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Air quality, noise and proximity to urban infrastructure can arguably have an important impact on the quality of life. Environmental quality (the price of good health) has become a central tenet for consumer choice in urban locales when deciding on a residential neighbourhood. Unlike the market for most tangible goods, the market for environmental quality does not yield an observable per unit price effect. As no explicit price exists for a unit of environmental quality, this paper aims to use the housing market to derive its implicit price and test whether these constituent elements of health and well-being are indeed capitalised into property prices and thus implicitly priced in the market place.

A considerable number of studies have used hedonic pricing models by incorporating spatial effects to assess the impact of air quality, noise and proximity to noise pollutants on property market pricing. This study presents a spatial analysis of air quality and noise pollution and their association with house prices, using 2,501 sale transactions for the period 2013. To assess the impact of the pollutants, three different spatial modelling approaches are used, namely, ordinary least squares using spatial dummies, a geographically weighted regression (GWR) and a spatial lag model (SLM).

The findings suggest that air quality pollutants have an adverse impact on house prices, which fluctuate across the urban area. The analysis suggests that the noise level does matter, although this varies significantly over the urban setting and varies by source.

Air quality and environmental noise pollution are important concerns for health and well-being. Noise impact seems to depend not only on the noise intensity to which dwellings are exposed but also on the nature of the noise source. This may suggest the presence of other externalities that arouse social aversion. This research presents an original study utilising advanced spatial modelling approaches. The research has value in further understanding the market impact of environmental factors and in providing findings to support local air zone management strategies, noise abatement and management strategies and is of value to the wider urban planning and public health disciplines.

Buildings contribute significantly to CO₂ production. They are also subject to considerable taxation based on value. Analysis shows that while similar attributes contribute to both value and CO₂ production, there is only a loose relationship between the two. If we wish to use taxation to affect policy change (drive energy efficiency behaviour), we are unlikely to achieve this using only the current tax base (value), or by increasing the tax take off this current tax base (unlike extra taxation of cigarettes to discourage smoking, for example). Taxation of buildings on the basis of energy efficiency is hampered by the lack of current evidence of performance. This paper aims to model the now-obligatory (at sale or letting) energy performance certificate (EPC) data to derive an acceptable appraisal model (marked to market, being the EPC scores) and deploys this to the entire population of properties. This provides an alternative tax base with which to model the effects of a tax base switch to energy efficiency and to understand the tax incidence effects of such a policy.

The research uses a multiplicative hedonic approach to model energy efficiency utilising EPC holding properties in a UK jurisdiction [Northern Ireland (NI)] as the sample. This model is then used to estimate discrete energy assessments for each property in the wider population, using attributes held in the domestic rating (property tax) database for NI (700,000+ properties). This produces a robust estimate of the EPC for every property in its current condition and its cost-effective improved condition. This energy assessment based tax base is further used to estimate a new millage rate and property tax bill (green property tax) which is compared against the existing property tax based on value to allow tax incidence changes to be analysed.

The findings show that such a policy would significantly redistribute the tax burden and would have a variety of expected and some unexpected effects. The results indicate that while assessing the energy performance of houses can be a complex process involving many parameters, much of the explanatory power can be achieved via a relatively small number of input variables, often already held by property tax jurisdictions. This offers the opportunity for useful housing stock modelling – such as the savings possible from power switching. The research also identifies that whilst urban areas display the expected “heat island” effect in terms of energy consumption, urban properties are on average more efficient than suburban/rural properties. This facilitates spatial targeting of policy messages and initiatives.

Analogous with other studies, data deficiencies introduce the risk of omitted variable bias. Modelling of the energy efficiency in the sample is limited to property attributes that are available for the wider population of properties. While this limits the modelling exercise, it is a perennial issue facing mass appraisal worldwide (where knowledge of the transacted sample attributes generally exceeds knowledge of the unsold properties). That said, the research demonstrates the benefits of sharing data and improving knowledge of the housing stock, as taxation databases would be stronger, augmented with EPC-derived property attributes for example.

