# **INTRODUCTION**

The vulnerability of the agricultural sector to exogenous shocks continues to be of interest to policymakers working on rural development issues. This is especially a problem for low-income countries because agriculture accounts for a larger fraction of their economy, accounting for about 60 percent of the labor force and producing on average 25 percent of GDP. In contrast, agriculture accounts for only 15% of GDP in middle-income countries and only 5% of GDP in the United States (World Bank 2003). Climate change has increasingly been recognized as a longer-term threat to the agriculture sector <u>(IPCC 2001). The general consensus is that changes in temperature</u> and precipitation normals will lead to adjustments in land and water regimes that will affect agricultural productivity (IPCC 1997). The temperature and precipitation normals reflect long-term weather patterns and are defined as the average of 30 years of weather. Qualitative evidence suggests that developing countries in the low latitudes will be especially vulnerable. Not only are such regions near or beyond optimal temperature conditions for agricultural production (so any warming will only worsen existing production conditions), but also many of the countries are subject to technological, resource, and institutional constraints that are likely to constrain productivity (Mendelsohn and Dinar 1999). Yet, the magnitude of likely impacts from climate change in developing countries is not well understood.

Although research suggests that global food production is likely to be robust, experts predict tropical regions will see a reduction in agricultural yields <u>(Mendelsohn and Dinar 1999; Kurukulasuriya and Rosenthal 2003). Large adverse impacts on</u> productivity, especially among smallholders who depend on farm productivity as a source of livelihood and subsistence can lead to a rise in poverty levels (World Bank 2003). Consequently, this study contributes to the limited quantitative research on measuring the potential impacts of climate change in low-latitude developing countries where detailed quantitative estimates of the impact of climate change and variability are scarce.

The primary interest of the study is to estimate the impact of changes in long-term climate (temperature and precipitation normals) on the agricultural performance of smallholders (i.e. households that cultivate less than 10 acres of farmland) in Sri Lanka. Perhaps fortunately, there are no observed changes in climate normals over time yet in Sri Lanka. We consequently cannot turn to time series analysis to understand how farms are affected by climate change. Instead, we adopt a cross-sectional approach, the Ricardian approach (Mendelsohn et al 1994). The intuition here is that if climate conditions in region A become more like current climate conditions in region B, then farmers in region A will adapt and become more like farmers are currently in region B. Past Ricardian studies have strictly depended on aggregate district or county level data (Mendelsohn et al 1994; <u>1999; 2001). In this study, we use observations about individual</u> farmers, rather than aggregate data, to conduct the analysis.

The use of individual farm data poses new opportunities and challenges. One of the opportunities is that there is a rich set of data about individual farmer characteristics that can serve as better controls. The individual farm data have many socio-economic and demographic characteristics that are likely to affect farm productivity. This micro data is generally not available at the district or county level. Consequently, a micro level 11