Real Estate Values Research Articles

A definition of the body of knowledge for real estate: reconceptualizing the discipline and delineating the jurisdictions of its practice

PurposeFollowing calls at different times in the United States for the definition of the body of knowledge (BOK) of real estate discipline, this briefing sets out to define the intellectual boundaries of real estate and applies the definitional concept to map out the scopes of real estate professions and real estate valuation vocationDesign/methodology/approachThe study essentially uses a literature review to draw out definitional issues that have been tackled before. It reviews calls that have been made in the past for a definition of the BOK of the real estate discipline. Further, it reviews past attempts at definition to reveal why they failed at the definition project.FindingsThe study found three key suggestions made in the past: that there is a need to define real estate’s BOK, that there is a need to use a “central structure” to define the BOK of real estate, and that definition of the BOK of real estate should rely on the activity nodes that constitute real estate. The study has relied on these three key ideas to define real estate as the science of value creation, distribution and sustenance in built space.Practical implicationsThe definition of the BOK will help in curriculum development for real estate education. It will help faculties and departments to single out what fits into the real estate curriculum and what does not fit in.Originality/valueA definition of the BOK for real estate: reconceptualizing the discipline and delineating jurisdictional boundaries of its practice.

Faktor yang Mempengaruhi Nilai Perusahaan pada Perusahaan Sektor Property & Real Estate yang Terdaftar di Bursa Efek

The purpose of this research is to test in reality whether profitability, leverage, and company size affect company value in real estate and property companies listed on the Indonesia Stock Exchange during the 2019-2023 period. This study uses secondary data, there are 10 companies that meet the research criteria many as 50 observation data. This study uses a quantitative method. The research variables used are profitability, leverage, and company size. This test uses multiple linear analysis and the eviews 13 software program. These results illustrate that profitability and leverage do not affect company value, while company size has a negative effect. according to the results of the regression test using (REM), the Determination Coefficient R² = 0.493716, indicating that 49.37% of company value is influenced by (ROAS), (DERA), and (UP), while the remaining 50.63% is explained by other factors.

Climate Risk Assessment Framework in Real Estate: A Focus on Flooding

Climate change exacerbates flood hazards, resulting in risks to real estate values that should be considered by long-term investors. Flood risk presents two major financial risks: market risk and credit risk. Market risk refers to potential property value loss, and credit risk increases the likelihood of mortgage defaults. However, methods and comprehensive data for quantifying global real estate flood risks are lacking. To address this problem, this paper proposes two flood risk assessment frameworks: the local-oriented approach (LOA) and global-oriented approach (GOA). Two hazard and three vulnerability assessment methods are also introduced to support these frameworks. The LOA vulnerability estimates of regions with complete records are required to support the GOA. Taiwan was selected as an example for the LOA assessment, and the results were used to estimate vulnerability overseas in GOA assessments. The results of case studies for buildings located in four cities in different countries were compared. The proposed framework enables investors and asset owners to globally quantify climate risks in real estate, even when the available data are incomplete. Users can choose the most appropriate approach on the basis of the available data and their tolerance for uncertainty.

Texas Rural Land Market Integration: A Causal Analysis using Machine Learning Applications

Texas rural land markets have several special features that makes it unique from other rural land markets in the United States. In 2021, Texas agricultural land, including buildings, is valued at $299.88 billion, which is almost 10% of the nation's total agricultural real estate value and 83% of the state's land is categorized as rural. In addition, due to its size and geologic features, Texas’ diverse landscape creates complex and widely divergent conditions affecting ownership and marketing of the land. Despite this complexity, lack of granular level and reliable transactional data on land sales has prevented thorough investigation into Texas land markets to uncover various interdependencies. Using quarterly transactional land value data from 1966-2017, this study uses cutting-edge machine learning algorithms and probabilistic graphical models to uncover causal interaction patterns of different land markets in Texas. The results reveal that Texas rural land markets are interdependent. Current and potential landholders and lenders can use the results from this work to aid strategic decision making. Financial institutions and investment groups could be made aware of the trend of one land market relative to other markets and adjust their holdings accordingly. Landowners may better understand changes in net wealth, which affect their ability to borrow capital and operate efficiently. Moreover, lenders may also benefit from the information to manage collateral and thus maintain the stability of their operation.

