The Choice of Estimation Method and Its Effect on Efficiency Measurement in Public Education: Stochastic Frontier Regression vs. Data Envelopment Analysis

The purpose of this paper is to extend the empirical literature on efficiency measurement in public education. Two estimation methods often used in determining efficiency in the production of public education are used to determine if the results from the methods are similar. The Oklahoma public schools are of interest because Oklahoma has a large number of districts with very different characteristics. The methods of estimation are Stochastic Frontier Regression (SFR) and Data Envelopment Analysis (DEA). SFR estimates the inefficiency model simultaneously with the production or cost function. In the DEA model, the first stage estimates the efficiency scores and the second stage uses a Tobit regression model to determine causes of inefficiency. In this study, the empirical results of the SFR and DEA efficiency scores for the majority of Oklahoma school districts are not identical, suggesting that the method of estimation affects the efficiency scores. In general, SFR generated a more favorable score than that of DEA. The results from the two estimation methods in the inefficiency model are also different. However, both methods suggest that the most important determinants of inefficiency are socioeconomic factors associated with each district.