Transit Costs and Cost Efficiency: Bootstrapping Nonparametric Frontiers.

This paper explores a selection of recently proposed bootstrapping techniques to estimate non-parametric convex (DEA) cost frontiers and efficiency scores for transit firms. Using a sample of Norwegian bus operators, the key results can be summarised as follows: (i) the bias implied by uncorrected cost efficiency measures is numerically important (close to 25%), (ii) the bootstrapped-based test rejects the constant returns to scale hypothesis (iii) explaining patterns of efficiency scores using a two-stage bootstrapping approach detects only one significant covariate, in contrast to earlier results highlighting, e.g., the positive impact of high-powered contract types. Finally, comparing the average inefficiency obtained for the Norwegian data set with an analogous estimate for a smaller French sample illustrates how the estimated differences in average efficiency almost disappear once sample size differences are accounted for.

Measuring efficiency of Tunisian schools in the presence of quasi-fixed inputs: A bootstrap data envelopment analysis approach

The objective of this paper is to measure the efficiency of high schools in Tunisia. We use a statistical Data Envelopment Analysis (DEA)-bootstrap approach with quasi-fixed inputs to estimate the precision of our measure. To do so, we developed a statistical model serving as the foundation of the Data Generation Process (DGP). The DGP is constructed such that we can implement both smooth homogeneous and heterogeneous bootstrap methods. Bootstrap simulations were used to estimate and correct the bias, and to construct confidence intervals for the efficiency measures. The simulation results show that the efficiency measures are subject to sampling variations. The adjusted measure reveals that high schools with residence services would have to give up less than 12.1 percent of their resources on average to be efficient.Educational economics; Efficiency; Productivity; Data Envelopment Analysis; Bootstrap; Quasi-fixed inputs

Comparing Efficiency Across Markets: An Extension and Critique of the Zhang and Bartels (1998) Methodology

The use of non-parametric frontier methods for the evaluation of product market efficiency in heterogeneous markets seems to have gained some popularity recently. However, the statistical properties of these frontier estimators have been largely ignored. The main point is that nonparametric frontier estimators are biased and that the degree of bias depends on specific sample properties, most importantly sample size and number of dimensions of the model. To investigate the effect of this bias on comparing market efficiency, this contribution estimates the efficiency for several datasets for two main product categories. Following Zhang and Bartels (1998), these results comprise re-estimates for the larger samples limiting their size to that of the smaller samples when the model dimensions for different samples are identical. Furthermore, sample sizes are adjusted to mitigate the eventual differences in dimensions in specification. This allows comparing market efficiency for different markets on a more equal footing, since it reduces the bias effect to a minimum making the comparison of market efficiency possible. However, the article also points out the critical limitations of this Zhang and Bartels (1998) approach in certain respects. Apart from reporting these negative results, we also offer some suggestions for future work.Market Efficiency, Heterogeneous Product Markets, Bias, Monte-Carlo Simulation

An application of statistical interference in DEA models: An analysis of public owned university departments' efficiency

This paper uses Data Envelopment Analysis (DEA) model formulations in order to determine the performance levels of 16 departments of the University of Thessaly. Particularly, the constant returns to scale (CRS) and variable returns to scale (VRS) models have been applied alongside with bootstrap techniques in order to determine accurate performance measurements of the 16 departments. The study illustrates how the recent developments in efficiency analysis and statistical inference can be applied when evaluating institutional performance issues. The paper provides the efficient departments and the target values which need to be adopted from the inefficient departments in order to operate in the most productive scale size (MPSS). Moreover it provides bias corrected estimates alongside with their confidence intervals. The analysis indicates that there are strong inefficiencies among the departments, emphasizing the misallocation of resources or/and inefficient application of departments policy developments.University efficiency; DEA; Bootstrap techniques; Kernel density estimation, Economic research; Europe; University rankings.

