Economic impact of climate change on African agriculture

Using a cross sectional dataset of over 9,500 farms in Senegal, Niger, Burkina Faso, Ghana, Egypt, Ethiopia, Kenya, Cameroon, Zambia, South Africa and Zimbabwe, this dissertation explores using the Ricardian approach the likely economic impact of climate change on the agriculture sector in Africa. The results show that the elasticity of net revenue with respect to temperature and precipitation is -1.3 and 0.4, respectively. The elasticity of net revenue with respect to temperature is -1.6 for dryland farms but 0.5 for irrigated farms. The elasticity of net revenue with respect to precipitation is 0.5 for dryland farms but only 0.1 for irrigated farms. Three climate change scenarios from Atmosphere/Ocean General Circulation Model or Atmosphere/Ocean Global Climate Models (AOGCMs) reveal that African net revenues may rise by up to {dollar}97 billion if future warming is mild and wet but that net revenues would fall by up to {dollar}48 billion if future climates are hot and dry. Dryland farms would be affected the most by either beneficial or harmful scenarios. Irrigated farms are relatively resilient to climate change.; The dissertation also addresses a methodological deficiency in that previous Ricardian analyses of agriculture either omitted, or treated, irrigation as though it is exogenous. A choice model of irrigation is developed in the context of a Ricardian model of cropland. An analysis is undertaken of how climate affects the decision to employ irrigation and then how climate affects the net revenues of dryland and irrigated land. This Ricardian "selection" model, using a modified Heckman model, is more appropriate for modeling irrigation and the endogeneity of irrigation.; Finally, the dissertation compares how well satellite versus weather station measurements of climate predicts agricultural performance. Weather stations entail sporadic observations that require interpolation where observations are missing. In contrast, satellites have trouble measuring some ground phenomenon such as precipitation but they provide complete spatial coverage of various parameters over a landscape. The results suggest that satellites provide promising measures of temperature but that ground station data may still be preferred for measuring precipitation in rural settings.