The long-run average outcome for an area will often include some fraction of losses. Although the individual data capture these short-run outcomes, we assume that the estimated cross-sectional model reflects long run consequences. The model captures how farmers adjust to climate over decades not weather year by year. We consequently assume that the predictions we make using this model are long-run not short-run predictions. We consequently censor losses when they occur in future climate scenarios to avoid giving the impression that farmers would continue to grow food in places that are permanently unprofitable. If areas become permanently unsuitable for growing food, we assume that there will be no farming activity. We assume that farm income will go to zero in these cases.

# **DATA**

By the close of the 1990s, the agriculture sector in Sri Lanka accounted for 26% of GDP and employed nearly 50% of the total rural labor force. The most important export crops are tea, rubber and coconut. Other important crops include paddy rice, fruits, vegetables, spices and cereals.

The island is characterized by diverse agro-ecological zones including dry, wet and intermediate climatic regions (RRDI 2003). Two annual monsoonal seasons produce significant geographical variation on temperature and precipitation. The monsoons lead to two distinct cropping seasons in the island. The most significant season ( _Maha_ season) is from October to February and brings rain to the entire country. The second season (Yala season) is from May to September but only a part of the country receives rain during this period. These monsoons lead to a substantial dry and intermediate zone in the lowlands and some very wet highlands. The majority of irrigated and drought-prone farms are in the dry and intermediate lowlands.

We utilize a unique dataset that combines the detailed household-level information from the Sri Lanka Integrated Survey (SLIS) 1999-2000 (World Bank 2001) with climate data from the FAO (FAO 2000). The SLIS survey was conducted across all 25 administrative districts (9 provinces) in the country between October 1999 and the third quarter of 2000. The dataset is based on interviews of 7,500 households and includes data on 35,181 individuals. Included in the sample are farming households who were administered a detailed farm production (input and output) questionnaire. Given reservations by the World Bank regarding the quality of the data from the North and Eastern Provinces of the country due to regional hostilities at the time, these two regions are excluded from our analysis. These two regions contain 8 districts, leaving 17 districts in our sample. This is an important area for paddy cultivation and it is our intention to examine this region when more reliable data become available. In this paper, we limit our analysis to smallholder agricultural producers<sup>3</sup> . The resulting sample contains 1,552 households, which represent (when weighted) around 900,000 smallholders in Sri Lanka.

> 3  In order to reduce measurement error, 10 extreme observations (in terms of net revenue per hectare) were removed from the sample. Quantile analysis at the median, with the extreme observations included, are similar to the results in the paper.

14