Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector

Abstract

The Surrey Energy Economics Centre (SEEC) consists of members of the School of Economics who work on energy economics, environmental economics and regulation. The School of Economics has a long-standing tradition of energy economics research from its early origins under the leadership of Professor Colin Robinson. This was consolidated in 1983 when the University established SEEC, with Colin as the Director; to study the economics of energy and energy markets. SEEC undertakes original energy economics research and since being established it has conducted research across the whole spectrum of energy economics, including the international oil market, North Sea oil & gas, UK & international coal, gas privatisation & regulation, electricity privatisation & regulation, measurement of efficiency in energy industries, energy & development, energy demand modelling & forecasting, and energy & the environment.SEEC research output includes SEEDS -Surrey Energy Economic Discussion paper Series (details at www.seec.surrey.ac.uk/Research/SEEDS.htm) as well as a range of other academic papers, books and monographs. SEEC also runs workshops and conferences that bring together academics and practitioners to explore and discuss the important energy issues of the day.SEEC also attracts a large proportion of the School's PhD students and oversees the MSc in Energy Economics & Policy. Many students have successfully completed their MSc and/or PhD in energy economics and gone on to very interesting and rewarding careers, both in academia and the energy industry.

Technology Invention and Diffusion in Residential Energy Consumption. A Stochastic Frontier Approach

“…In this respect, it has been argued that the contribution of technology in the framework of stochastic frontier can be indirectly captured by a number of factors, as for instance by the price and income effects (see Filippini and Hunt, 2012). More recently, Filippini et al (2014) introduced a specific variable to control the amount of wasted energy due to households not using the best available technologies, although admitting the limitations of this approach, such as the lack of data on consumers' behaviour, heterogeneity in the level of electricity consumption and the fact that such a method is not able to disentangle the energy saving deriving from a more efficient use of inputs or from the adoption of energy saving technologies.…”

“…They find inconsistency in several States between the standard energy intensity indicators and energy efficiency scores deriving from the stochastic frontier approach used in the analysis, suggesting further investigation on this direction. More recently, Filippini et al (2014) focus on the impact of government policies aimed at improving energy efficiency in the residential sector. Although the large number of in-force policy instruments existing in the EU, they find room for efficiency gains and a high level of variability across countries, although not significant differences between new and old EU Member States have been detected.…”

The Role of Energy and Investment Literacy for Residential Electricity Demand and End-use Efficiency

“…The dataset includes information on the level of energy services, which is usually not measured as it can be difficult to collect this information. 5 Information on the level of energy services is a critical issue when using SFA (Filippini et al, 2014). Finally, to our knowledge, this paper is the first one to provide a systematic analysis of the impact of both energy and investment literacy on the total electricity consumption of households while controlling for the effects of the general level of education of the household members.…”

“…While the Stochastic Frontier Analysis (SFA) has been used with aggregated energy data (e.g., Filippini and Hunt (2012); Filippini et al (2014)), we use dis-aggregated data since residential consumers are typically very heterogeneous and household level data can add more detail to the knowledge of consumer response. Weyman-Jones et al (2015) are one of the first to estimate energy efficiency using SFA with dis-aggregated household survey data.…”

Alternative Energy Solutions Using BIPV in Apartment Buildings of Developing Countries: A Case Study of North Cyprus

“…Studies have revealed that 30% of CO 2 emissions in the EU are from buildings. Further, it has been found that the energy used in heating living spaces in residential buildings accounts for 57%, while that for water is about 25% of the entire energy used [1][2][3].…”