The EPC lead in time for wide residential coverage is likely to be considerable. The paper contributes to emerging literature and policy debate surrounding the effect, performance measurement and implementation of energy efficiency certification, through a greater understanding of the sectorial and geographical dispersion of energy efficiency. It provides high level research to help guide policy and decision-making, identifying key locales where there is more of a physical problem and locations where there is more to gain in terms of targeting energy improvement and/or encouraging behavioural change. The paper also allows a glimpse of the implications of a change towards a taxation regime based on energy efficiency, which contributes to the debate surrounding the “greening” of property based taxes.

The London office market is a major destination of international real estate capital and arguably the epicentre of international real estate investment over the past decade. However, the increase in global uncertainties in recent years due to socio-economic and political trends highlights the need for more insights into the behaviour of international real estate capital flows. The purpose of this study is to evaluate the influence of the global and domestic environment on international real estate investment activities within the London office market over the period 2007–2017.

This study adopts an auto-regressive distributed lag approach using the real capital analytics (RCA) international real estate investment data. The RCA data analyses quarterly cross-border investment transactions within the central London office market for the period 2007–2017.

The study provides insights on the critical differences in the influence of the domestic and global environment on cross-border investment activities in this office market, specifically highlighting the significance of the influence of the global environment in the long run. In the short run, the influence of factors reflective of both the domestic and international environment are important indicating that international capital flows into the London office market is contextualised by the interaction of different factors.

The authors provide a holistic study of the influence of both the domestic and international environment on cross-border investment activities in the London office market, providing more insights on the behaviour of global real estate capital flows.

Belfast's “peace walls” exist to physically segregate and provide a measure of security to the communities on the religious divide in Northern Ireland. Whilst they do ostensibly achieve this aim, it may well be that these structures have the capacity to prevent the restoration of normal community interactions and market processes and may also be providing their benefits at a high price with regard to issues such as house price reduction. Indeed, the effect of these structures on surrounding residential property values remains somewhat of an unknown quantity. This paper therefore measures the effect of proximity to locations with social and political conflicts. The paper aims to quantify and measure the disamenity implications and costs of artificial barriers (peace walls) within the Belfast housing market.

This paper attempts to measure the disamenity effect of peace walls on house prices, primarily focusing on the effect of distance, calculated using a hedonic pricing specification and spatially referenced data. The data are derived from 3,836 house sales transactions over a one year period in 2011.

The emerging findings demonstrate that a greater negative pricing effect is evident with proximity to the peace walls, with the exception of the apartment sector. The findings also highlight the complex market pricing structure of Belfast and offer insight as how to best classify submarkets.

The results of the research are of particular interest to property valuers and social policy makers in regions with contested space.

Tactile barriers scar the urban terrain, formalise ethno-segregation across Belfast and have implications for spatial planning in the urban environment and housing studies and policy. Such an externality may have a pervasive and endogenous effect on house prices and the identification of submarkets yet there is implicit acceptance of peace lines as de facto standard and a dearth of empirical evidence relating to direction and magnitude of the location-specific effects of peace walls on house prices in Belfast. This paper is arguably the first to empirically examine the location-specific effects of peace walls on property value across the Belfast area.

The price-to-rent ratio is often regarded as an important indicator for measuring housing market imbalance and inefficiency. A central question is the extent to which house prices and rents form part of the same market and thus whether they respond similarly to parallel stimulus. If they are close proxies dynamically, then this provides valuable market intelligence, particularly where causal relationships are evident. Therefore, this paper aims to examine the relationship between market and rental pricing to uncover the price switching dynamics of residential real estate property types and whether the deviation between market rents and prices are integrated over both the long- and short-term.

This paper uses cointegration, Wald exogeneity tests and Granger causality models to determine the existence, if any, of cointegration and lead-lag relationships between prices and rents within the Belfast property market, as well as the price-to-rent ratios amongst its five main property sub-markets over the time period M4, 2014 to M12 2018.

