Estimating and explaining efficiency in a multilevel setting: A robust two-stage approach
AbstractVarious applications require multilevel settings (e.g., for estimating fixed and random effects). However, due to the curse of dimensionality, the literature on non-parametric efficiency analysis did not yet explore the estimation of performance drivers in highly multilevel settings. As such, it lacks models which are particularly designed for multilevel estimations. This paper suggests a semi-parametric two-stage framework in which, in a first stage, non-parametric efficiency estimators are determined. As such, we do not require any a priori information on the production possibility set. In a second stage, a semiparametric Generalized Additive Mixed Model (GAMM) examines the sign and significance of both discrete and continuous background characteristics. The proper working of the procedure is illustrated by simulated data. Finally, the model is applied on real life data. In particular, using the proposed robust two-stage approach, we examine a claim by the Dutch Ministry of Education in that three out of the twelve Dutch provinces would provide lower quality education. When properly controlled for abilities, background variables, peer group and ability track effects, we do not observe differences among the provinces in educational attainments
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Bibliographic InfoPaper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 10/657.
Length: 36 pages
Date of creation: Jul 2010
Date of revision:
Productivity estimation; Multilevel setting; Generalized Additive Mixed Model; Education; Social segregation;
Other versions of this item:
- De Witte, K. & Verschelde, M., 2010. "Estimating and explaining efficiency in a multilevel setting: A robust two-stage approach," Working Papers 17, Top Institute for Evidence Based Education Research.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-10-23 (All new papers)
- NEP-ECM-2010-10-23 (Econometrics)
- NEP-EFF-2010-10-23 (Efficiency & Productivity)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kristof DE WITTE & Mika KORTELAINEN, 2008. "Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete environmental variables," Center for Economic Studies - Discussion papers ces0833, Katholieke Universiteit Leuven, Centrum voor Economische Studiën.
- De Witte, K., 2009. "Dropout from secondary education: All's well that begins well," Working Papers 14, Top Institute for Evidence Based Education Research.
- Halkos, George & Tzeremes, Nickolaos, 2012. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from the UK regions," MPRA Paper 38147, University Library of Munich, Germany.
- Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier approach for investigating the Averch-Johnson effect," MPRA Paper 35491, University Library of Munich, Germany.
- Halkos, George & Tzeremes, Nickolaos, 2011. "A conditional full frontier modelling for analyzing environmental efficiency and economic growth," MPRA Paper 32839, University Library of Munich, Germany.
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