Narrow Results

There is a paucity of information on conditioning factors that hinder or promote adoption of multiple climate-smart practices and on the synergies among such practices in increasing household resilience by improving agricultural income. This study analyzes how heat, rainfall, and rainfall variability affect farmers’ choices of a portfolio of potential climate smart practices — agricultural water management, improved crop seeds, and fertilizer — and the impact of these practices on farm income in the Nile Basin of Ethiopia. We apply a multinomial endogenous switching regression approach by modeling combinations of practices and net farm income for each combination as depending on household and farm characteristics and on a set of climatic variables based on geo-referenced historical precipitation and temperature data. A primary result of this study is that farmers are less likely to adopt fertilizer (either alone or in combination with improved varieties) in areas of greater rainfall variability. However, even when there is high variability in rainfall, farmers are more likely to adopt these two yield-increasing inputs when they choose to (and are able to) include the third part of the portfolio: agricultural water management. Net farm income responds positively to agricultural water management, improved crop variety or fertilizer when they are adopted in isolation as well as in combination. But this effect is greater when these practices are combined. Simulation results suggest that a warming temperature and decreased precipitation in future decades will make it less likely that farmers will adopt practices in isolation but more likely that they will adopt a combination of practices. Hence, a package approach rather than a piecemeal approach is needed to maximize the synergies implicit in various climate smart practices.

This paper discusses the development of a computable general equilibrium (CGE) model with detailed specification for land use. The model considers two aspects of land use: land as a measure of production cost and land as a physical entity that can be used in a variety of ways. To analyze the economic effects of climate change, we integrated the CGE model and an econometric model. The results based on this model, which captures how land allocation responds to changes in temperature and precipitation, are introduced as elasticities in the CGE model to offset the demand curve for land among 13 different land uses in 27 regions of Brazil. The simulations are based on climate data from a benchmark period (1975–2005) and Intergovernmental Panel on Climate Change climate projection scenarios for the periods 2010–2039, 2040–2069, and 2070–2099. The results predict negative changes in real gross domestic product ranging from $-$0.0054% to $-$0.0198%, depending on the scenario.

The text and associated Supplemental Materials contribute internally consistent and therefore entirely comparable regional, temporal, and sectoral risk profiles to a growing literature on regional economic vulnerability to climate change. A large collection of maps populated with graphs of Monte-Carlo simulation results support a communication device in this regard — a convenient visual that we hope will make comparative results tractable and credible and resource allocation decisions more transparent. Since responding to climate change is a risk-management problem, it is important to note that these results address both sides of the risk calculation. They characterize likelihood distributions along four alternative emissions futures (thereby reflecting the mitigation side context); and they characterize consequences along these transient trajectories (which can thereby inform planning for the iterative adaptation side). Looking across the abundance of sectors that are potentially vulnerable to some of the manifestations of climate change, the maps therefore hold the potential of providing comparative information about the magnitude, timing, and regional location of relative risks. This is exactly the information that planners who work to protect property and public welfare by allocating scarce resources across competing venues need to have at their disposal — information about relative vulnerabilities across time and space and contingent on future emissions and future mitigation. It is also the type of information that integrated assessment researchers need to calibrate and update their modeling efforts — scholars who are exemplified by Professor Nordhaus who created and exercised the Dynamic Integrated Climate-Economy and Regional Integrated Climate-Economy models.

There is a substantial concern for the economic impacts of global warming. This study identifies the effects of seasonal temperatures on total economic output in the cities of China, and then projects the changes in local economic performance under future climate and development scenarios. The results suggest that there are significant negative effects of warm seasonal temperature but positive effects of cold seasonal temperature on economic growth. These different effects increase as more lags of temperature are included. By 2090, the cities may have the average reduction of 44% in GDP per capita under RCP8.5, but some of them in Northeast China are predicted to get positive impacts under RCP2.6. The difference in the estimated aggregate impacts under the two RCPs could be as much as 24%. The poor cities are likely to have higher economic damages, which amplifies the economic inequality. Finally, the ranges of economic impacts projected by different climate models are presented.

Many studies of climate change adaptation have relied on farmers’ perceptions of climate change to explain why farmers are adopting new farming methods, and to advise adaptation policy framework that justifies Climate Smart Agriculture (CSA) especially in Africa. These studies have rarely verified whether farmers’ perceptions are consistent with observed changes in meteorological conditions to establish sufficient premise. This study compares farmers’ perceptions of changes in precipitation and temperature in a rainfed agriculture region of Ghana against objective measurements made in nearby weather stations in the region. The study finds that farmers correctly perceived the increase in temperature over time but incorrectly perceived a reduction in precipitation, while objective data showed high fluctuations with no clear trend. It is possible that farmers mistakenly assumed reduction in soil moisture meant to support crop growth requirements was caused by less rainfall when in fact it was caused by higher temperature.

This study examines the effect of weather on outdoor recreation and specifically leisure farms in Taiwan. We find that temperature has a complex effect on visits, revenues, and occupancy rates. Cool temperatures are the least desirable, very cold temperatures and warm temperatures are the most beneficial, and hot temperatures are less beneficial. Sites designed for winter activities benefit the most from cold temperatures whereas sites designed for walking and boating do best in warm temperatures. Global warming is likely to harm the sites suited for winter activities but should prolong the outdoor season for most leisure farms in Taiwan. But leisure farms may want to find ways to cope with hot temperatures.