Publication: Exploring Adaptation to Climate Change in Agriculture : The Potential of Cross-Sectional Analysis
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2005-07
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2012-08-13
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Scientists are confident of a link between greenhouse gas emissions, the increasing concentration of those gases in the atmosphere, and climate change. However, the final impacts from climate change are difficult to estimate, since we have no direct experience with new climates. Past climate change has been small and slow, making the impacts hard to discern. Further, technological changes have obscured signals from historic climate changes. Despite these difficulties, the impact literature has made many strides toward understanding and quantifying climatic impacts.
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“Mendelsohn, Robert; Dinar, Ariel. 2005. Exploring Adaptation to Climate Change in Agriculture : The Potential of Cross-Sectional Analysis. Agricultural and Rural Development Notes; No. 1. © World Bank. http://hdl.handle.net/10986/9661 License: CC BY 3.0 IGO.”
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Publication Cross-Sectional Analyses of Climate Change Impacts(World Bank, Washington, D.C., 2004-06)The authors explore the use of cross-sectional analysis to measure the impacts of climate change on agriculture. The impact literature, using experiments on crops in laboratory settings combined with simulation models, suggests that agriculture will be strongly affected by climate change. The extent of these effects varies by country and region. Therefore, local experiments are needed for policy purposes, which becomes expensive and difficult to implement for most developing countries. The cross-sectional technique, as an alternative approach, examines farm performance across a broad range of climates. By seeing how farm performance changes with climate, one can estimate long-run impacts. The advantage of this approach is that it fully captures adaptation as each farmer adapts to the climate they have lived in. The technique measures the full net cost of climate change, including the costs as well as the benefits of adaptation. However, the technique is not concern-free. The four chapters in this paper examine important potential concerns of the cross-sectional method and how they could be addressed, especially in developing countries. Data availability is a major concern in developing countries. The first chapter looks at whether estimating impacts using individual farm data can substitute using agricultural census data at the district level that is more difficult to obtain in developing countries. The study, conducted in Sri Lanka, finds that the individual farm data from surveys are ideal for cross-sectional analysis. Another anticipated problem with applying the cross-sectional approach to developing countries is the absence of weather stations, or discontinued weather data sets. Further, weather stations tend to be concentrated in urban settings. Measures of climate across the landscape, especially where farms are located, are difficult to acquire. The second chapter compares the use of satellite data with ground weather stations. Analyzing these two sources of information, the study reveals that satellite data can explain more of the observed variation in farm performance than ground station data. Because satellite data are readily available for the entire planet, the availability of climate data will not be a constraint. A continuing debate is whether farm performance depends on just climate normals-the average weather over a long period of time-or on climate variance (variations away from the climate normal). Chapter 3 reveals that climate normals and climate variance are highly correlated. By adding climate variance, the studies can begin to measure the importance of weather extremes as well as normals. A host of studies have revealed that climate affects agricultural performance. Since agriculture is a primary source of income in rural areas, it follows that climate might explain variations in rural income. This is tested in the analysis in Chapter 4 and shown to be the case. The analysis reveals that local people in rural areas could be heavily affected by climate change even in circumstances when the aggregate agricultural sector in the country does fine.Publication Will African Agriculture Survive Climate Change?(Oxford University Press on behalf of the World Bank, 2006-08-23)Measurement of the likely magnitude of the economic impact of climate change on African agriculture has been a challenge. Using data from a survey of more than 9,000 farmers across 11 African countries, a cross-sectional approach estimates how farm net revenues are affected by climate change compared with current mean temperature. Revenues fall with warming for dryland crops (temperature elasticity of -1.9) and livestock (-5.4), whereas revenues rise for irrigated crops (elasticity of 0.5), which are located in relatively cool parts of Africa and are buffered by irrigation from the effects of warming. At first, warming has little net aggregate effect as the gains for irrigated crops offset the losses for dryland crops and livestock. Warming, however, will likely reduce dryland farm income immediately. The final effects will also depend on changes in precipitation, because revenues from all farm types increase with precipitation. 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The paper also studies how farm type choice varies across farmers in each zone, using a multinomial logit choice model. Farmers are observed to choose from one of the following five types of farms: rainfed crop-only, irrigated crop-only, mixed rainfed (crop and livestock), mixed irrigated, and livestock-only farming. The authors compare current decisions against future decisions as if the only change were climate change. They focus on two climate scenarios from existing climate models: the Canadian Climate Centre scenario, which is hot and dry, and the Parallel Climate Model scenario, which is mild and wet. The results indicate that the change in farm types varies dramatically by climate scenario but also by agro-ecological zone. Policy makers must be careful to encourage the appropriate suite of measures to promote the most adapted farm type to each location.Publication Can China Continue Feeding Itself? The Impact of Climate Change on Agriculture(Washington, DC: World Bank, 2008-01)Several studies addressing the supply and demand for food in China suggest that the nation can largely meet its needs in the coming decades. However, these studies do not consider the effects of climate change. This paper examines whether near future expected changes in climate are likely to alter this picture. The authors analyze the effect of temperature and precipitation on net crop revenues using a cross section consisting of both rainfed and irrigated farms. Based on survey data from 8,405 households across 28 provinces, the results of the Ricardian analysis demonstrate that global warming is likely to be harmful to China but the impacts are likely to be very different in each region. The mid latitude region of China may benefit from warming but the southern and northern regions are likely to be damaged by warming. More precipitation is beneficial to Chinese farmers except in the wet southeast. Irrigated and rainfed farmers have similar responses to precipitation but not to temperature. Warmer temperatures may benefit irrigated farms but they are likely to harm rainfed farms. Finally, seasonal effects vary and are offsetting. Although we were able to measure the direct effect of precipitation and temperature, we could not capture the effects of change in water flow which will be very important in China. Can China continue feeding itself if climate changes? Based on the empirical results, the likely gains realized by some farmers will nearly offset the losses that will occur to other farmers in China. If future climate scenarios lead to significant reductions in water, there may be large damages not addressed in this study.
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