MODELING ONTARIO REGIONAL ELECTRICITY SYSTEM DEMAND USING A MIXED FIXED AND RANDOM COEFFICIENTS APPROACH

Abstract In examining the municipal peak and kilowatt-hour demand for electricity in Ontario, we begin by exploring the issue of homogeneity across geographic regions. A common model across municipalities and geographic regions cannot be supported by the data. We consider various procedures which deal with this heterogeneity and yet reduce the multicollinearity problems associated with regional specific demand formulations. The recommended model controls for regional differences assuming that the coefficients of regional-seasonal specific factors are fixed and different while the coefficients of economic and weather variables are random draws from a common population for any one municipality by combining the information on all municipalities through a Bayes procedure.

[1]  J. W. Dunn,et al.  The demand for electricity and natural gas in the northeastern United States. , 1981 .

[2]  K. Anderson.  Residential Demand for Electricity: Econometric Estimates for California and the United States , 1973 .

[3]  Residential Electricity Revisited , 1980 .

[4]  Cheng Hsiao,et al.  Analysis of Panel Data , 1987 .

[5]  F. Fisher,et al.  A study in econometrics : the demand for electricity in the United States , 1964 .

[6]  Patricia E. Beeson.  TOTAL FACTOR PRODUCTIVITY GROWTH AND AGGLOMERATION ECONOMIES IN MANUFACTURING, 1959‐73* , 1987 .

[7]  R. A. Lyman.  Price elasticities in the electric power industry , 1978 .

[8]  J. Quigley.  Residential Energy Standards and the Housing Market: A Regional Analysis , 1984 .

[9]  Rural Residential Demand for Electricity , 1983 .

[10]  W. Anderson,et al.  Residential energy demand in the United States: A regional econometric analysis , 1980 .

[11]  R. Koenker,et al.  Residential demand for electricity : An econometric approach , 1979 .

[12]  Lester D. Taylor,et al.  The demand for electricity: a survey , 1975 .

[13]  A. Zellner.  An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias , 1962 .

[14]  R. Halvorsen.  Demand for electric energy in the United States , 1976 .

[15]  N. Uri.  A mixed time-series/econometric approach to forecasting peak system load , 1979 .

[16]  T. Mount,et al.  Electricity demand in the United States: an econometric analysis , 1973 .

[17]  Geoffrey J. D. Hewings,et al.  SPACE‐TIME EMPLOYMENT MODELING: SOME RESULTS USING SEEMINGLY UNRELATED REGRESSION ESTIMATORS* , 1982 .

[18]  E. Malinvaud,et al.  Statistical Methods of Econometrics. by E. Malinvaud , 1972 .

[19]  Philip K. Verleger,et al.  Dynamic Demand Analyses for Gasoline and Residential Electricity , 1974 .

[20]  Mundlak.  Models with Variable Coefficients: Integration and Extension , 1978 .

[21]  Y. Mundlak.  On the Pooling of Time Series and Cross Section Data , 1978 .

[22]  A. Zellner.  On the Aggregation Problem: A New Approach to a Troublesome Problem , 1969 .

[23]  Robert A. Pollak,et al.  Habit Formation and Dynamic Demand Functions , 1970, Journal of Political Economy.

[24]  D. Lindley,et al.  Bayes Estimates for the Linear Model , 1972 .

[25]  Marc Nerlove,et al.  Pooling Cross-section and Time-series Data in the Estimation of a Dynamic Model , 1966 .

[26]  Edwin Kuh,et al.  Capital stock growth : a micro-econometric Approach , 1963 .

[27]  R. Halvorsen,et al.  Residential Demand for Electric Energy , 1975 .

[28]  Econometric estimation of peak electricity demands , 1979 .

[29]  Robert A. Meyer,et al.  Estimating the Demand for Electricity by Time of Day , 1971 .

[30]  H. S. Houthakker,et al.  Some Calculations on Electricity Consumption in Great Britain , 1951 .

[31]  Michael P. Murray.  The Demand for Electricity in Virginia , 1978 .

[32]  R. Betancourt.  An econometric analysis of peak electricity demand in the short run , 1981 .