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Energy Demand Modeling with Noisy Input-Output Variables

Lov Kumar Kher, Fereidoon P. Sioshansi, and Soroosh Sorooshian

Year: 1987
Volume: Volume 8
Number: Number 4
DOI: 10.5547/ISSN0195-6574-EJ-Vol8-No4-4
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One of the most important challenges facing energy analysts is to predict future energy consumption levels. The volatility of energy prices following the 1973 oil embargo and the unexpected elasticity of demand to higher prices caught most energy forecasters off the mark (see Energy Daily, "How It Didn't Turn Out: The Forecasters Who Failed," 1986). The same can be said of electricity forecasters who consistently overshot growth rates for over a decade despite compelling signs to lower their projections (Uhler and Nelson, 1985), (see Figure 1).

Noisy Data and Uncertain Coefficients: A Reply

Soroosh Sorooshian, Lot, Kher, and F. P. Sioshansi

Year: 1989
Volume: Volume 10
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol10-No1-16
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[N]o one (except KSS, as far as I know) has recommended using the bonds approach for forecasting. KSS however, does not reply on a well-founded statistical basis for their forecasting procedure: it is decidedly ad hoc. We are pleased that Herbert has recognized the potential of "the bounds approach for forecasting" as a viable alternative for forecasting. His major concern is with the "ad hoc" nature of our forecasting procedure. This apparent occurs because forecasts generated by the NVM do not come with confidence intervals similar to those placed on forecasts generated by classical regression techniques. We wish to reply.

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