temperatures farmers choose to have fewer beef cattle, chickens and sheep but more goats and dairy cattle. Finally, in Table 8d, large farmers’ expected income falls by an average of 26% with 2.5 ° C warming and 67% with a 5 ° C warming. A 15% decrease in precipitation is expected to increase large livestock farmers’ incomes by 2%.

# **_AOGCM scenarios_**

We also examined a set of climate change scenarios predicted by AOGCMs. The climate scenarios reflect the A1 SRES scenarios from the following models: CCC (Boer et al. 2000), CCSR (Emori et al. 1999), and PCM (Washington et al. 2000). For each model, we examined country level climate change scenarios in 2020, 2060, and 2100. For each climate scenario, we added the change in temperature predicted by each climate model to the baseline temperature in each district. We also multiplied the percentage change in precipitation predicted by each climate model by the baseline precipitation in each district or province. This gave us a new climate for every district in Africa for each model and each time period.

Table 9 summarizes the climate scenarios of the three models for the years 2020, 2060, and 2100. The models predict a broad set of scenarios consistent with the range of outcomes in the most recent IPCC (Intergovernmental Panel on Climate Change) report (Houghton et al. 2001). In 2100, PCM predicts a 2 ° C temperature increase in Africa, CCSR a 4 ° C increase, and CCC a 6 ° C increase. Rainfall predictions are noisier: PCM predicts a 10% increase in rainfall in Africa, CCC a 10% decrease, and CCSR a 30% decrease. In addition to the mean rainfall in Africa varying substantially across the scenarios, there is also substantial variation in rainfall across countries within each scenario.

Examining the path of climate change over time reveals that temperatures are predicted to increase steadily until 2100 for all three models. Precipitation predictions, however, vary across time: CCC predicts a declining trend, CCSR an initial decrease, and then increase, and decrease again, and PCM an initial increase, and then decrease, and increase again.

We used the parameters from our estimated models to simulate the impacts of climate change on the expected revenue of livestock management under various scenarios. Table 10 examines the results using the models estimated for all farms. Table 10a shows the changes in the probabilities of choosing a particular animal for each climate scenario. All the scenarios predict that farmers would choose fewer beef cattle and chickens, but more goats and sheep. The choice of dairy cattle, however, depends on the scenarios. On average, the probabilities of choosing beef cattle decrease by 1% in 2020, 2% in 2060 and 3% in 2100. The probability of choosing sheep increases over the same period.

We show the changes in the conditional net incomes per animal in Table 10b. The CCC model predicts net income from beef cattle will steadily decrease over the next century. PCM predicts a substantial drop in income from beef cattle until 2060, but the drop stabilizes afterwards. CCSR predicts a substantial drop in income from beef cattle through 2060, but an increase afterward. Net incomes for sheep and chickens also decrease over time, but the decreases are smaller. The responses for dairy cattle and goats are dependent on the scenarios, but generally change little.

16