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This paper demonstrates that standard central limit theorem (CLT) results do not hold for means of nonparametric, conditional efficiency estimators, and provides new CLTs that permit applied researchers to make valid inference about mean conditional efficiency or to compare mean efficiency across groups of producers. The new CLTs are used to develop a test of the restrictive “separability” condition that is necessary for second-stage regressions of efficiency estimates on environmental variables. We show that if this condition is violated, not only are second-stage regressions difficult to interpret and perhaps meaningless, but also first-stage, unconditional efficiency estimates are misleading. As such, the test developed here is of fundamental importance to applied researchers using nonparametric methods for efficiency estimation. The test is shown to be consistent and its local power is examined. Our simulation results indicate that our tests perform well both in terms of size and power. We provide a real-world empirical example by re-examining Aly et al. (R. E. Stat., 1990) and rejecting the separability assumption implicitly assumed by Aly et al., calling into question results that appear in hundreds of papers that have been published in recent years. This article is protected by copyright. All rights reserved

Directional distances provide useful, flexible measures of technical efficiency of pro- duction units relative to the efficient frontier of the attainable set in input-output space. In addition, the additive nature of directional distances permits negative input or outputs quantities. The choice of the direction allows analysis of different strate- gies for the units attempting to reach the efficient frontier. Simar et al. (2012) and Simar and Vanhems (2012) develop asymptotic properties of full-envelopment, FDH and DEA estimators of directional distances as well as robust order-m and order-α di- rectional distance estimators. Extensions of these estimators to measures conditioned on environmental variables Z are also available (e.g., see Daraio and Simar, 2014). The resulting estimators have been shown to share the properties of their corresponding ra- dial measures. However, to date the algorithms proposed for computing the directional distance estimates suffer from various numerical drawbacks (Daraio and Simar, 2014). In particular, for the order-m versions (conditional and unconditional) only approx- imations, based on Monte-Carlo methods, have been suggested, involving additional computational burden. In this paper we propose a new fast and efficient method to compute exact values of the directional distance estimates for all the cases (full and partial frontier cases, unconditional or conditional to external factors), that overcome all previous difficulties. This new method is illustrated on simulated and real data sets. Matlab code for computation is provided in an appendix.

This paper studies the role of direct democracy in ensuring efficient and cost- effective provision of goods and services in the public sector. The sample consists of the population of municipalities in the German State of Bavaria, where in the mid-1990s considerable direct democratic reforms granted citizens with wide opportunities to directly participate in local affairs through binding initiatives. Using information on the municipal resources and the municipal provision of public goods, and applying a fully non-parametric approach to estimate local government overall efficiency, the analysis shows that more direct democratic activity is associated with higher government efficiency. This result suggests that more inclusive governance through direct decision-making mechanisms may induce more accountable and less inefficient governments.

Municipal solid waste collection is a public service with impact on the environment, public health, and the appearance of a municipal area. The standard of efficiency achieved in providing this service has a direct impact on household expenditure, since the costs of collection are recovered through citizens’ taxes. The failure to consider relevant performance drivers recently led some Italian waste utilities into bankruptcy and financial collapse. Following prior research to identify the environmental and operational variables affecting the efficiency and quality of waste collection services, this study applies a more suitable and robust non-parametric method based on conditional order-m efficiency to identify the performance drivers of the waste collection services in 40 municipalities in Verona province, Italy. The exogenous variables studied could be clustered as 1) customer features (size of population served, population density, tourist flows, and percentage of non-residential customers; 2) household features, measured by number of inhabitants per house; and 3) operational features, represented by tons of waste collected for each load, method adopted (curbside or street bin), and maturity achieved with a given method. The study demonstrates that all variables affect the cost efficiency of waste collection with different intensity and direction.

