Econometric and Computational Issues in Estimating Demand for Energy by Time-of-Day
提出一个两步时间序列与截面模型来估计电力或天然气的分时段需求，并展示高效计算方法。样本外验证显示平均预测误差在4.5%至15%的可接受范围内，对32个区域的未来预测表明模型有良好潜力。
A two-step time-series and cross-section model is used to estimate time-of-day (TOD) demand for electricity or natural gas and to demonstrate an efficient computational method. Post-sample validation of the model results in several regions found average forecast errors in the aceptable range of 4.5% to 15%. Future hourly electricity-demand forecasts made for 32 regions using an historical trend scenario and a Data Resources Inc. macro model scenario indicate a good potential for the model. 12 references. (DCK)