OS DESAFIOS DO DIREITO DAS SUCESSÕES NA HERANÇA DE BENS DIGITAIS NO BRASIL

This scientific article addresses the Inheritance of Digital Assets and the role of Succession Law in Brazil, with information regarding current legislation and examples of concrete cases. It presents examples of digital goods such as cryptoassets, items in virtual games, items stored on the Blockchain, among others. In this way, without intending to exhaust the topic, the authors bring up the importance of Succession Law linked to the lack of specific legislation on the topic, leaving it at the mercy of the judiciary to resolve broad issues or even the need for the owner of the assets to make a will directing instructions to heirs on how to access a certain asset, given the variety of items and their diverse economic value, which in some cases can even be compared to the values ​​of real estate in Brazil.

The Effect of War on Spatial Differentiation of Real Estate Values and Urban Disorder in the Damascus Metropolitan Area

The Syrian war, which commenced in 2011, transformed the Damascus real estate market due to heightened insecurity and tenure disputes. Using the hedonic price models, including 2411 housing transactions over the period 2010–2022, this study aims to understand the spatial dynamics of the real estate market in wartime. Our findings indicate that war variables have had a significant impact on the differentiation of property prices. Notably, property attributes have a more substantial impact on real estate values than district location, with severely damaged buildings in Damascus City resulting in an 89% decline in prices, while prices in Rural Damascus districts have decreased by 50%. Additionally, this study examines the urban texture of Damascus using correlation and homogeneity statistics derived from the gray-level co-occurrence matrix obtained from Google Earth Engine. Our findings show that correlations were highly differentiated, particularly among Rural Damascus districts, with a total decline of 87.2%. While homogeneity values decreased overall between 2015 and 2019, they improved slightly after 2019. This study guides decision makers in mitigating severe property value variations across war-affected urban areas by fostering spatial justice in property rights and promoting balanced investment and sustainable real estate development during the post-war recovery phase.

“General Plan” in Real Estate Valuation for Selected Planning Purposes

Abstract The article presents considerations on the importance of the provisions of the municipality’s general plan referred to in the Act of March 27, 2023 on Spatial Planning and Development, as well as the importance of the provisions of the local general plan, referred to in the Act of July 12, 1984 on Spatial Planning when estimating real estate for the purposes of determining the amount of compensation and fees referred to in Art. 36 section 3 and 4 of the Act on Spatial Planning and Development. Due to the fact that the Act of 1984 refers to the general spatial development plan of settlement units (called the general plan), prepared and adopted on the basis of the Act of January 31, 1961 with the same name, the article also discusses this type of plan. Moreover, activities related to determining the value of real estate were indicated, including the above-mentioned planning purposes, and the understanding of concepts such as “real estate data” and “intended use in the local plan” were presented. Attention was also focused on the essence of the above-mentioned types of plans, as well as the differences between the general plan of the commune and the local general plan and general spatial development plan of settlement units.

Indonesia’s real estate value potential: the role of green innovation and effective management control systems

Indonesia’s real estate value potential: the role of green innovation and effective management control systems

Prioritization of Source Data Necessary for the Valuation of Real Estate with Mineral Deposits: The Case of Poland

Real estate valuation with mineral deposits in Poland can be conducted using comparative, income, and cost approaches. When determining the value of such real estate, a property valuer must obtain information from multiple sources. These sources not only help to establish the legal status but also allow for determining the type of geological and mining asset of the deposit, characterizing and assessing the quality of the deposit, describing the deposit's resources, and evaluating the exploitation potential. Analysis of the source documentation also enables the assessment of the environmental state post-exploitation and helps determine the external conditions related to the liquidation of deposits after exploitation. The need to include the above information in the appraisal report requires the property valuer to gather a large amount of source information scattered across private and institutional resources. Therefore, this study aims to identify and prioritize the source data necessary for the valuation process of land properties with mineral deposits in Poland using selected business techniques. As part of achieving the research goal, the method of valuing the subject special property will be recognized, and the source materials will be identified. Their prioritization will be performed using two business techniques: the MoSCoW method and the Action Priority Matrix. In the final stage of the study, utility classes of the source materials for the valuation of the subject property will be developed

