Variable selection for dynamic measures of efficiency in the computer industry

Data Envelopment Analysis (DEA) measures of efficiency are very sensitive to the choice of variables for two reasons: the number of efficient firms is directly related to the number (n) of variables and the selection of the n variables greatly affects the measure of efficiency. A methodology is proposed which identifies the optimal number of variables, and which identifies the contribution of each variable to the measure of efficiency. The computer industry is used as an example to illustrate the method.