© 2016 Elsevier B.V. The objective of this paper is to assess the influence of public subsidies on farm technical efficiency using recent advances in nonparametric efficiency analysis. To this end, we use robust conditional frontier techniques as well as insights from recent developments in nonparametric econometrics. The paper contributes to the ongoing methodological discussion on how to model the effect of public subsidies on farmers’ production decisions. The analysis is conducted using an unbalanced panel data of 1604 observations from 313 French farms located in the French region Meuse over the period 2006–2011. The estimates indicate that public subsidies influence negatively the conditional technical efficiency of farms. This suggests that public subsidies affect both the range of the attainable set for the inputs and outputs and the distribution of the efficiency scores inside the attainable set. publisher: Elsevier articletitle: The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach journaltitle: European Journal of Operational Research articlelink: http://dx.doi.org/10.1016/j.ejor.2016.11.014 content_type: article copyright: © 2016 Elsevier B.V. All rights reserved. ispartof: European Journal of Operational Research vol:259 issue:3 pages:1112-1120 status: published

We propose a non-parametric methodology to study the presence of economies of scope between teaching and research (i.e., the teaching–research nexus). In particular, the paper advocates a conditional version of the ‘benefit-of-the-doubt’ approach to estimate the relationship between professors’ overall academic output, measured by a composite measure of multi-dimensional and importance-adjusted scores of teaching effectiveness and research productivity, and the time devoted to teaching and to research. The methodology is illustrated with a dataset of professors working at a Business & Administration department of a university college where the time allocation of teaching and research was assigned exogenously. The outcome of the analysis indicates the presence of limited scope economies for professors with an extensive research time.

This paper studies the influence of educational innovations on school performance. We apply a tailored, fully nonparametric conditional efficiency model to study secondary school efficiency in the Netherlands. The application uses official school data and a self-collected questionnaire on recent innovations in schools. In the nonparametric model, it is assumed that schools aim to maximize educational attainments of students under a budget constraint. The results suggest that innovations are positively related to efficiency. We find that profiling, pedagogic, process and education chain innovations are significantly related to school efficiency, whereas innovations in the professionalization of teachers are insignificantly related to school efficiency. Furthermore, the number of locations per school and the number of schools per governing body are negatively and significantly related to school efficiency. School type and region significantly influence school efficiency, whereas share of disadvantaged students, degree of urbanization and student/teacher ratio do not have significant influence.

In European countries, wastewater treatment service is often provided by utilities, which have to comply with environmental laws and, at the same time, should control costs in order to restrain tariff growth and earn profits. By applying a conditional order-m efficiency method, this study provides some insights to the operational variables affecting the efficiency of 137 plants owned by a water utility operating in Tuscany, Italy. These performance drivers are categorized as: 1) wastewater features, 2) plant technology, 3) other plant features, 4) output quality, and 5) sludge disposal method. Starting from some controversial results from prior literature, this paper provides some useful insights on the best policies that could be adopted by a utility to catch cost savings.

The objective of this paper is to assess the impact of public subsidies on farm technical efficiency using recent advances in nonparametric efficiency analysis. To this end, we use robust conditional frontier techniques as well as insights from recent developments in nonparametric econometrics. The paper contributes to the ongoing methodological discussion on how to model the effect of public subsidies on farmers’ production decisions. The analysis is conducted using an unbalanced panel data of 1,604 observations from 313 French farms located in the French region Meuse over the period 2006-2011. The estimates indicate that public subsidies influence negatively the conditional technical efficiency of farms. This suggests that public subsidies affect the range of attainable values for the inputs and outputs, and hence the shape of the boundary of the attainable set, as well as the distribution of inefficiencies inside the attainable set., L’objet de cet article est d'évaluer l’influence des subventions publiques sur l’efficacité technique des exploitations en utilisant des méthodes non-paramétriques récentes d'analyse d'efficacité. À cette fin, nous utilisons des techniques de frontières conditionnelles robustes ainsi que des développements récents de l'économétrie non-paramétrique. Le papier contribue à la discussion méthodologique en cours sur la façon de modéliser l'effet des subventions publiques sur les décisions de production des agriculteurs. L'analyse est réalisée à partir d'un panel non-cylindré de 1 604 observations provenant de 313 exploitations françaises situées dans la région Meuse sur la période 2006-2011. Les estimations indiquent que les subventions publiques influent négativement sur l'efficacité technique conditionnelle des exploitations. Cela suggère que les subventions publiques affectent à la fois la frontière des possibilités de production ainsi que la distribution des scores d'efficacité à l'intérieur de la frontière de production.

