Experience Curve models in the electricity supply industry

There has been much controversy over the use of the Experience Curve for forecasting purposes. The Experience Curve model has been criticised both on theoretical grounds and because of the practical problems of using it. An alternative model of experience effects due to Towill has certain attractions from the standpoint of theory. However, a rather deeper question is whether experience curve type models produce superior forecasts to thsoe derived using extrapolative techniques. This paper examines these questions in the context of three time series taken from the electricity supply industry, viz: average thermal efficiency; works costs; and price of electricity. The two latter series require price deflation. Both the implied GDP consumption deflator, and a wholesale price index for fuel and electricity were used for this prupose. It is argued that because of the absence of substitutes and of the effects of competition, along with the high quality of data available on the electricity supply industry, these three series provide a favourable test of the experience curve approach to forecasting. The two experience curves performed on the whole markedly worse than the simpler extrapolative methods on the two financial series examined. For the average thermal efficiency series the Towill model and the Experience Curve model marginally outperformed the extrapolative methods. Overall, there was little support for using either the Experience Curve or Towill models. These are obviously more difficult to use than simple univariate models and do not provide significantly better forecasts. Moreover, the Towill model gave rise to considerable estimation and specification problems with the data used here.