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 model is intended to estimate the structure beneath Ricardian results in order to understand how...

This paper uses quantitative methods to examine the way African farmers have adapted livestock management to the range of climates found across the African continent. The authors use logit analysis to estimate whether farmers adopt livestock. They then use three econometric models to examine...

This paper analyzes the impact of climate change on animal husbandry in Africa. It regresses the net revenue from raising animals in small and large farms across Africa on climate, soil, and other control variables to test the climate sensitivity of livestock. The study is based on a survey of...

The authors explore how Latin American livestock farmers adapt to climate by switching species. They develop a multinomial choice model of farmer's choice of livestock species. Estimating the models across over 1,200 livestock farmers in seven countries, they find that both temperature and...

The authors explore how Latin American farmers adapt to climate by changing crops. They develop a multinomial choice model of farmer's choice of crops. Estimating the model across over 2,000 farmers in seven countries, they find that both temperature and precipitation affects the crops that...

This study estimates the vulnerability of Latin American agriculture to climate change using a Ricardian analysis of both land values and net revenues. Examining a sample of over 2,500 farms in seven countries, the results indicate both land value and net revenue are sensitive to climate. Both...

This paper estimates a model of a farm that treats the choice of crops, livestock, and irrigation as endogenous. The model is composed of a multinomial choice of farm type, a binomial choice of irrigation, and a set of conditional land value functions. The model is estimated across over 2,000...