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location'sdemandandthepurchasers'affordabilitydeterminetheproperty'soptimalvalue.To meet this optimal price the facilities in the properties are arranged through house sorting. Before sorting, it is important to find the significant facilities that contribute to the property value. The previous works mostly through qualitative assessment have identified the important factors influencing residential property value. The current article aims to determine the significant property facilities that are contributing to its value using statistical techniques. The facilities of a residential property considered in this study are Total Area, Age, Maintenance Cost, Number of bedrooms, Number of Toilet, Number of Balconies, facing of the property, Furnishing, Availability of Power Backup, Security, Elevator, Parking facilities. Data needed for the study were collected through a ground survey and interviews with the owners and real estate agents in the Greater Hyderabad Municipal Corporation (GHMC) Region. A total of 202 residential apartments that are yet to be sold were considered for the model development and 32 sold-out properties were obtained to validate the models. The significant facilities are identified using the p-test and the Group Methods of Data Handling- Neural Network (GMDH-NN) and linear regression techniques are adopted to develop the models for all possible combinations of the most significant factors. The accuracy of the developed models is assessed using R2 and Root Mean Square Error (RMSE) and Mean Average Percentage Error (MAPE). The study's findings indicate that the total area of the Residential apartment and the maintenance cost are the most significant factors. Both GMDH-NN and linear regression models developed using these factors show that the consideration of the Total area alone as a variable for prediction of property value has R2 > 0.748 and the RMSE and MAPE being less than 30%. The accuracy of prediction for the validation datasets using the Total area of the property as an input variable is more than 70% for both models. Identifying the significant factors using statistical techniques and then developing the models using these factors is the novelty of the research. the proposed models in the article can be used directly to understand the preferred facilities in Residential properties in the GHMC region and the adopted framework can be used for property valuation in general for any region

There is public perception that agricultural property value in Alberta is negatively affected by abandoned but unreclaimed oil and gas well sites. This exploratory research examines whether a difference in property values exists between those with reclaimed well sites and properties with abandoned but unreclaimed well sites (i.e., reclamation status). A total of 485 property transfer records from the provincial registry and oil and gas well information from an industry database were used in the research. Stepwise, sequential-search regression was applied to derive an optimized set of potential factors and covariates to predict per-acre agricultural property value. Property sale date, residential density, and agricultural land capability class were the covariates. Property location, well type, and reclamation status were the factors. The data analysis did not support the public perception about reclamation status but did confirm property location and the listed covariates as significant predictors of agricultural property value in Alberta.

Over the past several decades, the rapid growth of Southwestern United States desert cities is creating significant climate and water scarcity challenges. City planners are using green infrastructure to mitigate these challenges and develop more livable, sustainable, and resilient communities. This study uses hedonic pricing modeling (HPM) to evaluate how constructed wastewater wetlands impact home values integrated into the project design. It compares Crystal Gardens in Avondale, AZ, consisting of 14 engineered wastewater filtering ponds, to nearby neighborhoods with desert landscaping. HPM revealed higher values for Crystal Gardens homes overall (7%) and significant increases for homes on the ponds (14%). Results demonstrate the economic value of integrating water-related infrastructure in desert cities for home sales. For a more accurate benefit assessment, additional research is needed on how the ecosystem services provided by these constructed wetlands contribute to greater property values.

The rapid expansion and urbanization of Lagos state of Nigeria due to uncontrolled rural - urban migration seems to have succeeded in transforming the peri-urban areas of Ota, Ogun state into a mini economic hub, thus propelling property values skywards. The present study ascertains if passing rents, as well as sales value for the various apartments in Canaan city estate as charged by the project developer, is overpriced, and underpriced or fair-priced. The rental data collected from the residents of the estate were compared with rental opinion obtained from practicing estate surveyors and valuers in Ogun State. 240 questionnaires were administered to residents of the estate while 22 questionnaires were administered to registered estate surveying and valuation firms. Interviews and questionnaires were deployed to solicit data from the Physical Planning Department (PPD) being the managers of the estate. The retrieved data were then collated and presented using figures and Tables. Findings showed that the passing rents for all cadres of residential apartments in the estate were discounted with the most discounted apartment type being the 2-bedroom luxury flats and the least discounted apartment type being the 4-bedroom semi-detached houses. For sales value, findings showed that the high end apartments – the detached houses, semi-detached and also the 3-bedroom terrace houses were hugely discounted. Unfortunately, the 1-bedroom and 2-bedroom flats were the least discounted while the 2-bedroom luxury flats and 3-bedroom flats were either within range or slightly overpriced. The study concluded that the passing rents were underpriced due to the income nature of tenants and subsequently, the sales value proposed by the developer of the estate was underpriced. The study recommended an upward review of sales prices should the estate proprietor still continue with the sales of its apartment within Canaan city.

