Astrid Cullmann

Efficiency Analysis of German Electricity Distribution Utilities -Non-Parametric and Parametric Tests

This study applies non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. Traditional issues in electricity sector benchmarking are addressed, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany. Labour, capital, and peak load capacity are used as inputs, and units sold and the number of customers as output. The data cover 307 (out of 553) German electricity distribution utilities. A data envelopment analysis (DEA) is applied with constant returns to scale (CRS) as the main productivity analysis technique, whereas stochastic frontier analysis (SFA) with distance function is the verification method. The results suggest that returns to scale play but a minor role; only very small utilities have a significant cost advantage. Low customer density is found to affect the efficiency score significantly, in particular in the lower third of all observations. Surprisingly, East German utilities feature a higher average efficiency than their West German counterparts. The correlation tests imply a high coherence of the results.

From Transition to Competition -Dynamic Efficiency Analysis of Polish Electricity Distribution Companies

In this paper, we test the hypothesis that the economic transition toward a market economy increases the efficiency of firms. We study 32 Polish electricity distribution companies between 1997 and 2002, by applying common benchmarking methods to the panel: the non-parametric data envelopment analysis (DEA), the free disposal hull (FDH), and, as a parametric approach, the stochastic frontier analysis (SFA). We then measure and decompose productivity change with Malmquist indices. We find that the technical efficiency of the companies has indeed increased during the transition, while allocative efficiency has deteriorated. We also find significantly increasing returns to scale, suggesting that the regulatory authority should allow companies to merge into larger units.

Innovation, R&D Efficiency and the Impact of the Regulatory Environment: A Two-Stage Semi-Parametric DEA Approach

This paper assesses the relative efficiency of knowledge production in the OECD using a nonparametric DEA approach. Resources allocated to R&D are limited and should therefore be used efficiently given the institutional and legal constraints. This paper presents efficiency scores based on an intertemporal frontier estimation for the period 1995 to 2004 and analyzes the impact of the regulatory environment using the single bootstrap procedure suggested by Simar and Wilson (2007). The empirical evidence supports the hypothesis that barriers to entry, aimed at reducing competition, lower research efficiency by attenuating the incentive to innovate and to allocate resources efficiently.

Potential Gains from Mergers in Local Public Transport: An Efficiency Analysis Applied to Germany

We analyze potential gains from hypothetical mergers in local public transport using the non-parametric Data Envelopment Analysis with bias corrections by means of bootstrapping. Our sample consists of 41 public transport companies from Germanys most densely populated region, North Rhine-Westphalia. We merge them into geographically meaningful, larger units that operate partially on a joint tram network. Merger gains are then decomposed into individual technical efficiency, synergy and size effects following the methodology of Bogetoft and Wang [Bogetoft, P., Wang, D., 2005. Estimating the Potential Gains from Mergers. Journal of Productivity Analysis, 23(2), 145-171]. Our empirical findings suggest that substantial gains up to 16 percent of factor inputs are present, mainly resulting from synergy effects.

Unobserved Heterogeneity and International Benchmarking in Public Transport

We analyze the technical efficiency of German and Swiss urban public transport companies by means of SFA. In transport networks we might face different network structures or complexities, not observed, but influencing the production process. The unobserved factors are typically modeled as separable factors. However, we argue that the entire production process is organized around different network structures. Therefore, they are inevitably non-separable from the observed inputs and outputs. The adopted econometric model is a random coefficient stochastic frontier model. We estimate an input distance function for the years 1991 to 2006. The results underline the presence of unobserved non-separable factors.

Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector

In this paper, we analyze the technical efficiency and CO2 reduction potentials of German power and heat plants, using a non-parametric sequential Data Envelopment Analysis. We apply a metafrontier framework to evaluate plant-level efficiency in the transformation of inputs into desirable (energy) and undesirable (CO2 emissions) outputs, taking into account different fossil fuel generation technologies. We use a unique data set of coal-, lignite-, gas- and biomass-fired power plants from 2003 through 2010 that provides an unbalanced panel of 1459 observations; the results are also checked against a balanced panel with a smaller number of observations. Although we find intra-group differences within energy generation technology, natural gas fired power plants clearly have the highest efficiency. Furthermore, the analysis points to significant savings potentials for CO2 and fuel-input, and derives policy conclusions for the ongoing electricity sector reformation.

Regional Differences of Production and Efficiency of Mexican Manufacturing: An Application of Nested and Stochastic Frontier Panel Models

This study examines the regional divide for Mexican manufacturing. Mexicos north-south disparity is widely noted, but rarely analyzed empirically and at detailed regional level. We use a panel of municipality-level data to estimate regional production functions. An important contribution is the application of nested panel and stochastic frontier models to capture latent regional characteristics and the computation of performance indicators for all municipalities. There is evidence for considerable differences in economic structure and productivity of the south to the central manufacturing belt and the north. Variation of efficiency is however pronounced, indicating that strong municipalities prevail in highly inefficient states.

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.

Overcoming Data Limitations in Nonparametric Benchmarking: Applying PCA-DEA to Natural Gas Transmission

We empirically demonstrate a practical approach of efficiency evaluation with limited data availability in some regulated industries. We apply PCA-DEA for radial efficiency measurement to U.S. natural gas transmission companies in 2007. PCA-DEA reduces dimensions of the optimization problem while maintaining most of the variation in the original data. Our results suggest that the methodology reduces the probability of over-estimation of individual firm-specific performance.

R&D efficiency and heterogeneity – a latent class application for the OECD

Expenditures devoted to research and development (R&D) are scarce and thus need to be used as efficiently as possible given the financial constraints countries are facing. This article assesses the relative efficiency of R&D expenditures for 26 OECD member countries and two nonmember countries. As countries differ in their national innovation systems and states of economic development and industrialization, e.g. transition economies in Eastern Europe versus Asian countries versus Anglo-Saxon countries, the measurement of R&D efficiency needs to consider differences in the technology of knowledge production. By means of a latent class model for stochastic frontiers, we relax the assumption of a homogeneous technology frontier and model technological differences in knowledge production among countries. Empirical evidence suggests the existence of different classes stressing the importance of accounting for countries’ disparities within R&D efficiency analysis.