Stars and standards: Energy efficiency in rental markets

Burfurd, Ingrid; Gangadharan, Lata; Nemes, Veronika

doi:10.1016/j.jeem.2012.05.002

Cited by 25 publications

(17 citation statements)

References 19 publications

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“…A similar picture is present in other countries such as Australia where 70% of the rental stock is provided by such small scale 'non professional' landlords , and in the United States where single property landlords comprise 55% of the market (Burfurd et al, 2012). Most UK private landlords maintain their properties themselves or engage an estate agent to do so on their behalf (Burfurd et al, 2012). There are few specialist private rental maintenance firms and also few rental only development of a large enough size to have their own maintenance staff, as is common in other countries in particular the USA.…”

Section: Energy Efficiency Performancesupporting

confidence: 53%

“…In contrast to the social rented sector, where one organisation owns multiple dwellings (DCLG, 2012) 78% of private landlords in the UK only own one property and as a whole individual landlords own the bulk of the private rented housing stock (Scanlon and Kochan, 2011). A similar picture is present in other countries such as Australia where 70% of the rental stock is provided by such small scale 'non professional' landlords , and in the United States where single property landlords comprise 55% of the market (Burfurd et al, 2012). Most UK private landlords maintain their properties themselves or engage an estate agent to do so on their behalf (Burfurd et al, 2012).…”

Section: Energy Efficiency Performancementioning

confidence: 84%

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Attitudes and behaviours of private sector landlords towards the energy efficiency of tenanted homes

Hope

Booth

2014

Energy Policy

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The UK's housing stock generates approximately 27 per cent of the country's total annual carbon emissions. In light of the legally binding targets to reduce carbon emissions, new housing is subject to a tightening of regulations governing energy demand and efficiency resulting in a gradual improvement in carbon emissions. The question is how to achieve the deep carbon emission reductions from existing domestic properties, of which 75 per cent will still be in use in 2050. Government has sought to provide incentives to homeowners to improve the energy efficiency of their households, and mandate improvements in socially rented housing using a range of fiscal measures, most recently the 'Green Deal'. There has however been little consideration of the 18 per cent of UK households who privately rent their home, a tenure that is growing fast. The aim of this research is to investigate the factors that influence private sector landlords when considering energy efficiency improvements to their tenanted homes. The results indicate that Government policy has consistently failed to engage private sector landlords in the issue of energy efficiency and thus measures must be taken to understand the motivations of landlords in order to design effective incentives and interventions.

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Section: Energy Efficiency Performancesupporting

confidence: 53%

Section: Energy Efficiency Performancementioning

confidence: 84%

Attitudes and behaviours of private sector landlords towards the energy efficiency of tenanted homes

Hope

Booth

2014

Energy Policy

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“…The extant literature on potential additional drivers to invest in energy efficient housing is particularly scarce. In related studies, Banfi et al (2005), Burfurd et al (2012) and Fuerst et al (2015) published findings indicating that rental housing tenants are prepared to pay higher rent for buildings that have adopted energy-saving measures. Burfurd et al (2012) used laboratory experiments to show that information on the energy efficiency of a dwellingeither mandatory or voluntaryimproves the market efficiency and increases investment in energy efficiency in the housing rental market, while the lack of information can give rise to an undesirable 'lemons market' outcome.…”

Section: Introductionmentioning

confidence: 99%

Green signalling effects in the market for energy-efficient residential buildings

Fuerst

Oikarinen

Harjunen³

2016

Applied Energy

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Empirical evidence from recent studies suggests that the price premium on energy-efficient buildings is potentially higher than the pure capitalisation of energy savings but the empirical evidence on the size of the non-savings components is scant. This study aims to fill this research gap by investigating whether the mandatory energy efficiency ratings for residential properties imply benefits that go beyond energy savings. Using a sample of several thousand apartment transactions from Helsinki, Finland, we first test if higher ratings were significantly associated with higher prices. In addition to a large number of property and neighbourhood characteristics, this dataset contains information on building-level energy usage which allows us to distinguish between the cost savings effect of energy consumption and the value of more intangible factors associated with the energy label. The hedonic model yields a statistically significant 3.3% price premium for apartments in the top three energy-efficiency categories and 1.5% when a set of detailed neighbourhood characteristics are included. When maintenance costs containing energy usage costs are added, a robust and significant price premium of 1.3% persists whereas no differentiation is found for the medium and lower rating categories. These findings may be indicative of energy-efficient buildings having signalling valueand therefore an additional incentive to invest in such buildings-for 'green' consumers. However, a favourable energy rating did not appear to speed up the sales process in the analysed market.

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“…Such (semi)subjective knowledge items cannot be treated by numerical mathematics and/or statistics. Conventional statistical methods, which are directly or indirectly related to the basic law of large numbers, are difficult or impossible to apply if the studied EEM tasks are unique and complex (see [39]). …”

Section: Discussionmentioning

confidence: 99%

“…However, if an N variable has a stochastic nature (e.g., weather predictions), then it is possible to develop a conventional decision tree (see, e.g., [39]). One has to keep in mind that a decision, that is, a quantification of all (some) of the variables, D, is made prior to any stochastic generation of the N variables.…”

Section: Sustainability Decision Makingmentioning

confidence: 99%

Analysis of Sustainability Decision Trees Generated by Qualitative Models Based on Equationless Heuristics

2018

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Sustainability processes are complex and therefore ill-known, inconsistent, and subjective, and must be studied despite a shortage of information. It is prohibitively difficult to study them on quantitative levels using quantitative methods. The presented qualitative approach enables us to solve these issues. There are just three values used to describe the qualitative variables and their derivatives, plus/increasing, zero/constant, and negative/decreasing. An n-dimensional equation-less qualitative model is a set of pairwise relations. Such relations represent a shallow knowledge of the sustainability systems being studied. The solution of the qualitative model is a set of scenarios. The behaviour of this model is described by all of the possible transitions among these scenarios. A decision maker can easily compile a decision tree if he/she knows all of the possible transitions. The generated tree can be evaluated using traditional methods if all of the relevant probabilities are known. Otherwise, some heuristics are used to evaluate the best decision.

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Stars and standards: Energy efficiency in rental markets

Cited by 25 publications

References 19 publications

Attitudes and behaviours of private sector landlords towards the energy efficiency of tenanted homes

Attitudes and behaviours of private sector landlords towards the energy efficiency of tenanted homes

Green signalling effects in the market for energy-efficient residential buildings

Analysis of Sustainability Decision Trees Generated by Qualitative Models Based on Equationless Heuristics

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