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Population ageing is fast becoming a major social concern across the globe. This ageing trend unavoidably fuels elders’ demand for healthcare services. As the main users of health care service, whether the healthcare is geographically approachable in local areas is more imperative to senior residents with restricted mobility. This paper proposes to examine the effect of elders’ healthcare accessibility on property prices of Taipei Metropolis, Taiwan.

Luo and Qi’s (2009) enhanced two-step floating catchment area method – taking both healthcare demand and supply into account – was used to measure three types of healthcare services: “physician-to-elder ratio”, “hospital bed-to-elder ratio” and “ambulance-to-elder ratio”. Spatial quantile regression (SQR) model was then used to examine the spatial effect of healthcare accessibility on different property price ranges.

The “physician-to-elder ratio” and “hospital bed-to-elder ratio” demonstrated expected consistent positive effects across all quantiles of property prices (p < 0.01) in SQR, and its effects aggravated as the quantiles of property prices rose. The “ambulance-to-elder ratio” demonstrated a non-linear influence on property prices (i.e. a negative effect on lowest quantile prices but a positive on higher quantile prices) possibly due to the semi-obnoxious characteristic of the ambulance. That is, residents living in lower priced neighbourhoods may dislike ambulances’ annoying sound of sirens (i.e. ambulances’ disamenity), while residents living in higher valued neighbourhoods may on the contrary appreciate ambulances’ healthcare services (i.e. amenity).

These findings are expected to offer some insights for government’s policies in providing elders in their later years with good residential quality and easy access to healthcare resource.

This paper is one of the few studies that consider the capitalization of the spatial healthcare accessibility to elders into property prices. In this ageing trend across the globe, although all the accessibility to medical resources should be equally critical, the application of spatial quantile regression revealed residents’ inconsistent tendency against semi-obnoxious ambulances. It provides a different perspective in defining the importance of healthcare accessibility in neighbourhoods.

This paper aims to analyze how nearby property prices are affected by new construction projects in Stockholm. If there is an impact on property prices, the authors endeavor to investigate whether the effects vary among different areas within the municipality, for different groups of inhabitants and for different types of housing (i.e. public versus private housing).

The authors use a difference-in-difference specification in a hedonic model, and the sample consists of more than 90,000 observations over the period 2005-2013.

The results are robust and indicate that house prices in nearby areas increase following the completion of infill development. The results also indicate that infill development has a positive spillover effect on nearby dwelling prices only in areas with lower incomes, more public housing units and more inhabitants born abroad.

It provides an analysis on how nearby property prices are affected by new construction projects by creating a restricted control area, so as to make the treatment group and the control group more homogeneous. Thus, it mitigates any potential problems with spatial dependency, which can cause biased standard errors.

This study aims to measure the occurrence of gentrification and to relate gentrification with housing values.

The authors have used Getis-Ord statistics to identify and quantify gentrification in different residential areas in a case study of Stockholm, Sweden. Gentrification will be measured in two dimensions, namely, income and population. In step two, this measure is included in a traditional hedonic pricing model where the intention is to explain future housing prices.

The results indicate that the parameter estimate is statistically significant, suggesting that gentrification contributes to higher housing values in gentrified areas and near gentrified neighbourhoods. This latter possible spillover effect of house prices due to gentrification by income and population was similar in both the hedonic price and treatment effect models. According to the hedonic price model, proximity to the gentrified area increases housing value by around 6%–8%. The spillover effect on price distribution seems to be consistent and stable in gentrified areas.

A few studies estimate the effect of gentrification on property values. Those studies focussed on analysing the impacts of gentrification in higher rents and increasing house prices within the gentrifying areas, not gentrification on property prices in neighbouring areas. Hence, one of the paper’s contributions is to bridge the gap in previous studies by measuring gentrification’s impact on neighbouring housing prices.

This paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.

The hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.

Rental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.

Residential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.

Residential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.

This paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.

Global warming exacerbates sea level rise and extreme weather events that cause severe flooding, resulting in lost productivity and property damage. To reduce the impact of flooding, residents are avoiding purchasing homes in high-risk areas. There are numerous studies on the relationship between flood hazards and housing prices in developed countries, but few in developing countries. Therefore, this study aims to investigate the relationship between flood hazards and housing prices in Hat Yai, Songkhla, Thailand.

