Temperature variability and long-run economic development
研究利用卫星夜间灯光数据衡量经济活动，通过空间一阶差分方法识别因果效应，发现日间温度波动显著抑制经济活动，而季节波动影响较小，年际波动的影响则随温度水平变化。
This study examines the effects of temperature variability on long-run economic development. To identify causal effects, a novel econometric strategy is employed, based on spatial first-differences. Economic activity is proxied by satellite data on nightlights. Drawing on climate science, the study distinguishes between temperature variability on three time scales: day-to-day, seasonal, and interannual variability. The results indicate that day-to-day temperature variability has a statistically significant, negative effect on economic activity, while seasonal variability has a smaller but also negative effect. The effect of interannual variability is positive at low temperatures, but negative at high temperatures. Furthermore, the results suggest that daily temperature levels have a non-linear effect on economic activity with an optimal temperature around 15 degrees Celsius. However, most of the estimated effects of variability cannot be explained with this non-linearity and instead seem to be due to larger uncertainty about future temperature realisations. The empirical effects can be found in both urban and rural areas, and they cannot be explained by the distribution of agriculture. The results indicate that projected changes of temperature variability might add to the costs of anthropogenic climate change especially in relatively warm and currently relatively poor regions.