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The purpose of this paper is to evaluate the parcel-level impacts of the zoning change.

Using hedonic regression and propensity score matching econometric techniques, this paper analyses single-family housing prices within Fulton County Georgia. This paper combines data on the parcel-level zoning changes with nearby housing sales transactions to study the potential externality effects because of rezoning induced by private parties.

The paper finds evidence of heterogeneous rezoning effects, depending upon the type of rezoning conducted. At a distance within 0.75 miles, housing prices appreciate by 8.31% when nearby privately initiated rezoning maintains the residential character of a neighbourhood. However, housing prices decline by 21.26% when residential housing zones are converted to non-residential housing zones. The negative influences of rezoning residential use to non-residential uses decline as distance increases.

The analysis provides quantitative information on the impact of rezoning on residential property prices. Planning officials and developers can use these results to assuage homeowner fears of potential negative housing price effects associated with rezoning.

This paper focusses on analysing the impact of crime on the housing market in Los Angeles (LA) County. By looking at different types of crime instead of general crime measures and controlling by spatial dimension of prices and crime as well as endogeneity, a model is developed that allows for the understanding of how a specific crime impacts the housing market transaction price. To perform the analysis, the paper merges different data sets (crime, housing transaction and census data) and then computes the distances to crucial transport modes to control the accessibility features affecting housing prices. The latter allows estimating the association of housing prices and crime in the distance and estimating the impact on housing depending on it.

This paper focusses on the following crimes: aggravated assault, burglary (property crime), narcotics, non-aggravated assault and vandalism. The paper shows firstly how incidents of reported crime are distributed across space and how they are related to each other – thus highlighting crime models with spatial influences. Secondly, the research utilises instrumental variables within the methodology to estimate house prices using spatial analysis techniques while controlling for endogeneity. Thirdly, it estimates the direct impact of crime on house prices and explores the impact of housing and neighbourhood features.

Results suggest that house transaction prices and crime are closely correlated in two senses. Housing prices are endogenously negatively associated with the levels of narcotics and aggravated assaults. For narcotics, the impact of distance is shorter (1,000 m). However, for burglary, vandalism and non-aggravated assaults, the price reaction suggests a positive association: the further away the crime occurs, the higher the prices. The paper also shows the large spatial association of different crimes suggesting that they occur together and that their accumulation would make negative externalities appear affecting the whole neighbourhood.

The use of a huge database allows interesting findings, but one limitation can be to not have longer time observations to identify the crime evolution and its impact on housing prices.

Large implications as the relationship identified in this paper allow defining precise policies to avoid crime in different areas in LA. In addition, crime has significant but quantitative small effects on LA housing transaction prices suggesting that the effect depends on the spatial scale as well as lack on information about where the crimes are committed. Lack on information suggests low transparency in the market, affecting the transaction decision-taken process, affecting the risk perception and with relevant implications over household welfare.

This paper relates the spatial association among crimes defining the hotspots and their impacts on housing transaction prices.

It was not until the late 1960s that housing attracted much attention from academic social scientists. Since that time the literature has expanded widely and diversified, establishing housing with a specialised status in economics, sociology, politics, and in related subjects. As we would expect, the new literature covers a technical, statistical, theoretical, ideological, and historical range. Housing studies have not been conceived and interpreted in a monolithic way, with generally accepted concepts and principles, or with uniformly fixed and precise methodological approaches. Instead, some studies have been derived selectively from diverse bases in conventional theories in economics or sociology, or politics. Others have their origins in less conventional social theory, including neo‐Marxist theory which has had a wider intellectual following in the modern democracies since the mid‐1970s. With all this diversity, and in a context where ideological positions compete, housing studies have consequently left in their wake some significant controversies and some gaps in evaluative perspective. In short, the new housing intellectuals have written from personal commitments to particular cognitive, theoretical, ideological, and national positions and experiences. This present piece of writing takes up the two main themes which have emerged in the recent literature. These themes are first, questions relating to building and developing housing theory, and, second, the issue of how we are to conceptualise housing and relate it to policy studies. We shall be arguing that the two themes are closely related: in order to create a useful housing theory we must have awareness and understanding of housing practice and the nature of housing.

Even as multi-story apartment building development proposals in existing neighbourhoods represent a substantial component of policy debate at local planning boards, there is limited evidence for the impact of such residential developments on surrounding apartment values. This paper aims to address the void in knowledge, and the impact of multi-story apartment building developments on apartment values in residential high-rise areas located outside city and district centres is investigated in Helsinki Metropolitan Area, Finland.

Whether a multi-story apartment building development is followed by an increase in housing values depends on both positive and negative externalities. To specify valuation effects of proximate development projects, advanced research design combining matched sample methodology and hedonic-based difference-in-difference approach is used.

It appears from the analysis that completion of a single multi-story apartment building has an immediate positive impact on apartment values within 300 metre radius, while there is no statistically significant impact on price trend.

This paper studies apartment values only in Helsinki Metropolitan Area, Finland, and it is important to notice that local regulations and market conditions may have a notable impact on the outcomes.

This study is the first of its kind to provide with statistically significant evidence for positive impacts from multi-story apartment building development in Finnish residential high-rise areas and may have a crucial role in helping to dispel prejudices related to such developments.

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.

