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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]

This paper uses detailed production data from a half million Chinese manufacturing plants over 1998–2007 to estimate the effects of temperature on firm-level total factor productivity (TFP), factor inputs, and output. We detect an inverted U-shaped relationship between temperature and TFP and show that it primarily drives the temperature-output effect. Both labor- and capital- intensive firms exhibit sensitivity to high temperatures. By mid 21st century, if no additional adaptation were to occur, we project that climate change will reduce Chinese manufacturing output annually by 12%, equivalent to a loss of $39.5 billion in 2007 dollars. This implies substantial local and global economic consequences as the Chinese manufacturing sector produces 32% of national GDP and supplies 12% of global exports. [ABSTRACT FROM AUTHOR]

Climate change shifts the distributions of a set of climatic variables, including temperature, precipitation, humidity, wind speed, sunshine duration, and evaporation. This paper explores the importance of those additional climatic variables other than temperature and precipitation. Using the county-level agricultural data from 1980 to 2010 in China, we find that those additional climatic variables, especially humidity and wind speed, are critical for crop growth. Therefore, omitting those variables is likely to bias the predicted impacts of climate change on crop yields. In particular, omitting humidity tends to overpredict the cost of climate change on crop yields, while ignoring wind speed is likely to underpredict the effect. Our preferred specification indicates that climate change is likely to decrease the yields of rice, wheat, and corn in China by 36.25%, 18.26%, and 45.10%, respectively, by the end of this century. [ABSTRACT FROM AUTHOR]

This paper estimates the causal effect of urban road expansion on Vehicle-Kilometers Traveled (VKT) in 103 Chinese cities. We develop a novel matching IV strategy to address endogeneity concerns that complements traditional historical infrastructure instruments to provide time-varying identification in a panel data setting. We find that the estimated elasticity of VKT with respect to road length is approximately 1, indicating that newly built urban roads lead to a proportional increase in total traffic. Given significant ongoing infrastructure investment and more recently enacted traffic alleviation policies in many Chinese cities, this result provides important new information on the impacts of infrastructure investment on traffic. [ABSTRACT FROM AUTHOR]