What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables

Witte, Kristof De; Kortelainen, Mika

doi:10.1080/00036846.2012.665602

Cited by 135 publications

(112 citation statements)

References 24 publications

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“…Hence, it is possible to find works using this approach to measure the efficiency of units operating in multiple frameworks such as the educational sector (Bonaccorsi et al, 2006;Cherchye et al, 2010;De Witte and Rogge, 2011;Haelermans and De Witte, 2012;De Witte and Kortelainen, 2013;, banks and mutual funds (Daraio and Simar, 2005;Daouia and Simar, 2007;Blass et al, 2008;Badin et al, 2010), post offices (Cazals et al, 2008), public libraries (De Witte and Geys, 2011;, regional welfare or environment Tzeremes, 2011a, Halkos andTzeremes, 2013), local services (Rogge and De Jaeger, 2012;Verschelde and Rogge, 2012) or the water sector Marques, 2010a, 2010b;Carvalho and Marques, 2011;Vidoli, 2011). However, to the best of our best knowledge, this methodology has only been applied previously in the health sector to measure the efficiency of health administrative districts in Greece (Halkos and Tzeremes, 2011b) considering only continuous exogenous variables.…”

Section: Introductionmentioning

confidence: 99%

Efficiency assessment of primary care providers: A conditional nonparametric approach

Ferrera

Alonso-Morán

Nuño-Solinís

et al. 2015

European Journal of Operational Research

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This paper uses a fully nonparametric approach to estimate efficiency measures for primary care units incorporating the effect of environmental factors. This methodology allows us to account for different types of variables (continuous and discrete) regarding the main characteristics of patients served by those providers. In addition, we use an extension of this nonparametric approach to deal with the presence of undesirable outputs in data, represented by the number of readmissions and hospitalization rates of ambulatory care sensitive condition (ASCS). The empirical results of our application show that all the exogenous variables considered have a significant and negative effect on efficiency estimates.

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Section: Introductionmentioning

confidence: 99%

Efficiency assessment of primary care providers: A conditional nonparametric approach

Ferrera

Alonso-Morán

Nuño-Solinís

et al. 2015

European Journal of Operational Research

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“…Also, 474 farms (or 91.33%) of the total lie on the respective conditional α-quantile frontiers. Overall, accounting for the operational environment leads to a much more concentrated distribution of the estimated efficiency scores suggesting that the operating environment does affect the productive performance of the olive growing farms Kortelainen, 2013). Fig.…”

Section: Resultsmentioning

confidence: 99%

“…De Witte & Kortelainen (2013) extended the ideas of Simar (2005 and2007) to general Z vectors involving multiple continuous and discrete (both ordered and unordered) environmental factors. Moreover, they developed appropriate tools of statistical inference.…”

Section: Methodsmentioning

confidence: 99%

“…Robust nonparametric efficiency estimators along with a probabilistic formulation of the production process have been applied to banking, mutual funds, post offices, and education (e.g. Daouia & Simar, 2007;Daraio & Simar, 2007;De Witte & Kortelainen, 2013). To the best of knowledge, there has been so far only one application to agricultural sector; that was by Kourtesi et al (2012) on cereal growing farms in Greece.…”

Section: Introductionmentioning

confidence: 99%

“…weather conditions for the agricultural sector or resource stocks for resource-based industries). The innovations are based on recent developments concerning modeling and statistical inference in nonparametric frameworks (Racine et al, 2006;De Witte & Kortelainen, 2013). …”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Technical efficiency of Greek olive growing farms: a robust approach with panel data

Kourtesi

Fousekis

Polymeros

2013

Span. j. agric. res.

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The assessment of technical efficiency (TE) provides information to managers and to policy makers about differences in performance among production units and the potential for improvements. Economic research on this important topic has evolved largely around two alternative approaches, namely, the parametric and the nonparametric. The first allows for random noise and, as a consequence, for some observations to lie outside the production set while the second assumes that all observations belong to the production set with probability equal to 1. The parametric models require restrictions on the shape of the production frontier (benchmark) and on the underlying data generation process (e.g. Stevenson, 1980;Battese & Coelli, 1988). Therefore, they lack robustness in cases where the functional forms of the frontier and/or the error structure are not correctly specified. The estimation of nonparametric frontier models has been, until recently, pursued through envelopment techniques such as the Data Envelopment Analysis (DEA) (Charnes et al., 1978) and the Free Disposal Hull (FDH) (Deprins et al., 1984) that are quite appealing since they rely on very few assumptions. They are, however, by construction quite sensitive to outliers or to extreme values. This is certainly an important problem when one is interested in assessing TE of production units in economic activities where the amount of output is subject to random shocks. In farming, for example, the level of realized output can be quite different from the planned one because of weather conditions and pest attacks.During the last decade considerable research effort has been devoted to the development of robust nonparametric efficiency estimators. Cazals et al. (2002) AbstractThe assessment of technical efficiency in the agricultural sector and the influence of exogenous (environmental) variables on the production process has been a major topic of economic research especially for managers and policy makers. The methological innovation of the present study involves the impact of environmental variables on efficiency and the utilization of panel data for the empirical analysis. This has been pursued using full nonparametric robust frontier techniques (the alpha-quantile estimator) and a panel data set of olive growing farms in Greece from the Farm Accountancy Data Network of the EU. According to the empirical results, the ratio of owned to total land, the ratio of family to total labor, the degree of specialization, and a farm's location have a statistically significant impact on performance, which is not constant but varies over the 2006 to 2009 period considered.

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Applications of Data Envelopment Analysis in Education

Thanassoulis

Witte

Johnes

et al. 2016

International Series in Operations Research &Amp; Management Science

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What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables

Cited by 135 publications

References 24 publications

Efficiency assessment of primary care providers: A conditional nonparametric approach

Efficiency assessment of primary care providers: A conditional nonparametric approach

Technical efficiency of Greek olive growing farms: a robust approach with panel data

Applications of Data Envelopment Analysis in Education

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