Real Estate Values Research Articles

Total Least Squares Estimation in Hedonic House Price Models

In real estate valuation using the Hedonic Price Model (HPM) estimated via Ordinary Least Squares (OLS) regression, subjectivity and measurement errors in the independent variables violate the Gauss–Markov theorem assumption of a non-random coefficient matrix, leading to biased parameter estimates and incorrect precision assessments. In this contribution, the Errors-in-Variables model equipped with Total Least Squares (TLS) estimation is proposed to address these issues. It fully considers random errors in both dependent and independent variables. An iterative algorithm is provided, and posterior accuracy estimates are provided to validate its effectiveness. Monte Carlo simulations demonstrate that TLS provides more accurate solutions than OLS, significantly improving the root mean square error by over 70%. Empirical experiments on datasets from Boston and Wuhan further confirm the superior performance of TLS, which consistently yields a higher coefficient of determination and a lower posterior variance factor, which shows its more substantial explanatory power for the data. Moreover, TLS shows comparable or slightly superior performance in terms of prediction accuracy. These results make it a compelling and practical method to enhance the HPM.

The equity implications of TOD in Curitiba

Transit Oriented Development (TOD) projects are being increasingly adopted worldwide as a way to promote the coordination between transport and land-use planning. However, little attention has been given to how TOD projects are associated with socioeconomic and spatial inequalities and its effects on people’s access to economic activities and public services, particularly in the Global South. In this paper we analyze how socio-spatial inequalities have been shaped by transport and land-use planning in Curitiba (Brazil), a city internationally recognized for its TOD planning based on Bus Rapid Transit (BRT). We examine how the spatial organization of the BRT system is associated with the distribution of population densities, socioeconomic groups, and real-estate values and its implications in terms of inequalities of access to employment opportunities and health services. The results show that Curitiba's TOD has had limited influence on population densities, but contributed for the unequal distribution of its benefits, privileging high-income classes and premium real-estate along its main BRT corridors. These effects contribute to push low-income communities to peripheral urban areas with limited accessibility benefits from the transit system. Our findings suggest that Curitiba’s success story should be seen as a cautionary tale about the consequences of TOD planning, which perpetuate the spatial concentration of resources and reinforce inequalities of access to opportunities. The broader lesson of this study is that TOD planning must be constantly evaluated by its socials and environmental impacts, and be guided by mixed housing, and social inclusion to avoid potential consequences in terms of segregation and peripheralization of poorer communities.

Macro-financial imbalances and cyclical systemic risk dynamics: understanding the factors driving the financial cycle in the presence of non-linearities

Abstract This paper develops a multivariate filter based on an unobserved component model to estimate the financial cycle. Our model features: (1) a dynamic relationship between the financial cycle and key variables; (2) time-varying shock volatility for trend and cycle components. We demonstrate that our approach not only exhibits superior early warning properties for banking crises but also outperforms commonly used indicators in terms of data fit for decomposition exercises, as evidenced by the higher marginal likelihood. We document three important properties of the financial cycle. First, the sensitivity of the financial cycle to changes in real estate valuations increased during the post-90s period. Second, the sensitivity of the cycle to changes in financial conditions displays volatility and country specificities. Finally, our reduced form estimates suggest that the banking crisis of 1988 was preceded by positive contributions from the risk appetite shock, while the primary source of vulnerabilities emanated from the housing market in the run-up to the Global Financial Crisis.

Organizational and administrative procedures for determining the damage and extent of damage to real property as a consequence of russian aggression

One of today's urgent needs is to provide compensation and indemnification to citizens of Ukraine for damage and destruction of specific categories of real estate objects caused by the military aggression of the Russian Federation. The state tries to protect the property rights of Ukrainians, guaranteeing them the right to compensation or compensation for destroyed or damaged property through national protection methods. In practice, we are still far from applying the procedure for obtaining compensation for damages. However, we must do everything today to record the relevant facts and prepare the necessary documents. Since war crimes do not have a statute of limitations, we are only at the beginning of the formation of practice in this direction. For this purpose, the theoretical principles were analyzed, and practical recommendations were given regarding organizational and management procedures for determining damage and real estate damage due to Russian aggression. Methodology. This research was conducted using an analytical method, which involved a comprehensive analysis of normative legal acts and Ukraine's institutional base. The focus was on the potential for creating a system to protect the property rights of individuals and legal entities in the aftermath of the Russian Federation's aggression. The research object was the legislators and normative-legal national and international documents pertaining to property rights protection. The research results show that in Ukraine, there are legal, institutional, and technical prerequisites for creating a system for calculating damaged and destroyed real estate caused by the Russian Federation's military actions. For the full functioning of the damage compensation system, the existing legislative and regulatory legal framework must be supplemented with legal acts that would allow the regulation in the legal field of the issue of institutional and technical provision of property rights, considering the international system of jurisdiction. Scientific novelty and practical significance. The main problematic tasks that must be solved to build and operate an effective reimbursement system of real estate value are defined. Considering that the solution to this problem is of international importance, the defined system of measures aims to improve the ways of solving this problem. Keywords: aggression, compensation, damages, compensation, property rights, regulatory acts, real estate.

