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General Paper

Efficiency in education: a review of literature and a way forward

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Pages 339-363 | Published online: 21 Dec 2017
 

Abstract

This paper provides an extensive overview of the literature on efficiency in education. It summarizes the earlier applied inputs, outputs and contextual variables, as well as the used data sources of papers in the field of efficiency in education. Moreover, it reviews the papers on education that applied methodologies as data envelopment analysis, Malmquist index, Bootstrapping, robust frontiers, metafrontier or stochastic frontier analysis. Based on the insights of the literature review, a second part of the paper provides some ways forward. It attempts to establish a link between the parametric ‘economics of education’ literature and the (semi-parametric) ‘efficiency in education literature’. We point to the similarities between matching and conditional efficiency; difference-in-differences and metafrontiers; and quantile regressions and partial frontiers. The paper concludes with some practical directions for prospective researchers in the field.

Acknowledgements

We thank participants of the Workshop on Efficiency in Education of Lancaster University, Wim Groot, Carla Haelermans, Sergio Perelman, Emmanuel Thanassoulis, Geraint Johnes, Jill Johnes, Maria Portela, Eline Sneyers, John Ruggiero, Tommaso Aggastisti, two anonymous referees and the associate editor for valuable comments and suggestions on an earlier draft.

Notes

1 See CitationLovell (1993) or CitationCoelli et al (1998) for a detailed discussion on the methods for analysing technical efficiency.

2 There are a large number of publications that review the literature about educational effectiveness research (eg CitationMortimore, 1991; CitationReynolds, 2010; CitationReynolds et al, 1994; CitationTeddlie, 2010, among others).

3 Papers from 2015 can be found online before the year starts.

4 The Appendix is available from authors upon request.

5 A review of the advantages and shortcomings of different frontier analysis techniques can be found in CitationFried et al (2008).

6 We thank an anonymous referee for pointing this out.

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