Testing over-representation of observations in subsets of a DEA technology

This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and suggests good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space.Data Envelopment Analysis (DEA); Over-representation; Data density; Binomial test; Convex hull

Event-specific Data Envelopment Models and Efficiency Analysis

Most, if not all, production technologies are stochastic. This article demonstrates how data envelopment analysis (DEA) methods can be adapted to accommodate stochastic elements in a state-contingent setting. Specifically, we show how observations on a random input, not under the control of the producer and not known at the time that variable input decisions are made, can be used to partition the state space in a fashion that permits DEA models to approximate an event-specific production technology. The approach proposed in this article uses observed data on random inputs and is easy to implement. After developing the event-specific DEA representation, we apply it to a data set for Western Australian wheat farmers. Our results highlight the need for acknowledging stochastic elements in efficiency analysis.

Profit Efficiency Analysis Under Limited Information. With an Application to German Farm Types

Lack of information about technology and prices often hampers the empirical assessment of the validity of the profit maximization hypothesis. We show that the non-parametric Data Envelopment Analysis (DEA) methodology comprises natural tools for dealing with such incomplete information. In particular, we focus on the economic meaning of the DEA model that builds on assumptions of monotone and convex production possibility sets, and provide some extensions that further exploit this economic interpretation. This perspective on DEA is all the more attractive since its original use for technical efficiency analysis is sometimes questionable given its restrictive production assumptions. An application to German farm types complements our methodological discussion. By using nonparametric tools to test specific hypotheses about profit differences, we further demonstrate the potential of the non-parametric approach in deriving strong and robust statistical evidence while imposing minimal structure on the setting under study.profit maximization hypothesis; Data Envelopment Analysis; non-parametric techniques; agriculture

Inferring the Latent Incidence of Inefficiency from DEA Estimates and Bayesian Priors

Data envelopment analysis (DEA) is among the most popular empirical tools for measuring cost and productive efficiency. Because DEA is a linear programming technique, establishing formal statistical properties for outcomes is difficult. We show that the incidence of inefficiency within a population of Decision Making Units (DMUs) is a latent variable, with DEA outcomes providing only noisy sample-based categorizations of inefficiency. We then use a Bayesian approach to infer an appropriate posterior distribution for the incidence of inefficient DMUs based on a random sample of DEA outcomes and a prior distribution on the incidence of inefficiency. The methodology applies to both finite and infinite populations, and to sampling DMUs with and without replacement, and accounts for the noise in the DEA characterization of inefficiency within a coherent Bayesian approach to the problem. The result is an appropriately up-scaled, noise-adjusted inference regarding the incidence of inefficiency in a population of DMUs.Data Envelopment Analysis, latent inefficiency, Bayesian inference,Beta priors, posterior incidence of inefficiency

Profit efficiency analysis under limited information. With an application to German farm types.

Efficiency; Information;

New Tools for Dealing with Errors-in-Variables in DEA.

We develop a series of novel conceptual tools to systematically account for errors-in-variables in Data Envelopment Analysis (DEA). These tools allow for statistical inference while requiring minimal statistical distribution assumptions, and therefore constitute a valuable addition to the tools currently available for dealing with errors-in-variables. An empirical application for large European Union financial institutions illustrates the proposed approach.Data Envelopment Analysis (DEA), errors-in-variables, efficiency depth, robust reference sets, financial institutions

New tools for dealing with errors-in-variables in DEA.

Errors in variables; Tool;

The Size and Service Offering Efficiencies of U.S. Hospitals.

Hospital productivity has been a research topic for over two decades. We expand on this research to include measures of dis/economies of scope. By using the Free Coordination Hull (FCH) we are able to determine if hospitals in our sample can become more efficient if they provide more services (diseconomies of scope) or if two smaller hospitals with a reallocation of resources could become more efficient (economies of scope). Using data from the American Hospital Association for the years 2004-2007, we found variations among hospital markets (measured by the Core Based Statistical Area). We can determine whether dis/economies of scope exist by comparing the results from two linear programming problems. Focusing on four markets: Los Angeles, Philadelphia, Madison, WI, and New Orleans we found variations in how best these hospitals operating in these markets could change in order to increase both scale and scope efficiencies. This approach could be used by policy makers and managers in order to reduce costs by sharing, reducing, or expanding services in hospitals. Findings from a study such as this should aid reform programs by providing more information on the sources of hospital inefficiency.Hospital, Efficiency, Economies of Scope, Hospital Markets

The political economy of efficient public good provision: evidence from flemish libraries using a generalised conditional efficiency framework.

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.Nonparametric estimation; Conditional efficiency; Political economy; Public good provision; Libraries;

The political economy of efficient public good provision: evidence from Flemish libraries using a generalised conditional efficiency framework

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.Nonparametric estimation, Conditional efficiency, Political economy, Public good provision, Libraries.