Study of Influential Factors on Housing Prices by Using MLR

With the emergence of the 2019 pandemic, the global economy experienced a downturn, but the housing market quickly rebounded post-pandemic, heightening the anxiety surrounding home buying. Previous research predominantly employed regression models to forecast housing prices, but these studies largely focused on specific factors. Hence, this article aims to offer a more comprehensive viewpoint by exploring the impact of multiple independent variables on housing prices, particularly emphasizing the effects of the age of buildings, the surrounding environment, and architectural factors. The methodology used in this study is the Multiple Linear Regression (MLR) model. It analyzes the real estate market data in Taipei, meticulously constructing and validating multiple models. The findings reveal that the age of buildings and the distance to the nearest subway station negatively influence housing prices, whereas the number of convenience stores positively impacts them. Among these factors, the quantity of convenience stores exerts the most significant effect on housing prices. Overall, this article provides a novel perspective and tools for understanding and predicting housing prices, assisting real estate developers and buyers in making more informed decisions in the complex real estate market. This study highlights the multidimensional nature of real estate value and contributes to the sustainable development of the real estate market.

Переход от инвентаризационной стоимости объектов недвижимости к кадастровой при налогообложении недвижимости физических лиц: процесс и его последствия

Purpose: to consider the process of changing the calculation of taxation in Russia in recent years, its procedure and the consequences of changing the calculation of real estate tax. To show the need to change the introduced progressive scale of property tax for owners of residential facilities. To assess the possibility of changing the methods of calculating the base for taxation of individuals. Methods: analysis of the chronology of the establishment of taxes in the Russian Federation and the transition of recalculation of land tax in time. Comparison of tax calculation by inventory and cadastral values, property taxes in the Russian Federation. Results: the main reasons preventing the formation of an objective base for property taxation are identified: the insufficiency and unreliability of the information used, including at the initial stage of applying mass valuation of property as initial data and the imperfection of the developed methodology of cadastral valuation. Practical significance: historically, with the formation of states, a fiscal system was introduced. Taxation of real estate in modern Russia is regulated by a set of regulatory documents. Among the basic concepts of the field of taxation, the concept of the real estate tax base should be highlighted – the monetary expression of income from the sale of an immovable object. Thus, in recent years, changes have been made in the definition of the real estate tax base, which has a key impact on the formation of both the value and valuation of real estate and the formation of the fiscal policy itself in Russia. This article examines the process of changing the calculation of taxation in Russia in recent years, its procedure and the consequences of changing the calculation of real estate tax.

The phenomenon of stigmatization in the real estate market

Motivation: The following article covers the entire path of stigmatization, from that which directly affects a person to special cases of real estate stigmatization. Market participants have created many types of stigmatization that discredit a property. These range from the more abstract ones (e.g., paranormal phenomena taking place on a property or superstition) to the more serious ones (e.g., a restricted use area). The following article focuses on properties located in restricted use areas and the impact of this factor on property values. It analyzes court rulings by Polish courts on compensation in connection with the decrease in the value of real estate due to the establishment of a restricted use area.Aim: The main goal of the article is to identify the phenomenon of stigmatization in the real estate market, while the specific goal is to identify the phenomenon of stigmatization of real estate in restricted use areas around airports.Results: One of the main reasons why stigmatization occurs in the real estate market is ignorance and people’s fear of what they don’t know. The most common objects of stigmatization are restricted use areas around airports. However, in the court rulings described in the article, there is no consensus on whether stigmatization of real estate in itself affects the value of real estate.

