Technical efficiency of European railways: a distance function approach

Abstract

This study has two principal objectives. The first objective is to measure and compare the performance of European railways. The second objective is to illustrate the usefulness of econometric distance functions in the analysis of production in multioutput industries, where behavioural assumptions such as cost minimization or profit maximization, are unlikely to be applicable. Using annual data on 17 railways companies during 1988-1993, multioutput distance functions are estimated using corrected ordinary least squares (COLS). The resulting technical efficiency estimates range from 0.980 for the Netherlands to 0.784 for Italy, with a mean of 0.863. The distance function results are also compared with those obtained from single-output production functions, where aggregate output measures are formed using either total revenue or a Tornqvist index. The results obtained indicate substantial differences in parameter estimates and technical efficiency rankings, casting significant doubt upon the reliability of these single-output models, particularly when a total revenue measure is used to proxy aggregate output.

Economic Efficiency and Frontier Techniques

“…Hailu and Veeman (2000) employ a parametric input distance that incorporates both desirable and undesirable outputs so more environmentally sensitive productivity and efficiency measures can be obtained. Coelli and Perelman (2000) illustrate the usefulness of econometric distance functions in the analysis of production in multiple output industries, where behavioural assumptions such as cost minimization or profit maximization, are unlikely to be applicable. Finally, Sickles, Good and Getachew (2002) model a multiple output technology using a semi-parametric stochastic distance function where multivariate kernel estimators are introduced to address the endogeneity of multiple outputs.…”

“…Alternatively to Bayesian analysis, other research such as Hailu and Veeman (2000), Coelli and Perelman (2000) or Sickles, Good and Getachew (2002) are also attempting to analyze multiple output technologies by means of parametric frontier models. Hailu and Veeman (2000) employ a parametric input distance that incorporates both desirable and undesirable outputs so more environmentally sensitive productivity and efficiency measures can be obtained.…”

Provision of environmental output within a multi-output distance function approach

“…It is also common to nd in the literature a ranking of rms according to their mean e ciencies (Coelli and Perelman 1999;Coelli and Perelman 2000) or plots for mean, median and maximum e ciency levels (Koop 2003). We investigate the consequences in e ciency rankings when provision of environmental outputs is incorporated into e ciency analysis.…”

Parametric Decomposition of the Malmquist Index in Output-Oriented Distance Function: Productivity in Chinese Agriculture

“…According to [11] this specification fulfills a set of desirable characteristics: flexible, easy to derive and allowing the imposition of homogeneity. The flexible form of translog has been widely used to estimate distance functions as it meets all the required characteristics ( [4,6,9,10,12]).…”

“…The parameters of the distance function can be estimated only if linear homogeneity in outputs is imposed. Following [11], all output quantities in the right hand side of Equation (15) …”