This paper demonstrates that standard central limit theorem (CLT) results do not hold for means of nonparametric conditional efficiency estimators, and provides new CLTs that do hold, permitting applied researchers to estimate confidence intervals for mean conditional efficiency or to compare mean efficiency across groups of produc- ers along the lines of the test developed by Kneip et al. (JBES, 2015b). The new CLTs are used to develop a test of the “separability" condition that is necessary for second-stage regressions of efficiency estimates on environmental variables. We show that if this condition is violated, not only are second-stage regressions meaningless, but also first-stage, unconditional efficiency estimates are without meaning. As such, the test developed here is of fundamental importance to applied researchers using non- parametric methods for efficiency estimation. Our simulation results indicate that our tests perform well both in terms of size and power. We present a real-world empiri- cal example by updating the analysis performed by Aly et al. (R. E. Stat., 1990) on U.S. commercial banks; our tests easily reject the assumption required for two-stage estimation, calling into question results that appear in hundreds of papers that have been published in recent years.

The objective of this paper is to assess the impact of public subsidies on farm technical efficiencyusing recent advances in nonparametric efficiency analysis. To this end, we use robust conditionalfrontier techniques as well as insights from recent developments in nonparametric econometrics.The paper contributes to the ongoing methodological discussion on how to model the effect ofpublic subsidies on farmers’ production decisions. The analysis is conducted using an unbalancedpanel data of 1,604 observations from 313 French farms located in the French region Meuse overthe period 2006-2011. The estimates indicate that public subsidies influence negatively theconditional technical efficiency of farms. This suggests that public subsidies affect the range ofattainable values for the inputs and outputs, and hence the shape of the boundary of the attainableset, as well as the distribution of inefficiencies inside the attainable set.; L’objet de cet article est d'évaluer l’influence des subventions publiques sur l’efficacité techniquedes exploitations en utilisant des méthodes non-paramétriques récentes d'analyse d'efficacité. Àcette fin, nous utilisons des techniques de frontières conditionnelles robustes ainsi que desdéveloppements récents de l'économétrie non-paramétrique. Le papier contribue à la discussionméthodologique en cours sur la façon de modéliser l'effet des subventions publiques sur lesdécisions de production des agriculteurs. L'analyse est réalisée à partir d'un panel non-cylindré de1 604 observations provenant de 313 exploitations françaises situées dans la région Meuse sur lapériode 2006-2011. Les estimations indiquent que les subventions publiques influentnégativement sur l'efficacité technique conditionnelle des exploitations. Cela suggère que lessubventions publiques affectent à la fois la frontière des possibilités de production ainsi que ladistribution des scores d'efficacité à l'intérieur de la frontière de production.

Students’ evaluations of teacher performance (SETs) are increasingly used by universities. However, SETs are controversial mainly due to two issues: (1) teachers value various aspects of excellent teaching differently, and (2) SETs should not be determined on exogenous influences. Therefore, this paper constructs SETs using a tailored version of the non-parametric Data Envelopment Analysis approach. In particular, we account for different values and interpretations that teachers attach to ‘good teaching’. Moreover, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics.

This paper presents a methodology to aggregate multidimensional research output. Using a tailored version of the non-parametric data envelopment analysis model, we account for the large heterogeneity in research output and the individual researcher preferences by endogenously weighting the various output dimensions. The approach offers three important advantages compared to the traditional approaches: (1) flexibility in the aggregation of different research outputs into an overall evaluation score; (2) a reduction of the impact of measurement errors and a-typical observations; and (3) a correction for the influences of a wide variety of factors outside the evaluated researcher’s control. As a result, research evaluations are more effective representations of actual research performance. The methodology is illustrated on a data set of all faculty members at a large polytechnic university in belgium. The sample includes questionnaire items on the motivation and perception of the researcher. This allows us to explore whether motivation and background characteristics (such as age, gender, retention, etc.,) of the researchers explain variations in measured research performance.

This study intends to understand how disaster is related to countries’ production efficiency using a sample of 137 countries over 1980–2011. We analyze the effect of the number of man-made and natural disaster occurrences on countries’ technological change (swift of the frontier) and technological catch-up (distribution of efficiencies). The results reveal an inverted “U” shape relationship between countries’ technological change and technological catch-up with disaster occurrences. This finding suggests that the effect on countries’ production efficiency is positive for lower number of disaster events; however, after a specific threshold value, the effect becomes negative. The results also reveal that low-income countries are negatively affected much quicker compared to high-income countries. Finally, it is evident that the negative effect of disaster occurrences impacts first countries’ technological catch-up and then their technology change.

Simar and Wilson (J. Econometrics, 2007) provided a statistical model that can rationalize two-stage estimation of technical efficiency in nonparametric settings. Two- stage estimation has been widely used, but requires a strong assumption: the second- stage environmental variables cannot affect the support of the input and output vari- ables in the first stage. In this paper, we provide a fully nonparametric test of this assumption. The test relies on new central limit theorem (CLT) results for uncondi- tional efficiency estimators developed by Kneip et al. (Econometric Theory, 2015a) and new CLTs for conditional efficiency estimators developed in this paper. The test can be implemented relying on either asymptotic normality of the test statistics or using bootstrap methods to obtain critical values. Our simulation results indicate that our tests perform well both in terms of size and power. We present a real-world empiri- cal example by updating the analysis performed by Aly et al. (R. E. Stat., 1990) on U.S. commercial banks; our tests easily reject the assumption required for two-stage estimation, calling into question results that appear in hundreds of papers that have been published in recent years.

We analyse the effect of competition on technical efficiency of Italian airports by applying a novel conditional nonparametric frontier analysis for the first time to the airport industry. We find that competition affects mostly the frontier of best performers, whilst airports that are lagging behind are less influenced. A novel two stage approach shows that, on average, competition has a negative impact on technical efficiency. We estimate a measure of pure efficiency , whitened from the main effect of the competition, whose distribution has a bi-modal shape, indicating the existence of two differently managed groups of airports.

The growing economic and environmental importance of managing water resources at a global level also entails greater efforts and interest in improving the functioning and efficiency of the increasingly more numerous wastewater treatment plants (WWTPs). In this context, this study analyzes the efficiency of a uniform sample of plants of this type located in the region of Valencia (Spain). The type of efficiency measure used for this (conditional order-m efficiency) allows continuous and discrete contextual variables to be directly involved in the analysis and enables the assessment of their statistical significance and effect (positive or negative). The main findings of the study showed that the quality of the influent water and also the size and age of the plants had a significant influence on their efficiency levels. In particular, as regards the effect of such variables, the findings pointed to the existence of an inverse relationship between the quality of the influent water and the efficiency of the WWTPs. Also, a lower annual volume of treated water and more modern installations showed a positive influence. Additionally, the average efficiency levels observed turned out to be higher than those reported in previous studies.

Simar and Wilson (J. Econometrics, 2007) provided a statistical model that can rationalize two-stage estimation of technical efficiency in nonparametric settings. Two-stage estimation has been widely used, but requires a strong assumption: the second-stage environmental variables cannot affect the support of the input and output variables in the first stage. In this paper, we provide a fully nonparametric test of this assumption. The test relies on new central limit theorem (CLT) results for unconditional efficiency estimators developed by Kneip et al. (Econometric Theory, 2015a) and new CLTs for conditional efficiency estimators developed in this paper. The test can be implemented relying on either asymptotic normality of the test statistics or using bootstrap methods to obtain critical values. Our simulation results indicate that our tests perform well both in terms of size and power. We present a real-world empirical example by updating the analysis performed by Aly et al. (R. E. Stat., 1990) on U.S. commercial banks; our tests easily reject the assumption required for two-stage estimation, calling into question results that appear in hundreds of papers that have been published in recent years.