The findings provide some novel insights in relation to the pricing dynamics within Belfast. Housing and rental prices are cointegrated suggesting that they tend to move in tandem in the long run. It is further evident that in the short-run, the price series Granger-causes that of rents inferring that sales price information unidirectionally diffuse to the rental market. Further, the findings on price-to-rent ratios reveal that the detached sector appears to Granger-cause those of other property types except apartments in both the short- and long-term, suggesting possible spill-over of pricing signals from the top-end to the lower strata of the market.

The importance of understanding the relationship between house prices and rental market performance has gathered momentum. Although the house price-rent ratio is widely used as an indicator of over and undervaluation in the housing market, surprisingly little is known about the theoretical relationship between the price-rent ratio across property types and their respective inter-relationships.

House price-to-rent (P-t-R) ratios are among the most widely used measures of housing market conditions. Given the theoretical and apparent bidirectional, causal relationships and imbalances between the housing market, broader economy and financial market determinants, it is important to understand the relationship between macro- and micro-economic characteristics in relation to the P-t-R ratio to enhance the understanding of housing market dynamics. This paper studies the joint dynamics and persistence of house prices and rents and examines the temporal interactions of the P-t-R ratio and economic and financial determinants.

The authors examine the lead–lag relationships between the P-t-R ratios and a spectrum of macroeconomic variables using cointegration and causality methods, initially at the aggregate position and also across housing types within the Northern Ireland housing market to establish whether there are subtle differences in how various housing segments react to changes in economic activity and market fundamentals.

The findings reveal price switching dynamics and some very distinct long- and short-run relationships between macroeconomic and financial indicators and the P-t-R ratios across the various housing segments. The results exhibit monetary supply, foreign exchange markets and the stock market to be important drivers of the P-t-R ratio, with P-t-R movements seemingly tied, or are in tandem, with the overall economy, particularly with the construction sector.

The study shows that the P-t-R ratio can be used as an early measure for establishing the effects of macroprudential policy changes and how these may manifest across housing tiers and quality, which can further act as a signal for preventing or at least mitigating future irrational price cyclicity. These insights serve to inform housing and economic policy and macroprudential policy design, principally within lending policy and the effect of regulatory interventions and further enhance the understanding of the P-t-R ratio on housing market structure and dynamics.

This study is the first in the housing literature that examines the causal relationships between the P-t-R ratio and macroeconomic activity at the sub-market level. It investigates whether and how money supply, inflation, foreign exchange markets, general economic productivity and other important macroeconomic factors interact with the pricing of different property types over time.

Information transparency is crucially important in price setting in real estate, particularly when information asymmetry is concerned. This paper aims to examine how a change in government policy in relation to information disclosure and transparency impacts residential real estate price discovery. Specially, this paper investigates how real estate traders determined asking prices in the context of the Scottish housing market before and after the implementation of the Home Report, which aimed to prevent artificially low asking prices.

This paper uses spatial lag hedonic pricing models to empirically observe how residential asking prices are determined by property sellers in response to a change in government policy that is designed to enhance market transparency. It uses over 79,000 transaction data of the Aberdeen residential market for the period of Q2 1998 to Q2 2013 to test the models.

The empirical findings provide some novel insights in relation to the price determination within the residential market in Scotland. The spatial lag models suggest that spatial autocorrelation in property prices has increased since the Home Report came into effect, indicating that property sellers have become more prone to infer asking prices based on prior sales of dwellings in close vicinity. The once-common practice of setting artificially low asking prices seems to have dwindled to a certain extent statistically.

The importance of understanding the relationship between information transparency and property price determination has gathered momentum over the past decade. Although spatial hedonic techniques have been extensively used to study the impact of various property- and neighbourhood-specific attributes on residential real estate market in general, surprisingly little is known about the empirical relationship between spatial autocorrelation in real estate prices and information transparency.

The purpose of this study is to examine whether PV uptake is associated with key housing market determinants and linked to socio-economic profiles. An abundance of extant literature has examined the role of solar photovoltaic (PV) adoption and user costs, with an emerging corpus of literature investigating the role of the determinants of PV uptake, particularly in relation to the built environment and the spatial variation of PV dependency and dissimilarity. Despite this burgeoning literature, there remains limited insights from the UK perspective on housing market characteristics driving PV adoption and in relation spatial differences and heterogeneity that may exist.

