- (iv) Agricultural losses can result from climate variability and the increased frequency of changes in temperatures and precipitation (including droughts and floods).

A large body of literature has developed to analyze these effects, both in developed and in developing countries, although the impact of climate change on agriculture became of interest only in the 1990s. The interest was spurred by the expectation that accumulation of CO2 and other greenhouse gases will lead to global warming and other significant climate changes. Although there are a large number of studies on the effects of climate change in general, and global warming in particular, on agriculture in developed countries, there is a paucity of such studies in developing countries, especially in Africa. However, there is growing interest in studying these effects and making regional comparisons. This section presents a brief review of literature both for developed and developing countries.

Two main methods have been used in the literature to study the impact of climate change on agriculture. The traditional approach is a production function method which relies on empirical or experimental production functions to predict environmental change (Mendelsohn et al. 1994). To overcome the main weakness of this approach<sup>6</sup> most studies employ a method that corrects for the bias in the production function technique by using the economic data on the value of land to analyze the impact of climate on agriculture. This new method, referred to as the Ricardian approach, has, however, been criticized for not fully controlling for the impact of important variables that could also explain the variation in farm incomes; for assuming that prices are constant and adjustment costless; and for possibly yielding biased results when land within locations is heterogeneous and land owners behave optimally (Mendelsohn et al. 1994; Kurukulasuriya & Rosenthal 2003). Timmins (2003) also argues that while the Ricardian method is extremely practical for predicting the consequences of global warming with limited data, it may yield biased results when land use decisions depend on the climate attributes being valued and when land has unobserved attributes that differ with the use to which it is put. The authors argue that using an instrumentation strategy would correct for this bias. Sections 4.2 and 4.3 briefly review some relevant studies that use Ricardian and production function approaches.

# **_4.2 Ricardian approach studies_**

Mendelsohn et al. (1994) use the Ricardian technique to estimate the value of climate in US agriculture using cross-sectional data for about 3000 counties in the US. Their results show that climate has complicated effects on agriculture, which can be highly non-linear and vary by season. Specifically they find that increased temperatures are likely to reduce average farm values, but increased precipitation to improve them. Their results further show that a scenario of increasing temperatures by an average 5 _°_ C and precipitation by a corresponding 8% average leads to a loss in land value from warming to an annual neighborhood damage of 4–5%. However, the same policy change scenario results in a 1% gain when using the croprevenue approach. A number of studies that employ the Ricardian approach have supported findings by Mendelsohn et al. (1994) of an adverse impact of climate change on agriculture.

> 6 The traditional approach has been argued to have a bias in that it overestimates the damage climate change causes to agriculture (Mendelsohn et al. 1994). It is also criticized because price effects cannot satisfactorily be included in domestic level models.

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