Nonparametric Efficiency Analysis Research Articles

Nonparametric efficiency analysis with unobserved inputs in multi-output settings

Transport service providers are increasingly interested in benchmarking. The digitized nature of railway management, which relies heavily on automation and intangible inputs, conflicts with standard assumptions in the benchmarking literature that maintain full knowledge of all input factors. This creates a potential for omitted variable bias during efficiency measurement. In addition, designing accurate improvement actions requires output-specific rather than overall efficiency scores. To address these concerns we compute output-specific cost efficiency scores for multi-output entities where a subset of inputs remain unobserved to the analyst. We apply the method to highly customized data on Belgian railway traffic control rooms. We document that the magnitude of the omitted variable bias differs across outputs. Moreover, the results of a metafrontier analysis suggest that there are substantial differences in production possibilities across control rooms.

Modelling Time-Varying Rankings with Autoregressive and Score-Driven Dynamics

AbstractWe develop a new statistical model to analyse time-varying ranking data. The model can be used with a large number of ranked items, accommodates exogenous time-varying covariates and partial rankings, and is estimated via the maximum likelihood in a straightforward manner. Rankings are modelled using the Plackett–Luce distribution with time-varying worth parameters that follow a mean-reverting time series process. To capture the dependence of the worth parameters on past rankings, we utilise the conditional score in the fashion of the generalised autoregressive score models. Simulation experiments show that the small-sample properties of the maximum-likelihood estimator improve rapidly with the length of the time series and suggest that statistical inference relying on conventional Hessian-based standard errors is usable even for medium-sized samples. In an empirical study, we apply the model to the results of the Ice Hockey World Championships. We also discuss applications to rankings based on underlying indices, repeated surveys and non-parametric efficiency analysis.

Portfolio optimization with asset preselection using data envelopment analysis

This paper uses data envelopment analysis (DEA) approach as a nonparametric efficiency analysis tool to preselect efficient assets in large-scale portfolio problems. Thus, we reduce the dimensionality of portfolio problems, considering multiple asset performance criteria in a linear DEA model. We first introduce several reward/risk criteria that are typically used in portfolio literature to identify features of financial returns. Secondly, we suggest some DEA input/output sets for preselecting efficient assets in a large-scale portfolio framework. Then, we evaluate the impact of the preselected assets in different portfolio optimization strategies. In particular, we propose an ex-post empirical analysis based on two alternative datasets: the components of S &P500 and the Fama and French 100 portfolio formed on size and book to market. According to this empirical analysis we observe better performances of the DEA preselection than the classic PCA factor models for large scale portfolio selection problems. Moreover, the proposed model outperform the S &P500 index and the strategy based on the fully diversified portfolio.

Meta-frontier and technology switchers: A nonparametric approach

The concept of meta-frontier has been proposed in order to deal with group heterogeneity among entities for nonparametric efficiency analysis. In brief, the meta-frontier is defined as the envelopment of the group-specific frontiers and naturally allows one to distinguish inefficiency from technology gap. While this concept has demonstrated its usefulness for empirical studies and been extended in several directions, two major shortcomings are the fixed number of groups and the static allocation of entities across groups. This is particularly problematic when dealing with panel data. In this paper, we extend the meta-frontier approach when technology switchers are considered, and quantify the impacts of the switchers on inefficient behavior and technology gap. We demonstrate the usefulness of our new methodology with the case of the technology clubs in the world economy.

Greenhouse Gas Emission Reduction Potentials in Europe by Sector: A Bootstrap-Based Nonparametric Efficiency Analysis

The reduction of greenhouse gas emissions is the key action to limit global warming. An important source of greenhouse gas emissions and pollution is the inefficiency of production processes. We report results from a stochastic nonparametric efficiency analysis using directional distance functions to take account of undesirable outputs like greenhouse gases. With this approach, we are able to provide estimates of the potential emission reductions for 7 main sectors in 16 European countries. A specially adapted bootstrapping approach allows to implement a bias correction of the estimates and to compute confidence intervals. The results show that static efficiency improvements are a quantitatively important element of the emission reductions which are required to achieve the reduction targets of the European Union.

