The effect of correlation coefficient among multiple input vectors on the efficiency mean in data envelopment analysis

In some of the papers on data envelopment analysis (DEA), there have been explained that if correlation coefficient between each pair of input (output) vectors is strong and positive, one of the input (output) vector could be omitted. The objective of this paper is to determine correlation coefficient threshold that beyond which omission of one or more input vectors have no statistically significant effect on the efficiency mean. The threshold identification in terms of some of the DEA models including CCR, CCRCSW, BCC and BCCCSW are performed. To analyze the data, analysis of variance (ANOVA) is used.

[1]  Karen Yong.  Efficiency of Hospitals in Victoria under Casemix Funding : A Stochastic Frontier Approach , 2000 .

[2]  William W. Cooper,et al.  SHORT COMMUNICATION: MEASURING EFFICIENCY OF DECISION MAKING UNITS , 1979 .

[3]  Joe Zhu,et al.  Identifying Excesses and Deficits in Chinese Industrial Productivity (1953-1990): a Weighted Data Envelopment Analysis Approach , 1998 .

[4]  T. J. Cook,et al.  Evaluating the administrative efficiency of courts , 1982 .

[5]  Toshiyuki Sueyoshi,et al.  Estimation of Stochastic Frontier Cost Function Using Data Envelopment Analysis: an Application to the AT&T Divestiture , 1991 .

[6]  A. Charnes,et al.  A goal programming/constrained regression review of the Bell system breakup , 1988 .

[7]  Henry W. Altland,et al.  Applied Regression Analysis for Business and Economics , 2002, Technometrics.

[8]  F. Hosseinzadeh Lotfi,et al.  A method for finding common set of weights by multiple objective programming in data envelopment analysis. , 2000 .

[9]  Paul R. Kinnear,et al.  SPSS For Windows Made Simple , 1994 .

[10]  Riccardo Russo,et al.  A Student's Guide to Analysis of Variance , 1999 .

[11]  Emmanuel Thanassoulis,et al.  DEA and its use in the regulation of water companies , 2000, Eur. J. Oper. Res..

[12]  G. Casella,et al.  Statistical Inference , 2003, Encyclopedia of Social Network Analysis and Mining.

[13]  R. Bartels,et al.  The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand , 1998 .

[14]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[15]  D. Kleinbaum,et al.  Applied regression analysis and other multivariable methods, 3rd ed. , 1998 .

[16]  Shiuh-Nan Hwang,et al.  DATA ENVELOPMENT ANALYSIS IN MEASURING THE EFFICIENCY OF FOREST MANAGEMENT , 1993 .

[17]  Peter Smith,et al.  Model misspecification in Data Envelopment Analysis , 1997, Ann. Oper. Res..

[18]  Hardeo Sahai,et al.  The Analysis of Variance , 2000 .

[19]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .