Real Estate Values Research Articles

CEO compensation and real estate prices: pay for luck or pay for action?

This paper uses variation in real estate prices to study Chief Executive Officer (CEO) pay for luck. We distinguish between pay for luck and pay for responding to luck (action) by exploiting US GAAP accounting rules, which mandate that real estate used in the firm’s operations is not marked-to-market. This setting allows us to empirically disentangle pay for luck from pay for action, as a change in the value of real estate is only accounted for when the CEO responds to changes in property value. We show that CEO compensation is associated with the following two managerial responses to changes in real estate values: (i) real estate sales and (ii) debt issuance. Overall, we show that CEOs are rewarded for taking value-enhancing actions in response to luck.

The COVID-19 Housing Boom: Is a 2007–2009-Type Crisis on the Horizon?

While the current housing market remains relatively strong, with housing prices setting records, concerns are growing of a potential housing bubble similar to that of 2007–2009; this paper compares the current housing market environment with that of 2007–2009 and concludes that the many of the factors that caused the 2007–2009 crisis do not exist today. Factors associated with subprime mortgages, poor and non-existent underwriting loan requirements, weak regulatory oversight, exaggerated credit ratings, under-capitalization in the banking sector and excessive speculative activity in the housing market have been addressed by regulation, which is aimed at preventing another financial crisis similar to 2007–2009. Equally important, major fundamental factors affecting real estate valuation are providing support for the housing market and housing prices; these factors are impacting both the demand and supply side of the housing market. The factors include the lack of inventories of homes available for sale, the underproduction of housing, decreased household mobility limiting supply and the increase in housing demand from millennials and institutional investors; these fundamental factors were not evident during the 2007–2009 period. Despite a number of indicators signaling a potential topping out and overvaluation of housing prices, the authors conclude that the fundamental factors will limit the extent that the housing market weakens over the next few years.

Nonparametric Prediction Distribution from Resolution-Wise Regression with Heterogeneous Data

Modeling and inference for heterogeneous data have gained great interest recently due to rapid developments in personalized marketing. Most existing regression approaches are based on the conditional mean and may require additional cluster information to accommodate data heterogeneity. In this article, we propose a novel nonparametric resolution-wise regression procedure to provide an estimated distribution of the response instead of one single value. We achieve this by decomposing the information of the response and the predictors into resolutions and patterns, respectively, based on marginal binary expansions. The relationships between resolutions and patterns are modeled by penalized logistic regressions. Combining the resolution-wise prediction, we deliver a histogram of the conditional response to approximate the distribution. Moreover, we show a sure independence screening property and the consistency of the proposed method for growing dimensions. Simulations and a real estate valuation dataset further illustrate the effectiveness of the proposed method.

Modeling and Simulation of Real Estate Valuation Based on Genetic Neural Network Model

China’s real estate market is developing rapidly, but the house price is abnormal. The nonlinear relationship between housing characteristics and real estate value is difficult to calculate, resulting in the difficulty of house price prediction. Based on this, the relationship model between characteristic variables and house prices is constructed by using the machine learning method. At the same time, genetic algorithm is used to screen the specific values. The experimental results show that the optimized model converges in 56 iterations; in the application test, the research model found that in 90% of the test samples, the error between the predicted value and the actual measured value shall not exceed 10%. Experiments show that the genetic algorithm is effective in optimizing the BP house price valuation model and improves the calculation efficiency and valuation accuracy of the valuation model.

The unintended consequence of collateral-based financing: Evidence from corporate cost behavior

This paper examines how real estate appreciation correspondingly changes collateral value, which affects debt structure choices and consequent operating decisions. Specifically, we explore whether collateral-based financing provides a link between real estate values and corporate cost behavior. Our baseline results show that an appreciation of a firm’s real estate assets alleviates its cost stickiness. A further analysis shows that this influence is stronger for firms with less prior bank debt, less dependence on external financing, and a lower leverage ratio. We also observe that the impact of collateral shocks on cost stickiness is more pronounced when selling, general and administrative (SG&A) costs create less future value for mature firms and for firms with weaker external governance. Collectively, our results support the argument that an increase in bank debt arising from collateral value appreciation mitigates agency problems and thus lessens cost stickiness.

Criteria for determining the market value of real estate for adjustments to their cadastral value

The analysis of the formed market system is given, in which the procedure for determining the ca-dastral value seems to be the most problematic. It is the cadastral value that is the basis for calculat-ing the main indicators of the payment of non-property objects and determines the subject of dis-putes between the state, citizens and entrepreneurs in terms of the amount of such payments.
 According to the current legislation, namely Federal Law No. 135-FZ of 29.07.1998 "On Valuation activities in the Russian Federation", the results of cadastral valuation can be challenged by individ-uals and legal entities in court or in a commission established under the Federal Register.
 Since the cadastral value was determined by mass valuation methods, the final value may incorrectly reflect market reality. However, all the current regulatory legal acts, methodological guidelines for evaluation are aimed at more correct execution of appraisal activities and, accordingly, at displaying adequate results of real estate valuation.

Automation of Negative Infrastructural Externalities Assessment Methods to Determine the Cost of Land Resources Based on the Development of a “Thin Client” Model

This article discusses the need to transform real estate valuation methods. It is associated with the problems of obtaining unreliable results affecting the subsequent adoption of management decisions. As an important element of land plots assessment, the authors define the Negative Infrastructural Externalities arising from the presence of infrastructure and other regime-forming facilities. These externalities represent the loss of title holders due to the encumbrances arising from the use of land plots. The world community (and the authors as part of it) sees one of the transformation methods in the automation of the evaluation process. Therefore, the purpose of this study is to develop a mechanism of automating the Negative Infrastructural Externalities assessment process in the conditions of a non-existent and weak market activity of land relations. Modern trends dictate the saving of hardware, labor and money resources; in this connection, the methods of Negative Infrastructural Externalities assessment are implemented on the basis of the “thin client” technology. The research is based on the following methods: the analytical method is used to perform a critical analysis of the problem area and to substantiate the research topic’s relevance; methods of object-oriented programming and methods of modular programming (Cowan’s axiom of modularity) are used as tools for developing the web application logic, as well as the interaction of its individual elements; the attribute-driven design approach is used in the creation of software architectures. The result of the study is the developed and substantiated architecture of a web application for assessing negative infrastructural external factors in determining the land value, the implemented modular structure of the specified web application and the developed conceptual model of the database. The practical implementation of the listed proposals is made by means of the Python programming language. The advantage of the created automated system is the possibility of multi-disciplinary use of the expert assessment approach when changing the settings.

PENGARUH INTELLECTUAL CAPITAL TERHADAP NILAI PERUSAHAAN DENGAN FINANCIAL DISTRESS SEBAGAI VARIABEL INTERVENING PADA PERUSAHAAN PROPERTY DAN REAL ESTATE YANG TERDAFTAR DI BEI TAHUN 2018-2020

Property and Real Estate Company is one type of business that is growing rapidly in Indonesia. Property and Real Estate Company is one of the companies listed on the Indonesia Stock Exchange and is considered more productive and can provide wide-ranging effects so as to increase the added value of Property and Real Estate, increase workforce, generate foreign exchange sources, and contribute to taxes and customs. biggest. The purpose of this study was to determine the effect of Intellectual Capital on Company Value with Financial Distress as an intervening variable in Property and Real Estate companies listed on the IDX in 2018-2020. The population of this study is all property and real estate companies listed on the 2018-2020 period (IDX) as many as 73 companies. The sampling technique was determined by purposive sampling. Data analysis and hypothesis testing in this study used the Structural Equation-Partial Least Square (PLS-SEM) method.
 The results of the direct influence hypothesis test using the Smart PLS 3.0 application, show that intellectual capital has a negative but not significant effect on financial distress, intellectual capital has a significant negative effect on firm value, financial distress has a positive but not significant effect on firm value. The results of the indirect effect hypothesis test show that intellectual capital has a positive but not significant effect on firm value through financial distress.

Cyclical capitalization: basic models

The relevance of market cycles is known in the financial markets and in the context of real estate valuations it manifests itself in the estimate of the “exit value” of the Discounted Cash Flow Analysis. The hypothesis that the market cycle has a behaviour very similar to what happened in the past introduces some risks and uncertainty in the estimated value. To allow a more extensive use of cyclical capitalization in formulating value judgments, this paper proposes two methodological adaptations to the original model: the first, based on the presence of a regular market trend; the second based on the hypothesis of irregular market cycles and therefore more representative of the dynamics to which a specific real estate segment is exposed. In the perspective of a more extensive availability of information, data and extra-data, other application areas are also identified on which further investigations need to be developed.