MODELING THE BENEFITS OF A MARRIAGE REVERSE ANNUITY CONTRACT WITH DEPENDENCY ASSUMPTIONS USING ARCHIMEDEAN COPULA

Social security benefits may not be enough for retirement. Equity release products like marriage reverse annuities can boost retirement income for older couples. Marriage reverse annuity’s contract convert all or part of the real estate value of elderly spouses while they are living (joint life status) or after one partner dies (last survivor status). Since husband and wife face the same death risk, the chance of death between spouses is believed to be dependent for realism. Thus, copula models the future dependency model of a husband and wife. Sklar's theorem states that copulas link bivariate distribution and marginal cumulative functions. One of the most common copulas is Archimedean copula. Clayton, Gumbel, and Frank are Archimedean copula that will be used in this investigation. The Indonesian Mortality Table IV data is used to obtain the marginal distribution of the male and female which will then be used to construct copulas (Clayton, Gumbel, and Frank) that combine two marginal distributions into a joint distribution. The marginal distribution of Indonesian Mortality Table IV is uncertain, hence Canonical Maximum Likelihood parameter estimation is utilized to estimate the parameter of copulas. Multiple-state models depict the marriage reverse annuity model for joint life and last survivor status. The probability structure is based on Sklar's theorem and copula survival function. The contract benefits calculation utilizing copulas (Clayton, Gumbel, and Frank) shows that joint life status benefits are higher than last survivor status. Joint life status uses the dependence assumption with Frank's copula to calculate the smallest annual benefit value of a marriage reverse annuity contract, while last survivor status uses the independence assumption (without copula).

Avalúos inmobiliarios: un estudio de caso sobre el sistema Continental frente al Common Law

We use Colombia as a case study of a situation where emerging real estate valuation practices, mostly based upon the logic of Common Law legal systems, and oriented to market prediction and global standards, collides with a valuation tradition based upon the Continental legal tradition. In this tradition, the valuation process first and foremost must satisfy limiting regulatory checklists. These requirements minimize the value of focusing on market analyses to offer accurate predictions (appraisals). Our analysis builds upon the Laws 9 of 1989 and 388 of 1997, and their corresponding implementation legal enactments (resoluciones), showing that the valuation practice for public purposes determines a logic where appraisers operate as ‘temporary public workers’. Appraisers and their associations (Lonjas) have subsequently transferred such limiting procedural principles to valuation for business purposes, which should be oriented to market analysis and prediction.

Enhancing Real Estate Valuation in Kazakhstan: Integrating Machine Learning and Adaptive Neuro-Fuzzy Inference System for Improved Precision

Enhancing Real Estate Valuation in Kazakhstan: Integrating Machine Learning and Adaptive Neuro-Fuzzy Inference System for Improved Precision

Transferred Bias Uncovers the Balance Between the Development of Physical and Socioeconomic Environments of Cities

Evaluating the balance between a city’s physical and socioeconomic environmental development is crucial for creating sustainable and livable urban spaces. Although they might appear contradictory, they jointly support the comprehensive sustainable urban development strategy. Traditional methods usually focus on assessing this balance from a specific perspective, such as how neighborhood greenery shapes real estate value. Yet, they fail to deliver a holistic balance assessment in developing the physical and socioeconomic dimensions. To fill this gap, this study introduces a research framework that measures this balance through house prices based on transferred bias. Using house price as an indicator shaped by both physical and socioeconomic environments, the framework first constructs a series of deep learning models to estimate house prices through street view images for each city. These models capture the relationship between neighborhood appearance and house price. Second, by leveraging transfer inference, we introduce neighborhood appearance from one city into the model trained from another city. This process identifies the transferred bias, which is the disparity between inaccurate inference resulting from a mismatched neighborhood appearance and the trained model. Through transferred bias, we can quantify the differences in physical and socioeconomic environments across cities and evaluate the urban balances of these two environments. The results show that the transferred bias effectively quantifies the disparities among cities in physical and socioeconomic environments, thereby facilitating further investigation into the urban balance between these two environments.

