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When missing reliable comparables, estimating inappropriately is a high risk in the use of both market-oriented and income approach methods. Therefore, it is useful to identify effective alternatives in accordance with the estimation method to arrive at the estimated value in the absence of comparables. This paper examines the use of the asking price for estimating the market value of a fruit tree orchard, missing comparable data of similar assets. The analysis was conducted by considering two different scenarios. In the first, asking prices from the same segment of the land to be estimated were used in two market-oriented appraisal methods: the General Appraisal System (GAS) and the Nearest Neighbors Appraisal Technique (NNAT). In both these approaches, market prices were replaced with detected asking prices. The second scenario was based on the use of the Remote Segments Approach (RSA). The comparison was conducted between the market segment of the fruit orchard to be valued and other comparison market segments, consisting of three other species of fruit trees, grown in the same area where the fruit orchard to be estimated is located. The results showed that in the first scenario, the estimated value appeared to be unreliable and excessively high compared to actual market conditions. Using the segment comparison method, which applies asking prices for the purpose of determining the capitalization rate, produced more reliable results. The appraisal also appeared more objective, transparent, and consistent with valuation standards. In the presence of similar limiting conditions, RSA can be an effective support to the activity of the appraiser in the valuation process of agricultural land. [ABSTRACT FROM AUTHOR]

In recent years, machine learning algorithms have been used in the mass appraisal of real estate. In this study, 5 machine learning algorithms are used for residential type real estate. Machine learning algorithms used for mass appraisal in this study are Artificial Neural Networks (ANN), Random Forest (RO), Multiple Regression Analysis (MRA), K-Nearest Neighborhood (k-nn), Support Vector Regression (SVR). To test the study, real estate data collected from the central districts of Ankara, were used. The main purpose of this study is to find out which machine learning algorithm gives the best results for the mass appraisal of real estates and to reveal the most important variables that affect the prices of real estate. According to the results obtained for the city of Ankara, it was observed that the best algorithm for mass appraisal is RF in residential-type real estates, followed by the ANN, k-nn, and linear regression algorithms, respectively. According to the results obtained from the residential real estate, it was concluded that heating and distances to places of importance had the greatest effect on the value.

The paper aims to promote a model for determining residential land prices within a suburb of Hue city, Vietnam to improve the efficiency of land price determination and management. The study conducted surveys of 27 variables of 200 residential land plots in order to run the hedonic model using SPSS 26.0 software. The result developed a model that explained 78% of the change in land prices by incorporating five factors: area of land, width of road attached to the land plot, distance to hospital, ability to generate cash flow and planning information. Meanwhile, the writers also produced a map of residential land prices in the 2022 suburban areas of Hue city, Vietnam. This is a helpful tool in land market consulting and land valuation procedures.

This research article explores the valuation of mixed-use developments and their impact on urban planning and city regeneration. The study introduces a Multi-Criteria Decision Making (MCDM) methodology to analyze complex buildings developed in Shanghai from 2009 to 2019. Two MCDM appraisals are offered in different developments using three groups of key indicators that served as benchmarks for other Chinese clusters and global megacities. The article addresses two primary research questions: how mixed-use assets can be assessed using MCDM, and what the key performance indicators and factors contributing to the success of mixed-use developments are. The findings highlight the importance of connectivity, previous real estate experience, ESG strategies, international branding, architectural design, financial metrics, and adaptability of the real estate industry in evaluating mixed-use assets. The study provides insight to stakeholders involved in real estate development, including urban planners, developers, and investors, enabling them to make informed decisions and improve sustainable practices. The research also highlights the importance of considering ESG principles, community benefits, and long-term strategies when assessing mixed-use developments to drive social change and contribute to urban regeneration.

The scale of environmental pressure caused by the construction sector has prompted a search for new technical solutions to minimize the negative impact of this part of the national economy on the environment. The drive to evaluate the adopted solutions has led to the creation of building assessment systems - environmental certificates.