Executive profiles and performance of real estate services: Evidence of reverse causality from Europe

What executive profiles govern the industry of real estate services in Europe? Does heterogeneity emerge in these profiles if different industry sectors and/or geographical areas are considered? Ultimately, does this heterogeneity impact on their firms' performance? As a key component of the real estate value chain, real estate services are central to direct, properly support, and also guarantee the ex post sustainability of urban development projects. However, knowledge on what factors affect their performance is still absent. In light of this gap, in this study we draw on Upper Echelons Theory and analyze the socio-demographic features of key executives from a panel of listed European real estate service firms. We not only search for homogeneity/heterogeneity in these executives' profiles, but also for a potential connection with their firms' profitability. Results from our analysis show that, given their homogeneity, gender, age, and tenure do not apparently represent a catalyst for firm performance differential; in contrast, on the basis of their heterogeneity, advanced education and past industry experiences outside real estate can positively count. The theoretical contribution of our study, which proposes a model of inter-environment reverse causality, and implications for research and urban policy making are then presented.

Residential Buildings’ Real Estate Values Linked to Summer Surface Thermal Anomaly Patterns and Urban Features: A Florence (Italy) Case Study

Climate-change-related extreme events impact ecosystems, people, economy, and infrastructures, with important consequences on the real estate market as well. This study aims to investigate the variation of residential buildings’ real estate values in a historic Italian city in relation to the summer surface thermal anomaly pattern and urban features surrounding buildings. Open data from remote sensing products and the national database of the Revenue Agency of Italy were used. Real estate values of residential buildings were spatially analyzed in four urban belts, and the association with daytime summer surface hot- and cool-spot zones was studied through odds ratio (OR) statistic. Urban features (impervious area, tree cover, grassland area, and water body) surrounding residential buildings with different real estate values were also analyzed. Considering the whole Florentine municipality, 13.0% of residential buildings fell into hot-spot zones (only 0.6% into cool-spot ones), characterized by very low tree cover surfaces (generally <1%), most of which were in the central belt (37% of all buildings in central belt). Almost 10% of these buildings belonged to the highest market value class revealing a positive association (OR = 1.53) with hot-spot zones. This study provides useful information to plan targeted building interventions to avoid a probable decrease of the value of residential properties in high heat-related risk areas.

Approach to hedonic model and analyzing factors affecting real estate prices in Hanoi

In real estate valuation techniques and housing market research, real estate prices are often analyzed using The Hedonic model based on factors that affect real estate prices. The Hedonic model shows the factors that affect real estate prices. The determinants of real estate prices in Hanoi in this article use 240 observations. The variables that have the greatest influence on real estate prices are the location of the property, the area of the land, the area of the house, the distance from the property to the city center, and the distance from the property to the street frontage.

공인중개사의 직무만족이 업무몰입 및 서비스가치에 미치는 영향

This study deduces job satisfaction factors that affect work commitment by empirically analyzing the relationship between job satisfaction of real estate agents and service value, and a hypothetical model explaining the effect of real estate agents' work commitment on service value. The purpose is to build and verify. In order to achieve the purpose of this study, the effect of job satisfaction on work commitment and service value was statistically analyzed for 240 real estate brokers who are currently engaged in real estate brokerage business in Seoul and Gyeonggi Province. As a result, it was found that the intrinsic and extrinsic satisfaction of real estate agents had a significant effect on work commitment. In addition, it was analyzed that work commitment affects the service value of customers. Therefore, in order to enhance the work immersion of real estate agents, intrinsic and extrinsic satisfaction factors must be improved. As the real estate agent's own work commitment improves, the real estate agent's job satisfaction will increase. For this purpose, real estate agents will need to make efforts to increase the service value of their customers through their efforts for intrinsic and extrinsic satisfaction and immersion in their work.

