Quantifying Non-Linear Weather Effects on Staple and Cash Crops in Climate Risk Clusters: A Panel Data Analysis

Abstract

This study investigates the long-term impacts of climate change on crop yields by analyzing global historical data from 1961 to 2024 across 25 selected countries, to to reveal how historical weather patterns affected crop yields in the most vulnerable regions of the world. Utilizing crop yield data from FAOSTAT and weather time series from the World Bank Climate Knowledge Portal, three distinct climate risk groups of countries were defined: Group 1 (strong warming, stable precipitation), Group 2 (no significant warming, strong precipitation decrease), and Group 3 (mild warming, strong precipitation decrease). A Linear Mixed-Effects Model (LMM) was employed to quantify the non-linear impacts and interactions of climate variables, including annual temperature maximums, minimums, precipitation, warm and cold spell durations, and the Standardized Precipitation Evapotranspiration Index, on primary staple and cash crops. Results reveal a stark regional asymmetry. In temperate regions (Group 1), agrotechnological advancements have successfully cushioned climate shocks over the past decades, although this buffering effect faces biophysical limits due to non-linear temperature thresholds, particularly for root crops like potatoes and sugarbeet. In tropical–subtropical areas (Group 2) and the Mediterranean (Group 3), climate extremes exert severe pressure on vital crops. Prolonged warm spells significantly reduce yields for perennials like bananas, coffee, and dates, while other Mediterranean crops like olives thrive under longer warm spells. While country-specific institutional capacities often generate substantial yield heterogeneity, major exceptions emerge for staple crops like wheat in Group 2 and barley in Group 3, where low Intraclass Correlation Coefficients (ICC) demonstrate that regional climatic drivers override national boundaries. The findings underscore that universal climate strategies are inefficient, and policymakers must prioritize crop-specific and localized adaptation frameworks for future food security.