Cost Efficiency in the Swiss Gas Distribution Sector

This paper studies the cost structure of gas distribution utilities in Switzerland. Three stochastic frontier models are applied to a panel of 26 companies operating from 1996 to 2000. Efficiency is assumed to be constant over time. The analysis highlights the importance of output characteristics such as customer density and network size. The results suggest that the utilities could slightly reduce their operating costs by improving efficiency. There is no evidence of significant unexploited scale economies. However, our analysis indicates that the estimates of scale economies could be sensitive to the assumptions regarding the variation of output with output characteristics.cost efficiency; scale economies, gas distribution, stochastic frontier analysis

Cost Efficiency in Regional Bus Companies: An Application of Alternative Stochastic Frontier Models

This paper evaluates cost and scale efficiencies of Switzerland’s regulated bus companies operating in regional networks. The adopted methodology can be used in benchmarking analyses applied to incentive regulation systems. Moreover, the estimations can be used to evaluate the bidding offers for the tendering processes predicted by the ongoing reform policies. Since these companies operate in different regions with various characteristics that are only partially observed, it is crucial for the regulator to distinguish between inefficiency and exogenous heterogeneity that influences the costs. A number of stochastic cost frontier models are applied to a panel of 94 companies over a 12-year period from 1986 to 1997. The main focus lies on the ability of these models to distinguish inefficiency from the unobserved firmspecific heterogeneity in a network industry. The estimation results are compared and the effect of unobserved heterogeneity on inefficiency estimates is analyzed.

Scale and cost efficiency in the Swiss electricity distribution industry: evidence from a frontier cost approach

The deregulation of the electricity industry is currently on the political agenda in many countries. In most countries, the deregulation of the sector is combined with a (re-) regulation of the electricity networks in most of the countries. In this paper, we analyze the costs structure of 59 Swiss electricity distribution network operators with respect to cost and scale efficiency of the industry. A stochastic frontier model is applied to estimate the average costs of efficient network operators as a benchmark for the industry. Moreover, the heterogeneity of service areas is taken into account. The Swiss authorities might use our results to regulate the prices for the access to the distribution networks.stochastic frontier analysis; electricity distribution; efficiency measurement; regulation; benchmarking; returns to scale; returns to density

Analisi dell’efficienza di costo delle compagnie di bus italiane e svizzere

In this paper we have examined the scale and cost efficiency of Italian and Swiss regional bus companies. For this purpose, we have used the estimation of a frontier cost model using a fixed effect approach. Two translog cost frontier models were specified and estimated using panel data. The first model was estimated for a sample of 58 Italian bus companies, whereas the second model was estimated for a sample of 55 Swiss bus companies. The findings on efficiency were discussed in the political and regulatory setting under which the Swiss and the Italian regional bus companies are operating

Cost efficiency in regional bus companies: an application of alternative stochastic frontier models

This paper evaluates cost and scale efficiencies of Switzerland’s regulated rural bus companies operating in regional networks. The adopted methodology can be used in benchmarking analyses applied to incentive regulation systems. Moreover, the estimations can be used to evaluate the bidding offers for the tendering processes predicted by the ongoing reform policies. Since these companies operate in different regions with various characteristics that are only partially observed, it is crucial for the regulator to distinguish between inefficiency and exogenous heterogeneity that influences the costs. A number of stochastic cost frontier models are applied to a panel of 94 companies over a 12-year period from 1986 to 1997. The main focus lies on the ability of these models to distinguish inefficiency from the unobserved firmspecific heterogeneity in a network industry. The estimation results are compared and the effect of unobserved heterogeneity on inefficiency estimates is analyzed

Cost efficiency in network industries: Application of stochastic frontier analysis