This paper studies the role of direct democracy in ensuring efficient and cost- effective provision of goods and services in the public sector. The sample consists of the population of municipalities in the German State of Bavaria, where in the mid-1990s considerable direct democratic reforms granted citizens with wide opportunities to directly participate in local affairs through binding initiatives. Using information on the municipal resources and the municipal provision of public goods, and applying a fully non-parametric approach to estimate local government overall efficiency, the analysis shows that more direct democratic activity is associated with higher government efficiency. This result suggests that more inclusive governance through direct decision-making mechanisms may induce more accountable and less inefficient governments.

Existing university rankings apply fixed and exogenous weights based on a theoretical framework, stakeholder or expert opinions. Fixed weights cannot embrace all requirements of a `good ranking' according to the Berlin Principles. As the strengths of universities differ, the weights on the ranking should differ as well. This paper proposes a fully nonparametric methodology to rank universities. The methodology is in line with the Berlin Principles. It assigns to each university the weights that maximize (minimize) the impact of the criteria where university performs relatively well (poor). The method accounts for background characteristics among universities and evaluates which characteristics have an impact on the ranking. In particular, it accounts for the level of tuition fees, an English speaking environment, size, research or teaching orientation. In general, medium sized universities in English speaking countries benefit from the benevolent ranking. On the contrary, we observe that rankings with fixed weighting schemes reward large and research oriented universities. Especially Swiss and German universities significantly improve their position in a more benevolent ranking.

The 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.

The German potable water supply industry is regarded as being highly fragmented, thus inhibiting high potentials for efficiency improvements through consolidation. Focusing on a hypothetical restructuring of the industry, we apply Data Envelopment Analysis (DEA) to analyze the potential efficiency gains from mergers between water utilities at the county level. A conditional efficiency framework is used to account for the operating environment. Highest efficiency improvement potentials turn out to result from reducing individual inefficiencies. The majority of the 84 merger cases is characterized by merger gains, which are decomposed into a technical efficiency effect, a harmony effect and a scale effect. The results suggest to improve incentives for efficient operations in water supply and a consolidation of the industry structure.

The German potable water supply industry is regarded highly fragmented, thus preventing efficiency improvements that could happen through consolidation. Focusing on a hypothetical restructuring of the industry, we use a cross-section sample of 364 German water utilities in 2006, applying Data Envelopment Analysis, to analyze the potential efficiency gains from hypothetical mergers between water utilities at the county level. A conditional efficiency framework is applied to account for the water utilities' operating environments. A conditional order-m approach is applied for the detection of potential outlying observations. Merger gains are decomposed into a technical efficiency effect, a harmony effect and a scale effect. The greatest efficiency improvement potentials turn out to result from reducing individual inefficiencies while pure merger gains are found to be low. The results suggest improving incentives for efficient operations in water supply and a consolidation of the smallest water utilities. The final publication is available at Springer via http://dx.doi.org/10.1007/s11123-014-0407-x // This publication was produced as part of the GRASP project, funded by the European Commission through the 7th Framework Programme under contract no. 244725.

This paper contributes to the link between social and cultural factors with countries innovation performance. By measuring 25 countries’ innovation efficiency with the use of conditional and unconditional DEA (Data Envelopment Analysis) frontiers the paper provides empirical evidence of the effect of culture on countries’ innovation efficiency. Particularly, conditional and unconditional full frontier models are used alongside with bootstrap techniques in order to determine the effect of national culture on countries’ innovation performance. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating such issues. The results reveal that national culture has an impact on countries’ innovation efficiency. Analytically, the results indicate that higher PDI (power distance index), IDV (individualism) and UAI (uncertainty avoidance) values have a negative effect on countries innovation efficiency, whereas masculinity values appear to have a positive effect on countries innovation performance.

