Benchmarking and Firm Heterogeneity in Electricity Distribution: A Latent Class Analysis of Germany
AbstractIn January 2009 Germany introduced incentive regulation for the electricity distribution sector based on results obtained from econometric and nonparametric benchmarking analysis. One main problem for the regulator in assigning the relative efficiency scores are unobserved firm-specific factors such as network and technological differences. Comparing the efficiency of different firms usually assumes that they operate under the same production technology, thus unobserved factors might be inappropriately understood as inefficiency. To avoid this type of misspecification in regulatory practice estimation is carried out in two stages: in a first stage observations are classified into two categories according to the size of the network operators. Then separate analyses are conducted for each sub-group. This paper shows how to disentangle the heterogeneity from inefficiency in one step, using a latent class model for stochastic frontiers. As the classification is not based on a priori sample separation criteria it delivers more robust, statistical significant and testable results. Against this backround we analyze the level of technical efficiency of a sample of 200 regional and local German electricity distribution companies for a balanced panel data set (2001-2005). Testing the hypothesis if larger distributors operate under a different technology than smaller ones we assess if a single step latent class model provides new insights to the use of benchmarking approaches within the incentive regulation schemes.
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Bibliographic InfoPaper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 881.
Length: 25 p.
Date of creation: 2009
Date of revision:
Stochastic frontiers; latent class model; electricity distribution; incentive regulation;
Find related papers by JEL classification:
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-09 (All new papers)
- NEP-ECM-2009-05-09 (Econometrics)
- NEP-EFF-2009-05-09 (Efficiency & Productivity)
- NEP-ENE-2009-05-09 (Energy Economics)
- NEP-REG-2009-05-09 (Regulation)
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