Automated Real Estate Valuation With Machine Learning: A Case Study on Apartment Sales in Yerevan

Real estate is one of the major sectors of the Armenian economy and has been developing dynamically since Armenia transitions from planned to market economies in early 1990s. More recently, large online platforms have been developed in Armenia to advertise real estate offerings, thus reducing information asymmetry, and increasing liquidity in both sales and rental markets. Simultaneously, granular geospatial data became increasingly affordable via platforms such as OpenStreetMap, Google Maps and Yandex Maps. With granular data concerning a representative portion of the real estate offering available online, it is increasingly tenable to monitor the real estate market in real time and develop analytical tools that can automatically and accurately estimate the value of real estate assets based on their internal and external features. This paper sets out to analyze Armenia real estate market and assess the performance of a special class of machine learning models while predicting the price of a square meter of apartments in Yerevan. Furthermore, it is presented the way to determine the most decisive factors which have an influence on the price of apartments on sale.

IMPACT OF THE COVID-19 PANDEMIC ON THE DEVELOPMENT OF MORTGAGE LENDING IN RUSSIA

Relevance of the research topic. The coronavirus crisis has had a controversial impact on the mortgage market. On the one hand, mortgages during the Covid-19 pandemic have become more profitable due to lower interest rates and a decrease in the size of the down payment. On the other hand, for many citizens who are faced with the loss of work or a decrease in income, mortgages during the coronavirus period have turned into an overwhelming debt. Government support in the field of mortgage lending during the Covid-19 pandemic spurred the growth of mortgage loans, this support helped to meet part of the demand for mortgage transactions for 2021. Also, banks, from a decrease in interest on preferential mortgages on their proposed programs, received low income, in this situation borrowers who took out a mortgage under the state program in the first three or four months won. Mortgage lending is a very risky financing, both for lenders and borrowers, due to a number of interrelated reasons, such as imperfection of Russian legislation, reduced incomes of the population, and the COVID-19 pandemic. The situation with the COVID-19 pandemic has put many residents of Russia in a difficult position, especially those who, due to restrictive measures, faced disruptions in the activities of their organizations, having significantly lost income, but at the same time bears the burden of paying various kinds of loans, including including mortgage lending. Due to the introduction of the program for concessional mortgage lending, the dynamics of the mortgage market has increased, however, a decline in demand for mortgage loans is predicted after the completion of this program, which will lead to a decrease in the cost of housing. This trend will affect the collateral value of real estate purchased with a mortgage. The main problems of mortgages in the Russian Federation now are low incomes of the country as a whole and of each person individually, significant inflation, monopolization of the housing construction market, migration features, insufficient government participation in supporting mortgages and the underdevelopment of the mortgage securities market. The solution of the indicated restrictions will be possible only as a result of the general, progressive development of the country's economy in all its spheres: politics, social, construction, banking and other sectors. The purpose of the study is to assess the impact of the Covid-19 pandemic on the development of mortgage lending in Russia. Methods of comparison, generalization, analysis, tabular method were used in the work.

Relation between the Views and the Real Estate Application to a Mediterranean Coastal Area

The landscape is a factor considered when choosing to purchase a dwelling, and, therefore, it influences the price of the real estate market. However, it is difficult to measure and assess its role, since it has a series of features that work in an integrated way and are hard to quantify separately. The characteristics of the views from each dwelling must also be considered, as well as their intrinsic characteristics or proximity to public services. This study proposes an automatic method to analyze the quality of the views, including both its dimensions and its composition in order to be able to estimate the economic weight of the views in the real estate value. A series of measurements of the views from 226 dwellings are integrated into the final index equation. The results are then compared with the estimated dwelling prices. The results highlight that the average price increases up to 18.1% in dwellings with a larger high-quality visual basin. It has also been noted that it is difficult to establish a correlation between the quality of the views and the housing prices due to the multifactorial nature of the housing prices.

A Study on the Effect of Housing Choice on Residential Satisfaction in Seoul Metropolitan Area : Focusing on Characteristics by Region, Life Cycle, and Income

The purpose of this study is to reveal the effect of housing choice factors and resident characteristics on housing satisfaction by region, income, and life cycle using data from the Korea Labor Survey Panel through regression analysis. As a result of the analysis, the following results and implications were derived. First, housing choice factors do not necessarily have a positive effect on housing satisfaction, and housing choice that expects an increase in real estate value has a negative effect on housing satisfaction. In addition, it is necessary to provide an equal educational environment and comfortable living environment for each living area, and to provide appropriate convenience facilities for living areas with low residential satisfaction. Second, affordable rental housing should be provided near employment sites or public transportation to increase employment accessibility for young people in Seoul and Gyeonggi-do, while providing affordable housing for young people from low-income families. In addition, long-term rental housing and job support should be continued for the middle-aged and elderly, and housing repair and care services should be provided in areas densely populated with the elderly.