Greenhouse Gas Emission Reduction Potentials in Europe by Sector: A Bootstrap-Based Nonparametric Efficiency Analysis

Greenhouse Gas Emission Reduction Potentials in Europe by Sector: A Bootstrap-Based Nonparametric Efficiency Analysis

Determinants of Allocative, Cost and Scope Efficiencies: A Comparative Analysis of Banks and Insurance Companies in Pakistan

The purpose of this research paper is to empirically investigates determinants of allocative, cost and scope efficiencies as well as impact of financial crisis and stock market performance on efficiencies. Pakistan’s banks and insurance companies’ sector were taken for the purpose of comparative analysis. For this objective both Islamic/takaful and conventional sectors were occupied. Twelve years data (2007-2018) of PSX’s banking and insurance sector was taken. Two stage non-parametric efficiency analysis was done, in the first stage, estimation for efficiency scores we used DEA for both sectors. In second phase, efficiency scores are regressed on the selected determinants by Tobit Regression. For measuring stock market performance CASR is calculated. Inadequate efficiency in insurance sector is evidenced against banking sector. Efficiency of takaful firms as new entrants of the market was not good comparatively to conventional insurance firms. Islamic and conventional banks are operated at almost same efficiency level. Performance of stock market has inverse and both (significant and insignificant) relationship with efficiency, means different events and fundamentals don’t affect the performance of sectors that is why efficiencies are not hit by this way. As well as determinants have different relationship with allocative, cost and scope efficiencies scores.

Dynamic directional nonparametric profit efficiency analysis for a single decision-making unit: an aggregation approach

We propose a simple and intuitive nonparametric technique to assess the profit performances of a single decision-making unit over time. The particularity of our approach lies in recognizing that technological change may be present in the profit evaluation exercise. We partition the periods of time into several time intervals, in such a way that the technology is fixed within intervals but may differ between intervals. Attractively, our approach defines a new Luenberger-type indicator for dynamic profit performance evaluation when a single decision-making unit is of interest, and provides a coherent and systematic way to compare the profit performance changes between the periods of time and the time intervals. To define the interval-level concepts, we rely on a flexible weighting linear aggregation scheme. We also show how the new indicator can be decomposed into several dimensions. We illustrate the usefulness of our methodology with the case of the Chinese low-end hotel industry in 2005–2015. Our results highlight a performance regression, which is mainly due to the technical components of the indicator decomposition.

How to measure the usage of regional potentials of renewable energies. An empirical analysis of German counties

This paper answers two rarely considered questions: How well do German regions exploit their potential to produce renewable energy and which factors impact on this exploitation efficiency? By applying the new quantitative-empirical concept of exploitation efficiency, we measure the degree, to which regions have exploited their natural and socio-economic potentials of producing energy from renewable source at a specific point in time. This approach allows, with respect to wind power, solar power and biogas energy, a relative comparison of regions, monitoring their performance over time as well as the identification of best-practice regions. Applying our innovative method, we compare German districts in the time period 2000-2014. We use a robust, non-parametric efficiency analysis and validate its results by qualitative expert interviews in selected counties in Lower Saxony. The results show strong disparities in terms of the exploitation efficiency between districts and federal states. This exploitation efficiency moreover varies significantly for different types of renewable energy. We also observe specialization tendencies in this context. Our empirical results are very detailed both from a spatial and from a temporal perspective and therefore allow for drawing several conclusions for local and federal state policies. For instance, those districts (and federal states) with currently rather low exploitation efficiencies need to learn from those with high efficiencies. Such learning effects may sustainably contribute to a successful turnaround in energy policy.

Regulatory own goals: the unintended consequences of economic regulation in professional football

ABSTRACTResearch questionIn 2010, the governing body of European football, UEFA, approved ‘Financial Fair Play’ regulations. Designed to encourage financial discipline, promote stability and foster competitive balance, they focus on a financial breakeven constraint. We analyse the impact of such constraints on the joint sporting and financial efficiency of English football clubs.Research methodsThe simultaneous production of both sporting and financial outputs are modelled using stochastic, non-parametric efficiency analysis. The sample is an unbalanced panel representing 60 clubs spanning the 2003/2004 to 2016/2017 seasons.Results and findingsThe Financial Fair Play breakeven regulation reduces average club efficiency, raises the relative importance of financial goals (capturing revenue share) whilst lowering the relative importance of sporting goals (capturing point share). The efficiency costs of regulation are not borne equally by clubs.ImplicationsBreakeven regulations reduce the joint sporting and financial efficiency of regulated clubs, with the efficiency loss positively related to the severity of the breakeven constraint. The Financial Fair Play regulations further entrench the financial and sporting power of elite clubs and potentially undermine league competitive intensity by shifting the relative focus of clubs away from sporting productivity toward financial productivity.

