2015
DOI: 10.1007/s12053-015-9418-3
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Do energy efficiency measures really reduce household energy consumption? A difference-in-difference analysis

Abstract: This study investigates the impact of energy efficiency measures installed through the Carbon Emission Reduction Target (CERT) and the Community Energy Saving Programme (CESP) on domestic gas and total energy consumptions. The recently released National Energy Efficiency Data-Framework (NEED) database is used to examine the changes in domestic gas and total energy consumptions for the dwellings in the sample relative to the changes in gas and total energy consumptions for a comparable control group in the year… Show more

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Cited by 63 publications
(59 citation statements)
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References 22 publications
(29 reference statements)
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“…This study finds a 13.8% mean reduction in gas consumption by the difference in difference technique. By this metric, the study concurs with 13.3% reduction in Britain [1] and 13% in New Zealand [30]. As expected, this study finding of 13.8% gas reduction is below the 21% average reduction by 444 self-selected households analysed by Scheer et al [45].…”
Section: Discussionsupporting
confidence: 88%
“…This study finds a 13.8% mean reduction in gas consumption by the difference in difference technique. By this metric, the study concurs with 13.3% reduction in Britain [1] and 13% in New Zealand [30]. As expected, this study finding of 13.8% gas reduction is below the 21% average reduction by 444 self-selected households analysed by Scheer et al [45].…”
Section: Discussionsupporting
confidence: 88%
“…Unfortunately, we could not measure the health effect of upgrades in this study, nor could we monitor internal temperatures. Given our limited sample size, we could not calculate the energy savings associated with certain measures, as others such as Adan and Fuerst (2015) for example have done. These are limitations of this work.…”
Section: Discussionmentioning
confidence: 99%
“…The control group is the object that has not been affected by the policy, the treatment group is the object affected by the policy, and then the policy is implemented by changing the two groups of experiments accordingly. In recent years, many studies have used this method to evaluate the emission reduction effect of the emissions trading policy [45][46][47]. In this study, we use 11 provinces and municipalities (Hebei, Henan, Hubei, Hunan, Jiangsu, Zhejiang, Tianjin, Chongqing, Inner Mongolia, Shanxi, and Shaanxi) that piloted emissions trading in 2007 as treatment groups, and then employe propensity score matching (PSM) to match the remaining 18 provinces as control groups.…”
Section: Emissions Trading System Effect Estimation: a Did Modelmentioning
confidence: 99%