implies knowledge about the local conditions. On the other, people migrate in pursuit of better pastures or opportunities. It is not clear whether this variable would be important.

# **PREDICTIONS**

In this section, we utilize the coefficients from Model 2 in order to estimate the impact on net revenues in Sri Lanka of global warming. We rely on the climate forecasts of four different climate models (PCM (Washington et al 2000), CCSR (Emori et al 1999), CSIRO (Gordon and O’Farrell 1997), and HAD3 (Gordon et al 2000). Each model predicts precipitation and temperature by 2100 assuming greenhouse gas emissions continue unabated. We use the climate scenarios specific to Sri Lanka to analyze the impact on farm profitability (see table 3). The four models predict different annual increases in temperature normals of 1.7<sup>◦</sup> C (PCM), 2.7<sup>◦</sup> C (CCSR), 2.8<sup>◦</sup> C (CSIRO) and 3.3<sup>◦</sup> C (HAD3) and in precipitation normals of 50% (PCM), 6% (CCSR), 5% (CSIRO) and 10% (HAD3). Both temperature and precipitation are playing a role in the predicted agricultural impacts.

The very large increase in precipitation coupled with the very small warming predicted by PCM leads to large increases in overall productivity and benefits (30%). CCSR and CSIRO predict medium warming scenarios for Sri Lanka with small increases in precipitation that lead to gains for the aggregate agricultural sector of 11% and 6% respectively. HAD3, which reflects large reductions in precipitation and increases in temperature for Sri Lanka, predicts that net revenues per hectare could reduce by 23%.

The results of our study highlight the importance of precipitation relative to temperature for agriculture in tropical countries. While scientists demonstrate greater confidence regarding temperature changes in the tropics under climate change, there is far greater uncertainty about precipitation. The results from the four climate models reveal that change in precipitation levels, not temperature, drives productivity. In particular, reductions in precipitation especially when it is needed for local agricultural practices (as evident from HAD3) can have large adverse effects. In contrast, beneficial rainfall during key agricultural months can lead to substantial dividends even if accompanies by higher annual temperatures. Additional research in tropical countries must thus focus on measuring impacts on agricultural productivity due to changes in rainfall.

These aggregate effects for the country however mask the diversity of impacts likely to affect the heterogeneous geographic regions. Table 4 presents the net revenues per hectare for 17 districts under the four separate climate scenarios and current conditions (see also Figure 3). Effects vary from losses of 35% to gains of more than 50% in net revenues depending on the climate scenario. In general, the South East and the North Central regions experience a large negative impact from climate change. Conversely, the Central province is positively affected and the South West is also spared or stands to benefit marginally. From an agro-ecological standpoint, the large negative impacts are experienced in the predominantly dry zone climates. The dry zones are also currently the most stressed from climate pressures, although these regions are currently used for rice cultivation when combined with effective irrigation. On the other hand, positive impacts are expected in the higher elevation intermediate zones (these regions contain tea crops and other high value fruits and vegetables). In general the higher 20