The performance of economic producers is often affected by external or environmental factors that, unlike the inputs and the outputs, are not under the control of the Decision Making Units (DMUs). These factors can be included in the model as exogenous variables and can help to explain the efficiency differentials, as well as improve the managerial policy of the evaluated units. A fully nonparametric methodology, which includes external variables in the frontier model and defines conditional DEA and FDH efficiency scores, is now available for investigating the impact of external-environmental factors on the performance. In this paper, we offer a state-of-the-art review of the literature, which has been proposed to include environmental variables in nonparametric and robust (to outliers) frontier models and to analyse and interpret the conditional efficiency scores, capturing their impact on the attainable set and/or on the distribution of the inefficiency scores. This paper develops and complements the approach of Badin et al. (2012) by suggesting a procedure that allows us to make local inference and provide confidence intervals for the impact of the external factors on the process. We advocate for the nonparametric conditional methodology, which avoids the restrictive “separability” assumption required by the two-stage approaches in order to provide meaningful results. An illustration with real data on mutual funds shows the usefulness of the proposed approach.

"Provision of most public goods (e.g., health care, libraries, education, police, fire protection, utilities) can be characterised by a two-stage production process. In the first stage, basic inputs (e.g., labour and capital) are used to generate service potential (e.g., opening hours, materials), which is then, in the second stage, transformed into observed outputs (e.g., school outcomes, library circulation, crimes solved). As final outputs are also affected by demand-side factors, conflating both production stages likely leads to biased inferences about public productive (in)efficiency and its determinants. Hence, this paper uses a specially tailored, fully non-parametric efficiency model allowing for both outlying observations and heterogeneity to analyse efficient public good provision in stage one only. We employ a dataset comprising all 290 Flemish public libraries. Our findings suggest that ideological stance of the local government, wealth and density of the local population and source of library funding (i.e., local funding versus intergovernmental transfers) strongly affect library productive efficiency. (Author's abstract) "Die Bereitstellung der meisten öffentlichen Güter (zum Beispiel Gesundheitsversorgung, Bibliotheken, Bildung, Polizei, Brandschutz, Stadtwerke) kann durch einen zweistufigen Produktionsprozess charakterisiert werden. In der ersten Stufe werden Produktionsfaktoren (beispielsweise Arbeit und Kapital) zur Erzeugung eines Dienstleistungspotenzials (beispielsweise Öffnungszeiten, Materialien) genutzt. Dieses Potenzial wird dann, in der zweiten Phase, in den beobachtbaren Output transformiert (zum Beispiel in Schulleistungen der Schüler, dem Bücherumlauf einer Bibliothek, aufgedeckte Straftaten). Da das Endergebnis auch von den Faktoren der Nachfrageseite bestimmt ist, führt eine unzureichende Trennung beider Produktionsstufen wahrscheinlich zu verzerrten Rückschlüssen bezüglich der öffentlichen produktiven (In-)Effizienz und ihrer Determinanten. Daher wird in dem Paper ein speziell zugeschnittenes, vollständig nichtparametrisches Effizienz-Modell benutzt. Dieses Modell ermöglicht isoliert für die 1. Produktionsstufe die Analyse der effizienten Bereitstellung öffentlicher Güter in einem Schritt. Dabei benutzen die Autoren einen Datensatz, welcher alle 290 flämischen öffentlichen Bibliotheken enthält. Die Ergebnisse legen nahe, dass die ideologische Einstellung der Gemeindeverwaltungen, Wohlstand und Dichte der ortsansässigen Bevölkerung, sowie die Art der Bibliotheksfinanzierung (zum Beispiel lokale Finanzierung oder überregionale Transfers) stark die produktive Effizienz der Bibliotheken beeinflussen." (Autorenreferat)

Conditional efficiency measures are very natural tools to capture the efficiency of firms facing heterogeneous environmental conditions. They are defined by the distance of a unit to the support of a conditional distribution, conditional to the level of these external factors. The traditional approach is to estimate nonparametrically this distribution and this requires the use of appropriate smoothing techniques. In this paper, we consider an alternative approach to estimate its support. We first assume flexible nonparametric location-scale models linking the inputs and the outputs to the environmental factors to eliminate in the inputs/outputs the dependence on Z. Then we use these “pre-whitened” inputs and outputs to define the optimal frontier function. This provides a “pure” measure of efficiency more reliable to produce rankings or benchmarks of units among themselves, since the influence of external factors has been eliminated. We estimate both the full frontier and its more robust version, the order-m frontier. The asymptotic properties are established. We can also recover the frontiers in the original inputs/outputs space and we give their asymptotic properties. The approach is illustrated with some selected simulated data but also with a real dataset from the bank industry.