The pandemic, followed by the Russian aggression against Ukraine, caused rapid changes in the economy. European countries experienced unprecedented price increases, which resulted in a significant increase in the cost of capital. This resulted primarily in limited access to capital and a significant reduction in investments in the real estate market. In addition, investors began to withdraw capital from investments in the real estate market to other assets, encouraged by their rising rates of return. The article presents how the indicated circumstances translated into the financial efficiency of companies from the Real Estate sector. Listed companies of the European Economic Area in the years 2019-2022 were analyzed. Changes in the main accounting measures and market measures for individual countries as well as the characteristics of real estate market participants were analyzed.

The research objective of the article was to assess the potential of residential property in Poland as an inflation hedge investment. The study was conducted using innovative measures of the level of inflation hedging. The study was made for Poland’s six largest local residential markets, for two types of investments, for different investment horizons (from 6 to 15 years). The research period adopted was: 3Q2006-4Q2022. In all cities, investments providing only capital gains allowed an attractive inflation hedging level to be achieved. Investments that additionally included rental offered a high inflation hedging level. The variation in the six cities studied in terms of inflation hedging through housing investment was found to be very low. The question of how extending the investment horizon affected the inflation hedging ability was not firmly answered. Frequently, the extension of the investment horizon has been accompanied by an increase in the level of hedging.

The aim of this research was to analyze the effects of revitalization activities performed in a selected historical urban layout using the mixed method in which statistical analysis was supported by Geographic Information System (GIS) tools on the price level of residential premises on the secondary market. The subject of the analyses is “Old” Nowa Huta (Krakow, Poland), which was designed as an ideal independent city in the mid-20th century. The analysis covered the period from January 1, 2007 to December 31, 2020.

The COVID-19 pandemic has disrupted economies and industries worldwide, including the real estate sector. This study aims to assess the effects of the pandemic on commercial real estate prices in the Malaysian market. By examining variations in property types and considering key factors influencing pricing, the research contributes to a better understanding of the pandemic’s impact on the real estate market. To analyze the effects of the COVID-19 pandemic on commercial real estate prices, a mixed-method approach was employed. The study combines data from direct real estate indices, which provide insights into property prices based on transaction data, and listed real estate, which includes publicly traded real estate investment trusts (REITs). By utilizing both sources, a comprehensive analysis of the market is achieved. The sample for this study consists of commercial real estate properties in the Malaysian market. It includes properties from various sectors, such as retail, hospitality, and office buildings. The sample is representative of the overall market and captures the different property types affected by the pandemic. The analysis begins by comparing direct real estate indices to highlight the limitations and potential biases associated with using these indices. It then examines the variations in commercial real estate prices during the COVID-19 outbreak, focusing on the different property types. Statistical techniques, such as regression analysis and trend analysis, are employed to identify patterns and quantify the impact on commercial real estate prices. The study’s main findings reveal that the retail and hospitality sectors experienced the most significant impact on commercial real estate prices during the COVID-19 pandemic. These sectors witnessed a substantial decline in property values due to restrictions, lockdown measures, and reduced consumer demand. Office buildings, although moderately affected, also experienced some decline in prices. This research contributes to the existing literature on the effects of the COVID-19 pandemic on commercial real estate prices, specifically in the Malaysian market. By combining data from direct and listed real estate sources, the study provides a comprehensive understanding of the variations in property prices across different sectors. The findings offer valuable insights for real estate investors, policymakers, and industry professionals in adapting to the changing market conditions and making informed decisions regarding commercial real estate investments. In conclusion, this article sheds light on the effects of the COVID-19 pandemic on commercial real estate prices in the Malaysian market. The research methodology, which combines data from direct and listed real estate, allows for a comprehensive analysis of property variations among different sectors. The findings emphasize the significant impact on the retail and hospitality sectors, while showing office buildings to have been moderately affected. It also provides important insights for stakeholders in the real estate industry, enabling them to make informed decisions and develop appropriate strategies.