Prediction of Economic Growth by Using Machine-Learning Algorithms through Sentiment Index Analysis in Economy of Pakistan

The neural network method's ability to mimic nonlinear communications without prior information is a major benefit for accurate function approximation. It differs from ARIMA and linear regression, which need linearity and may not work for all data sorts. Compared to (seasonal) ARIMA models, neural networks yield similar results. Neural networks also model and predict multivariate time series using causal and co-integration research. In contrast to the traditional economic forecasting approach, machine-learning techniques have prioritized precise forecasting without predetermined assumptions or conclusions. Owing to their enhanced predictive abilities and technological advancements, they provide more adaptability and have gained widespread acceptance in several fields. In terms of estimating US real estate values, machine-learning technology fared better than traditional econometric models, as shown. Total there were 131601 economic and financial news, which may include the phrases along with the names specified by the bank, and it may also include local media and mainstream. Machine learning uses the strength of data-driven algorithms and state-of-the-art computational techniques to improve decision-making in a range of industries. The findings of this research contribute to better forecasting practices and show how machine learning may provide more accurate forecasts in real-world scenarios.

물류센터 등급 제안을 위한 듀얼 인덱스 평가 모델

This study proposes a new grading model for distribution center(DC)s. For a particular DC, the proposed model considers input variables such as (1) three key factors including site, building, and facility; (2) individual declared land value; and (3) demand-supply balance of the region. Unlike most existing models, we do not consider the rental fee of DC because it is usually accompanied by extra benefits that are hardly open to the public. Since grading of a DC using single value is difficult due to the diverse nature of these variables. we propose a dual index model. The first index represents the relative quality grade (A, B, or C) of a DC. It is quantitatively determined by the values of the ten key variables that affect the value of a DC, multiplied by the weight factors obtained using AHP method, divided by the individual declared land value of the DC. The second index indicates the relative level of the floor area ratio of the region. For the investors, sites with higher floor area ratio are typically regarded as more attractive ones. This dual index model will help both lessors and lessees assess the real estate value of a DC intuitively. It can also be used as a tool for investors to determine the location and other characteristics of the DC to build. This model aims to contribute to the long term demand-supply balance of DCs in Seoul capital area, fostering stable growth of the logistics industry.

Leverage Strategies of Real Estate Investment Trusts and Real Estate Operating Companies

This paper employs empirical data in three major Asian real estate markets - Hong Kong, Japan, and Singapore, from 2001 to 2021, to study the leverage strategies of two related types of real estate companies – real estate investment trusts (REITs) and real estate operating companies (REOCs). The business model of the former must adhere to a real-estate-focused investment strategy while the latter undertakes a whole range of real estate development activities including land acquisition, financial feasibility analysis, construction, investment and asset management to redevelopment and disposal, and are not subject to the REIT rules with respect to tax transparency, earning distribution, real estate holding and leverage limit. We find that REOCs use 18.96% more debt than REITs after controlling for the agency and market risks, dividend yields, and property sector, country, and year fixed effects of firms; dividend payout has no effect on the leverage strategies; and high tax ratio increases the debt usage of REOCs relative to REITs. We also analyze the liquidation costs and business uniqueness effects. We find real estate value to total firm value ratio, as a proxy of liquidation cost, has negative effects on debt ratios for both real estate firms. Due to their uniqueness, REOCs with a high concentration of rental revenue stream are more vulnerable to liquidation risks, and thus more likely to have lower debt ratio. REITs however tend to have higher debt usage as rental incomes enhance cash-flow liquidity.

Wpływ pandemii COVID-19 na rynek wtórny nieruchomości. Studium przypadku

The topic of the paper is the analysis of the situation in the secondary real estate market in Krakow from 2017 to 2020. The research was conducted based on data obtained from the register of real estate prices and values. The results of the research helped detect changes occurring in the indicated years; the number of transactions in the housing market in the city oscillated around the value of 4,000 for each year. The high demand for real estate was significantly disrupted by 2020 and the outbreak of the COVID-19 pandemic. Despite an almost 50% drop in the number of transactions and reduced interest from potential buyers, the price of 1m2 of residential space rose steadily. Thus, the pandemic only affected the number of transactions, while no deceleration of the rising trend was observed in terms of the average transaction price or the average price per square meter.

