This paper presents an application of Data Envelopment Analysis (DEA) to energy audit data by defining climate control systems as production processes. This method is proposed as an alternative to the use of regression based models which have been used in previous analyses of this type of data. The advantage of this method is the ability to compute relative efficiency measures for each observation in the data and to define these values without the assumption of a particular specification of the technology. Furthermore, this method can be used with a large number of inputs and outputs.
AignerD.J.LovellC.A.K.SchmidtP. (1977). “Formulation and Estimation of Stochastic Frontier Production Function Models.” Journal of Econometrics6: 21-38.
2.
BankerRajiv D. and Richard C. Morey (1986). “Efficiency Analysis for Exogenously Fixed Inputs and Outputs.” Operations Research34: 513-521.
3.
BerndtE.R.WatkinsG.C. (1986). “Modeling Energy Demand: The Choice Between Input and Output Energy Measures.” The Energy Journal7(2): 69-79.
4.
CharnesA.CooperW.W.RhodesE. (1978). “Measuring the Efficiency of Decision Making Units.” European Journal of Operations Research2(6): 429-444.
5.
ChernW.S. (1975). “Electricity Demand by Manufacturing Industries in the U.S.” Report ORNL-NSFEP-87. Oak Ridge, TN: Oak Ridge National Laboratory.
6.
DubinJ.A. (1985). Consumer Durable Choice and the Demand for Electricity. Amsterdam: North Holland Publishing Company.
7.
FäreR.GrosskopfS. (1985). “A Nonparametric Cost Approach to Scale Efficiency.” Scandinavian Journal of Economics87: 594-604.
8.
FäreR.GrosskopfS.LovellC.A.K. (1985). The Measurement of Efficiency and Production. Boston, MA: Kluwer-Nijhoff Publishing.
9.
FarrellM.J. (1957). “The Measurement of Productive Efficiency.” Journal of the Royal Statistical Society. Series A (General) 120(3): 253-281.
10.
FerrierG.D.LovellC.A.K. (1990). “Measuring Cost Efficiency in Banking: Econometric and Linear Programming Evidence.” Journal of Econometrics46: 229-245.
11.
FørsundF.R.HjalmarssonL. (1988). “Choice of Technology and Long-Run Technical Change in Energy Intensive Industries.” The Energy Journal9(3): 79-97.
12.
GrosskopfS. (1986). “The Role of the Reference Technology in Measuring Productive Efficiency.” Economics Journal96(382): 499-513.
13.
HalvorsenR. (1977). “Energy Substitution in U.S. Manufacturing.” Review of Economics and Statistics59(4): 381-388.
14.
HirschbergJ.G.AignerD.J. (1983). “An Analysis of Commercial and Industrial Customer Response to Time-of-Use Rates.” The Energy Journal4: 104-126.
15.
JansonM.A. (1988). “Combining Robust and Traditional Least Squares Methods: A Critical Evaluation.” Journal of Business and Economic Statistics6(4): 415-427.
16.
LovellC.A.K.SchmidtP. (1988). “A Comparison of Alternative Approaches to the Measurement of Productive Efficiency.” A. Dogramaci and R. Fare, eds., Applications of Modem Productivity Theory: Efficiency and Productivity. Boston, MA: Kluwer Academic Publishers.
17.
PindyckR.S. (1979). “Interfuel Substitution and the Industrial Demand for Energy: An International Comparison.” Review of Economics and Statistics61(2): 169-179.
18.
RuffnerJ.A.BainF.E., ed. (1985). Weather of U.S. Cities. Detroit, MI: Gale Research Company.
19.
SeifordL.M.ThrallR.M. (1990). “Recent Developments in DEA.” Journal of Econometrics46: 7-38.
20.
TrimbleJ.HirstE. (1983). “Energy Use in Institutional Buildings: Estimates From State Energy-Audit Surveys.” Journal of Business and Economic Statistics1(4): 337-347.