There is a belief among investors that real estate is an excellent way to protect capital from depreciation due to inflation. Research does not provide a clear answer as to whether this investors’ belief is correct, but some approaches indicate that simple econometric methods are not able, especially in the short term, to clearly indicate the existence of a relationship between inflation and property prices (Fogler, 1984). The purpose of the study –was to find the relationship between residential real estate prices and inflation in the Polish economic conditions. Methodology of the study - the study used cointegration analysis with the Engle - Granger test. The research was carried out in the period from the first quarter of 2009 to the fourth quarter of 2021. The real estate hedonic indices calculated by NBP (National Bank of Poland) and the actual and forecasted inflation rates published by the GUS (Central Statistical Office) and the NBP (National Bank of Poland) were used in the research. The result - the analysis led to a negative verification of the research hypothesis, as it could not be proved that real estate prices were related to the level of inflation during the researched period. Originality/value - the study fills a gap in the Polish market regarding the analysis of the possibility of using real estate as a hedge against inflation. The research concerned only the Polish market, but this issue has not been taken up for years, also in mature economies.

This paper analyzes the long-run determinants of US outward FDI (OFDI) stock, focusing mainly on the Euro Area (EA) for the period 1985–2019. We consider a sample of 54 developed and emerging host countries representing over 70% of the total US OFDI stock. We aim to capture different determinants by country groups zooming in on the European Union (EU). We implement a Dynamic Common Correlated Effects Pooled Mean Group (DCCEPMG) estimator for this aim. Our econometric approach is especially suited for analyzing integrated economic areas as it allows us to deal with cross-section dependence (CSD), non-stationarity, structural breaks, and slope homogeneity usually present in large panel data. Our main results suggest that horizontal (HFDI) and vertical (VFDI) strategies coexist for all country groups. However, as we move towards more homogeneous groups, the results show the greater importance of VFDI. Additionally, we find that some variables have a common long-run effect on US OFDI, especially for smaller and more homogeneous groups. [ABSTRACT FROM AUTHOR]

We show that a contraction of mortgage supply after the Great Recession has increased housing rents. Our empirical strategy exploits heterogeneity in MSAs' exposure to regulatory shocks experienced by lenders over the 2010-2014 period. Tighter lending standards have increased demand for rental housing and have led to higher rents, depressed homeownership rates and an increase in rental supply. Absent the credit supply contraction, annual rent growth would have been 2.1 percentage points lower over 2010-2014 in MSAs where lending standards rose from their 2008 levels.

Investors are increasingly allocating capital into the real estate market through indirect investment vehicles such as REITs. There are currently no classic REITs in Poland, but given the experience of other countries and the expectations of Polish investors, an act is being prepared to regulate their functioning. The introduction of legal regulations regarding REITs has not always resulted in successful proliferation of these vehicles in each country. The German market for G-REITs is such an example, were only six G-REITs have evolved. There is also the example of the market in the United States, where extremely dynamic development of such institutions has been observed, especially in the recent years. At the end of 2019, 219 institutions of this type were operating on the US market.

The real estate market in areas with many socio-economic activities needs to be strictly managed due to the difference between the market price of urban land and the price of land set by the state. This study identifies and analyzes the influence of some factors on land prices in peri-urban areas to develop land pricing standards consistent with the price level in Nghe An province. The study surveyed 362 land users and 200 samples of successfully transferred properties in the study area. Based on the multivariate regression method, the study builds a residential land price model and calculates the market price of residential land. The authors also established a map of land value areas to help State agencies manage land prices effectively. The research serves as a basis for State agencies to study the formation and development of the real estate market to develop appropriate land price management measures.

The paper presents a proposal for an approach to the valuation of forest, wooded and bushy real estate located in cities, which allows for the assessment of the impact of natural, protective and landscape factors on the value of this type of real estate. The main problem in the valuation of this type of real estate is the correct estimation of the impact on the value of the non-production factors described above. Considering the above, the main goal of the study was to identify the factors influencing the prices and value of forested, wooded and shrubby properties located in urbanized areas. The supplementary goal was to confirm the suitability of the methods and statistical models used in the study for similar measurements. By implementing the adopted goals, the article presents an analysis of the impact of these factors on the prices and value of real estate. The study covered the southwest part of the city of Kraków, located between the Vistula River and the Kraków-Rzeszów railway line in the north and east, and the southern and western border of the city. Urban forests perform mainly social functions, constituting only a marginal source of wood raw material. The results of the study showed that, in the case of similar properties, prices are significantly influenced by factors such as location, type and nature of the surroundings, form of access to the road, landscape and recreational values, manner of use and development status, as well as the permissible form of development, which is a measure of the profitability of timber production. The work ended with a discussion on the results and proposed directions for further research.

