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A robust approach to determining the dynamic efficiency parameter for Dutch gas and electricity TSOs

ACM, the competition regulator for Netherlands, publishes Oxera’s study

Last year, ACM commissioned Oxera to conduct a study on dynamic efficiency for Dutch transmission system operators (TSOs). The objective of the study was to advise on the scope of productivity improvement that an efficient TSO could achieve over a regulatory period due to technological improvement (also referred to as ‘frontier shift’) or cheaper inputs. In particular, the aim of the analysis was to produce productivity growth estimates using Total Factor Productivity (TFP) and Output Price Index (OPI) measures, to be applied over the regulatory period starting in 2017 for TenneT (the electricity transmission operator) and Gasunie Transport Services (GTS) (the gas transmission operator).

To this end, we:

  • built a dataset with productivity-related information for all sectors of the Dutch market economy, by sourcing up-to-date productivity data using the latest methodology standards;
  • derived a robust set of comparator industries to capture productivity trends in activities relevant to electricity and gas TSOs;
  • identified the most appropriate measurement period for productivity analysis;
  • collated a range of dynamic efficiency parameter estimates from academic sources and regulatory precedents.

The core TFP and OPI estimates based on our study are consistent with each other. Over the preferred period of analysis, for our preferred comparator set:

  • average year-on-year TFP (GO)[1] growth was 0.4%. The gap between the Consumer Price Index (CPI) and input price inflation was 0.1%. Hence, a combined estimate that captures both productivity improvements and input price pressure is about 0.5% per annum;
  • OPI (GO) decreased annually by 0.5% relative to economy-wide CPI.

Hence, a dynamic efficiency target that captures the ‘combined effect’ of productivity growth and input price pressure is estimated to be 0.5% per annum. Extensive sensitivity analysis in terms of alternative data sources, comparator set and timeframe of analysis indicated that the core estimate is largely robust to alternative assumptions.

In terms of external sources, we identified some relevant academic studies and regulatory determinations of dynamic efficiency assessment of transmission operators. However, owing to a wide range of estimates, a limited number of studies, and/or a lack of clarity (in terms of the methodology, data employed, or whether the estimates represented the combined effect and excluded catch-up effects) associated with this evidence, we consider that less weight should be placed on these sources and more weight placed on the empirical analysis.

The full study is available here.

[1] GO refers to the gross output measure of productivity growth—the basis for the ACM’s previous method decisions. We also considered the value-added (VA) measure of productivity growth in our study.