Applying micro-based data at the Super Output Area-level geography, this study develops a series of ordinary least squares, spatial econometric models and a logistic regression analysis to examine built environment, housing tenure and deprivation attributes on PV adoption at the regional level in Northern Ireland, UK.

The findings emerging from the research reveal the presence of some spatial clustering and PV diffusion, in line with several existing studies. The findings demonstrate that an urban-rural dichotomy exists seemingly driven by social interaction and peer effects which has a profound impact on the likelihood of PV adoption. Further, the results exhibit tenure composition and “economic status” to be significant and important determinants of PV diffusion and uptake.

Housing market characteristics such as tenure composition across local market structures remain under-researched in relation to renewable energy uptake and adoption. This study examines the role of housing market attributes relative to socio-economic standing for adopting renewable energy.

A number of studies have investigated the relationship between energy performance certificates (EPCs) and house prices. A majority of studies have tended to model energy performance pricing effects within a traditional hedonic conditional mean estimate model. There has been limited analysis that has accounted for the relationship between EPCs and the effects across the pricing distribution. Moreover, there has been limited research examining the “standard cost improvements EPC score”, or “potential score”. Therefore, this paper aims to quantify and measure the dynamic effects of EPCs on house prices across the price spectrum and account for standardised cost-effective retrofit improvements.

Existing EPC studies produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price effect. The approach within this study applies a quantile regression approach to empirically estimate how quantiles of house prices respond differently to unitary changes in the proximal effects of EPCs and structural property characteristics across the conditional distribution of house prices. Using a data set of 1,476 achieved transaction prices, the quantile regression models apply both assessed EPC score and bands and further examine the potential EPC rating for improved energy performance based on an average energy cost improvement.

The findings show that EPCs are valued differently across the quantiles and that conditional quantiles are asymmetrical. Only property prices in the upper quantiles of the price distribution show significant capitalisation effects with energy performance, and only properties with higher EPC scores display positive significant effects at the higher end of the price distribution. There are also brown discount effects evident for lower-rated properties within F- and G-rated EPC properties at the higher end of the pricing distribution. Moreover, the potential energy efficiency rating (score) also shows increased effects with sales prices and appears to minimise any brown discount effects. The findings imply that energy performance is a complex feature that is not easily “averaged” for valuation effect purposes.

While numerous studies have investigated the pricing effects of EPCs, they have tended to provide a single estimate to determine the relationship with price. This paper extends the traditional analytical insights beyond the conditional mean estimate by examining the quantiles of the relationship between EPCs and house prices to enhance the understanding of this esoteric and complex issue. In addition, this research applies the assessed energy efficiency potential to establish whether effective cost improvements enhance the relationship with sales price and capitalisation effects.

Understanding the key locational and neighbourhood determinants and their accessibility is a topic of great interest to policymakers, planners and property valuers. In Northern Ireland, the high level of market segregation means that it is problematic to understand the nature of the relationship between house prices and the accessibility to services and prominent neighbourhood landmarks and amenities. Therefore, this paper aims to quantify and measure the (dis)amenity effects on house pricing levels within particular geographic housing sub-markets.

Most hedonic models are estimated using regression techniques which produce one coefficient for the entirety of the pricing distribution, culminating in a single marginal implicit price. This paper uses a quantile regression (QR) approach that provides a “more complete” depiction of the marginal impacts for different quantiles of the price distribution using sales data obtained from 3,780 house sales transactions within the Belfast Housing market over 2014.

The findings emerging from this research demonstrate that housing and market characteristics are valued differently across the quantile values and that conditional quantiles are asymmetrical. Pertinently, the findings demonstrate that ordinary least squares (OLS) coefficient estimates have a tendency to over or under specify the marginal mean conditional pricing effects because of their inability to adequately capture and comprehend the complex spatial relationships which exist across the pricing distribution.

Numerous studies have used OLS regression to measure the impact of key housing market externalities on house prices, providing a single estimate. This paper uses a QR approach to examine the impact of local amenities on house prices across the house price distribution.