In this article, we use tests of explosive behavior in real house prices with annual data for the case of Australia for the period 1870–2020. The main contribution of this paper is the use of very long time series. It is important to use longer span data because it offers more powerful econometric results. To detect episodes of potential explosive behavior in house prices over this long period, we use the recursive unit root tests for explosiveness proposed by Phillips et al. (2011), (2015a,b). According to the results, there is a clear speculative bubble behavior in real house prices between 1997 and 2020, speculative process that has not yet been adjusted.

Variance in the cost method of valuation as caused by certain variables is objectionable in the profession of estate surveying and valuation at both local and international best practices. The study aimed at determining the variables for the variance in the application of the cost method of valuation for estate surveying and valuation practice in Uyo. The sample of the population used for the research comprised 110 estate surveyors in Uyo. The survey method was used for the research. The sampling technique was purposive sampling. The data were analyzed using standard deviation and analysis of variance (ANOVA). The findings showed that depreciation rates of σ2 =113.974 and σ = 10.676 were over 60% of the total variance of values among estate surveyors and valuers. The construction rates and errors in manual measurements and computation of areas, volumes and dimensions showed σ2 = 6.004 and σ = 2.4503, which accounted for 15% of total variance. The study recommends the use of a regional-based scientific approach to measure depreciation for consistency and high precision. Automated techniques, such as GPS, AutoCAD, Google Earth pro, are recommended to minimize variance in measurements.

Most of the cities in Iran have experienced very rapid development. The urban population in the last decade has been increased by migration, and cities in Iran are faced with many problems. Housing is becoming one of the major problems, and standard housing indices have taken an important place in urban planning to provide good conditions for better urban planning. Region 6 of Tehran municipality is home to a large portion of upper-middle social class people for whom owning a house is more than merely a place to live. The aim of the research was to analyze qualitative and quantitative indices for Region 6 of Tehran municipality. The study is based on analytical and descriptive methods. The secondary data collected from the latest Iran census report in 2016 and composite methods used to measure the special effects of changes in population size, growth rate, and indices of quantitative and qualitative assessment are wide-ranging housing which was analyzed based on the t-test, correlation test and regression with SPSS and GIS software. GIS software is used as an effective tool for generating maps to better understanding the behaviors of residents in a neighborhood. The result shows that Region 6 of Tehran is among the areas of serious urban decline and neighborhoods in the neighboring regions are influenced by the activities of other bordering neighborhoods.

Investment in REITs has become significant in recent years due to the stability and sustainable performance of the investment. A study on the management perspective is very important but this perspective is very limited. Asset management will derive from the profit optimization of the investment. Therefore, it is important to assess asset management strategies to ensure the sustainable performance of the assets. This paper aims to assess asset management strategies among matured REIT companies in developed countries in comparison with Malaysian REIT companies from the perspective of the managers. This research employed qualitative analyses by using content analysis techniques. A total of 41 REIT companies from the United States (US), Japan, Singapore, Australia and Malaysia were assessed. The analyses focused on the similarities and differences between the strategy framework identified in the literature review and the strategies adopted by global REITs and Malaysian REITs under review. The study will enable all REIT stakeholders to become well-informed on global REIT asset management that will derive the maximum profit from the investment. The success of developed countries’ REITs will provide guidelines for Malaysian REITs to adopt the best practice of strategic asset management from REITs in mature markets. Furthermore, this study is one of few papers that have discussed the issue of strategic property investment, particularly focusing on REITs.