The Positive and Negative Effects of Sustainability on Real Estate Transaction Prices

In last decades, there is a trend to renew buildings and make them more sustainable. Studies have shown that energy measures (as an aspect of sustainability) often increase the value of real estate. The effect of other sustainability measures on real estate values, however, is unknown. This study examines the relationship between multiple sustainability aspects and the transaction prices of different types of real estate. For this study, we used official data on commercial real estate transactions from the Land Registry Office in the Netherlands and sustainability assessment scores from a Dutch sustainability consultant. In total, 10,652 real estate transaction prices between 2012 and 2023 and corresponding sustainability scores were used to perform regressions and hedonic imputation analyses. The results show that, opposed to energy, other aspects of sustainability often correlate negatively with transaction prices in the lower segment of sustainable real estate. These aspects correlate positively in the upper segment of sustainable real estate.

Determination of outliers when building a multivariate regression model of prices in residential real estate market of the region

The paper is aimed at selecting the optimal method for identifying outliers in the initial data when building a multivariate regression model of prices in the regional residential real estate market. The study was based on offers for sale of apartments in prefab flat blocks located in Irkutsk. In this regard, a basic multiplicative multivariate regression model was built, describing the dependence of cost indicators on the pricing factors of real estate. The identified outliers were iteratively removed from the basic model. The methods for detecting outliers included calculation of standard deviation (z-score), calculation of the Mahalanobis distance, as well as a method developed in the study for bringing the prices of objects to the characteristics of the reference object. The optimal method for detecting outliers in the initial data was selected by comparing the characteristics of the final variable-based multivariate regression models obtained after removing outliers from them. The analysis of the results proved the method of bringing the prices of objects to the characteristics of the reference object to be the optimal method of identifying outliers when building a multivariate regression model of prices in the regional residential real estate market. This method significantly reduces the approximation errors of the basic multivariate regression model of the market, thereby increasing the adequacy of the results of the real estate valuation conducted on its basis.

Основные виды соседских вмешательств по праву Германии и Швейцарии

This article analyses the neighbour law in the law of Germany and Switzerland with the question of borrowing foreign experience in Russia. For this purpose, the classification of neighbours’ interventions is examined in detail. Each type is considered in the context of foreign doctrine and judicial practice, its impact on the balance of interests of neighbours and the state is studied, and a conclusion is made about the necessity or lack thereof for potential borrowing in Russia. Also important terms and principles accompanying neighbourly relations are analysed: materiality of interference, economic feasibility of measures to reduce harmful effects, the principle of good neighbours in the context of cohabitation. The ways of protection of the owner’s rights against them are considered, among which there are negatory action, tort action, challenging the decision of a public authority, compensation action. As a result of the study, the following conclusions are drawn. Not all types of interference in the right of ownership by a neighbour could be relevant in Russia, in particular intangible (affecting the value of real estate without direct interference in use) and aggregate interferences (from several sources and issuers) are applied in Germany with great difficulty (most often only reaching the Supreme Court), but positive (physical) interferences and negative (interfering in use without direct physical interference), taking into account the text of the draft reform of the Civil Code of the Russian Federation (where they are indirectly taken into account) would be important in the future and could find a place in the legal system of the Russian Federation.

