Stochastic non-parametric efficiency measurement and yardstick competition in electricity regulation

Stochastic non-parametric efficiency measurement constructs production or cost frontiers that incorporate both inefficiency and stochastic error. This results in a closer envelopment of the mean performance of the companies in the sample and diminishes the effect of extreme outliers. This paper uses the Land, Lovell and Thore (1993) model incorporating information on the covariance structure of inputs and outputs to study efficiency across a panel of 14 electricity distribution companies in the UK during the 1990s. The purpose is to revisit the 1999 distribution price control review carried out by the UK regulator. The regulator’s benchmarking is contrasted with the stochastic nonparametric efficiency results and with other comparative efficiency models offering close envelopment of the data. Some conclusions are offered about the possible regulated price effects in the UK case

A comparison of residential energy demand behaviour in Britain and Australia

This research highlights an interesting finding comparing energy use in the residential sector in the United Kingdom and Australia. Energy consumed per capita is largely similar, however the energy available is manifestly different. Australia is blessed with a greater abundance of energy than the United Kingdom. Particularly, in the main area of study in Australia, Victoria state, Brown coal is easy and cheap to access. It is therefore politically more difficult to argue that the population affords more expensive sustainable energy resources even though Australia is one of the countries that can readily produce this type of energy. Britain, however, is a net importer of energy. A large proportion of this energy is natural gas which is a fossil fuel, and therefore contributes to the negative effects of climate change. The findings of this research focus on what motivates residential users of energy to use energy more sustainably. It presents the conclusions of previous research as a backdrop, and reveals the complexity of occupant behaviour. Key drivers are financial incentives and the role of large organisations such as governments in influ-encing behaviour. This may take significant time

Regulatory benchmarking with panel data

This paper considers panel data procedures for regulatory benchmarking that allow for both latent heterogeneity and inefficiency, encapsulating the regulatory dilemma in comparative efficiency analysis for incentive regulation. It applies a distance function model with appropriate concavity properties for econometric estimation to a panel of electricity distribution utilities in Turkey, since electricity industry reform is a major policy issue there. The results confirm the importance of allowing simultaneously for heterogeneity and inefficiency and emphasise the need for specific time-invariant heterogeneity information, such as geographical data, on regulated utilities in different regions

Economy-wide estimates of rebound effects: evidence from panel data

Energy consumption and greenhouse emissions across many countries have increased overtime despite widespread energy efficiency improvements. One explanation offered in the literature is the rebound effect (RE), however there is a debate about its magnitude and the appropriate model for estimating it. Using a combined stochastic frontier analysis (SFA) and two-stage dynamic panel data approach, we explore these two issues of magnitude and model for 55 countries over the period 1980 to 2010. Our central estimates indicate that in the short-run, 100% energy efficiency improvement is followed by 90% rebound in energy consumption, but in the long-run it leads to a 136% decrease in energy consumption. Overall, our estimated cross-country RE magnitudes indicate the need to consider or account for RE when energy forecasts and policy measures are derived from potential energy efficiency savings

Case study evidence and behavioural analysis of residential energy consumption in the UK

This paper investigates residential energy consumption in the UK by using a novel and topical approach based on behavioural analysis. A key lesson from recent advances in behavioural economics is that the responses of individuals to both policy incentives and uncertainty may differ from the predictions of classical rational optimising behaviour. By employing a focused case study approach using both quantitative and qualitative response analysis, it considers the motivations of residential householders in the UK to reduce fossil fuel use, with additional perspectives from UK landlords, a global environmental NGO, a senior politician, and two senior stakeholder strategy managers from a large energy company. Our interpretative behavioural analysis shows that a variety of incentives are necessary to encourage behaviour change. However, case study participants largely agree on the beneficial role of government regulation and efforts to "nudge" them in the right direction with regard to their energy use. As a means of more effectively reducing carbon dioxide emissions, we conclude that policy should focus on sustainable energy use. The findings allow us to understand why important recent policy initiatives such as the UK Green Deal failed to achieve their objectives and they suggest lessons for more effective incentive based policy making in the field of residential energy consumption

An empirical study of stochastic DEA and financial performance: the case of the Turkish commercial banking industry

This study breaks important new ground in the analysis of financial institutions. It is one of the first empirical uses of Stochastic Data Envelopment Analysis (SDEA) in the efficiency literature. The pattern of efficiency is examined for the year 1999. The purpose of stochastic setting of DEA is two-fold: to accommodate both the inefficiency and the presence of measurement errors; and to convert the resulting stochastic linear programmes for DEA into deterministic non-linear DEA programmes. The results show that there are wide variations in the DEA efficiency scores and SDEA results suggest that these are due to measurement errors or other stochastic factors in the raw data, probably attributable to macroeconomic shocks and issues of changes in banking regulations

Measuring the efficiency of European airlines: an application of DEA and Tobit Analysis

The liberalisation movement in European airlines industry was initiated in the late 1980s to create a more competitive environment. This has aimed to result in an increase in efficiency and productivity of the industry. The radical changes which have occurred since then have given risen to the need to evaluate the efficiency in the early phases of the liberalisation process. This study utilises Data Envelopment Analysis (DEA) to assess the efficiency of airlines. The Tobit model applied to the second stage is conducted in an effort to identify the effects of various explanatory variables on efficiency. Applying DEA with Tobit models to detect the efficiency and the determinants of (in)efficiency serves a variety of policy purposes and aimed at improving performance. Our analysis is based on a panel data set of 17 airlines European airlines over the period of 1991-1995

European airlines: a stochastic DEA study of efficiency with market liberalisation

Stochastic DEA constructs production frontiers that incorporate both inefficiency and stochastic error. This results in a closer envelopment of the mean performance of the companies in the sample and diminishes the effect of extreme outliers. We use the Land, Lovell and Thore (1993) model incorporating information on the covariance structure of inputs and outputs to study efficiency across a panel of 17 European airlines in the 1990s during the early phase of liberalisation. After allowing for stochastic error in computing the relative efficiencies we conclude that the airlines that were efficient in 1995 resembled those that were efficient in 1993 but not those in 1991. The airlines that were efficient in 1995 were the larger companies

An overview of issues in measuring the performance of national economies

This chapter reviews the ways that economists measure the aggregate economic performance of national economies. Efficiency and productivity analysis using the methodologies of data envelopment analysis and stochastic frontier analysis has made a significant contribution to this challenge after the initial research, which arose in the context of the analysis of economic growth. That initial research led to the idea of measuring total factor productivity change, TFPC, and its identification with an unobserved data residual representing technological progress. The contribution of efficiency and productivity analysis has been to expand our understanding of what TFPC could consist of and what could drive it and how we can expand our understanding of it beyond the idea of an unexplained data residual. Amongst the critical questions in this search is the exact definition of what measure of economic performance economists should use. The conventional answer is to measure economic performance by real gross domestic product, GDP, i.e. the gross value-added measure of GDP. However, it has been frequently suggested that a broader measure of economic welfare should be used, and research in this area is particularly lively now in the early part of the twenty-first century. We interpret the concept of the relative performance of national economies very widely and devote attention to examining a wide range of different concepts of economic performance including but certainly not limited to the value-added definition of GDP