Estimating Macrofiscal Effects of Climate Shocks from Billions of Geospatial Weather Observations
利用高频高分辨率天气数据构建数百个变量，通过LASSO筛选出最能解释GDP和宏观财政变量的子集，发现温和天气减少、高温和严重干旱增加会降低GDP，且财政政策可缓解这些冲击。
The literature studying the macroeconomics of weather has focused on temperature and precipitation annual averages, while micro studies have focused more on extreme weather measures. We construct hundreds of variables from high-frequency, high-spatial-resolution weather measurements. Using the LASSO, we identify the parsimonious subset of variables that can best explain GDP and key macrofiscal variables. We find that scarcer mild temperatures and an increase in the occurrence of high temperatures and severe droughts reduce GDP. These variables substantially improve the share of GDP variations explained by weather. Additional evidence suggests that fiscal policy mitigates these shocks.