Econometric Analysis Of The Impact Of Climate Extremes On Agricultural Economic Output In China

As we all know, weather and climate affect social economy to some degree, but the magnitudes are not well known. Four measures of weather are introduced into the renowned Cobb-Douglas production function along with some traditional socio-economic factors such as capital and labor to build a new applied econometric model. Specifically, agricultural output is modeled using a transcendental logarithmic production function with measures of regional weather included. Econometric analysis methods are applied to quantitatively assess both the long-run equilibrium relationship and the short-term fluctuation between the agricultural economic output and the climate extremes. Some conclusions can be summarized as follows:(1) The Granger causality test output show that, China's agricultural economic output is influenced by climate extremes at the 0.05 significance level. The long-run equilibrium relationship between economic output and weather is verified. On the contrary, the impact of short-term fluctuation of weather is not significant. The results of the long-run equilibrium model indicate that extreme high temperature, extreme low temperature, extreme precipitation and drought have significantly negative effects on agricultural economic output. When the days of the four measures of climate extremes increase by 1% each, agricultural economic output will drop 0.112%,0.031%,0.033% and 0.047% respectively. The estimated coefficient of the error corrected term is -0.282.(2) The elasticities of the four measures of climate extremes to agricultural economic output vary across the contiguous region of China. The aggregate impacts of climate extremes on agricultural economic output follow a probabilistic distribution. The results of the aggregate impacts of climate extremes have been calculated and sorted by the output standard deviations caused by the variability. It is evident that the East China, Central China, and South China are most sensitive to changes of climate extremes, and Northwest, North China, and Northeast are Comparatively less sensitive to the variability. (3) At 1%, 10%, 50% and 90% exceedance probabilistic levels, the risk values of agricultural economy from the high temperature extremes have no obvious spatial characteristics; the risk values of agricultural economy affected by the low temperature extremes in the north are much higher than those of the south; the risk values from the precipitation extremes are marked with distinctly geographical characteristics that the risks values of the south areas of the Yangtze River are the highest, the northeast ranks the second, north China and northwest rank the last; the risk of drought to the north areas of the Huai River are higher than those of the south, especially, the risk values of north China, Gansu and Ningxia in northwest have space-connected property.(4) At 1%, 10%, 50% and 90% exceedance probabilistic levels, the aggregate risk from the four measures of climate extremes are marked with obviously spatial differences: the aggregate risk values of agricultural economy of the south areas of the Yangtze River are distinctively higher than those of the north; northeast ranks the second, and northwest ranks the last.