Monitoring Efficiency in Public Education – A Value-Added Approach

Abstract

This study examines the inefficiency of public secondary schools in Texas using value-added and data envelopment analysis (DEA). The empirical application uses four-year panel data from 410 school districts and applied seemingly unrelated regression (SUR) to determine the effect of socioeconomic and environmental factors on students test scores. Next, the raw test scores are adjusted using predicted residuals from the SUR regression model and applied as outputs in an output-oriented DEA model. Several school characteristics are used as inputs in the DEA model that generates school specific (in)efficiency scores. The study found the secondary schools in Texas are mostly efficiency, the average efficiency across all schools and for all years is 90.5 percent. However, the Malmquist productivity index found the total factor productivity (TFP) decreased over the time. The study found dropout rate, poverty, low English proficiency, and disability affects test scores negatively; and the cohort test score from the prior year affect current year test scores positively. To our knowledge this is the first effort to measure efficiency of secondary school in Texas using robust mythology. This study provides valuable insights to policymakers, education researchers, and parents to make informed decisions on school choice.