strong transmission of the interannual variations in climate-induced biophysical yield shocks to agriculture markets when adding a more realistic decision-making approach based on adaptive expectations into the Global Change Analysis Model. Producers’ imperfect expectations of market and weather conditions generated market fluctuations that further magnified market responses to climate variability. The study results showed that assuming perfect foresight, a standard assumption in the economic equilibrium modeling, significantly underestimates the volatility of crop prices and consumption (i.e., on average by 55% and 41%, respectively) when compared to the more realistic decision-making approach. They found heterogeneity in the interannual variability across crops and regions, which international trade can considerably mediate. Studying interannual variability provides fundamentally new insights for measuring and understanding climate impacts on global agriculture. The framework proposed in the study lays the foundation for further investigations of the full range of climate impacts on biophysical and human systems.

PNNL Contact

Katherine Calvin, Pacific Northwest National Laboratory, katherine.calvin@pnnl.gov

Funding

This research was supported by the U.S. Department of Energy, Office of Science, as part of research in MultiSector Dynamics, Earth and Environmental System Modeling Program.

Published: November 22, 2021

X. Zhao et al., “Global agricultural responses to interannual climate and biophysical variabilityEnvironmental Research Letters, 16, 104037 (2021). [DOI: 10.1088/1748-9326/ac2965]