Observed and unobserved heterogeneity in stochastic frontier models: An application to the electricity distribution industry

In this study we combine different possibilities to model firm level heterogeneity in stochastic frontier analysis. We show that both observed and unobserved heterogeneities cause serious biases in inefficiency results. Modelling observed and unobserved heterogeneities treat individual firms in different ways and even though the expected mean inefficiency scores in both cases diminish the firm level efficiency rank orders turn out to be very different. The best fit with the data is obtained by modelling unobserved heterogeneity through randomizing frontier parameters and at the same time explicitly modelling the observed heterogeneity into the inefficiency distribution. These results are obtained by using data from Finnish electricity distribution utilities and the results are relevant in relation to electricity distribution pricing and regulation. -- Research Highlights: → We show that both observed and unobserved heterogeneities of firms cause biases in inefficiency results. → Different ways of accounting firm level heterogeneity end up with very different rank orders of firms. → The model which combines the characteristics of unobserved and observed heterogeneity fits the data best.