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Climate change will influence yields while sea level rise can inundate producing lands. The research reported investigates the individual and simultaneous effects of these factors on production, trade and consumption of rice the world’s number one food crop. A global rice trade model is utilized to do this. The results indicate that the combination of yield and sea level effects causes a significant reduction in production and an increase in rice prices which may have important policy implications for food security. Global rice production is reduced by 1.60% to 2.73% while global rice price increases by 7.14% to 12.77%. Sea level rise is particularly a risk factor in Bangladesh, Japan, Taiwan, Egypt, Myanmar and Vietnam. In the face of such developments, adaptation may well be desirable and thus an investigation is done over adaptation options of increased technical progress or trade liberalization with the results showing that both can mitigate such damages.

Researchers of climate change have suggested that climate change and variability has a significant influence on the epidemiology of infectious diseases, particularly vector-borne diseases. The purpose of this study is to explore how climate conditions and the dengue fever epidemic in Taiwan are related and to estimate the economic impact of climate change on infectious diseases. To achieve these objectives, two different methods, one involving the Panel data model and the other the Contingent Valuation Method (CVM), are applied in this study. At first, we use the Panel data model to assess the relationship between climate conditions and the number of people infected by dengue fever during the period from January 2000 to February 2006 in 308 cities and townships in the Taiwan. The results of the empirical estimation indicate that climate conditions have an increasingly significant impact on the probability of people being infected by dengue fever. The probability of being infected by dengue fever due to climate change is then calculated and is found to range from 12% to 43% to 87% which represent low, mid, and high probabilities of infection caused by climate change when the temperature is increased by 1.8°C. The respondent’s willingness to pay (WTP) is also investigated in the survey using the single-bounded dichotomous choice (SBDC) approach, and the results show that people would pay NT$724, NT$3,223 and NT$5,114 per year in order to avoid the increased probabilities of 12%, 43%, and 87%, respectively, of their being infected with dengue fever.

One of the issues with respect to climate change involves its influence on the distribution of future crop yields. Many studies have been done regarding the effect on the mean of such distributions but few have addressed the effect on variance. Furthermore, those that have been done generally report the variance from crop simulators, not from observations. This paper examines the potential effects of climate change on crop yield variance in the context of current observed yields and then extrapolates to the effects under projected climate change. In particular, maximum likelihood panel data estimates of the impacts of climate on year-to-year yield variability are constructed for the major U.S. agricultural crops. The panel data technique used embodies a variance estimate developed along the lines of the stochastic production function approach suggested by Just and Pope. The estimation results indicate that changes in climate modify crop yield levels and variances in a crop-specific fashion. For sorghum, rainfall and temperature increases are found to increase yield level and variability. On the other hand, precipitation and temperature are individually found to have opposite effects on corn yield levels and variability.

The El Nino-Southern Oscillation (ENSO) effect has been found to be associated with regional climate variations in many regions of the world, and, in turn, with variation in crop yields. Previous studies have found that early releases of ENSO phase information could permit agricultural producers to make adjustments in their decisions and in turn generate an increase in agricultural sector welfare. This study examines whether the value of the agricultural responses can be enhanced by releasing more detailed ENSO information. Namely we evaluate the implications for projected agricultural welfare under release and adaptation to the Stone and Auliciems five phase definition of ENSO states as opposed to the more standard three phase definition. This value is estimated using a stochastic, U.S./global agricultural model representing 22 climate years. The results indicate that the release and exploitation of the more detailed ENSO phase definition almost doubles the welfare impact. The results also indicate that there is room for up to another doubling of information value through further refinements.

Some argue that global climate change may alter the frequency and strength of extreme events. This paper examines the economic damages in the agricultural sector arising from a shift in El Nino Southern Oscillation (ENSO) event frequency and strength. The assumptions about the frequency of ENSO shift are motivated by an article by Timmermann etal. (1999). The damage estimates reported here are in the context of the global agricultural system. Annual damages in the 3 to 4 hundred million U.S. dollar range are found if only the frequency of ENSO events changes. However, annual damages rise to over $1 billion if the events also intensify in strength. Event anticipation and crop mix adaption on the part of farmers can help offset the damages but cannot fully alleviate them.

One concern of agriculturalists when regarding climate change involves the effects on pest populations. Climate change may allow pest migration or population expansions which may adversely affect agricultural productivity, profitability and possibly even viability. We examine the effect of current climate variations on the average and variability of U.S. per acre pesticide costs across the U.S. as a proxy for investigating the consequence for pest populations. Empirically, we find that increases in rainfall increases average per acre pesticide usage costs for corn, cotton, potatoes, soybeans, and wheat while hotter weather increases pesticide costs for corn, cotton, potatoes, and soybeans but decreases the cost for wheat. We also investigated the influence of climate on the variability of pesticide costs. There we find that hotter temperatures increase pesticide cost variance for corn, potatoes, and wheat while decreasing it for soybeans. Rainfall increases cause an increase in cost variability for cotton while decreasing it for corn, potatoes, soybeans, and wheat.

Global climate change portends shifts in water demand and availability which may damage or cause intersectoral water reallocation in water short regions. This study investigates effects of climatic change on regional water demand and supply as well as the economy in the San Antonio Texas Edwards Aquifer region. This is done using a regional model which portrays both hydrological and economic activities. The overall results indicate that changes in climatic conditions reduce water resource availability and increase water demand. Specifically, a regional welfare loss of $2.2–$6.8million per year may occur as a result of climatic change. Additionally, if springflows are to be maintained at the currently desired level to protect endangered species, pumping must be reduced by 9–20% at an additional costof $0.5 to $2 million per year.