CIM-WV: A 2D semantic segmentation dataset of rich window view contents in high-rise, high-density Hong Kong based on photorealistic city information models

Large-scale assessment of window views is demanded for precise housing valuation and quantified evidence for improving the built environment, especially in high-rise, high-density cities. However, the absence of a semantic segmentation dataset of window views forbids an accurate pixel-level assessment. This paper presents a City Information Model (CIM)-generated Window View (CIM-WV) dataset comprising 2,000 annotated images collected in the high-rise, high-density urban areas of Hong Kong. The CIM-WV includes seven semantic labels, i.e., building, sky, vegetation, road, waterbody, vehicle, and terrain. Experimental results of training a well-known deep learning (DL) model, DeepLab V3+ , on CIM-WV, achieved a high performance (per-class Intersection over Union (IoU) ≥ 86.23%) on segmenting major landscape elements, i.e., building, sky, vegetation, and waterbody, and consistently outperformed the transfer learning on a popular real-world street view dataset, Cityscapes. The DeepLab V3+ model trained on CIM-WV was robust (mIoU ≥ 72.09%) in Hong Kong Island and Kowloon Peninsula, and enhanced the semantic segmentation accuracy of real-world and Google Earth CIM-generated window view images. The contribution of this paper is three-fold. CIM-WV is the first public CIM-generated photorealistic window view dataset with rich semantics. Secondly, comparative analysis shows a more accurate window view assessment using DL from CIM-WV than deep transfer learning from ground-level views. Last, for urban researchers and practitioners, our publicly accessible DL models trained on CIM-WV enable novel multi-source window view-based urban applications including precise real estate valuation, improvement of built environment, and window view-related urban analytics.

Exploring real estate valuation practices in an informal market

This study investigates the intricate realm of real estate valuation in the Palestinian neighborhoods of East Jerusalem. Drawing on 27 interviews with real estate appraisers and an analysis of betterment tax valuations, arbitration reports, and court minutes spanning the years 1991–2023, we unpack the distinct valuation practices in this informal urban setting. We discuss the unique challenges involved in valuations in informal real estate markets and how appraisers address them, suggesting that appraisers in East Jerusalem grapple with structural, top-down challenges—arising from inconsistent Israeli planning regulations, geopolitical instability, and an underdeveloped mortgage market—and bottom-up obstacles stemming from limited transaction reporting by local Palestinian residents. To navigate these challenges, appraisers employ creative solutions, such as a 'copy & paste' strategy, referencing older arbitration verdicts, and creating complementary databases. They also rely on local knowledge and their familiarity with the field. Our research sheds light on the innovative methods appraisers utilize to assess land value in the complex and dynamic environment of East Jerusalem, and in informal areas more broadly.

The Externality Impact of Urban Rail Transit on Urban Real Estate Prices in China

China has the largest and fastest growing urban rail transit system in the world. The system plays an important role in China's urbanization process, city governance and residents' daily commutes. The development of urban rail transit (URT) has influenced China's urban spatial structure and real estate supply, and has produced externalities on real estate value, including both positive and negative externalities. The research shows a positive correlation between URT and China’s real estate prices in general. The closer rail transit systems are, the greater the premium on real estate prices. In addition, the impact of rail transit on real estate prices shows a trend of first increasing and then decreasing. Different land use types and urban areas will also be affected. The research also found that the three stages of URT construction: planning, engineering construction and traffic operation have different effects on housing prices. At the same time, the impact of URT on land price will also change with China's economic situation and urbanization process. These influencing mechanisms above between URT and real estate prices may be linked to some factors. This research attempts to explain it by introducing urban spatial and land rent transformation, changes in real estate supply and demand, gentrification process, and different employment and housing pattern. This research points out the shortcomings and possible research directions of existing studies. In order to provide a reference for academic research and government policy making.

Plague, Religion and Urban Space in Sixteenth-Century Antwerp

Summary Antwerp’s response to the outbreak of plague in the 1570s offers new insights into the effects of epidemics on urban communities in relation to their religious, economic, and spatial fabric. Antwerp’s transition from a Catholic to Calvinist government in 1577, and back to Catholicism in 1585, allows us to study its reaction to and the effects of plague across religious boundaries within a short time span. Using GIS, we have compared various rich datasets concerning plague: the register of houses locked in quarantine; the health certificates issued by authorities; plague fatalities recorded in St. Jacob’s parish; a wide range of urban regulations; and information about the size of households, their composition, rents and real estate values in Antwerp. Combined analysis shows that Catholics and Protestants, whose houses were concentrated in different city districts and who had distinct professional and economic profiles, experienced plague quite differently, both physically and spiritually.

