The economic impact of global warming likely varies across farms because of differences in climate, technology, and adaptive capacity. Therefore, aggregate estimates of the average effect of warming may be insufficient to model climate change vulnerability. In this study, I propose a quantile model for the distributional effect of climate change. I estimate inter-quantile regressions of land value on climate using agricultural census data for 464,277 commercial farms in Brazil. I find that the effects of climate change in Brazilian agriculture vary significantly by climate, land quality, and irrigation choice. A 1 degrees C of warming is more detrimental to farms in warm climates, those with high-quality land, and those using irrigation. A 10 0-mm decrease in annual precipitation is more damaging to farms in dry climates, those with low-quality land, and those using irrigation. The heterogeneity in climate change effects is particularly large within the subset of farms in the warmest or the driest climates, as the most vulnerable farms appear to be those that have reached their limits for climate adaptation. (c) 2020 Elsevier Inc. All rights reserved.
DePaula, G
The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian census data
Journal Of Environmental Economics And Management