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Residential Electricity Revisited

Hendrik S. Houthakker

Year: 1980
Volume: Volume 1
Number: Number 1
DOI: 10.5547/ISSN0195-6574-EJ-Vol1-No1-4
View Abstract

Abstract:
The following is a report on various attempts to update and improve an earlier analysis of residential electricity demand (Houthakker, Verleger, and Sheehan, 1974-hereafter referred to as HVS). To understand what is new the reader should first know what has been maintained, namely:1. the logarithmic flow-adjustment model which estimates this year's consumption from last year's consumption, this year's price and income, and possibly (though not in HVS) from other variables,2. the pooling of annual time series for 48 states using the error component approach of Balestra & Nerlove, 3. the use of a "marginal price" for electricity.The present paper may be regarded as a verification of the first of these hypotheses, and to some extent of the other two.



Residential Substitution of Off-peak for Peak Electricity Usage under Time-of-Use Pricing

Douglas W. Caves and Laurits R. Christensen

Year: 1980
Volume: Volume 1
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol1-No2-4
View Abstract

Abstract:
This article reports on the methodology, procedures, and conclusions from the first phase of our econometric analysis of the Wisconsin Time-of-Use (TOU) Electricity Pricing Experiment.' Dur-ing Phase I, which took place during the summers of 1976 and 1977, we confined our attention to assessing consumer ability and/or willingness to shift electricity usage from peak to off-peak (P/OP)



Asymmetry in the Residential Demand for Electricity

Trevor Young, Thomas H. Stevens, and Cleve Willis

Year: 1983
Volume: Volume 4
Number: Special Issue
DOI: 10.5547/ISSN0195-6574-EJ-Vol4-NoSI-10
No Abstract



Fair Value Versus Original Cost Rate Base Valuation During Inflation

Walter J. Primeaux, Jr., Edward L. Bubnys, and Robert H. Rasche

Year: 1984
Volume: Volume 5
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol5-No2-6
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Abstract:
Valuation of public utility property for rate-making purposes has been controversial since the beginning of public regulation. Despite much academic research and practical experience, there is no consensus of academicians or practitioners concerning the appropriate value of physical property used for providing service to customers. In public utility rate making, the value of this physical property, net of depreciation, is called the rate base. An important question is how well regulatory processes adjust the rate base for price level changes during periods of inflation.Statutes of the individual states determine how public utility property will be valued for rate-making purposes. Three basic methods are employed. Original cost jurisdictions set the rate base at the value of the property when it was first installed in a public utility application; the fair value method attempts to adjust the base to a level that more correctly reflects its current value; and the reproduction cost approach tries to establish a value that would permit reproduction of the property. Because the reproduction cost approach is not now being used by any state, this study focuses on the original cost and fair value methods.



Residential Electricity Demand Modeling in the Australian Capital Territory: Preliminary Results

W. A. Donnelly

Year: 1984
Volume: Volume 5
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol5-No2-8
View Abstract

Abstract:
The demand for electricity has recently become a topic of major interest in Australia, where very little empirical analysis has been done (see Hawkins, 1975; Saddler et al., 1980; Department of National Development and Energy, 1981; Brian and Schuyers, 1981; and Donnelly and Saddler, 1982). Two of the policy issues being raised concern the appropriate pricing strategies that should be adopted by supplying authorities and the need for additional generating capacity. An understanding of the relative importance of the factors influencing electricity demand is required to aid public policy making, particularly since substantial investment is now being considered.



Residential Electricity Demand: A Suggested Appliance Stock Equation

Christopher Garbacz

Year: 1984
Volume: Volume 5
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol5-No2-11
View Abstract

Abstract:
A large amount of work in residential electricity demand has relied on logit estimation of a disaggregated appliance stock. (See the seminal work by McFadden et al., 1977.) While this approach may be suitable for certain types of models with certain goals in mind, a simple formulation of an appliance stock equation may sometimes be appropriate. For example, if the goal is to estimate seasonal patterns in elasticities employing a national micro-data set (as in the National Interim Energy Consumption Survey 1978-1979; see U.S. Department of Energy, 1980), then it may be appropriate to develop an appliance stock equation to predict the size of an appliance stock index (approximating a continuous variable). The present appliance stock equation is part of a three-equation model that is estimated in log-linear form via 2SLS.



