Empirical Analysis of Dynamic Efficiency and Innovation in Power Distribution Networks: The Case of Norway

Mr Rahmatallah Poudineh, Heriot-Watt University

Following the liberalisation of the electricity market in Norway since the early 1998, the focus of regulator was mainly on cost reduction and efficiency as the main driving force behind the idea of competitive electricity market. However; sufficient and efficient investment is expected to be the next key issue in regulation of distribution and transmission networks as many of the current energy policy objectives such as the European electricity market integration, increasing the share of renewable in the energy mix, improving quality of services and roll out of the smart meters can only be realised through further investments.

The conventional cost-based regulation only stimulates allocative efficiency and strongly encourages overcapitalization (Averch-Johnson-Effect). On the other hand, the current forms of incentive regulation only lead to productive efficiency, predominantly incentivizing short term efficiency in terms of operational expenditures. Moreover, additional instruments such as quality regulation and/or additional allowances may incentivize replacement and expansions investments respectively. However, from a theoretical point of view, incentive regulation does not motivate dynamic efficiency in the sense of explicit regulatory stimuli for asset innovation leading to a dynamically efficient investment allocation. Thus, complex trade-offs result from the guiding idea of efficiency oriented network operation (productive efficiency) and incentivising the dynamic efficiency.

In pursuing this path, the objective of this paper is to analyse distribution companies in Norway in terms of incentive regulatory measures that lead the firms towards dynamic efficient investments in a smart grids context.

We use a dataset comprising a panel of 135 distribution companies from 2004 to 2010. Initially, we investigate whether theoretical variables influence the investment decision of the distribution companies and whether they can be manipulated through regulatory regime, by adopting a Bayesian Model Averaging (BMA) approach.  In the second stage we measure cost efficiency of distribution networks using an input distance function and stochastic frontier technique.