Measurement error, education production and data envelopment analysis

Abstract Data Envelopment Analysis has become a popular tool for evaluating the efficiency of decision making units. The nonparametric approach has been widely applied to educational production. The approach is, however, deterministic and leads to biased estimates of performance in the presence of measurement error. Numerous simulation studies confirm the effect that measurement error has on cross-sectional deterministic models of efficiency. It is also known that panel data models have the ability to smooth out measurement error, leading to more reliable efficiency estimates. In this paper, we exploit known properties of educational production to show that aggregation can also have a smoothing effect on production with measurement error, suggesting that efficiency analyses are more reliable than previously believed.