# **SUMMARY**

This paper develops the structural Ricardian method, a new approach to modeling agricultural performance using cross-sectional evidence, and uses the method to study animal husbandry in Africa. The traditional Ricardian approach measures the interaction between climate and agriculture (Mendelsohn et al. 1994; Seo et al. 2005) but it does not reveal how farmers actually adapt. It is consequently difficult to compare traditional Ricardian results with microeconomic models built from the details of agronomic research (e.g. Adams et al. 1990, 1999; Reilly et al. 1996). The Model is intended to estimate the structure beneath Ricardian results in order to understand how farmers change their behavior in response to climate. In this African livestock example, the Structural Ricardian Model estimates which species are selected, the number of animals per farm, and the net revenue per animal. All three of these elements are climate sensitive.

A three-equation model is developed to estimate each of the choices facing a farmer. For each farm, a primary animal is defined as the species that is observed to earn the greatest net revenue on that farm. A multinomial logit is then estimated to predict which primary animal each farmer selects. Given the primary animal chosen, the second equation estimates the number of animals of that type per farm. The final equation estimates the net revenue per animal by species.

The model is used to study the sensitivity of African animal husbandry decisions to climate. A survey of over 5000 livestock farmers in ten countries reveals that the selection of species, the net income per animal, and the number of animals are all highly dependent on climate. As climate warms, net income across all animals will fall but especially across beef cattle. The fall in net income causes African farmers to reduce the number of animals on their farms. The fall in relative revenues also causes them to shift away from beef cattle and towards sheep and goats. All farmers will lose income but the most vulnerable farms are large African farms that currently specialize in beef cattle.

Small livestock and large livestock farms respond to climates differently. Small farms are diversified, relying on dairy cattle, goats, sheep and chickens. Large farms specialize in dairy and especially beef cattle. Estimating a separate multinomial logit selection model for small and large farms reveals that the two types of farm choose species differently and specifically have different climate response functions. The regressions of the number of animals also reveal that large farms are more responsive to climate.

Several climate scenarios are tested using the estimated three-equation model. Some simple uniform climate change scenarios are tested that assume a warming of 2.5 _°_ C or 5 _°_ C and a change in precipitation of +15% or -15%. The purpose of these scenarios is to see how different districts across Africa respond to identical changes in climate. Uniform warming causes the probability of choosing beef cattle to fall where these are currently being chosen. In contrast, warming causes the probability of choosing sheep to rise, especially across the Sahel. Warming causes the number of animals to fall but especially beef cattle. Finally warming causes the net revenue from all animals to fall, but especially from beef cattle. Increasing precipitation causes the probability of choosing beef cattle, dairy cattle and sheep to fall and that of goats and chickens to increase. Wetter climatic conditions reduce the desired number and net revenue of beef cattle, dairy cattle, 2