Community support for public transit could come more easily if transit systems demonstrate positive fiscal impacts beyond those achieved through fare box returns. Transit systems have the potential to generate additional public revenues through catalyzing development around transit stations, yielding increased property values and property taxes. This paper provides an assessment of the property value changes and development impacts that have occurred around the SunRail commuter rail system since the locations of the stations were announced in 2007. We estimate tax revenue impacts resulting from property value changes around each station. The findings show that tax revenue impacts have been highly variable across the system, with some stations having experienced modest to substantial value increases, while others have remained stagnant. However, SunRail stations generally outperformed their control areas that were identified as part of this study. SunRail investments appear to have catalyzed new development around stations and yielded measurable (re)development benefits in the form of property tax increases from new transit-oriented developments.

Determining the impact of individual attributes on the value or price of real estate in business practice poses many problems. One of the solutions to this problem is the use of statistical methods. The article proposes correlation coefficients (and their partial modifications) that can be used to determine the impact of selected features on the value of real estate. In addition, several procedures were taken into account for the factors in further calculations, using different methods for determining weights. Empirical verification of the proposed solutions was based on the mass valuation of land properties. The obtained results were compared with valuations developed by property appraisers and valuation errors were calculated. Based on valuation errors, the proposed methods of calculation procedures were ranged, indicating those which provide results closest to the individual valuations carried out by property appraisers.

The hedonic property-value model has been refined over more than forty years to become one of the premier approaches to valuing environmental amenities. This article presents best practices...

This study explored the changes in housing values before-and-after the several stages of transit investments of SunRail stations in Orlando, FL by using a pre-post and intervention-control design. ...

The subject of the considerations presented in the article is the question of the criteria according to which the comparables, in the market value estimating process, should be selected. As the most important in the selection of comparative properties, the factor of similarity in relation to the subject property (measured by the Euclidean distance) was considered. As the key issue, the similarity assessment criterion and the influence of the adopted critical value of this criterion on the accuracy of estimates were chosen. The analysis of the above was carried out with taking into account the role of the significance of independent variables (measured by their correlation with the vector of the dependent variable). The results of the simulation tests carried out in the variants set by the criteria adopted were presented. On this basis, it has been shown that there is a potential most relevant solution in the collection of obtainable estimation results. This solution corresponds with the smallest sum of the differences of model prices (accepted as known) and corresponding estimates. The found minimum occurs for a specific layout of the above criterion values only.

While significant existing scholarship has confirmed that accessibility to “macro” transportation systems, such as transit, creates some value for real estate, few studies have examined the capitalized effect of “micro” transportation modes on property values. Even, despite the increased ridership and market shares of carsharing and bikesharing services, empirical evidence on its property value capitalization effects of the emerging transportation services remains far less limited. In this context, this research examines the residential value uplift induced from the proximity to carsharing (Zipcar) and bikesharing (CitiBike) services in New York City by employing Spatial Durbin Models with sales transaction data that are reported in the New York City Department of Finance in 2018. The results indicate that all else equal, single-family housing near CitiBike station sold at higher prices; a 10 percent decrease in distance was associated with a 4.1 percent increase in its value. The proximity to Zipcar and CitiBike services were positively valued in the multi-family housing market. Specifically, a 10 percent decrease in distance was associated with a 1.1 and 3.5 percent increase in the value of the housing, respectively.

One of the persistent environmental issues today is high noise levels in residential areas especially in the developing countries. There are several unorganized informal sector activities such as recreational, road traffic, household and religious activities, operation of power generating sets, incompatible uses in space among others that are the sources of noise pollution in residential areas. A number of empirical studies have been carried out on the impact of noise on residential property values. However, one finds it very difficult to ascertain whether noise pollution affects residential property value in Enugu Urban. The aim of this study is to ascertain whether noise pollution has significant influence on residential rental values in the study area. The study has discovered that residential properties affected by noise pollution have lower rental value compared to those unaffected by 3.1% of its rental value. The study has provided some insight to guide property buyers or users, investors, property managers, and valuers as regards property transactions. The study has suggested that property value spatial index of noise pollution in the study area can be built and use as a guide for urban management strategy to achieve sustainable development.

