Kurukulasuriya and Ajwad (2004) apply the Ricardian approach to farm level data from Sri Lanka. This additional level of detail allows the authors to control for a host of individual household and farmer characteristics such as the farmer’s human and physical capital. Increases in precipitation have a positive and significant impact on net revenues, whereas temperature has a strong negative impact. Other important variables include the level of education of the head of the household and land tenure status.

Mendelsohn et al. (2004a) address the problem of weather stations often being distant from one another and concentrated mainly in urban areas, especially in developing countries. Measures of climate in between stations as required by Ricardian analyses are often inferred using spatial statistical techniques to interpolate the data. Satellite measures, by contrast, directly observe surface temperature, although they do have trouble measuring some relevant phenomenon such as precipitation. These authors found that satellite data often outperformed weather station data in terms of their ability to explain variation in farm value.

Mendelsohn et al. (2004b) examine the role of climate averages and climate variance in determining farm values. When used together, climate averages explain the bulk of variation in agricultural performance, while variance improves the explanatory power of the regressions only slightly.

On the whole, the available studies confirm the existence of a nonlinear relationship between climate variables and agricultural performance and highlight the importance of using seasonal rather than annual averages for climate variables. The availability of water supplies also appears to be a critical determinant of agricultural performance. The Ricardian approach applied to the issue of climate change nevertheless suffers from a number of limitations both in methodology and in the manner in which it has hitherto been implemented.

The validity of the welfare measures requires unchanged prices (Cline 1996). But climate change will change the global supply of agricultural produce, meaning that prices cannot help but be affected. The Ricardian technique further assumes that a farmer will, when confronted with a change in climate, immediately behave in ways similar to a farmer long accustomed to farming in such conditions. If the Ricardian approach predicts significant losses of productivity even with full and immediate adaptation then the reality will be worse.<sup>9</sup> Fixed capital may become maladapted because of climate change (Quiggin & Horowitz 1999).

The Ricardian technique assumes that trade in agricultural produce is sufficient to equalize the returns on differentiated factors of production in all locations.<sup>10</sup> But impediments to the movement of goods might prevent prices for land of identical quality being equalized, particularly for land in different countries. Pooling information on land values from two or more countries might result in attempting to fit a single regression to what are essentially separate markets.

In the developing country context, data on agricultural land prices are seldom available and studies tend to use net revenues instead. But using net revenues assumes that the year studied is representative of the long run profitability of agriculture. If the survey year is atypical it might distort the results. Calculating net revenues also presents problems: valuing household labor inputs and the produce consumed by subsistence farms can be very difficult.

> 9 Transitional costs are the difference between the maximum value of net revenues per acre following perfect adaptation and the net revenues actually realized by the farmer given his lack of knowledge with respect to the new best crops to grow and how to grow them.

> 10 This is the factor price equalization theorem.

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