Real estate and business fixed assets in the early Islamic economy from a Zakah perspective

PurposeThe face value of nonowner-occupied real estate and business fixed assets is excluded from Zakah, according to most Fiqh scholars who argue that it has not been explicitly ordered during the lifetime of Prophet Muhammad (sas). This study aims to test the hypothesis that the role of these properties in the early Islamic economy was insignificant and, therefore, differed from today.Design/methodology/approachA qualitative historical analysis of primary Islamic sources and narrations from early Muslim historiography has been conducted to understand real estate sales and rent, construction costs and the number and size of houses owned by the Sahabah. In addition, inheritance reports and land gift records have been examined to obtain relevant information about the value of real estate. As for business fixed assets, the type, number and wealth of craftspeople as well as their tools have been analyzed to reveal their significance in comparison with today.FindingsThe findings of this study confirm the hypothesis that real estate for investment purposes and business fixed assets were quasi-non-existent during the lifetime of the Prophet (sas) and, therefore, irrelevant from a Zakah perspective.Originality/valueThis study intends to be a catalyst for the reconsideration of Zakah on these items of wealth and contributes to the Fiqhi discourse.

Developing a mobile application with geo-analytic tools to perform real estate valuation within smart cities

Urban land management policies and applications require comprehensive information about real estate development dynamics and value criteria. In this study, geo-analytic tools and a mobile app were produced for residential property valuation in smart cities. Geo-analytical tools were automated to process and use datasets extracted from the databases and ‘Smart Real Estate’ mobile app using data sets produced by the developed geo-analytics tools shares map services automatically. In this way, users can get real-time location data via web services by triggering geographic analysis tools at certain intervals. It can manage and analyse big geographic data to share smart city services about real estate to citizens.

Triple bottom line, environmental, social and governance and net zero in commercial real estate

Climate and sustainability are at the forefront of dialogue within corporate real estate (CRE) organisations. Nearly 40 per cent of global carbon dioxide emissions come from the real estate sector. Of these emissions, approximately 70 per cent are produced by building operations, while the remaining 30 per cent comes from construction.1 A common language and aligned path is essential in making progress if we, as an industry, are to meet the goals we are setting. Sustainability, when referring to the triple bottom line, is a concept that refers to the environmental, social and governance (ESG) performance of an organisation and measures three areas of impact: people, planet, profit. This paper explores how sustainability takes into account the needs of an organisation’s stakeholders (including the community, general public and its employees) along with its own interests. This results in stronger relationships with these groups. The U.S. General Services Administration (GSA) is a federal government entity with a mission to deliver the best customer experience and value in real estate, acquisition and technology services to the government and the American people. One of GSA’s strategic goals is to provide financially and environmentally sustainable, accessible and responsive real estate solutions that enable a productive federal workforce. This paper provides highlights of how GSA is driven by three guiding principles: buy clean, build clean; net zero operations by 2045; and design for people, design for impact. The challenge of finding appropriate solutions to meet the demands of today are presented in actionable ways in examples from GSA as it continues to partner with industry, other organisations and communities to develop innovative solutions that support customer missions, enable community development and protect the environment, while providing effective stewardship of taxpayer dollars.

Models database of information technology for valuation of real estate

The goal of the research is to find and analyze ways to improve the results of real estate valuation based on a comparative approach. The chosen approach suggests the use of an information technology for the valuation of residential real estate, which is built on the basis of a database of models of decision support systems (DSS). The problem solved with the use of the discussed approach is to establish the degree of similarity between the object under consideration and its analogs by determining the value as an integral quality indicator based on the analysis of value-creating factors. This is followed by the construction of a generalized relationship between the value of this indicator and the prices of analogs. According to the logic of the comparative approach, it is assumed that the obtained relationship holds for the evaluated object as well and can be used in the calculation of its value.
 The formation of the database of models was based on the analysis of information technology processes, where details of functional aspects of process implementation, informational and logical connections between them, rights of access to information environment, and the implementation of processes by different types of users (their roles) were considered. The proposed database of models is built as a mathematical and logical basis of information technology that is applied as a computer tool for appraisers and aims to maximize formalization and efficiency improvement of process implementation based on expert evaluation methods. The construction of the database of models is based on methods of value estimation using multiple criteria, with consideration of their significance, analysis of hierarchies, ranking, Delphi, and user access control based on defined roles.

City characteristics, land prices and volatility

We develop a model that describes how city characteristics affect the volatility of real estate rents and values. The model includes agglomeration externalities, which amplify the effect of productivity shocks on population growth and rents, as well as city characteristics that constrain population growth. While growth constraints make rents more subject to productivity shocks because of the inelastic supply, they can also suppress the benefits of agglomeration, which has the effect of decreasing the sensitivity of rents to productivity shocks. Our dynamic model exhibits persistent rent growth and rent-to-value ratios that vary across cities and over time. In particular, we show that productivity shocks have a larger initial effect on rents in more constrained cities, but a greater long-term effect in less constrained cities.