On testing equality of distributions of technical efficiency scores

The challenge of the econometric problem in production efficiency analysis is that the very efficiency scores to be analyzed are unobserved. Recently, statistical properties have been discovered for a class of estimators popular in the literature, known as data envelopment analysis (DEA) approach. This opens a wide range of possibilities for a well-grounded statistical inference about the true efficiency scores from their DEA-estimates. In this paper we investigate possibility of using existing tests for equality of two distributions for such a context. Considering statistical complications pertinent to our context, we consider several approaches to adapt the Li (1996) test to the context and explore their performance in terms of the size and the power of the test in various Monte Carlo experiments. One of these approaches showed good performance both in the size and in the power, thus encouraging for its wide use in empirical studies.Kernel Density Estimation and Tests, Bootstrap, DEA

Adjusting for cultural effects on countries’ education policy efficiency:an application of conditional full frontiers measures

In this paper using Data Envelopment Analysis (DEA) we evaluate the influence of national culture on education policy efficiency for 20 OECD countries. For that reason bootstrap techniques have been employed in order to produce biased corrected efficiency scores and confidence intervals are been calculated. By using probabilistic approaches it conditions the effect of national cultural values on the obtained countries’ educational efficiencies. The empirical results indicate that the efficiency of education policy is mainly influenced from differences of individualistic and masculinity values among the countries. However the results clearly indicate that education policy reforms must be based outside those national cultural bounds in order to support national economies on their foreseen challenges.Data Envelopment Analysis; Education; Linear programming; Statistics

Performance evaluation using bootstrapping DEA techniques: Evidence from industry ratio analysis

In Data Envelopment Analysis (DEA) context financial data/ ratios have been used in order to produce a unified measure of performance metric. However, several scholars have indicated that the inclusion of financial ratios create biased efficiency estimates with implications on firms’ and industries’ performance evaluation. There have been several DEA formulations and techniques dealing with this problem including sensitivity analysis, Prior-Ratio-Analysis and DEA/ output–input ratio analysis for the assessment of the efficiency and ranking of the examined units. In addition to these computational approaches this paper in order to overcome these problems applies bootstrap techniques. Moreover it provides an application evaluating the performance of 23 Greek manufacturing sectors with the use of financial data. The results reveal that in the first stage of our sensitivity analysis the efficiencies obtained are biased. However, after applying the bootstrap techniques the sensitivity analysis reveals that the efficiency scores have been significantly improved.Performance measurement; Data Envelopment Analysis; Financial ratios; Bootstrap; Bias correction

Next Stop: Restructuring?: A Nonparametric Efficiency Analysis of German Public Transport Companies

In this paper, we present a nonparametric comparative efficiency analysis of 179 communal public transport bus companies in Germany (1990-2004). We apply both deterministic data envelopment analysis (DEA) and bootstrapping to test the robustness of our estimates and to test the hypothesis of global and individual constant returns to scale. We find that the average technical efficiency of German bus companies is relatively low. We observe that the industry appears to be characterized by increasing returns to scale for smaller companies. These results would imply increasing pressure on bus companies to restructure.Public transport, buses, efficiency analysis, nonparametric methods, DEA, bootstrapping

Production Efficiency versus Ownership: The Case of China

In this study, we explore the pattern of efficiency among enterprises in China’s 29 provinces across different ownership types in heavy and light industries and across different regions (coastal, central and western). We do so by performing a bootstrap-based analysis of group efficiencies (weighted and non-weighted), estimating and comparing densities of efficiency distributions, and conducting a bootstrapped truncated regression analysis. We find evidence of interesting differences in efficiency levels among various ownership groups, especially for foreign and local ownership, which have different patterns for light and heavy industries.Efficiency; Data envelopment analysis; Bootstrapping; Ownership; China

Production Efficiency versus Ownership: The Case of China

In this study, we explore the pattern of efficiency among enterprises in China‘s 29 provinces across different ownership types in heavy and light industries and across different regions (coastal, central and western). We do so by performing a bootstrap-based analysis of group efficiencies (weighted and non-weighted), estimating and comparing densities of efficiency distributions, and conducting a bootstrapped truncated regression analysis. We find evidence of interesting differences in efficiency levels among various ownership groups, especially for foreign and local ownership, which have different patterns for light and heavy industries.efficiency, data envelopment analysis, bootstrapping, ownership, China