Sensitivity and dimensionality tests of data envelopment analysis efficiency scores

Extending Hughes and Yaisawarng, this paper addresses issues of dimensionality for enhancing the credibility of data envelopment analysis (DEA) results in practical applications and assisting practitioners in making an appropriate selection of variables for a DEA model. The paper develops a structured approach to testing whether changing the number of model variables for a fixed sample size affects DEA results. Using a simulation method, the paper tests whether a calculated DEA efficiency score reflects the dimension of the model or the existence of inefficiency. An empirical illustration is included.