Resource information
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 which species farmers choose:
a primary choice multinomial logit, an optimal portfolio
multinomial logit, and a demand system multivariate probit.
Comparing the results of the three methods of estimating
species selection reveals that the three approaches yield
similar results. Using data from over 9,000 African
livestock farmers in 10 countries, the analysis finds that
farmers are more likely to choose to have livestock as
temperatures increase and as precipitation decreases. Across
all methods of estimating choice, livestock farmers in
warmer locations are less likely to choose beef cattle and
chickens and more likely to choose goats and sheep. As
precipitation increases, cattle and sheep decrease but goats
and chickens increase. The authors simulate the way
farmers' choices might change with a set of uniform
climate changes and a set of climate model scenarios. The
uniform scenarios predict that warming and drying would
increase livestock ownership but that increases in
precipitation would decrease it. The climate scenarios
predict a decrease in the probability of beef cattle and an
increase in the probability of sheep and goats, and they
predict that more heat-tolerant animals will dominate the
future African landscape.