The monetary value of a given piece of real estate, a parcel, is often readily available from a geographic information system. However, for many applications, such as insurance and urban planning, it is useful to have estimates of property value at much higher spatial resolutions. We propose a method to estimate the distribution over property value at the pixel level from remote sensing imagery. We evaluate on a real-world dataset of a major urban area. Our results show that the proposed approaches are capable of generating fine-level estimates of property values, significantly improving upon a diverse collection of baseline approaches., Comment: 4 pages, 1 figure, Accepted to IGARSS 2023

In this study, we develop and apply a new methodology for obtaining accurate and equitable property value assessments. This methodology adds a time dimension to the Geographically Weighted Regressions (GWR) framework, which we call Time-Geographically Weighted Regressions (TGWR). That is, when generating assessed values, we consider sales that are close in time and space to the designated unit. We think this is an important improvement of GWR since this increases the number of comparable sales that can be used to generate assessed values. Furthermore, it is likely that units that sold at an earlier time but are spatially near the designated unit are likely to be closer in value than units that are sold at a similar time but farther away geographically. This is because location is such an important determinant of house value. We apply this new methodology to sales data for residential properties in 50 municipalities in Connecticut for 1994–2013 and 145 municipalities in Massachusetts for 1987–2012. This allows us to compare results over a long time period and across municipalities in two states. We find that TGWR performs better than OLS with fixed effects and leads to less regressive assessed values than OLS. In many cases, TGWR performs better than GWR that ignores the time dimension. In at least one specification, several suburban and rural towns meet the IAAO Coefficient of Dispersion cutoffs for acceptable accuracy.

Increases in land value, known as value uplift, follow from improvements in accessibility arising from new transport infrastructure. This paper investigates how different approaches in evaluating property value uplift could lead to different results. The case study of the light rail transit system in the Gold Coast, Queensland, Australia, is the context for this study. This paper addresses two of the critical aspects of the value uplift literature—how many of the results are determined by the method adopted and, perhaps more importantly, if there is a method which provides the best results. Historical data on private property sales are used to evaluate the timing, shape, and conditions for increases in land value or value uplift employing two of the most widely used modeling approaches: difference-in-differences and multilevel regression models. The more recent literature has also identified that the choice of control area is pertinent and so this study uses two different approaches for the selection of catchment areas: conventional distance-based methods and propensity score matching. The model results do confirm the increases in property prices because of better accessibility to Gold Coast light rail transit, but the amount of uplift does appear to depend both on the model approach and the method to select catchment and control areas. The paper discusses the implications of this for literature which has a variety of different methods established for research.

