for a particular parcel of land will depend on the productive advantages of that land. In equilibrium more fertile land attracts a higher rental value equal to the increase in net revenues. Otherwise a farmer could increase profits by using more or less of such land, thereby altering its rental value.

The productive value of particular characteristics of land such as soil quality may therefore be derived from their observed importance in determining rental values or, equivalently, net revenues. The productive value of land characteristics may also be derived from the sale value of land, in which case the implicit prices of characteristics reflect their contribution to productivity in perpetuity – an observation credited to David Ricardo and developed by, among others, Palmquist (1989). Several authors have already used the Ricardian technique to estimate the implicit value of a variety of farmland characteristics, including topsoil depth and drainage. Others have used the technique to determine the implicit value of climate.

In Mendelsohn et al. (1994) US farmland prices and net revenues were regressed on climate, soil and other variables. Much of the data used related to countywide averages, and spatial statistical techniques were used to construct countywide climatic variables from weather station data. The quadratic climate terms were significant, indicating a nonlinear relationship between farm value and climate.

Kumar and Parikh (1998) analyzed the climate sensitivity of Indian agriculture using the Ricardian approach. District level estimates of annual net revenues were regressed on climate and other socio-economic variables. Difficulties were encountered in estimating input and output prices where farms were subsistence farms and a major weakness of the study is that it captures the effect of climate only on the marketed farm sector.

Sanghi et al. (1998) conducted a Ricardian study for Brazil using district averages for net revenues and land values. They determined that the impact of climate change on agricultural productivity is negative, with the most pronounced impacts being felt in the central and western regions.

Maddison (2000) presents a Ricardian study for England and Wales. The study is unusual in that it is apparently the only one to have used actual sale price at the level of the individual farm to determine the value of climate. The results point to the importance to agriculture of frost days in winter. Maddison also found that the price per hectare of land depends strongly on the size of the farm.

Using census tract data, Reinsborough (2003) examined the extent to which climate explains variation in farm values and farm net revenues for Canada. The results are of particular interest because Canadian agriculture arguably stands to benefit from global warming. Reinsborough finds that climate variables are statistically significant along with latitude and population density, but that the potentially beneficial impacts of climate change cannot be ascertained with any degree of precision.

Precipitation and temperature alone do not necessarily provide a good indication of water available for agricultural production as water supplies often come from elsewhere. Mendelsohn and Dinar (2003) consider the impact of water availability on agricultural outcomes across the US, and whether adding variables which capture the availability of ground water and surface water to the standard Ricardian model changes the climate sensitivity of agriculture. Their results suggest that the ability to irrigate land can provide a valuable buffer against adverse climatic conditions.

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