Mapping the landscape: A systematic literature review on automated valuation models and strategic applications in real estate

In the rapidly evolving real estate industry, integrating automated valuation models (AVMs) has become critical for improving property assessment accuracy and transparency. Although there is some research on the subject, no thorough qualitative systematic review has been done in this field. This paper aims to provide an up-to-date and systematic understanding of the strategic applications of AVMs across various real estate subsectors (i.e., real estate development, real estate investment, land administration, and taxation), shedding light on their broad contributions to value enhancement, decision-making, and market insights. The systematic review is based on 97 papers selected out of 652 search results with an application of the PRISMA-based method. The findings highlight the transformative role of AVMs approaches in streamlining valuation processes, enhancing market efficiency, and supporting data-driven decision-making in the real estate industry, along with developing an original conceptual framework. Key areas of future research, including data integration, ethical implications, and the development of hybrid AVMs approaches are identified to advance the field and address emerging challenges. Ultimately, stakeholders can create new avenues for real estate valuation efficiency, accuracy, and transparency by judiciously utilizing AVMs approaches, leading to more educated real estate investment decisions.

A wall between real estate valuation standards and professional appraisal practice: A focus on Italian market

Real estate appraisal standards provide guidelines for the preparation of reliable valuations. These standards emphasize the central role of market data collection in market-oriented valuation methodologies such as the Market Comparison Approach (MCA), which is the most commonly used. The objective of this study is to highlight the difficulties in data finding, as well as the gap between the standards and the actual appraisal practices in Italy. Thus, a detailed comparison was made between the real estate data considered necessary by the standards and those ones reasonably detectable by appraisers, showing that some important market information is not reachable due to legal, technical and economic factors. Finally, a case study is presented in which the actual appraisal of a residential property is schematically described to support what is claimed with the research question and thus the degree of uncertainty around an estimate judgment.

The Determination of Capitalization Rate by the Remote Segments Approach: The Case of an Agricultural Land Appraisal

In the absence of comparative real estate data in the market segment of the property to be estimated, the appraiser may resort to income capitalization to estimate the market value. Often, however, the choice of which rate to apply is affected by subjective and arbitrary assessments. The estimation result can therefore be inaccurate and rather unclear. However, the Remote Segments Approach (RSA), through appropriate adjustments on the original values, prices, and incomes detected in the remote segments, makes it possible to arrive at an appraisal result consistent with estimative logic and real estate valuation standards. The proposed application illustrates the estimation of the market value of a specialized fruit orchard of avocado, which is to be considered new in relation to other fruit species already present in the reference area. The adjustments required by the RSA are solved with the General Appraisal System (GAS), defining the difference matrix based on relevant characters common to all segments considered. The application is carried out by comparing the segment in which the orchard being estimated falls (subject) with other remote market segments in which prices and incomes constituted by other tree crops are collected. The market value of the subject is derived by making adjustments to the prices and incomes observed in the remote segments of comparison with a comparison function constructed through relevant characters common to the segments considered. The comparison function makes it possible to arrive at the determination of the capitalization rate to be used in estimating the value of the fruit orchard by income approach. While it is based on the comparison of segments, the approach followed allows for a value judgment consistent with the estimation comparison and capable of providing a solution less conditioned by the appraiser’s expertise in the presence of particularly pronounced limiting conditions.

Improvement of simultaneous prediction using principal components approach

Prediction has a fundamental role both in linear regression analysis and in many applied sciences. The predictions of actual values or mean values of the response variable were obtained separately, earlier than defined the target function. It has been attracting a lot of interest because obtaining simultaneous predictions both of the mean values and actual values is more reasonable in many applied studies since the target function was reported. This paper purposes to improve the simultaneous prediction with the target function when the problem of multicollinearity exists in the linear regression model by defining new predictors based on the principal components estimator, which is more resistant to multicollinearity than the ordinary least squares estimator. The comparisons of proposed predictors are done theoretically by using the mean squared error of predictions. Then theoretical results are supported by an exhaustive simulation study. Also, performance comparisons of the newly suggested predictors are made for two real-life data sets, real estate valuation and cruise ship info. The findings show that the use of the proposed predictors will make a crucial contribution to applied studies in obtaining better predictions.