Prevailing environmental conditions are some of the many factors that a farmer will take into account when choosing which crops to grow and which livestock to rear. Mendelsohn et al. (1994) argue that cross-sectional evidence might be used to predict how farmers would adapt to a change in environmental conditions. By regressing measures of agricultural outcomes (as revealed by land values or net revenues) on various climate and other variables, they estimated the importance of climate in determining agricultural productivity. Using the Ricardian approach, Mendelsohn et al. predicted much lower damages (and in some scenarios net benefits) to US agriculture as a result of climate change than had previously been forecast.

This paper examines the impact of climate change on African agriculture using the same cross-sectional approach to examine how farmers in 11 countries have adapted to existing climatic conditions.<sup>7</sup> It then estimates the effects of predicted changes in climate while accounting for whatever farmer adaptation might occur. Apart from the geographical domain of its application this study differs from earlier ones by using farmers’ own perceptions of the value of their land. Previous research has by contrast relied on either observed sale prices or net revenues aggregated over geographically large tracts of terrain.<sup>8</sup> The study makes use of high resolution data describing soil quality and runoff. It also confronts the challenges involved in modeling the effect of climate on agriculture in a study that includes countries in the northern and southern hemispheres as well as the tropics.

To anticipate the results, it appears that both temperature and precipitation have a pronounced nonlinear effect on agricultural productivity. Higher temperatures are increasingly detrimental to agricultural activities, whereas more precipitation is beneficial. Runoff is also an important determinant of agricultural productivity. Combining the regression results with scenarios describing the direction and extent of climate change in Africa indicates that sizeable reductions in agricultural productivity are possible in Sub-Saharan Africa, even with cost effective adaptation. Elsewhere the impacts are more modest.

The remainder of the paper is structured as follows. Section 2 comprises a critical review of existing Ricardian analyses and an overview of the theoretical framework underpinning the approach. Section 3 describes the data available for the exercise. Section 4 reports on the results of the regression analysis linking perceived farm values with the structural and environmental attributes of the farm. Section 5 considers the plausibility of the findings and combines the regression results with country specific predictions of climate change for each of the eleven countries to obtain damage cost estimates. The final section concludes.

# **2. Literature review**

Economic theory predicts that where a fixed factor of production prevents entry into an industry the factor in question will command an equilibrium rental price reflecting its productivity. If we calculate the annual net revenue a farmer generates this is the maximum amount he would be willing to pay to rent the land for a year. And when the net revenues from farming exceed the annual rental cost of land the rental rate will be bid up until excess profits are eliminated. Where land is differentiated by quality a farmer’s willingness to pay

> 7 The countries are Burkina Faso, Cameroon, Egypt, Ethiopia, Ghana, Kenya, Niger, Senegal, South Africa, Zambia and Zimbabwe.

> 8 There has been a parallel attempt by Kurukulasuriya and Mendelsohn (2006) to analyze the relationship between net revenues and climate variables using data from the same project.

4