Magistritöö Geodeesia, kinnisvara- ja maakorralduse õppekaval Linnastumine ja kvaliteetne linnakeskkond on seotud rohevõrgustiku erinevate funktsioonidega. Magistritöös koostati ülevaade varasematest uuringutest, mis käsitlevad rohevõrgustiku mõju kinnisvara hinnale ning uuringutest, mida on Tallinna kinnisvara hinna kohta varasemalt uuritud. Statistiline analüüs rohevõrgustiku mõjust korterite hindadele tehti Tallinna näitel. Uurimistöö eesmärk oli selgitada, kas rohevõrgustik mõjutab kinnisvara väärtust ehk hinda. Töös vaadeldi Tallinna linnas korteriomanditega 2013 ̶2023 aastal tehtud tehinguid (kokku 92 389) ning loodi illustratiivseid jooniseid geograafilise infosüsteemi (GIS) tarkvara abil. Töös kasutati avalikult kättesaadavaid andmeid. Töö kasutati Maa-ameti geoportaali kaudu kättesaadavaid Eesti topograafia andmekogu (ETAK) andmeid ja Tallinna linnalt saadud shp-formaadis olevaid administratiivseid piire. Lisaks kasutati töös Tallinna Keskkonna- ja kommunaalametilt kättesaadavaid kaardikihte Tallinna haljas- ja rohealadest. Andmeid analüüsiti programmidega ArcGIS Pro ja MS Excel. Varasemate uuringute analüüsile tuginedes saab järeldada, et rohevõrgustikul on positiivne mõju kinnisvara väärtusele. Tallinnas kõige kõrgema keskmise ruutmeetrihinnaga korterid asuvad enamasti kesklinna linnaosas aga varieeruvust on palju ka teiste linnaosade ja asumite vahel. Lisaks mere äärsed alad omavad kõrgemaa ruutmeetrihinna. Tallinna linnaosade pindalad ning linnaosade rohealade osakaal üldisest pindalast on väga erinevad. Tulemustele tuginedes on näha, et rohealade osatähtsus on asumite vahel ebaühtlaselt jaotunud. Nii korrelatsioon- kui ka regressioonanalüüsi tulemusena leiti, et mingi korrelatsioon on olemas korterite keskmise ruutmeetrihinna ja rohealade vahel, aga avalikult kättesaadavate andmete põhjalt seda ei ole võimalik välja tuua. Urbanization and high-quality urban environment are related to many functions of the green network. Master’s thesis contains an overview of previous studies dealing with the impact of the green network and how it affects price level of real estate in Tallinn. A statistical analysis of the impact of the green network on apartment prices was made using the example of Tallinn. The purpose of the research was to find out does the green network affects the value of real estate. The study was focused on apartment transactions in the city of Tallinn from the year 2013 to 2023 (a total sales of 92 389). Illustrative drawings were made with geographic information system (GIS) software. The work was rendered with publicly available data. Data from digital boundaries of Geoportal of the Estonian Land Board Acency and the map layers shp-formats from the city of Tallinn were used as source to build the analysis. Data were analyzed with ArcGIS Pro and MS Excel. Based on previous studies, the green network has a positive effect on the property value. Apartments with the high average price per square meter in Tallinn are usually located in the city center, but there is a lot of variation between other city districts and settlements. Areas by the sea also have a higher price per square meter. The size and green shares of the Tallinn's districts varies. Based on the results, it can be seen that the importance of green areas is unevenly distributed between settlements. As a result of the correlation and regression analysis, there is some correlation between the apartment average price per square meter and the green areas, but it’s not possible to point it out based on publicly available data.

Does the proximity of transit increase property values, and can one example apply to another? Using a spatial and temporal hedonic price framework, a study of light rail transit’s impact on residential property values compares the station area property impacts of the Green and Blue lines in Saint Paul and Minneapolis. The study also points to when “value transfer” (used here to describe the comparison and application of property value impacts near transit) is appropriate, and what practitioners should keep in mind to maximize the effectiveness of the exercise. In the case of value transfer for transit, the study finds that intimate local knowledge matters more than special modeling specifications to appropriately capture the impacted properties and transfer the return of investment.

This research offers a view on how COVID-19 is affecting residential property value of Metro Seattle area. Data on residential property transactions in specific counties are collected. The research also documents the change of mortgage rates and number of work-from-home employee as well as gross domestic product change due to the COVID-19. The findings imply that for King County, which is usually considered as urban Seattle area, property values increases sharply during the pandemic as the mortgage rates change caused by COVID-19.

Aggregate resources are essential for road and building construction. In 2019, the US domestic production reached 1.53 billion tons of crushed stone valued at $18.7 billion produced by an estimated 1,430 companies operating 3,440 quarries, according to the U.S. Geological Survey (USGS) Mineral Commodity Summaries. But, it is also recognized that a quarry blasting below the water table is one of the most noxious, toxic and destructive uses of land, with no reasonable prospect of post-extraction-rehabilitation. If permitted and established in the wrong geographic location, a blasting quarry operation can result in significant deleterious impacts on the environment and local inhabitants and can disrupt short and long-term land use planning objectives. Because a quarry can remain operational for 100+ years, impacting five or more generations; quarries have the potential to cause permanent environmental degradation, destabilize communities, damage, sterilize or diminish the use and enjoyment of residential and non-residential properties, and reduce property values. Blasting is the preferred method of extracting rock in a quarry operation, the consequences of which can lead to environmental and property damage, and to injury or death of human and non-human life. In North America, licensing and operational oversight of a pit or quarry are primarily controlled by the individual states, territories and provinces, and address matters of compliance, while issues related to land use planning and zoning are entirely within the jurisdiction of the local municipalities, counties or regions. Accordingly, this research paper seeks to inform land use planners of the importance of protecting the environment and its inhabitants from the adverse effects, including the diminution in property values, associated with aggregate extraction operations generally and blasting quarries specifically, through the use of permanent onsite setbacks and offsite separation distances to avoid land use incompatibility and sensitive land uses.

