AN ITERATIVE APPROACH FOR WEATHER-CORRECTING ENERGY-CONSUMPTION DATA

Energy consumption data are influenced by the weather conditions. The use of weather unadjusted energy data in analysis and forecasting coul d give misleading and erroneous results. In this paper a new iterative econometric technique is developed to correct for abnormal weather co nditions in published energy consumption data. The technique is applie d to sectoral natural gas sales data for the province of Ontario, Cana da. The empirical results reveal that following the methods available in the literature results in weather-corrected data that still contain a significant portion of the abnormal weather impact. In addition, th e study suggests that residential and commercial natural gas data requ ire more weather correction than the data for the industrial sector.