The purpose of this study is to explore the effects of revitalization of old industrial buildings on the market value of the neighbourhood residential properties. Hong Kong’s economy has undergone a remarkable transformation in the past three decades. The most visible phenomenon in this transformation is the relocation of traditional manufacturing activities from Hong Kong to China since the 1990s. This has led many of the old industrial buildings in Hong Kong to be empty/underutilized and dilapidated. The Hong Kong Special Administrative Region Government launched the “Revitalizing Industrial Buildings Policy” to revitalize these underutilized properties with the aim to provide suitable land and premises to meet local’s economic and social needs.

The study used a hedonic price model to determine whether there is a relationship between revitalization projects and neighbourhood residential property values and the influence of revitalization programmes on the residential property price if there is such a relationship. The study is based on a sample of 4,015 residential transactions obtained from the residential developments located near three large-scale revitalization projects in an old industrial district, Kwun Tong.

Empirical findings suggest that revitalization programmes have not brought net positive price effects on the value of neighbourhood residential properties. This is in line with findings of some previous studies. However, it reveals that both the mode and scale of revitalization projects have different impacts on the neighbourhood: wholesale conversion has less negative impacts compared with redevelopment, while the larger the scale of a revitalization programme, the greater are the negative impacts on nearby property values. The study also finds that negative externalities generated by the revitalization during and post-revitalization stages are almost similar in magnitudes.

The results imply that industrial revitalization projects located adjacent to residential developments both reduce the value of the latter and discourage potential property buyers. The negative public perception of these properties diminishes their value and hence decreases the value of the property.

The paper raises the concern about the importance of adequately addressing issues of planning and zoning to minimize the negative externalities arising from urban renewal projects.

This research paper is first of its kind to analyze the effects of revitalized industrial buildings on the value of neighbourhood properties in Hong Kong. The tangible benefits identified in this study would be incentives, or otherwise, to motivate the revitalization policy in general.

The purpose of this paper is to analyse two questions. First, is there, and if so, how large is the price premium paid for a building exhibiting a cultural value? Second, are there any spillover effects of buildings with cultural values on sales prices of neighbouring houses?

Using a unique database of all buildings in the region of Halland, Sweden, combined with transaction data, hedonic models can be estimated, with spatially lagged variables describing proximity to three classes of culturally classified building – A, B and C – corresponding to building of national interest, building of regional interest and building of local interest. In addition, the authors also estimate models with a spatial specification on the error term, in an attempt to control for omitted variables.

The results indicate that cultural classification plays a role in determining the price of a property, with large effects (ranging between 36 and 60% price premiums) for the highest classification. In addition, the authors find evidence of a cultural externality, houses in the vicinity of building with high cultural value sell at a small, but statistically significant premium of 1%.

The cultural externality may be overlooked when it comes to valuation of cultural values in society, and therefore, it is likely that warranted protection acts to preserve cultural values in buildings become less than the social optimum. This paper suggests a new measure to cultural values contrasting previous research that rely on cultural preservation. This approach should limit problems with measurement errors that may lead to biased results.

Focuses on the effect of both proximity and size of shopping centres on surrounding residential property values, using hedonic modelling. States that the data bank consists of a subset of some 4,000 single‐detached, owner‐occupied housing units transacted all over the Quebec Urban Community territory between January 1990 and December 1991. Tests several functional forms and uses up to 60 descriptors. Reveals that in line with previous studies, findings indicate that shopping‐centre size exerts a positive contributory effect on values; they also tend to confirm the non‐monotonicity of the price‐distance function. Concludes that, in that respect, resorting to the gamma function for distance variables yields most interesting results and provides consistent estimates of optimal distances for various shopping‐centre size categories.

The paper develops a housing model equation for Spain and selected regions to estimate new supply elasticity. The aim of the paper is to assess the role of housing supply on price evolution and explain the fall in housing starts since the start of the credit crunch.

The paper uses a pooled EGLS specification controlling for the presence of cross-section heteroskedasticity. Fixed effect estimators are calculated to capture regional heterogeneity. The model uses secondary data (quarterly) for 17 Spanish regions over the period 1990-2012. A recursive procedure is applied to estimate model parameters starting with a baseline model (1990-1999) and successively adding one-year time information. Elasticities, as well as explanatory power from models, are reported and jointly analyzed. Elasticity is interpreted as the extent to which market mechanisms drive developer responses.

Elasticities of new supply are shown to be very stable during all periods but characterized by differences in response at a regional level. Elasticity ranges from 0.8 to 1.3 across regions. The model reports a non-market-oriented mechanism that guides building decisions. The credit crunch and debt crisis have had a double negative effect capturing the cumulative effect of exogenous shocks.

Elastic responses restrained the effects of over-pricing in the period of strong demand pressures in the early 2000s. Changes in elasticity parameters over time suggest that long-term elasticity in housing supply depends on the specific region analyzed. The results show that the credit crunch shock had varying degrees of severity in Spanish regions, dramatically reducing house-building because of the high sensitivity to changes in prices.

Estimated elasticity may be used to forecast responses to changes in housing prices. The results add to the understanding of the equilibrium mechanism in the housing market across regions.

This is the first article that analyses housing supply, calculates supply elasticities and measures the impact of the credit crunch on the housing market from the supply side in Spain. The paper adds evidence to the debate concerning the equilibrium mechanism in the housing market.

There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime.

The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data.

The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables.

The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.