Since the past decade, the regulation of several network industries is under revision in many western countries. The aim is to increase the efficiency of the provision of services by introducing new regulation instruments based on incentive mechanisms. Most of these regulation schemes used in practice are based on benchmarking, that is, measuring a company’s productive efficiency against a reference performance. In benchmarking applications the regulator is generally interested in obtaining a measure of firms’ efficiency in order to reward (or punish) companies accordingly. The reliability of efficiency scores is therefore crucial for an effective implementation of the incentive mechanism. One way to estimate this cost inefficiency of companies is by the application of Stochastic Frontier models. The results of the estimated inefficiency scores or the predicted cost from such a model can be used to set the standard against which the actual costs are compared with. As it is crucial to set the correct incentives, it would be desirable to have insights into the stability of the results obtained by different Stochastic Frontier models. The main objective of this thesis is therefore to study the sensitivity of different econometric methods in determining such benchmarks. This is accomplished by the use of traditional as well as recently developed approaches. Moreover, a new panel model based on Mundlak’s formulation will be discussed and applied. The main advantage of such parametric methods to non-parametric ones is that they allow to model explicitly cost differences due to heterogeneous production environments. As regulated companies operate in different regions and run different networks, they might incur different production costs due to firm-specific production environments. The resulting cost differences incurred by a more or less favorable production environment should not be confounded with inefficiency, since typically, the production environment is not under the control of the company. Hence, such cost differences should also be taken into account when elaborating an appropriate benchmark. Consequently, this thesis also considers the modeling of observable heterogeneity in production. Furthermore, since not all influences might be observed in practice, the ability of the models with regard to the inclusion of unobserved heterogeneity and the influence to estimated inefficiency is studied by the application of traditional as well as recently developed panel data models like the “true” random-effects model proposed by Greene (2002a, 2005). After defining different measures of inefficiency and reviewing the relevant literature, several such parametric methods are applied to two data sets to study the impact of different assumptions regarding the distribution of inefficiency and heterogeneity in a comparative analysis. The first data set consists of a sample of Swiss rural bus companies. Results suggest that estimated inefficiencies and the ranking of companies are strongly influenced by the different methods used. With regard to unobserved heterogeneity, the “true” randomeffects model proposed by Greene (2002a,2005) in combination with Mundlak’s formulation seems to be able to reduce different bias problems of other models and to give reasonable estimates. Estimation also suggests that in the sample, considerable economies of scale are present. Potential regulators should therefore support mergers among adjacent bus operators. The second application to a sample of Swiss gas distribution companies reveals that in contrast to the finding of the previous application, estimated inefficiencies are rather stable across estimated model. However, efficiency rankings of the companies vary. In contrast to the sample of bus companies, the latter is rather small, containing only 129 observations. Hence, richer econometric models could not be applied as the variation in the sample did not allow to separate unobserved, with regressors uncorrelated heterogeneity from inefficiency. As this separation was not possible, estimated inefficiency scores might be confounded with heterogeneity. A potential regulator should therefore not directly use these scores in an incentive-based regulation scheme. However, the predicted costs could be used in a yardstick competition. With regard to economies of scale, results suggest that expanding the existing networks does not help to lower average production costs, because the main cost driving factors are the network investment costs. Conversely, there exist economies of density, suggesting to intensify the use of existing networks. Overall, this thesis shows that estimated inefficiencies and their ranking are sensitive to the adopted method and that a single model which is able to overcome all practical and theoretical problems does not exists. Therefore, it is concluded that a potential regulator should use these models with caution. Seit den achziger Jahren des letzten Jahrhunderts ist die Regulierung verschiedener netzwerkgebundener Industrien in den meisten westlichen L¨andern in ¨Uberarbeitung. Das Ziel dieser Revisionen ist eine Effizienzsteigerung in der Leistungerbringung der regulierten Industrien. Dies wird mit der Einf¨uhrung neuer Regulierungsinstrumente erreicht, welche auf Anreizmechanismen beruhen. Die meisten in der Praxis angewendeten Instrumente beruhen auf einem Benchmarking, was bedeutet, dass das Betriebsergebnis der zu regulierenden Firmen mit einem Referenzergebnis verglichen wird. Ein Regulator erhofft sich durch die Anwendung solcher Benchmarking-Untersuchungen, Informationen ¨uber die Effizienz von Firmen zu erhalten, um diese entsprechend zu belohnen (oder zu bestrafen). Eine M¨oglichkeit, um solche Effizienzkennzahlen zu sch¨atzen, bie-ten die ”Stochastic Frontier” Modelle. Sie erlauben, die gesch¨atzten Kennziffern oder die vom Modell vorhergesagten Kosten mit den aktuellen Werten zu vergleichen. Um jedoch die korrekten Anreize zu geben, ist es entscheidend, die Verl¨asslichkeit der verschiedenen ”Stochastic Frontier” Modelle zu kennen. Das Ziel dieser Arbeit ist deshalb, die Sensitivit¨at der Resultate von verschiedenen ¨okonometrischen Methoden zu analysieren. Dieses wird mit der Anwendung sowohl traditioneller als auch k¨urzlich entwickelter Modelle erreicht. Des weiteren wird ein neues Paneldatenmodell, basierend auf der Idee von Mundlak, diskutiert und angewendet. Parametrische Modelle haben gegen¨uber nicht-parametrischen den Vorteil, unterschiedliche Produktionskosten aufgrund unterschiedlicher Produktionsumgebungen ber ¨ucksichtigen zu k¨onnen. Diese Unterschiede in den Produktionskosten entstehen, weil regulierte Firmen typischerweise in verschiedenen Gebieten mit unterschiedlichen Produktionsbedingungen operieren. Da eine Firma diese Produktionsbedingungen nicht selber beeinflussen kann, sollten diese Unterschiede nicht mit der Kosteneffizienz verwechselt werden und m¨ussen ber¨ucksichtigt werden, wenn ein angemessener Leistungsvergleich durchgef¨urt wird. Aus diesem Grund untersucht diese Arbeit, wie sich beobachtbare Unterschiede modellieren lassen. Des weiteren wird analysiert, in wieweit diese Modelle f¨ahig sind, nicht-beobachtbare Kostenunterschiede zu ber¨ucksichtigen. Dies ist n¨otig, da nicht alle Einfl¨usse auf die Produktion in der Praxis beobachtbar sind. Deshalb werden die traditionellen wie auch die k¨urzlich entwickelten Modelle (wie zum Beispiel das ”true random-effects” Modell von Greene (2002a, 2005)) auf ihre F¨ahigkeit, diese Unterschiede zu modellieren, untersucht. Nachdem zuerst verschiedene Masse f¨ur die Ineffizienz unter der Ber¨ucksichtigung der einschl¨agigen Literatur definiert werden, werden verschiedene parametrische Methoden auf zwei Datens¨atze angewendet, um den Einfluss verschiedener Annahmen bez¨uglich der Verteilung der Ineffizienz und der unterschiedlichen Produktionsbedingungen zu studieren. Der erste Datensatz besteht aus regionalen Busbetrieben der Schweiz. Die Resultate belegen, dass die gesch¨atzten Ineffizienzen der Firmen und deren Reihenfolge stark von den verwendeten Modellen abh¨angig sind. Das ”true random-effects” Modell von Greene (2002a, 2005) in Verbindung mit der Mundlak Anpassung scheint verschiedene Verzerrungsprobleme anderer Modelle zu reduzieren. Die Sch¨atzungen belegen, dass in dieser Industrie so genannte Gr¨ossenvorteile bestehen. Ein Regulator sollte deshalb daf¨ur sorgen, dass benachbarte Busbetriebe zusammengeschlossen werden. Die Anwendung auf eine Auswahl von schweizerischen Gasversorgungsunternehmen zeigt im Gegensatz zur ersten Anwendung relativ stabile Ineffizienzwerte. Andererseits muss erw¨ahnt werden, dass die Reihenfolge der gesch¨atzten Firmenineffizienzen von Modell zu Modell variiert. Da der Datensatz jedoch nur aus 129 Beobachtungen besteht, war es nicht m¨oglich, komplexere Modelle anzuwenden. Vor allem war es aufgrund geringer Variation in den Daten nicht m¨oglich, unbeobachtbare und mit den Regressoren korrelierte Produktionsunterschiede von den Ineffizienzen zu trennen. Demzufolge k¨onnten die gesch¨atzten Ineffizienzen verzerrt sein. Ein Regulator sollte deshalb die Werte nicht direkt in einer anreizorientierten Regulierungsmethode verwenden. Die von diesen Modellen vorhergesagten Kosten k¨onnten jedoch f¨ur einen ”Yardstick”Wettbewerb verwendet werden. Gr¨ossenvorteile scheinen in dieser Branche nicht zu bestehen, da der gewichtigste Kostenfaktor die Leitungsinvestitionskosten sind. Jedoch scheinen Dichtevorteile zu existieren, was nahelegt, dass die bestehenden Netze intensiver genutzt werden sollten. Zusammengefasst kann gefolgert werden, dass die gesch¨atzten Produtionsineffizienzen und ihre Rangfolge empfindlich vom gew¨ahlten Modell abh¨angen. Es scheint bislang kein Modell zu existieren, welches s¨amtliche theoretischen und praktischen Probleme l¨ost. Aus diesem Grund sollte ein Regulator diese Modelle mit Vorsicht verwenden