The choice of the state to develop the digital economy opens up new directions in the field of information technologies and in general, in the field of electronic document circulation. The turn to "digital technologies" was caused by the development of the global Internet network and quality communication.

The relationship between the street environment and the health, education, mobility, and criminal behaviors of its citizens has long been investigated by economists, sociologists and urban planners. Home buyers were found to pay a premium for better street appearance. Prior studies considering streetscapes mainly focus on objective measures such as the number of nearby trees, the tree canopy area, or the view index of physical features such as greenery, sky or building. However, subjective perceptions may have complex or subtle relationships to physical features, individual physical features or simply summing them up do not capture people’s comprehensive perception. In contrast, this study proposed a new approach for the urban-scale application to quantify both subjectively and objectively measured streetscape scores for six important perception qualities, namely Greenness, Walkability, Safety, Imageability, Enclosure, and Complexity. Built on prior quantitative studies in urban design quality and emerging applications in deep learning and open source street view imagery for urban perceptions, we integrated existing frameworks to (1) effectively collect and evaluate both subjectively and objectively- measured perceptions; (2) investigate the coherence and divergence in ML-predicted subjective scores and formula-derived objective scores; and (3) compare their effects in affecting house prices taking Shanghai as a case study using a large-scale dataset on home transactions. The results implied: first, the percentage increase in sales price attributable to street scores is significant for both subjective and objective measurements. In general subjective scores explained more variance over structural attributes and objective scores in hedonic price model. Particularly, objective Greenness, subjective Safety and Imageability scores positively affected house prices. Second, for Greenness and Imageability scores, the subjective and objective measures exhibited opposite signs in affecting house prices, which implied that there might be mechanisms related to the psychological, social-demographical characteristics of street users that have not been fully incorporated by objective measures that taking view indices or recombination of them. In addition, certain objective measure might outperform subjective counterpart when the connotation of the perception is self-evident and not complicated, for example the Greenness. For those concepts were not familiar to the average person, subjective framework exhibits better performance. This is the first study comprehensively expanding hedonic price method with both subjectively and objectively measured streetscape qualities. It suggested that city authorities could levy a street environment tax to compensate the public budget invested in street environment where developers secured benefits from a price premium. This study enriches our understanding of the economic values of the subjective and objective measures street qualities. It sheds light on promising future study areas where the coherence and divergence of the two measurements should be further stressed.

Spatial planning is of a particular importance to the community given that it brings order to the coexistence of people within certain territory and enables protection of significant public interests. International agreements, constitutions and various acts entitle state and local authorities to determine, through various spatial plans, under what conditions and in which way public spaces and privately owned property can be used. This further implies that spatial plans may limit ownership entitlements. From the owner's perspective, effects of state intervention in such cases may prove to be positive. For instance, transformation of agricultural land of an insufficient quality in urban building land could lead to the increase of a lot's market price. Nevertheless, there are some situations in which spatial plans may cause decrease of immovable property value. This, for example, will happen in case when authorities decide that a highway will be built near a peaceful housing block in the suburb. Contemporary legal systems widely acknowledge that public interest supersedes the private one, and that ownership right could be limited and even taken away if that appears necessary for the sake of fulfilling justified and important community's needs. In case of expropriation, owner is entitled to the so-called fair remuneration. However, when it comes to the decrease of immovable property value due to the changes of spatial plans, numerous questions and disagreements exist. In one decision of the European Court of Human Rights that dealt with the issue of spatial planning (Sporrong and Lönnroth v Sweden), an opinion has been expressed that spatial planning must be devised in such a way so as to strike a balance between community interests and those of private owners. That gave birth to the fair balance doctrine. In the meantime, it was also incorporated in the regulation of the Republic of Serbia. Planning and Construction Act provides that a competent authority which changes conditions making an integral part of the issued location conditions, shall be liable for the damage caused to the investor provided that he already undertook some activities pursuant to the primarily issued location conditions. This solution was undoubtedly adopted under the pressure of foreign investments. However, it could also improve a position of other persons suffering damage due to the changes of spatial plans and documents connected to them.

