Risk-Aversion and Willingness to Pay for Energy Efficient Systems in Rental Apartments

This paper uses a random utility model with a non-linear utility function to estimate the consumers’ valuation for energy efficient insulation and ventilation systems in apartment buildings. The proposed model is applied to data from a choice experiment conducted among 264 apartment tenants in Switzerland. The model relaxes the assumption of constant rate of substitution between income and energy-saving measures. These amenities are considered as non-market goods whose advantages are little known thus entailing certain risk-aversion in consumers’ preferences. The non-linear formulation can accommodate the common cases when the non-market attributes are measured by discrete variables. The analysis indicates that assuming constant rate of substitution could bring about misleading estimates of the willingness to pay, especially when the system is combined of several components. The findings provide evidence in favor of consumers’ risk-averse behavior facing choice situations regarding energy-efficient systems. The estimated risk premiums suggest that risk considerations remain a central issue in dealing with energy efficiency in residential buildings.choice experiment; willingness to pay; risk aversion; energy efficiency; housing

A Benchmarking Analysis of Electricity Distribution Utilities in Switzerland

This paper studies the sensitivity problems of the benchmarking methods used in the regulation practice. Three commonly used methods have been applied to a sample of 52 electricity distribution utilities to estimate their cost efficiency. These methods include stochastic frontier, corrected ordinary least squares and data envelopment analysis. The results indicate that both efficiency scores and ranks are significantly different across various models. Especially considerable differences exist between parametric and non-parametric methods.

Regulation and Measuring Cost Efficiency with Panel Data Models: Application to Electricity Distribution Utilities

This paper examines the application of different parametric methods to measure cost efficiency of electricity distribution utilities. The cost frontier model is estimated using four methods: Displaced Ordinary Least Squares, Fixed Effects, Random Effects and Maximum Likelihood Estimation. These methods are applied to a sample of 59 distribution utilities in Switzerland. The data consist of an unbalanced panel over a nine-year period from 1988 to 1996. Different specifications are compared with regards to the estimation of cost frontier characteristics and inefficiency scores. The results point to some advantages for the FE model in the estimation of cost function’s characteristics. The mutual consistency of different methods with regard to efficiency measures is analyzed. The results are mixed. The summary statistics of inefficiency estimates are not sensitive to the specification. However, the ranking changes significantly from one model to another. In particular, the least and most efficient companies are not identical across different methods. These results suggest that a valid benchmarking analysis should be applied with special care. It is recommended that the regulator use several specifications and perform a (mutual) consistency analysis. Finally, the out-of-sample prediction errors of different models are analyzed. The results suggest that benchmarking methods can be used as a control instrument in order to narrow the information gap between the regulator and regulated companies.

An Analysis of Cost-Efficiency in Swiss Multi-utilities

This study presents an empirical analysis of the cost efficiency of a sample of Swiss multi-utilities operating in the distribution of electricity, natural gas and water. The multi-utilities that operate in different sectors are characterized by a strong unobserved heterogeneity. Therefore the measurement of their performance poses an important challenge for the regulators. The purpose of this paper is to study the potential advantages of recently developed panel data stochastic frontier models in the measurement of the level of efficiency for multi-utility companies. These models are estimated for a sample of 34 multi-output utilities operating from 1997 to 2005. The alternative models are compared regarding the cost function slopes and inefficiency estimates. for the inefficiency estimates, the correlation between different models and the effect of econometric specification have been analyzed. The results suggest that the inefficiency estimates are substantially lower when the unobserved firm-specific effects are taken into account.cost function; efficiency; panel data; multi-output utilities

The temporal variation of cost-efficiency in Switzerland's hospitals: an application of mixed models

This paper uses a mixed effects model to examine the temporal variation of cost efficiency in Switzerland's general hospitals. The variations in total costs, the number of empty beds and the length of hospital stays are analyzed using financial data from a sample of 168 hospitals operating from 1998 to 2003, as well as hospitalization records disaggregated to Diagnosis Related Groups. Individual intercepts and random coefficients are used to account for the unobserved time-invariant heterogeneity and the differences in temporal patterns across hospitals and DRG categories. The analysis illustrates the usefulness of mixed models to account for unobserved factors such as quality, with a relatively weak assumption that their temporal variations, rather than their initial levels, be uncorrelated with efficiency changes. The results indicate that hospitals have adopted measures to curtail hospitalizations and reduce empty beds. The extent and effectiveness of these measures vary significantly across individual hospitals. However, there is no evidence in favor of a particular ownership type or subsidization regime. While the link between reduction rates of empty beds and gains in cost-efficiency is statistically significant, the expected association between shortening hospital stays and cost-efficiency cannot be clearly established in the dat

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.

Economies of scale, density and scope in Swiss Post’s Mail Delivery

Based on a cross-section data set of 2004 reflecting Swiss Post’s delivery cost we estimate its cost function and derive measures of economies of scale, density and scope.Economies of scale, economies of scope, economies of density

Benchmarking and Regulation in the Electricity Distribution Sector

In the last two decades electricity distribution sector have witnessed a wave of regulatory reforms aimed at improving efficiency through incentive regulation. Most of these regulation schemes use benchmarking namely measuring a company’s efficiency and rewarding them accordingly. The reliability of efficiency estimates is crucial for an effective implementation of those incentive mechanisms. A main problem faced by the regulators is the choice among several legitimate benchmarking models that usually produce different results. After a brief overview of the benchmarking methodologies, this paper summarizes the methods used in the regulation practice in several OECD countries, in which the benchmarking practice is relatively widespread. Repeated observation of similar companies over time namely panel data, allows a better understanding of unobserved firm-specific factors and disentangling them from efficiency estimates. Focusing on parametric cost frontier models, this paper presents two alternative approaches that could be used to improve the reliability of benchmarking methods, and based on recent empirical evidence, draws some recommendations for regulatory practice in power distribution networks.

Cut to the Bone? Hospital Takeovers and Nurse Employment Contracts

health economics, monopsony, labor contracts, mergers, non-profit firms, hospitals

Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies

This paper examines the performance of several panel data models to measure cost and scale efficiency in network industries. Network industries are characterized by a high degree of heterogeneity, much of which is network-specific and unobserved. The unaccounted-for heterogeneity can create bias in the inefficiency estimates. The stochastic frontier models that include additional firm-specific effects, such as the random-constant frontier model proposed by Greene (2004), can control for unobserved network effects that are random but time-invariant. In cases like railway networks the unobserved heterogeneity is potentially correlated with other exogenous, but observed, factors such as network size and density. In such cases the correlation with explanatory variables may bias the coefficients of the cost function in a random-effects specification. However, these correlations can be integrated into the model using Mundlak’s (1978) formulation. The unobserved network effects and the resulting biases are studied through a comparative study of a series of stochastic frontier models. These models are applied to a panel of 50 railway companies operating over a 13-year period in Switzerland. Different specifications are compared regarding the estimation of both cost frontier coefficients and inefficiency scores.