Journal Article10.1177/109114218901700404
Measuring School District Performance
137
TL;DR: Data Envelopment Analysis (DEA) as mentioned in this paperernández et al. proposed a method of measuring performance in the public sector, specifically performance of school districts, which is closely related to the family of Farrell type efficiency measures as well as data envelopment analysis and can be viewed as a generalization of earlier work on educational production functions.
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Abstract: This article provides a method of measuring performance in the public sector, specifically performance of school districts. The technique is closely related to the family of Farrell type efficiency measures as well as data envelopment analysis (DEA). It also can be viewed as a generalization of earlier work on educational production functions. The approach gauges performance relative to the best practice frontier constructed from enveloping observed data points. It is nonparametric, i.e., no parametric functional form is imposed on the data, and the approach readily admits multiple goals or outputs. By way of illustration we apply this approach to a sample of Missouri school districts for the 1985-1986 school year. In order to reduce the impact of outliers we employ jackknifing techniques.
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Citations
An Empirical Survey of Frontier Efficiency Measurement Techniques in Education
TL;DR: In this article, the authors provide a survey of the empirical analyses in education using frontier efficiency measurement techniques, including the measurement of inefficiency in education and the determinants of educational efficiency.
Efficiency in education: a review of literature and a way forward
TL;DR: The authors provide an extensive overview of the literature on efficiency in education, summarizing the earlier applied inputs, outputs and contextual variables, as well as the used data sources of papers in the field of education.
On the measurement of technical efficiency in the public sector
TL;DR: Evidence is provided that the existing Data Envelopment Analysis model will overestimate the level of technical inefficiency and that the modified model developed in this paper does a better job controlling for exogenous factors.
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Statistical Inference and Nonparametric Efficiency: A Selective Survey
TL;DR: A brief and selective survey of statistical inference in nonparametric, deterministic, linear programming-based frontier models can be found in this paper, with a discussion of recent attempts to employ resampling methods to derive empirical distributions for hypothesis testing.
314
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