Weather Effects in Energy Seasonal Adjustment: An Application to France Energy Consumption
提出一种综合天气指标（GWI），结合温度、风、日照、降雨和云量，通过K-means和LASSO方法改进能源消费数据的季节性调整，优于传统HDD方法，并估计法国能源需求的天气弹性。
This paper addresses the challenge of adjusting energy consumption data for weather variations by introducing a novel General Weather Indicator (GWI). The GWI combines multiple weather variables, including temperature, wind, sunlight, rain, and cloudiness, using a novel econometric approach that applies K-means for threshold identification and LASSO for variable selection. Through an empirical analysis of sectoral electricity and natural gas consumption in France, we demonstrate that the GWI outperforms the standard HDD approach by addressing three main concerns: the lack of statistical criteria for defining the base temperature, the reliance solely on temperature as the weather variable, and the assumption of a constant base temperature over time and space. Based on these results, we propose an analysis of the sectoral functional form and an estimation of weather elasticities for energy demand in France at both the monthly and daily levels.