This paper provides an overview of the challenges of management of facilities at public universities in Africa. Results reveal that: poor condition and the overcrowding of facilities, limited skills and capabilities of facility management departments, and lack of financial resources are the main challenges which the management of facilities at public universities in Africa faces. In worse situations, these problems have adversely affected the quality of the learning and teaching environment at the institutions and also threatened their existence. Prioritization of funding for the provision and improvement of quality facilities at public universities by governments, employment of well qualified and trained staff in the facility management departments at the public universities, and creation of innovative and smarter public-private partnerships aimed at the improvement of existing facilities and provision of new ones were identified as the key solutions that can be implemented to address the challenges that public universities in Africa are facing in relation to facilities. Findings will support public universities in Africa to address challenges of management of their facilities so that they can continue to achieve their intended objectives of offering high quality higher education, research and community engagement in order to accelerate socio-economic development of their countries on the continent in the future.

The integration of financial markets is an ongoing process throughout the world. Research shows that, from Australia through Europe to the United States, the capital and real estate markets are integrating, influencing each other. Although this process seems obvious, only research can show whether it actually occurs. Identifying these relationships is important for analyzing the entire market. Many methods, such as estimating the cost of equity, have been developed with the stock market in mind. Meanwhile, real estate valuation requires the cost of equity. Market integration is the rationale for using equity market methods on the real estate market.

The hidden vacancy rate reflects the adjustments of the market vacancy rate that may occur in the future, in the event of a change in market conditions. Its occurrence results from the fact that the current level of rented office space reflects the demand based on past levels of rent and past predictions of changes in the tenants’ demand for space during the term of the lease. Thus, the level of total, occupied office space at given moment does not result from demand based on the current market rent. This is the result of the duration of lease agreements concluded for more than one period. The hidden vacancy rate is also related to the costs of searching for office space that meets the specific criteria of tenants, removal costs and office space adaptation costs. The hidden vacancy rate cannot be observed in the market, but can be determined based on available market data.

The paper delivers original data on specialization in property valuation services in Poland. Its aim is to identify relatively homogeneous groups of property appraisers taking into consideration the scope of services performed by them and the types of clients served. Based on the survey results, it was possible to indicate major models in property valuation services consistent with market applications, which allows us to verify the thesis on specialization in doing business in property valuation.

One of the key determinants of the quality of real estate mass appraisal is the algorithm used for conducting such an appraisal. Other determinants include detailed methodological and substantive solutions within the scope of a selected, applied algorithm. This article is dedicated to one of the major stages of the process of land real estate mass appraisal with the use of the Szczecin Algorithm of Real Estate Mass Appraisal (SAREMA), namely defining and determining the so-called elementary terrains. The paper aims to present the methods for designating the boundaries of elementary terrains, the manner of defining their number and size and, consequently, the number of real properties that will be covered by an automated process of mass appraisal in a given area.

Using data on a sample of small Iowa towns consistently collected over two decades, we investigate how agglomeration economies, social capital, human capital, local fiscal policy, and natural amenities affect new firm entry. We find that human capital and agglomeration are more conducive to new firm entry than are natural amenities, local fiscal policy, or social capital. The impact of local fiscal policy is too small to overcome the locational disadvantages from insufficient endowment of human capital and agglomeration. A rural development approach that encourages firm entry in rural towns with the largest endowments of human capital and market agglomeration would be more successful than trying to raise firm entry in every town. [ABSTRACT FROM AUTHOR]

Students as property tenants are an underestimated and understudied aspect of the market. To date, there has been a widely held opinion that student decisions in the property market and their scope are mostly limited to the area of academic centres. It is estimated that, in Poland, over a million students enter into tenancy agreements annually, most of which are in the private property market. Such wide demand is directed at selected, diverse locations and dwellings of particular characteristics, satisfying the preferences of young people at a specific moment of their lives (the so-called “emerging adults”). The present article aims to present answers to the question of what motivates students who undertake transactions in the property market. Information on the characteristics of the sought after properties was obtained by way of surveys, leading to the generation of a set of the most important features determining the attractiveness of properties from the point of view of the analyzed population. The phenomenon of the popularity of particular locations (urban estates) has also been examined in detail.

