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The development of the real estate market is conditioned by a variety of endogenous and exogenous factors. Selected factors determine the local character of the real estate market, whereas others contribute to its classification as one of the main branches of the national economy. Rapid economic growth and the search for new investment opportunitie...
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... This is a natural person holding professional qualifications in the field of real estate valuation, granted under the provisions of the Act of 21 August 1997 on real estate management. According to Polish law, a real estate valuer may prepare studies and expert opinions, which do not constitute an appraisal report, concerning the real estate market as well as real estate consultancy [Renigier-Biłozor et al. 2014]. ...
... As a consequence of the tightening of the criteria for granting mortgages, the demand in the housing market may significantly decrease which, if the supply remains constant, may lead to a marked decrease in transaction prices [59,60]. On a national scale, additionally taking into account the processes associated with the tendency to overvalue property prices [61,62], after several years of price increases in Poland, there is a real possibility of a significant decline in housing prices, while taking into account the differences in the potential of regional markets related to local regulations and socio-economic conditions [63][64][65][66]. The property market, due to its characteristics, reacts to the events described above with some delay. ...
The price of dwellings is determined by a number of attributes among which location factors are usually the most important. Comprehensive analyses of the real estate market should take into account a broad spectrum of attributes including economic factors, physical, neighborhood and environment characteristics. The primary objective of the study was to answer the question of what determinants affect transaction prices within the housing market in Poznań. The analysis was performed on the basis of source data obtained from the Board of Geodesy and Urban Cadastre GEOPOZ in Poznań. In our study, we used two research regression methods: ordinary least squares and geographically weighted regression. The estimated models made it possible to formulate specific conclusions related to the identification of local determinants of housing prices in the Poznań housing market. The results of the study confirmed that the use of the proposed techniques makes it possible to identify attributes relevant to the local market, and, moreover, the use of spatial analysis leads to an increase in the quality of the description of the characteristics of the analyzed phenomenon. Finally, the results obtained indicate the diversity of the analyzed market and highlight its ambiguity and complexity.
... However, Lentz and Wang (1998) (2017), Yakubovsky et al. (2018) have underlined that, despite the enormous number of applications, statistic data analysis has theoretical weaknesses and may not be efficient in those markets where uncertainty is high due to the unavailability of or inaccuracy of information. According to Mark andGoldberg (1988), Fletcher et al. (2000), Helbich et al. (2014) multiple regression analysis (MRA) has several problems including the presence of excessive multicollinearity among attributes, and spatial autocorrelation among residuals, diminishing the stability of regression coefficients that are relatively ineffective in weak-form efficient real estate markets (Renigier- Biłozor, 2011;Renigier-Biłozor et al., 2014;d'Amato, 2018). ...
The main aim of the paper is to systematise the terms and methodologies used in the property valuation and market analyses domain (single property or mass valuation). The need for this is justified by different semantic and procedural approaches and legal regulations in countries around the world. The research was carried out using the method of critical analysis of current state-of-art literature of the subject, valuation standards, and opinions of practitioners and experts of real estate markets available on social media. Answers of international respondents were gathered as well by using questionnaires. The paper fulfils the gap in perception and comprehension of specific terms and modern tools by entities connected with real estate domain. The clash of two extreme realities is being dealt with: on the one hand, traditional solutions based on universally accepted methods and techniques as well as faith in the infallibility and objectivity of a human analysing the real estate market dominate; on the other, modern technologies that are boldly entering. The main conclusion of the study is that entities should change perception of different automated solutions (e. g. AVM, CAMA, AAVM) as being operating in contradiction to ingrained methods and use them as an additional tool.
... Housing prices are not constant in all areas of the city, and intraurban variation of residential properties price is determined by different characteristics of the location, including urban facilities and services, environmental and socioeconomic conditions, and security and safety [6,7]. On the other hand, the property price is changing over time because of changes in endogenous and exogenous factors such as the local and national economy [8][9][10], urban policy [11], macro-economic factors such as financial crises [12], world real estate economy, and stock markets [13]. Therefore, we can conclude that location and time of residential property transactions are two of the primary components of a residential property price if all other building characteristics are constant such as the size of the building and the lot, the number of rooms, and energy system [14]. ...