Conditional Demand Analysis for Estimating Residential End-Use Load Profiles

Dennis J. Aigner, Cynts Sorooshian, and Pamela Kerwin

Year: 1984
Volume: Volume 5
Number: Number 3
DOI: 10.5547/ISSN0195-6574-EJ-Vol5-No3-6
View Abstract

Abstract:
This paper reports some preliminary results from an ongoing study that uses regression methods to break down total household load into its constituent parts, each associated with a particular electricity-using end use or appliance. The data base used for this purpose consists of 15-minute integrated demand readings on a random sample of statistical control group customers from the Los Angeles Department of Water and Power TOD (time of day)-pricing experiment for the months of August 1978 (132 customers), 1979 (108 customers), and 1980 (80 customers). Twenty-four regression equations are fitted, each one aimed at explaining variation in the time-averaged load (averaged over days of the month) over customers as a function of temperature, house size, and binary indicator variables that indicate the presence or absence of each of the end uses of interest. This sort of method for extracting the individual contributions of end uses to total household load has become known as conditional demand analysis (Parti and Parti, 1981). The success of this method for isolating end-use loads statistically, without direct metering of the appliance, depends crucially on whether the ownership patterns of appliances are well mixed. For example, if (as in our sample) everyone owns at least one refrigerator, it will be impossible to isolate refrigerator load. Similarly,



An Application of the Expenditure Function in Electricity Pricing: Optimal Residential Time-of-Use Rate Option

Chi-Keung Woo

Year: 1985
Volume: Volume 6
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol6-No2-7
View Abstract

Abstract:
Caves et al. (1983) recently reported that mandatory time-of-use (TOU) pricing for residential customers served by four Illinois electric utilities fails to pass the cost-benefit test. Gains in economic efficiency are outweighed by the relatively high TOU meter costs. An obvious alternative is to offer a TOU rate option for which customer participation is voluntary (see, for example, Woo et al. [1983, Section D] and Malko and Faruqui [1980, pp. 161-62]). The problem of optimal pricing under self-selection has been analyzed by Faulhaber and Panzar (1977), Panzar and Sibley (1978), and Mirman and Sibley (1980). Following these studies, this paper derives the optimal electricity prices when a customer can choose between paying the TOU rates and the full incremental costs of a TOU meter and remaining on a flat rate schedule. My approach departs from the earlier studies in using the expenditure function to characterize the optimization problem as described by Diamond and McFadden (1974).



Seasonal and Regional Residential Electricity Demand

Christopher Garbacz

Year: 1986
Volume: Volume 7
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol7-No2-9
View Abstract

Abstract:
Following the seminal work of McFadden. Puig, and Kirschner (1977) and the general availability of national microdata sets, residential energy demand studies have been conducted for electricity, natural gas, fuel oil. LP gas, and wood (see Garbacz, 1984, 1985). Using the National Interim Energy Consumption Survey (NIECS) data, Garbacz (1984) developed a three-equation model (demand, price, and appliance stock) to estimate national electricity demand using two-stage least squares (2SLS) for house-holds by month. This study builds on the previous work to estimate elasticities by month and by region. It is hypothesized that elasticities vary substantially between the heating and cooling seasons. Previous work by Acton, Mitchell, and Sohiberg (1980); Parti and Parti (1980); Archibald, Finifter, and Moody (1982); Murray et al. (1978); and Garbacz (1984) supports this. Houthakker (1980), Halvorsen (1978), and Murray et al. (1978) also have found differences in elasticities by region.



A Residential Demand Charge: Evidence from the Duke Power Time-of-Day Pricing Experiment

Thomas N. Taylor and Peter M. Schwarz

Year: 1986
Volume: Volume 7
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol7-No2-10
View Abstract

Abstract:
Demand charges account for one-third to one-half of industrial and commercial electricity bills, and yet they have been virtually ignored, both theoretically and practically, as a component of residential tariffs. Our objective here is twofold: (1) to model and test the effects of a time-of-use demand charge on residential consumer behavior and (2) to evaluate, theoretically and empirically, its influence on utility system peak. Among the pragmatic issues are the effects of sustained hot weather on household response and the effects of the charge on demand at time of system peak compared to billing demand.




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