Two problems appear to be most topical in conjunction with mortgage valuation practices during an economic crisis: the assessment of sustainable long-term mortgage values and the assessment of liquidation discounts to prevailing market values which would provide for the most advantageous liquidation/quick sale strategy. This paper addresses the latter issue, which has traditionally proven intractable to analytical modeling. Apart from reviewing some research devoted to the subject of liquidation value modeling, predominantly from the Eastern European perspective, where this issue has, for years, commanded a particular economic interest, this paper synthesizes the best features of this research and builds on it to propose its own model, which lays equal emphasis on both the sellerside and demand-side perspectives. The first perspective accounts for the financial interests of a lender in forced sale disposals, while the latter perspective engages economic analysis on the side of market feasibility of identified efficient lender disposal strategies. By negotiating both perspectives, an optimal analytic solution to the issue of liquidation value discounts can be obtained. This is achieved by what we call a SI-MI framework which is developed throughout the paper.

One of the basic problems in the comparison-based property valuation process is to determine the influence of property attributes on their price differential. Due to the qualitative character of the majority of property attributes as well as to the distributions of both prices and attributes, their effect on the price differential is increasingly often assessed by means of non-parametric statistical methods. As a tool for determining the effect of attributes on prices, many authors propose parametric methods, in particular multiple regression models. The study presents a comparison of the results of property market attribute weight estimation obtained by means of the Spearman rank correlation coefficient with the ceteris paribus adjustment and the multiple regression model based on a set of transactions with built-up land property. In both of the analyzed methods, qualitative variables were modeled with the use of the Osgood semantic differential scale. The results of the analysis show the equivalence of the applied methods. Property attribute weights calculated using the method based on the rank correlation coefficient with the ceteris paribus adjustment and the multiple regression model, both with the same level of relevance, showed almost identical values. This indicates that both parametric and non-parametric methods can be used to estimate weights.

The main aim of this paper is to identify differences between Polish communes as regards their revenues from property taxes. To this end, we distinguished and described types of communes with similar configurations of features under analysis (incomes from real property tax, agricultural tax and forest tax). In the research procedure, we applied methods of multidimensional analysis, with particular emphasis on cluster analysis. The research was conducted on the basis of aggregated (to eliminate random fluctuations) values of income from properties in the years 2013-2015. On the basis of typological classification, we distinguished six clusters (groups) of communes of different quantitative characteristics of budget revenues from property taxes. We identified specific regularities in the distribution of the distinguished commune types.

The article presents the results of research into the appraisal of the usefulness and effectiveness of passive methods of robust estimation in real estate market analysis. Two methods are considered, i.e.: Baarda's and Pope's. The research is based on a database of flats sold in Kraków in 2015.

Regression methods can be used for the valuation of real estate in the comparative approach. However, one of the problems of predictive modelling is the presence of redundant or irrelevant variables in data. Such variables can decrease the stability of models, and they can even reduce prediction accuracy. The choice of real estate’s features is largely determined by an appraiser, who is guided by his/her experience. Still, the use of statistical methods of a feature selection can lead to a more accurate valuation model. In the paper we apply regularized linear regression which belongs to embedded methods of a feature selection. For the considered data set of real estate land designated for single-family housing we obtained a model, which led to a more accurate valuation than some other popular linear models applied with or without a feature selection. To assess the model’s quality we used the leave-one-out cross-validation.

