JSM 2011 Online Program

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Abstract Details

Activity Number: 475
Type: Contributed
Date/Time: Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract - #301249
Title: Dynamic Regression Models with Holiday Effects and SARMA Errors for Forecasting Short-Term Electricity Demand in Korea
Author(s): Myung Suk Kim*+
Companies: Sogang University
Address: SSME Department, Sogang Business School, , , South Korea
Keywords: double SARMA model ; dynamic regression model ; forecasting ; holiday day effects ; short term electricity loads
Abstract:

Dynamic regression models are applied to the prediction of hourly electricity demand in Korea that contain multiple cycles and holiday effects. The suggested dynamic regression models include the interaction terms of time effects and holiday effects in the transfer function. The stochastic disturbance is modeled using the double seasonal autoregressive moving average (SARMA) mechanism. One day ahead forecasting performance of the suggested model is compared with the traditional double SARIMA models over the next one year horizon. Our empirical results indicate that the suggested model outperforms the benchmark models.


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