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This paper examines the effects of extreme temperatures on mortality rates, using random year-to-year variation in temperature based on county-level panel data from China. The analysis finds a robust, U-shaped relationship between temperature and mortality rates, indicating that extremely cold or hot temperatures lead to excess deaths. The heat-related (cold-related) effect is 3.5 times (3.2 times) as large as previous findings that used U.S. data, and it is especially large for the elderly population, mainly due to excess deaths caused by cardiovascular diseases. Applying these results to climate change predictions from Hadley Centre Global Environmental Model shows that by 2061–2080 the annual mortality rate is likely to increase by 14.2% if global greenhouse gas emissions continue to rise throughout the 21st century, the estimated health cost of which is around 0.98 trillion Chinese Yuan per year. The paper also explores households' adaptation behaviors to extreme temperatures. It finds that although urban households adaptively increase energy consumption when they are exposed to cold temperatures and purchase more air conditioners on hot and cold days, rural households are unresponsive to temperature fluctuations. This finding implies that rural people may be more resource constrained and suffer more when extreme temperatures occur. [ABSTRACT FROM AUTHOR]

Abstract We perform two tests that estimate the mass of the upper tail of the distribution of aggregate US tropical cyclone damages. Both tests reject the hypothesis that the distribution of damages is thin tailed at the 95% confidence level, even after correcting for inflation and growth in population and per capita income. Our point estimates of the shape parameter of the damage distribution indicate that the distribution has finite mean, but infinite variance. In the second part of the paper, we develop a microfoundations model of insurance and storm size that generates a fat tail in aggregate tropical cyclone damages. The distribution of the number of properties within a random geographical area that lies in the path of a tropical cyclone is shown to drive fat tailed storm damages, and we confirm that the distribution of coastal city population is fat tailed in the US. We show empirically and theoretically that other random variation, such as the distribution of storm strength and the distribution of damages across individual properties, does not generate a fat tail. We consider policy options such as climate change abatement, policies which encourage adaptation, reducing subsidies for coastal development, and disaster relief policies, which distort insurance markets. Such policies can reduce the thickness of the tail, but do not affect the shape parameter or the existence of the fat tail. [ABSTRACT FROM AUTHOR]

Ricardian analyses of farmland values have become a cornerstone of the literature valuing the impacts of climate change on agriculture. However, concerns about the lack of a formal econometric strategy to deal with omitted farmland characteristics have raised doubts about the identification of such impacts. This paper proposes an original method for estimating Ricardian models with plot fixed effects to control for confounding omitted variables. Specifically, we use plot-level repeat-sales French data from 1996 to 2019 to investigate how differences in farmland prices between two sale dates are explained by differences in climate evolutions. We show that our repeat-Ricardian estimates suggest greater benefits of climate change than those found with standard Ricardian analyses. In particular, our repeat-Ricardian estimates indicate that warmer summers benefit French agriculture, in complete opposition to our pooled Ricardian estimates or to the remainder of the literature. Our repeat-Ricardian results are robust to several specifications, climate length-definitions and sub-samples. We provide elements suggesting that the repeat-Ricardian analysis is better able to capture crop-switching towards high-value crops requiring particular soil conditions (e.g. vineyards). Our repeat-Ricardian analysis also indicates greater benefits of climate change compared to those estimated with short-term weather-based approaches, shedding new lights on previous inconsistent findings from the literature. [ABSTRACT FROM AUTHOR]

Climate change effects on agricultural yields will be uneven over the world. A few countries, mostly in high latitudes, may experience gains, while most will see average yield decrease. This paper aims to quantify the role of market-mediated adjustments in attenuating the effects of climate change by allowing the expression of the new climate-induced pattern of comparative advantages within and between countries. To do this, we develop a quantitative general equilibrium trade model where the representation of land use choice is inspired from modern Ricardian trade models. We use spatially explicit information from the agronomic literature about potential yields before and after climate change for calibration and counterfactual simulations. The results show that the climate-induced yield changes generate large price movements that incentivize adjustments in production and trade. Both production and trade adjustments contribute to reducing welfare losses globally, with production adjustments making the larger contribution. [ABSTRACT FROM AUTHOR]