مقاله سال ۲۰۱۶

 مجله امگا – Omega

The English and Welsh water and sewerage sector is a long-life capital intensive industry, characterised by regional monopolies. The industry was privatised in 1989 and is regulated by Ofwat (Office of Water Services), the water service regulatory authority which acts as a proxy for a competitive market. Ofwat ensures that utility companies obtain a specified return on capital which is unique to the water sector whilst ensuring a competitive price for customers. To guarantee quality standards the industry is also regulated by the Drinking Water Inspectorate (DWI), National Resources Wales (NRW) and the Environment Agency (EA).

The aims of this paper are twofold: firstly to compare the conclusions from static and dynamic DEA highlighting the ineffi- ciencies that arise out of a dynamic framework, and secondly to investigate the presence of a preference for capital expenditure known as the capex bias. The bias arises because of differing incentive rates between operating and capital expenditure, or due to the nature of the industry as much of the infrastructure is built in order to meet expected future demand. The presence of the bias drives to the heart of the brief set by regulators to guarantee consumer value.

Data Envelopment Analysis (DEA) is used to measure efficiency within a dynamic context by examining the presence of quasi-fixed capital. The English and Welsh water and sewerage industry is characterised by quasi-fixed inputs such as mains, sewers and treatment works which have a long service life and cannot be adjusted to their optimal level instantaneously. A dynamic perspective of the measurement of efficiency is required as decisions on quasi-fixed inputs not only influence current production, but also future production. Intertemporal effects are incorporated through the inclusion of capital as an output in the current period production as well as an input from the previous period’s production. Firms therefore face a trade-off between increasing output today and producing capital to increase outputs in the future [21]. Dynamic DEA determines the optimal allocation of resources over the period by minimising dynamic costs given the technology. We allow for overall efficiency to be decomposed into a dynamic component and a static component. This approach determines the level of efficiency due to variable inputs and the inefficiency due to quasi-fixed inputs. We use a three stage approach by including environmental variables2 within the dynamic framework to ensure firms are compared on a level playing field. Input slacks ratios are obtained from the dynamic DEA which are then regressed upon the environmental variables. The predicted slack ratios are used to adjust the input variables upwards for those firms operating in a relatively favourable environment. The DEA is repeated including the adjusted inputs to obtain adjusted efficiency scores accounting for differences in the operating environments.