Input allocation in multi-output settings: Nonparametric robust efficiency measurements

Comparing decision making units to detect their potential efficiency improvement, without relying on parametric unverifiable assumptions about the production process, is the goal of nonparametric efficiency analysis (such as FDH, DEA). While such methods have demonstrated their practical usefulness, practitioners sometimes have doubts about their fairness. In multi-output settings, two main limitations could give credit to their doubts: (1) the production process is modelled as a “black box,” i.e., it is implicitly assumed that all the inputs produce simultaneously all the outputs; (2) only techniques investigating for outliers in all output directions simultaneously exist. In this article, we tackle these two limitations by presenting two new nonparametric robust efficiency measurements for multi-output settings. Our new measurements present several attractive features. First, they increase the realism of the modelling by taking the links between inputs and outputs into account, and thus tackle (1). Second, they provide flexibility in the outlier detection exercise, and thus also tackle (2). Overall, our new measurements better use the data available, and can be seen as natural extensions of well-known nonparametric robust efficiency measurements for multi-output contexts. To demonstrate the usefulness of our method, we propose both a simulation and an empirical application.

Determinants of Allocative, Cost and Scope Efficiencies: A Comparative Analysis of Banks and Insurance Companies in Pakistan

The purpose of this research paper is to empirically investigate determinants of allocative, cost and scope efficiencies as well as the impact of the financial crisis and stock market performance on efficiencies. Pakistan’s banks and insurance companies’ sector were taken for the purpose of comparative analysis. For this objective, both Islamic/takaful and conventional sectors were occupied. Twelve years of data (2007-2018) of PSX’s banking and insurance sector was taken. Two-stage non-parametric efficiency analysis was done, in the first stage, estimation for efficiency scores we used DEA for both sectors. In the second phase, efficiency scores are regressed on the selected determinants by Tobit Regression. For measuring stock market performance CASR is calculated. Inadequate efficiency in the insurance sector is evidenced by the banking sector. The efficiency of takaful firms as new entrants of the market was not good compared to conventional insurance firms. Islamic and conventional banks are operated at almost the same efficiency level. Performance of the stock market has an inverse and both (significant and insignificant) relationship with efficiency, which means different events and fundamentals don’t affect the performance of sectors. As well as determinants have different relationships with allocative, cost and scope efficiencies scores.

Assessing branch efficiency and managerial behaviour in a large Spanish commercial bank

ABSTRACTThis paper describes a two-stage procedure used to evaluate determinants of operational efficiency and profit dimensions, as an indication of the performance of branch managers in a large Spanish commercial bank, before and after the bailout of the Spanish banking system in 2012. This procedure is based on both the non-parametric and robust non-parametric frontier methods and on partial frontier-based outlier detection (following Daraio and Simar) which enables us to detect potential outliers in the data, after which a classical non-parametric efficiency analysis is performed. In the first stage, efficiencies are obtained from annual data supplied by bank branches regarding the period 2011–2014. High scores were obtained in operational and profit efficiencies for DEA (pure technical and scale efficiencies), FDH and order-α estimators. In general, the following hierarchies of scores were obtained: DEA<FDH<order-α. In the second stage of our analysis, a censored econometric model approach was applied (following Simar and Wilson) to identify the drivers of efficiency. Finally, the implications of this study for policymakers are discussed.

An Analysis of the Efficiency and Productivity of Social Enterprise Using DEA and MPI

본 연구는 20개 사회적기업의 2015년부터 2017년까지 3년간 자료를 대상으로 비모수 효율성 측정 모형인 DEA 모형과 Malmquist 생산성 측정 모형을 적용하여 효율성과 생산성 변화를 분석하였다. DEA 분석 결과에 따르면, 사회적기업의 CCR 모형에 의한 효율성의 평균은 2015년 0.878, 2016년 0.875, 2017년 0.862로 나타났으며 BCC 모형에 의한 효율성의 평균은 2015년 0.965, 2016년 0.958, 2017년 0.924로 나타났다. Malmquist 생산성 지수의 분석 결과에 따르면, 시계열 평균 생산성 지수 MPI가 2.9% 증가하였는데 이는 기술효율성 및 순수효율성변화의 감소보다는 기술변화 및 규모효율성변화의 증가에 기인한 것임을 알 수 있었다.This study analyzed changes in the efficiency and productivity by utilizing the three year long data of the 20 social enterprise from 2015 to 2017, using non-parametric efficiency analysis models, DEA model and Malmquist Productivity Index analysis model. According to the result of DEA, Technical Efficiency average based on CCR model of the social enterprise was 0.878 in 2015, 0.875 in 2016 and 0.862 in 2017. Pure Technical Efficiency due to BCC model was 0.965 in 2015, 0.958 in 2016 and 0.924 in 2017. According to the result of Malmquist Productivity Index, when the time series average productivity index was examined, MPI had increased 2.9%. This demonstrates that this is derived not so much from the decrease in the Technical Efficiency Change and Pure Efficiency Change but from the increase in the Technological Change and Scale Efficiency Change.