The aim of this paper is to infer the spatial extent of agglomeration economies for the creative service industries (CSI) in Barcelona and its relationship with firm performance controlling for urban characteristics and demand factors. Using micro-geographic data from the mercantile register for firms between 2006 and 2015, I estimated the effect of intra-industry and inter-industry agglomeration in rings around location on productivity in Barcelona. The main results are: (1) for CSI, at a micro-spatial level, localisation economies are important within the first 250 m; (2) for non-CSI, having employees in the CSI in close proximity (250–500 m) enhances their productivity; (3) for symbolic-based CSI firms, localisation economies—mainly understood as networking and/or knowledge externalities—have positive effects on TFP at shorter distances (less than 500 m), while for the two other knowledge-based CSI (i.e. synthetic and analytical) localisation economies seem not to be so important; and (4) market potential does not offset localisation economies for CSI. These results strongly suggest the importance of agglomeration externalities in CSI, which are strongly concentrated in the largest cities. [ABSTRACT FROM AUTHOR]

This study examined factors that influence the tenure choices of households in different counties and cities of Taiwan. Data collected in the Housing Status Survey by the Construction and Planning Agency of the Ministry of the Interior were analyzed using hierarchical generalized linear modeling (HGLM). The study designated the household sector as a unit at level 1 and counties and cities as a unit at level 2, with the difference among the counties and cities accounting for 9% of the total variation in rental and purchase decisions. Based on the empirical results, tenure choice was positively and significantly affected by such level-1 factors as gender, age, educational level, area per capita, number of rooms per capita, private loans, and permanent income. The level-2 attribute variable, the housing price to income ratio, had a significant negative effect on tenure choice; a higher ratio of housing price to income resulted in a higher preference among households toward leasing in their lease-or-buy decisions. With regard to the forecast ability comparison, the hit rate of HGLM (90.10%) was higher than that of the binary logistic regression model (87.26%). In terms of the forecasting accuracy evaluated using four measures of association, HGLM outperformed the traditional binary logistic regression model. Based on tenfold cross-validation, HGLM also showed a better hit rate than the traditional binary logistic regression model, meaning that the evaluation results had both robustness and reliability. [ABSTRACT FROM AUTHOR]

The aim of this article is to show the accessibility of real estate by transportation as a factor that significantly determines the decision to acquire it. Direct access to a public road, or access to an internal road that provides communication with the public road, are a factor affecting the value of real estate. In addition, this factor is taken into account in the process of changing the function of the area, especially in determining zoning and land use. The decision of purchasing real estate often depends on transportation accessibility, because it has an impact on developing the selected plot.

We compare the types of loans and their rates of returns for domestic versus offshore small and mid-sized private real estate credit funds. The data indicate offshore private credit funds issue smaller and subordinated loans to residential projects. Offshore lenders prefer projects in developed Asian markets, and obtain higher rates of return even after controlling for other things such as loan size, seniority, and borrower location. Our findings suggest the presence of pronounced segmentation across real estate lending markets in Asia as offshore lenders are not a substitute for domestic capital. [ABSTRACT FROM AUTHOR]

We develop a location analysis spatial model of firms’ competition in multi-characteristics space, where consumers’ opinions about the firms’ products are distributed on multilayered networks. Firms do not compete on price but only on location upon the products’ multi-characteristics space, and they aim to attract the maximum number of consumers. Boundedly rational consumers have distinct ideal points/tastes over the possible available firm locations but, crucially, they are affected by the opinions of their neighbors. Proposing a dynamic agent-based analysis on firms’ location choice we characterize multi-dimensional product differentiation competition as adaptive learning by firms’ managers and we argue that such a complex systems approach advances the analysis in alternative ways, beyond game-theoretic calculations. [ABSTRACT FROM AUTHOR]

Abstract We study the relationship between the excess returns of REITs and volatilities of macroeconomic factors in developing markets (Bulgaria and South Africa) and a ‘benchmark’ developed market (USA). As expected, our results generally indicate that conditional volatilities of macroeconomic risks, extracted through the GARCH (1,1) process, are time-varying. GARCH coefficients are largely significant for excess returns and retained principal components implying conditional time-varying volatility. We use the GMM to examine the linkage between volatilities of macroeconomic variables and REITs returns. The general result here is that macroeconomic risk cannot explain excess returns on REITs. However, we document a positive relationship between variability in REITs returns and the real economy for the US. US REITs portfolio managers and investors should be wary of fluctuations in these variables as they may accentuate volatility in REITs returns. [ABSTRACT FROM AUTHOR]