Property condition has a significant influence on property value, yet is not a widely used variable in pricing models. Using approximately 322,433 residential sales from over 1,300 different U.S. c...

This study aims to predict the prices of residential properties in Catonsville, MD based on publicly available tax assessment data maintained by Maryland government institutions. Recent legislation in Maryland has made it a requirement for local governments to provide up-to-date, easily accessible data to its constituents. This study used three regression techniques: Linear, Ridge, and Lasso regression. Extracting over 11,000 property records from Maryland’s Open Data Portal (ODP), we applied regression techniques to predict the price. We used various independent features to predict the price of residential properties including prior year housing sales price, size of house, house age, street address type (single family or townhouse), if the house has a basement, dwelling type, number of stories, and dwelling grade (scale from 1 to 6). Outperforming Lasso and Ridge regression, Linear regression can enhance the predictability of housing prices and significantly contribute to the correct evaluation of real estate price using only two years of historical data and without additional socioeconomic variables. We also found that among others; prior year housing sales price (positive), size of house (negative), and house age (positive) are the most significant factors in predicting housing sales price in Catonsville, MD.

Theorists have traditionally considered the effects of single rather than multiple landscape attributes on property prices, and ignored the interaction between landscape-specific housing attributes. The aim of this paper is to analyze the hedonic attributes of property prices and compare the effects on property prices of two key landscape attributes. Seventeen hedonic attributes are used to build a hedonic-pricing model with five dimensions: structure, neighborhood and community, location, environment, and time. A sample of 688 valid houses within 1,000 m of Xiangshan Park in the city of Zhuhai, China is collected. The selected hedonic attributes are found to have significant effects on property prices, explaining around 91% of the observed variation in price. Proximity to the sea has a greater positive influence on property prices than proximity to parks. In addition, people prefer to buy properties with sea views than to live close to the sea.

Bikesharing (BSS) is an emerging alternative mode of transportation with various benefits, such as reducing reliance on single-occupancy automobiles, boosting public health, lowering pollution levels, and enhancing accessibility. Accordingly, proximity to BSS stations can be factored into residential property values. Thus, this research attempts to explore whether (1) proximity to BSS was positively associated with residential property prices in Portland, Oregon, (2) proximity to BSS and public transportation modes showed synergistic effects on the values, and (3) the magnitude of the BSS premium intensified over time. The findings of spatial hedonic models indicate (1) a premium for proximity to BSS in both single-family and multi-family housing markets with varying magnitudes, (2) synergetic effects between BSS and public transportation modes, including light rail transit, streetcar, and bus, and (3) an unchanged premium for BSS between 2016 and 2019 with a few exceptions. The findings expand discussions around transportation-induced property value premium and offer policy implications.

This paper proposes an open-domain method for automatically annotating modifier constituents (20th-century') within Wikipedia categories (20th-century male writers) with properties (date of birth). The annotations offer a semantically-anchored understanding of the role of the constituents in defining the underlying meaning of the categories. In experiments over an evaluation set of Wikipedia categories, the proposed method annotates constituent modifiers as semantically-anchored properties, rather than as mere strings in a previous method. It does so at a better trade-off between precision and recall.

In order to determine the impact of transportation and walkability as one of the important smart growth principles in creating economic value, this study examines the impact of transportation and walkability on Residential Property Value in Shah Alam, Selangor, Malaysia neighborhoods. Based on secondary data collected on Brickz.com, a hedonic regression model was constructed to estimate median Residential Property Value in Shah Alam, Selangor for the Residential Property Value assessment. The model's findings demonstrate that transportation and walkability factors have less impact on estimated Residential Property Value than other residential structure characteristics such as number of floors, number of bedrooms, and land area. Only three variables from the Structure Characteristic were statistically significant in this study: Structure Characteristic no of the floor, Structure Characteristic No of the Bedroom and Structure Characteristic Land Area. Consequently, all transportation and walkability are insignificant towards residential house prices. This shows that there are still ways to increase house prices through attractive house structure planning. With this, the formation of an attractive house structure in development planning is an important aspect in increasing the demand for house prices while rising house prices efficiently. The adoption of the appropriate use of public transport uses the principle of good growth to achieve added value and improve the overall quality of life in the neighborhood.