Direct targeting of efficient DMUs for benchmarking

We propose a two-stage procedure for finding realistic benchmarks for nonparametric efficiency analysis. First, the efficient units are identified by a free disposal hull approach. These benchmarks are directly targeted by directional distance functions and the extent of inefficiency is measured along the direction towards an existing efficient unit. Two variants for finding the closest or the farthest benchmark are proposed. With this approach there is no need to use linear combinations of efficient units as benchmarks which may not be achievable in reality and also no need to accept slacks which are not reflected by the efficiency measure.

The Opportunity Cost of Financial Fair Play Regulation in Professional Football - An Efficiency Analysis

Research question: In 2010, the governing body of European football, UEFA, approved “Financial Fair Play” regulations. Designed to encourage financial discipline, promote stability and foster competitive balance, they focus on a financial breakeven constraint. We analyse the impact of such constraints on the joint sporting and financial efficiency of English football clubs. Research methods: The simultaneous production of both sporting and financial outputs are modelled using stochastic, non-parametric efficiency analysis. The sample is an unbalanced panel representing 60 clubs spanning the 2003/2004 to 2016/2017 seasons. Results and Findings: The Financial Fair Play breakeven regulation reduces average club efficiency, raises the relative importance of financial goals (capturing revenue share) whilst lowering the relative importance of sporting goals (capturing point share). The efficiency costs of regulation are not borne equally by clubs. Implications: Breakeven regulations reduce the joint sporting and financial efficiency of regulated clubs, with the efficiency loss positively related to the severity of the breakeven constraint. The Financial Fair Play regulations further entrench the financial and sporting power of elite clubs and potentially undermine league competitive intensity by shifting the relative focus of clubs away from sporting productivity toward financial productivity.

The influence of public subsidies on farm technical efficiency: A robust conditional nonparametric approach

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.

Revisiting the world technology frontier: a directional distance function approach

This paper revisits the finding of Caselli and Coleman (Amer Econ Rev 96:499–522, 2006) that poor countries are relatively more efficient in using unskilled labor whereas rich countries are more efficient in using skilled labor. The analysis is based on an approach using directional distance functions from nonparametric efficiency analysis which relies on very mild assumptions. We find that the central result of Caselli and Coleman is robust to using the nonparametric approach. The result is, however, sensitive to alternative definitions of skilled and unskilled labor, data sources and variations of the measurement approach.

Estimating alternative technology sets in nonparametric efficiency analysis: restriction tests for panel and clustered data

Nonparametric efficiency analysis has become a widely applied technique to support industrial benchmarking as well as a variety of incentive-based regulation policies. In practice such exercises are often plagued by incomplete knowledge about the correct specifications of inputs and outputs. Simar and Wilson (Commun Stat Simul Comput 30(1):159–184, 2001) and Schubert and Simar (J Prod Anal 36(1):55–69, 2011) propose restriction tests to support such specification decisions for cross-section data. However, the typical oligopolized market structure pertinent to regulation contexts often leads to low numbers of cross-section observations, rendering reliable estimation based on these tests practically unfeasible. This small-sample problem could often be avoided with the use of panel data, which would in any case require an extension of the cross-section restriction tests to handle panel data. In this paper we derive these tests. We prove the consistency of the proposed method and apply it to a sample of US natural gas transmission companies from 2003 through 2007. We find that the total quantity of natural gas delivered and natural gas delivered in peak periods measure essentially the same output. Therefore only one needs to be included. We also show that the length of mains as a measure of transportation service is non-redundant and therefore must be included.

Evaluating the performance of higher education institutions in Europe: a nonparametric efficiency analysis of 944 institutions

ABSTRACTAlthough a long tradition exists of studying the economics of education, performance comparisons of different kinds have traditionally been difficult to undertake. An important impediment has been the lack of comparable data. To a large extent, this study remedies the shortcomings of earlier studies. Our contribution is twofold. First, the current higher education policy of contraction and economizing, common to most European countries, make knowledge of potential efficiency gains crucial. Second, a unique database allows us to study a broad diversity of organizations as well as organizations located in a number of different European countries. The study suggests evaluating higher education institution (HEI) performance in a production theory context, applying the well-known data envelopment analysis (DEA) method to a cross section of 944 HEIs in 17 European countries. The DEA approach is particularly suitable in this context where little is known about production technologies and economic behaviour of the HEIs. On average, provision of education is found to be most efficient in the Slovak Republic followed by Belgium and Latvia, while Denmark and Norway display the lowest efficiency. The study also indicates a positive relation between efficiency and HEI size and efficiency and research intensity. Furthermore, the study points to the importance of continued data collection.