Using stochastic frontier analysis for the access price regulation of electricity networks

The deregulation of the electricity industry is currently on the political agenda in many countries. In most countries, the deregulation of the sector is combined with a (re-) regulation of the electricity networks in most of the countries. In many countries incentive-based regulation – e.g. price-cap regulation, yardstick regulation – was introduced to promote efficiency improvements in electricity networks. However, with information asymmetry between regulator and network owners, companies who are subject to an incentive-based regulation will be able to obtain an information rent. Benchmarking can help to address this regulator’s concern that it does not have good information about the scope for a company to make cost efficiencies (an asymmetry of information). In this paper, we analyze the costs structure of Swiss electricity distribution network operators with respect to cost and scale efficiency of the industry. A stochastic frontier model is applied to estimate the average costs of efficient network operators as a benchmark for the industry

Unobserved heterogeneity in stochastic cost frontier models: a comparative analysis

This paper studies a number of stochastic cost frontier models comparing their ability to distinguish unobserved heterogeneity from inefficiency variation among firms. The main focus is on the panel data models that incorporate firm-specific effects in a stochastic frontier framework, as proposed by Greene (2002, 2004). In cases where the unobserved heterogeneity is correlated with some of the explanatory variables, while the random effects estimators can be biased the fixed effects model may overestimate inefficiency scores. In line with Mundlak (1978), a simple method is proposed to include such correlations in random effects specification. The models are applied to a panel of 36 Swiss nursing homes operating from 1993 to 2001. The estimation results are compared and the resulted improvements are discussed. The results suggest that the proposed specification can avoid the inconsistency problem while keeping the inefficiency estimates unaffected

Cost efficiency in the Swiss gas distribution sector

This paper studies the cost structure of gas distribution utilities in Switzerland. Three stochastic frontier models are applied to a panel of 26 companies operating from 1996 to 2000. Efficiency is assumed to be constant over time. The analysis highlights the importance of output characteristics such as customer density and network size. The results suggest that the utilities could slightly reduce their operating costs by improving efficiency. There is no evidence of significant unexploited scale economies. However, our analysis indicates that the estimates of scale economies could be sensitive to the assumptions regarding the variation of output with output characteristics