Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach

By Massimo Filippini, L. Hunt. 2011

351 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/3a6cfb7a6994d879d15a8d9d374f5b079344678c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. D. Broadstock
2. Massimo Filippini
3. L. Hunt
4. J. Zorić
5. Dayong Zhang
6. Manuel Llorca
7. Luis Orea
8. R. B. Swain

In Environmental Engineering

1. Massimo Filippini
2. Manuel Llorca
3. Luis Orea
4. J. Zorić
5. A. Karimu
6. R. B. Swain
7. L. Hunt
8. Dayong Zhang

In Renewable Energy, Sustainability and the Environment

1. D. Broadstock
2. Massimo Filippini
3. Dayong Zhang
4. A. Karimu
5. R. B. Swain
6. J. Zorić
7. David I. Stern
8. Manuel Llorca

Citations in the corpus

• Impact of energy policy instruments on the estimated level of underlying energy efficiency in the EU residential sector (2013, methodology): “Following the approach proposed by Filippini and Hunt (2011, 2012) this paper employs a frontier demand energy model to estimate the „underlying energy efficiency‟ of residential sector for each EU member state over the period 1996 to 2009.”
• A new approach to measuring the rebound effect associated to energy efficiency improvements: An application to the US residential energy demand (2015, methodology): “3 The estimation of (3) can be performed using either cross-sectional or panel data as in Filippini and Hunt (2011, 2012). They also propose a relatively simple log-log functional form. 4 Filippini and Hunt (2011, 2012) advocate using panel data techniques to control for potential endogeneity proble”
• The causal relationship between energy use and economic growth in Switzerland (2013, neutral): “1 Recently, Filippini and Hunt (2011) identified Switzerland as one of the most energy-efficient (and less energy-intensive) countries in the OECD.”
• Modeling international trends in energy efficiency (2012, background): “…lists available at SciVerse ScienceDirect Energy Economics j ourna l homepage: www.e lsev ie r .com/ locate /eneco A few recent papers (Filippini and Hunt, 2011; Wang, 2011; Wei et al., 2009) pursue related but different approaches to modeling aggregate energy efficiency.”
• Efficiency Snakes and Energy Ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households (2016, methodology): “Filippini and Hunt (2011, 2012) describe how existing stochastic frontier analysis methods can be used to measure the distance between actual consumption and the MER, and thus measure efficiency, for US states and European countries respectively.”
• Renewable electricity and sustainable development goals in the EU (2020, positive): “In the case of energy goods, previous studies (Filippini and Hunt, 2011; Karimu and Brånnlund, 2013) derive the energy demand function to depend on real energy price, real GDP, policy variables such as taxes and weather conditions.”
• US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach (2012, methodology): “As stated above, the aim of this paper is to attempt to construct and measure the ‘underlying energy efficiency’ for the US residential sector across 48 ‘states’,7 building on previous work by Filippini and Hunt (2011).”