Assessing European primary school performance through a conditional nonparametric model

This paper uses a fully nonparametric framework to assess the efficiency of primary schools using data about schools in 16 European countries participating in PIRLS 2011. This study represents an original enterprise since most of the empirical research in the field is restricted to evaluations at regional or national level and focused on secondary education. For our purpose, we adapt the metafrontier framework to compare and decompose the technical efficiency of primary schools operating in heterogeneous contexts, which in our case is represented by different educational systems or countries. Similarly, we use an extension of the conditional nonparametric robust approach to test the potential influence of a mixed set of environmental school factors and variables representing cultural values of each country. Our results indicate that the intergenerational transmission of non-cognitive skills such as responsibility or perseverance are significantly related to school efficiency, whereas most school factors do not seem to have a significant influence on school performance

Equity and efficiency in private and public education: a nonparametric comparison.

We extend the nonparametric ‘revealed preference’ methodology for analyzing collective consumption behavior (with consumption externalities and public consumption), to render it useful for empirical applications that deal with welfare-related questions. First, we provide a nonparametric necessary and sufficient condition for collectively rational group behavior that incorporates the possibility of assignable quantity information. This characterizes collective rationality in terms of feasible personalized prices, personalized quantities and income shares (representing the underlying sharing rule). Subsequently, we present nonparametric testing tools for data consistency with special cases of the collective model, which impose specific structure on the preferences of the group members (in terms of consumption externalities and public consumption); and we show that these testing tools in turn allow for nonparametrically recovering (bounds on) feasible personalized prices, personalized quantities and income shares that underlie observed (collectively rational) group behavior. In addition, we present formally similar testing and recovery tools for the general collective consumption model, which imposes minimal a priori structure. Interestingly, the proposed testing and recovery methodology can be implemented through integer programming (IP and MILP), which is attractive for practical applications. Finally, while we argue that assignable quantity information generally entails more powerful recovery results, we also demonstrate that precise nonparametric recovery (i.e. tight bounds) can be obtained even if no assignable quantity information is available.Business; Economics; Efficiency; Management; Research; Research in economics; University; University-research;

Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete environmental variables.

This paper proposes a fully nonparametric framework to estimate relative efficiency of entities while accounting for a mixed set of continuous and discrete (both ordered and unordered) exogenous variables. Using robust partial frontier techniques, the probabilistic and conditional characterization of the production process, as well as insights from the recent developments in nonparametric econometrics, we present a generalized approach for conditional efficiency measurement. To do so, we utilize a tailored mixed kernel function with a data-driven bandwidth selection. So far only descriptive analysis for studying the effect of heterogeneity in conditional efficiency estimation has been suggested. We show how to use and interpret nonparametric bootstrap-based significance tests in a generalized conditional efficiency framework. This allows us to study statistical significance of continuous and discrete environmental variables. The proposed approach is illustrated by a sample of British pupils from the OECD Pisa data set. The results show that several exogenous discrete factors have a significant effect on the educational process.

Blaming the exogenous environment? Conditional efficiency estimation with continuous and discrete environmental variables

This paper proposes a fully nonparametric framework to estimate relative efficiency of entities while accounting for a mixed set of continuous and discrete (both ordered and unordered) exogenous variables. Using robust partial frontier techniques, the probabilistic and conditional characterization of the production process, as well as insights from the recent developments in nonparametric econometrics, we present a generalized approach for conditional efficiency measurement. To do so, we utilize a tailored mixed kernel function with a data-driven bandwidth selection. So far only descriptive analysis for studying the effect of heterogeneity in conditional efficiency estimation has been suggested. We show how to use and interpret nonparametric bootstrap-based significance tests in a generalized conditional efficiency framework. This allows us to study statistical significance of continuous and discrete environmental variables. The proposed approach is illustrated by a sample of British pupils from the OECD Pisa data set. The results show that several exogenous discrete factors have a significant effect on the educational process.

Equity and efficiency in private and public education: a nonparametric comparison

We present a nonparametric approach for the equity and efficiency evaluation of (private and public) primary schools in Flanders. First, we use a nonparametric (Data Envelopment Analysis) model that is specially tailored to assess educational efficiency at the pupil level. The model accounts for the fact that minimal prior structure typically available for the behavior (objectives and feasibility set) under evaluation, it reckons with outlier behavior in the available data, while it corrects for ‘environmental’ characteristics that are specific to each pupil. Second, we propose first- and second-order stochastic dominance (FSD and SSD) criteria as naturally complementary aggregation criteria for comparing the performance of different school types (private and public schools) in Flanders. While FSD only accounts for (Pareto) efficiency, SSD also takes (Pigou-Dalton) equality into consideration. We find that private schools outperform public schools in terms of SSD.financial intermediation, loan rates, price discrimination, variance analysis.

Efficiency in education

Education is important at national, local and individual levels. Its benefits accrue both to society and to individuals, and as such provision of education in many countries is paid for at least in part from the public purse. With competing demands for government funding, it is important for education to be provided as efficiently as possible. Efficiency occurs when outputs from education (such as test results or value added) are produced at the lowest level of resource (be that financial or, for example, the innate ability of students). This special issue is devoted to the topic of efficiency in education, and is well-timed given that governments around the world struggle with public finances in the wake of the global financial crisis of 2008. In this paper, we explore and provide an overview of the themes of the special issue and introduce the papers contained therein

ILR Research in Progress 2011-12

The production of scholarly research continues to be one of the primary missions of the ILR School. During a typical academic year, ILR faculty members published or had accepted for publication over 25 books, edited volumes, and monographs, 170 articles and chapters in edited volumes, numerous book reviews. In addition, a large number of manuscripts were submitted for publication, presented at professional association meetings, or circulated in working paper form. Our faculty's research continues to find its way into the very best industrial relations, social science and statistics journals.Research_in_Progress_2011_12.pdf: 46 downloads, before Oct. 1, 2020

Intraday forecasts of a volatility index: Functional time series methods with dynamic updating

As a forward-looking measure of future equity market volatility, the VIX index has gained immense popularity in recent years to become a key measure of risk for market analysts and academics. We consider discrete reported intraday VIX tick values as realisations of a collection of curves observed sequentially on equally spaced and dense grids over time and utilise functional data analysis techniques to produce one-day-ahead forecasts of these curves. The proposed method facilitates the investigation of dynamic changes in the index over very short time intervals as showcased using the 15-second high-frequency VIX index values. With the help of dynamic updating techniques, our point and interval forecasts are shown to enjoy improved accuracy over conventional time series models.Comment: 29 pages, 5 figures, To appear at the Annals of Operations Researc