By applying conditional and unconditional data envelopment analysis (DEA) models along side with statistical inference using bootstrap techniques; this paper investigates the link between China’s carbon dioxide emissions (CO2) environmental efficiency and its economic growth (measured in GNI per capita) for the time period of 1965 to 2009. The results reveal that China’s changing consumption patterns has caused emissions levels to increase dramatically the last two decades providing clear evidence of a negative effect of China’s GNI per capita increase on its environmental efficiency.

Students’ evaluations of teacher performance (SETs) are increasingly used by universities and colleges for teaching improvement and decision making (e.g., promotion or tenure). However, SETs are highly controversial mainly due to two issues: (1) teachers value various aspects of excellent teaching differently, and, to be fair, (2) SETs should be determined solely by the teacher’s actual performance in the classroom, not by other influences (related to the teacher, the students or the course) which are not under his or her control. To account for these two issues, this paper constructs SETs using a specially tailored version of the popular non-parametric Data Envelopment Analysis (DEA) approach. In particular, in a so-called ‘Benefit of the doubt’ model we account for different values and interpretations that teachers attach to ‘good teaching’. Within this model, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics. To show the potentiality of the method, we examine teacher performance for the Hogeschool Universiteit Brussel (located in Belgium). Our findings suggest that heterogeneous background characteristics play an important role in teacher performance.

Students’ evaluations of teacher performance (SETs) are increasingly used by universities and colleges for teaching improvement and decision making (e.g., promotion or tenure). However, SETs are highly controversial mainly due to two issues: (1) teachers value various aspects of excellent teaching differently, and, to be fair, (2) SETs should be determined solely by the teacher’s actual performance in the classroom, not by other influences (related to the teacher, the students or the course) which are not under his or her control. To account for these two issues, this paper constructs SETs using a specially tailored version of the popular non-parametric Data Envelopment Analysis (DEA) approach. In particular, in a so-called ‘Benefit of the doubt’ model we account for different values and interpretations that teachers attach to ‘good teaching’. Within this model, we reduce the impact of measurement errors and a-typical observations, and account explicitly for heterogeneous background characteristics arising from teacher, student and course characteristics. To show the potentiality of the method, we examine teacher performance for the Hogeschool Universiteit Brussel (located in Belgium). Our findings suggest that heterogeneous background characteristics play an important role in teacher performance. ispartof: CES - Discussion paper series 09.13 pages:1-24 status: published

Provision of most public goods (e.g., health care, library services, education, utilities) can be characterised by a two-stage ‘production’process. The first stage translates basic inputs (e.g., labour and capital) into service potential (e.g., opening hours), while the second stage describes how these programmatic inputs are transformed into observed outputs (e.g., school outcomes, library circulation). While the latter stage is best analysed in a supply-demand framework, particularly in the former stage one would like to have efficient public production. Hence, unlike previous work on public sector efficiency (which often conflates both ‘production’stages), this paper analyses how political economy factors shape efficient public good provision in stage one (using local public libraries as our centre of attention). To do so, we use a specially tailored, fully non-parametric efficiency model. The model is rooted in popular Data Envelopment Analysis models, but allows for both outlying observations and heterogeneity (i.e., a conditional efficiency model). Using an exceptionally rich dataset comprising all 290 Flemish public libraries, our findings suggest that the ideological stance of the local government, the wealth and density of the local population and the source of library funding (i.e., local funding versus intergovernmental transfers) are crucial determinants of library efficiency. ispartof: CES - Discussion paper series 09.10 pages:1-24 nrpages: 24 status: published