The lack of consensus in the literature on wind turbines and property values suggests that factors such as attitudes toward wind energy may influence whether turbines will impact property values. Based on identified attitudes at the municipality level in the Canadian province of Ontario, this study compares impacts on property values, estimated using a difference-in-differences hedonic approach, between municipalities that oppose wind energy development and those that have not expressed opposition. The results indicate that wind turbines have negatively impacted property values in “unwilling host” municipalities, while no significant impacts are found in unopposed municipalities.

Real Estate is an asset that provides profitable investment in return. Commercial property constitutes an important part of the real estate sector. In valuing commercial property, rental value is an essential component for valuers in applying valuation methods. Determining the rental value usually a difficult process as it involves a lot of influence factors. There are various factors that can be used but not the same for every commercial property. Therefore, this paper shows the modeling valuation comparison between two commercial property areas of Putatan and Limbang that represent the outskirts of the city in Sabah and Sarawak respectively. The purpose of this study is to find an effective approach to develop a suitable model for commercial property valuation using OLS and subsequently intends to identify factors that influence the commercial properties for both study areas. The OLS technique was used for this study to develop the property valuation model in Putatan and Limbang. The outcome shows that both study areas can be modeled using OLS for property valuation using similar factors but the Limbang area produced higher accuracy than Putatan based on the adjusted R2 value. However, in terms of the significant of the property value influence factors, both Limbang and Putatan produced different significant factors. Thus, it shows that most of the outskirt city commercial property valuation must be modeled using different influence factors. The model will benefit the local authorities, especially for commercial property valuation. Ultimately, revaluation also can be done easily with low cost, less time and few people needed for this approach.

Deprivation is a major risk to population health, in particular when experienced during childhood. Poor health in the early years accumulates and is expressed in adult health inequalities. Policy makers may aim to mitigate against the ill effects of deprivation by trying to increase social mobility and facilitating moves towards better earnings and living conditions or by protecting against the effects of downward moves and the experience of deprivation. This paper uses address change and property value data at the individual and family level to examine whether poor health outcomes occur more frequently among people who move between addresses and particularly those who move to properties with lower property values. We use the Northern Ireland Longitudinal Study, linking health and demographic data from 2001 and 2011 Censuses to house valuations for a representative 28% of the population aged 10–64 years (N = 342,681). Young persons (aged 10–15 years) living in a house valued at over £160,000 were half as likely to be reported as having mental ill health as those living in a house valued under £75,000 (OR = 0.49, CI: 0.31–0.78). There was no strong evidence that upward or downward mobility affected mental health or physical health for young people, but ill health of working aged persons showed a strong association with moving to houses of lower value. Results are discussed in terms of their implications for understanding the dynamics of social mobility and health and in terms of how various policies towards poverty may influence population health.

The effects of poverty on important outcome measures are devastating and well documented, but the conceptualization and operationalization of socioeconomic status (SES) are underdeveloped. Various indicators of SES are useful for different purposes. Free or reduced-price lunch (FRL) status is commonly used because of its convenience and predictive strength, but it has many limitations. This study explored property value as a convenient alternative or complement to FRL status. The conceptual alignment of property value with SES was compared with that of traditional indicators like parent income, education, and occupation. Empirically, hierarchical linear modeling and regression analyses were conducted to evaluate the effects of property value on math achievement in comparison with and in conjunction with FRL status. Property value is strongly related to Math achievement, and it complements conceptual and methodological flaws of FRL status by providing nuance at the local level and encompassing aspects of human and social capital.

The property value assessment in the real estate market still remains as a challenges due to incomplete and insufficient information, as well as the lack of efficient algorithms. House attributes, such as size and number of bedrooms, are currently being employed to perform the estimation by professional appraisers and researchers. Numerous algorithms have been proposed; however, a better assessment performance is still expected by the market. Nowadays, there are more available relevant data from various sources in urban areas, which have a potential impact on the house value. In this paper, we propose to fuse urban data, i.e., metadata and imagery data, with house attributes to unveil the market value of the property in Philadelphia. Specifically, two deep neural networks, i.e., metadata fusion network and image appraiser, are proposed to extract the representations, i.e., expected levels, from metadata and street-view images, respectively. A boosted regression tree (BRT) is adapted to estimate the market values of houses with the fused metadata and expected levels. The experimental results with the data collected from the city of Philadelphia demonstrate the effectiveness of the proposed model. The research presented in this paper also provides the real estate industry a new reference to the property value assessment with the data fusion methodology.

