Abstract

Setting reference rates for policy to reduce emissions from deforestation and forest degradation is challenging. This challenge is reflected in the number of proposals for reference rate design. In this paper I show how these proposals have basic structural weaknesses that increase the likelihood of reference rates being set with error. This leads to higher costs of reduced-deforestation policy. I propose that reference rates be designed to minimize the cost of forecast error. These ideas are illustrated through forecasting agricultural land expansion in deforesting countries.

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