This study uses spatial-lag, spatial error and spatial autoregressive lag and error (SARAR) models to analyze the effect of flood risk on property prices. The main analysis examines the degree of flood risk and housing rental prices from our survey of 380 residences. To test the robustness of the results, the authors examine a different data set of the same samples by using the official property valuation from the Ministry of Finance and the flood risk estimated by the Southern Natural Disaster Research Center.

The SARAR model was chosen for this study because of the occurrence of spatial dependence in both dependent variable and the error term. The authors find that flood risk has a negative impact on property prices in Hat Yai, which is consistent with both models.

This study is one of the first to use spatial econometrics to analyze the impact of flood risk on property prices in Thailand. The results of this study are valuable to policymakers for benefit assessment in cost–benefit analysis of flood risk avoidance or reduction strategies and to the insurance market for pricing flood risk insurance.

This paper investigates the impact of governance on economic growth, considering the spatial dependence between countries.

The study employs spatial regression models to estimate the impact of governance on economic growth in a sample of 116 countries worldwide in 2017.

The findings imply that the influence of governance on economic growth is statistically significant. Moreover, if all other economic control variables are constant, 1% increase in governance raises the economic growth on average by 1% at 10%, 5% and 1% significance levels, respectively. Furthermore, each country's rise in economic growth favorably and substantially influences the economic growth of its bordering nations. The unobserved characteristics or similar unobserved environments in adjacent countries also affect its economic growth.

This study adds to the discussion and investigation of the influence of governance on economic growth by considering the spatial dependence between countries, which is lacking in the literature.

This study aims to examine the market structure and the factors influencing the price of fuelwood in the Dormaa Municipal in the Bono region of Ghana.

A total of 200 fuelwood harvesters, 20 wholesalers and 20 retailers were sampled by using probability and non-probability sampling methods. Gini coefficient was used to analyse the market structure, whereas quantile regression was used to analyse the factors influencing the pricing of fuelwood.

The study results indicated that the fuelwood harvesters’ market is less concentrated, with a Gini coefficient of 0.22, likewise the fuelwood intermediaries’ market, with Gini coefficients of 0.22 and 0.32 for wholesalers and retailers, respectively. The price of fuelwood decreased when sold through the retailer and wholesaler outlets, but the price increased when sold via the end-user outlet. Less smoky fuelwood species attracted higher prices, whereas easy-to-light fuelwood species were sold at lower prices. Furthermore, fuelwood from Perpewa (Celtis zenkeri) and Acacia (Senna siamea) species received the highest prices in the market. It is recommended that fuelwood harvesters establish woodlots with acacia (Senna siamea), especially and Perpewa (Celtis zenkeri), both of which emit less smoke and have high calorific value with fast rotation period. This will ensure fuelwood availability and offer better prices to the harvesters, as such species command high prices in the market.

There is paucity or near unavailability of literature on the market structure and the influence of the hedonic attributes on different quartile prices of fuelwood; the result of this study provides the foundational springboard for future studies on fuelwood marketing.

The purpose of this study is to examine the net effect of golf courses’ proximity on home sale prices in Kern County, California.

A spatial Durbin error model is used with sales price data for 1,693 homes sold in Kern County in the third quarter of 2018. This paper compares 90 different spatial econometric models using Bayesian techniques to produce posterior model probabilities which guided model selection and the number of neighbors to use.

The results show that significant spatial dependence exists in home values in Kern County. Point estimates indicate that homes abutting golf courses are valued at less than those which are not. This study also finds that the farther away from golf courses the average home is, the higher its value.

This study contributes to the existing literature in three dimensions. First, this paper analyzes whether proximity to golf courses impacts home values in Kern County where a study of this nature has not been conducted. Second, the analysis uses transaction data for 2018 which was a period when the sport’s popularity was fading and golf courses closing. Third, Bayesian model comparison techniques are used to select the appropriate model.

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.

This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain.

This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach.

Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase.

Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize.

This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.