A room with a view: Automatic assessment of window views for high-rise high-density areas using City Information Models and deep transfer learning

Every windowed room has a view, which reflects the visibility of nature and landscape and has a strong influence on the health, living satisfaction, and housing value of inhabitants. Thus, automatic accurate window view assessment is vital in examining neighborhood landscape and optimizing the social and physical settings for sustainable urban development. However, existing methods are labor-intensive, inaccurate, and non-scalable to assess window views in high-rise, high-density cities. This study aims to assess Window View Indices (WVIs) quantitatively and automatically by using a photo-realistic City Information Model (CIM). First, we define four WVIs to represent the outside (i) greenery, (ii) water-body, (iii) sky, and (iv) construction views quantitatively. Then, we propose a deep transfer learning method to estimate the WVIs for the window views captured in the CIM. Preliminary experimental tests in Wan Chai District, Hong Kong confirmed that our method was highly satisfactory (R2 > 0.95) and fast (3.08 s per view), and the WVIs were accurate (RMSE < 0.042). The proposed approach can be used in computing city-scale window views for landscape management, sustainable urban planning and design, and real estate valuation.

FEATURES OF INVESTMENT IN THE REAL ESTATE MARKET

The aim of the article is to study the interaction between the rental market and the real estate market. They are considered by researchers as separate components of the real estate market in the urban development of Kharkiv. The relevance of the study is to determine the return on investment in real estate. The authors set the capitalization rate for different segments of the real estate market, namely – studya, one-bedroom, three-bedroom apartments. My research is of great importance for the prospects of modern urban economy. The question of the dependence of the rent on the cost of housing and the attractiveness of certain segments of the housing market is determined. An analysis of the cost of rent and sale for each segment and depending on the location. Factors that significantly affect the cost of sales and rent have been studied. Conclusions are made about the sustainable development of the real estate market in the city of Kharkiv and promising areas of investment. A study of the residential real estate rental market in Kharkiv was conducted. Data were collected on rental rates as of February 1, 2022 in all districts of Kharkiv. A study of the market of purchase and sale of residential real estate in Kharkov. The collection of real estate value data as of February 1, 2022 was collected in all districts of Kharkiv. Statistics on average prices in different market segments and are presented in a visual form in the table. The capitalization rate is calculated for hotels, one-room, two-room, three-room apartments. It is determined that the capitalization rate for hotels located in rural areas. Zhukovsky, Gagarin, Odesa, Oleksiyivka is about 23%. Thus, certain facilities are the most attractive for investment in the city of Kharkiv. As a result of the market research conducted by the authors, the interaction in the real estate rental and purchase and sale market within the development of Kharkiv's municipal economy was analyzed. Development trends and directions of perspective investment in each segment of residential real estate and depending on the location are determined.

Articulation work: Value chains of land assembly and real estate development on a peri-urban frontier

If the entanglements of real estate and finance capital are pivotal in ongoing urban transformations in cities of the global south, then a less visible but equally vital dimension is the process of land assembly on which residential and commercial real estate speculation and development are premised. This paper pries open the value chain of land assembly that underlies these transformations in a rapidly expanding peri-urban frontier of Bengaluru, India. Drawing on detailed interviews with land market intermediaries, operating across different scales, who were instrumental in assembling agricultural land for a large apartment complex, the paper shows how existing forms of social power and local knowledge are harnessed to create inter-scalar linkages that enable the creation and extraction of value in Indian real estate. It makes the case for understanding the economic and cultural work of intermediaries in animating land's value chain as ‘articulation work’. Finally, the paper assesses the varying forms and quantum of value that are generated and captured by different actors in the value chain, which stretches from the landowning farmer up to a major real estate company, to reflect on the micro-dynamics of speculative urbanism and agrarian urbanization.