Agricultural sectors play a key role in the economics of climate change. Land as an input to agricultural production is one of the most important links between economy and the biosphere, representing a direct projection of human action on the natural environment. Agricultural management practices and cropping patterns have a vast effect on biogeochemical cycles, freshwater availability and soil quality. Agriculture also plays an important role in emitting and storing greenhouse gases. Thus, to consistently investigate climate policy and future pathways for the economic and natural environment, a realistic representation of agricultural land-use is essential. Computable General Equilibrium (CGE) models have increasingly been used to this purpose. CGE models simulate the simultaneous equilibrium in a set of interdependent markets, and are especially suited to analyze agricultural markets from a global perspective. However, modelling agricultural sectors in CGE models is not a trivial task, mainly because of differences in temporal and geographical aggregation scales. The aim of this study is to overview some proposed modelling strategies, by reviewing the available literature and highlighting the different trade-offs involved in the various approaches