The effect of flooding on land property value is a major concern of all landowners. Numerous studies have already discussed the risk of potential decline in the value of land property situated in flood-prone areas; however, those that focused on the impact of flooding on land property in Malaysia are still limited. This chapter investigates the effect of flood on the value of agricultural and industrial land properties in Peninsular Malaysia. This chapter’s results suggest that a metre increase in flood depth significantly decreases land property value by 44.6%. This result helps policymakers in designing and developing the policies of land property development that would minimize land property devaluation due to flood depth and help landowners in understanding the effect of flood on land property values.

The concern of climate change and Greenhouse Gas emission have increased national consideration toward energy efficiency. Despite noticeable action which have taken by EU cities and Sweden government to mitigate the climate change, there is still shortage in appropriate energy measurements in old residential buildings. Due to the fact that a large share of residential buildings in Sweden have constructed more than 40 years ago, most of them need energy renovation to enhance efficiency and saving more energy. In order to encourage home owners toward energy efficiency renovations, some cost effective measurements have to introduce to people with the view of effect on property value. To this end, 50 detached houses and villas in Kronoberg County in Sweden have been chosen and analyzed to identify how renovation can increase the property value. These houses have been set in different categories by location, heating system, deep renovation, energy and aesthetic renovation. After that, compares the sold prices and biding prices for each category. Moreover, it analyses the people behavior toward renovation to see how can motive people to adopt necessary energy efficient renovation. This research also shows the current situation of building renovation, the most favourite renovation which are adopted by people as well as providing information about the factors affect the value of the house after renovation.

The art and science of determining residential property value has evolved due to the changing external factors, such as the economy, environmental (climate change) and social aspects. This research aims to identify the impact of climate change (floods) to determine residential economic attributes that could affect the value for residential property in flood risk areas. The case study covers all residential housing schemes in Langat River Basin area, which has been considered as the highest flood risk area in the State of Selangor, Malaysia. The methodology of this research is based on the conceptual analysis from previous studies from local and international scenarios. The systematic analysis of previous literature of real estate valuation theory consists of economic attributes such as structural, locational and environmental attributes involved in residential property valuation in relation to flooding. The findings reveal that the economic attributes' response to flood hazards for residential properties can be divided into three conditions, and they are: positive, negative or no effect on the climate change factor.

Using home sales data for 10 years and four sites in Maine (USA), we estimate marginal willingness to pay (WTP) for river proximity and present a criterion-validity test of the use of benefit transfer. Given the degraded state of Maine's waterways (partly due to damming of rivers for commerce), we find positive, concave relationships between housing values and river distance. We find statistically different estimates of marginal WTP across the four markets, but results from the same watershed are more similar. Also, we find mean WTP is diminishing with average river distance, which is consistent with the empirical functional form. Comparing original and benefit transfer estimates, we find errors range from 29% to over 1000%, growing with spatial distance between the study and transfer sites. Lastly, we estimate a difference-in-difference model for the single market that has witnessed dam removal, and we apply the results to the other markets (that could undergo dam removal as well). While informative, our results suggest caution in the use of benefit transfer in applications of hedonic property price analysis.

Bangkok suffered from the world’s worst traffic congestion in the 1990s due to rapidly increasing car ownership, reflecting the economic growth and road-dependent transport policy beginning in the 1960s. Due to its monocentric but scattered urban structure, traffic congestion is severe, causing tremendous economic loss, deteriorating air quality, and badly affecting the quality of life. A historical review reveals that the urban and transport plan and development were not efficiently coordinated, resulting in unorganized suburbanization and progressively more severe traffic congestion. It is important to reveal the impact of the transportation project on the housing market in order to incorporate the policies for transportation and urban development. To define the impact, the OLS hedonic price model and the local multiscale geographically weighted regression (MGWR) model were estimated, along with the condominium sales data. The results revealed that the impact of rail transit on a rise in property value significantly varied across the study area. It was estimated that, for the area along the major rail transit corridor in the city center, a premium of a location 100-m closer to the station would be more than 200 USD per square meter. At the same time, the value would be less than 80 USD for the area along the rail corridor in the suburb. These findings provide policy insights for future urban and railway development, including the proper coordination of rail transit development and urban development with subcenters, transit-oriented development, and improved pedestrian flow around transit stations.