The residential real estate market is very important because most people’s wealth is in this sector, and it is an indicator of the economy. Real estate market data in general and market transaction data, in particular, are inherently spatiotemporal as each transaction has a location and time. Therefore, exploratory spatiotemporal methods can extract unique locational and temporal insight from property transaction data, but this type of data are usually unavailable or not sufficiently geocoded to implement spatiotemporal methods. In this article, exploratory spatiotemporal methods, including a space-time cube, were used to analyze the residential real estate market at small area scale in the Dublin Metropolitan Area over the last decade. The spatial patterns show that some neighborhoods are experiencing change, including gentrification and recent development. The extracted spatiotemporal patterns from the data show different urban areas have had varying responses during national and global crises such as the economic crisis in 2008–2011, the Brexit decision in 2016, and the COVID-19 pandemic. The study also suggests that Dublin is experiencing intraurban displacement of residential property transactions to the west of Dublin city, and we are predicting increasing spatial inequality and segregation in the future. The findings of this innovative and exploratory data-driven approach are supported by other work in the field regarding Dublin and other international cities. The article shows that the space-time cube can be used as complementary evidence for different fields of urban studies, urban planning, urban economics, real estate valuations, intraurban analytics, and monitoring sociospatial changes at small areas, and to understand residential property transactions in cities. Moreover, the exploratory spatiotemporal analyses of data have a high potential to highlight spatial structures of the city and relevant underlying processes. The value and necessity of open access to geocoded spatiotemporal property transaction data in social research are also highlighted.
... The HW model is a typical no-arbitrage model. The singlefactor HW model assumes that the risk of the nominal short-term interest rate r N is risk-neutral, and the process is as follows [29]: ...
This paper aims to study the actual utility of real estate pricing models based on data mining and machine learning. In order to achieve this goal, this paper introduces appropriate trend estimation methods, adjusts pricing models and processes, and realizes trend estimation that changes over time to make the resulting pricing model have advantages such as dynamics, accuracy, and flexibility over the original model. Moreover, this paper proposes a real estate pricing model based on the quadratic exponential smoothing time-varying trend estimation. In addition, this paper uses the quadratic exponential smoothing method to calculate the index trend in the random process of the house price index, and performs segmentation processing on the pricing model according to the index cycle, so as to obtain the real estate pricing method under the time-varying trend. Finally, this paper adjusts the volatility parameters and the mean recovery rate to time-varying piecewise functions, uses the quadratic variation to calculate the volatility parameters and the martingale valuation method to calculate the mean recovery rate parameters, and establishes the real estate pricing model of the time-varying O–U process. Case studies show that the model constructed in this paper has good performance and has certain practical effects.
... While the impact of macroeconomic factors on the attractiveness of real estate projects has been quite comprehensively covered in the empirical literature (Duca and Ling, 2018;Renigier-Bilozor et al., 2014), the microeconomic analyses frequently suffer from being unidimensional as they mostly focus on modeling the expected rents (Ambrose et al., 2015;An et al., 2016;Plazzi et al., 2010). While the overwhelming focus on rents as one of the key drivers of anticipated investment profitability is warranted, it in no way excludes the need of an in-depth analysis of interactions between other stochastic variables underpinning financial forecasting. ...
Purpose – Relying on a unique proprietary Polish office market space database, the paper attempts to quantify the impact of buildings’ age on the financial performance of real estate assets.
Design/methodology/approach – Panel econometric modeling was utilized to disentangle the impact of buildings’ functional obsolescence and technical deterioration on their long-term financial performance.
Findings – In line with casual empiricism, our findings show a negative associative link between properties’ age and potential lease revenue. The concomitant stickiness of service charges presages a possible long-term deterioration of financial outcomes of real estate investments. While older buildings generally have higher occupancy rates, the absorption rates are found to be negatively affected by the properties’ age. On the bright side, the elasticity of vacancy rate with respect to rental rates is found to decrease as buildings get older.
Further, the rent differential is confirmed to be more pronounced in higher age properties hinting at an existing potential for price discrimination, which may at least partially compensate for stagnant rents.
Originality/value – Our empirical results confirm the properties’ age to be a statistically significant factor in shaping the long-term performance of real estate assets, which should be better accounted for in financial projections for real estate developments.
... This problem has been studied by Adams and F€ uss (2010), based on panel data covering 15 countries over 30 years. For comparison, Renigier-Biłozor et al. (2014) presented the importance of the macro environment for the condition of the local housing market. ...
The aim of this paper is to distinguish a number of factors that allow for a better understanding of investment process management in the housing construction industry. The research work that we performed consisted in conducting a questionnaire survey. A total of 192 Polish companies dealing with housing construction took part in the survey. The collected questionnaire responses were then subjected to a thorough analysis and interpretation, with the use of a method called exploratory factor analysis (EFA). In a nutshell, our analysis consisted in reducing the number of survey variables (73) in order to identify a few pivotal factors (4) with the greatest impact on investment processes management in the field of residential construction in Poland. These factors include: the activity of companies in the market environment (1), pro-social policy of the state (2), highly advanced technologies (3) and the use of appropriate market relations (4). In our study, we aim to show how successful construction processes are perceived by industry professionals. The scientific method that we used allows for assignment of a certain order of priority to specific groups of questionnaire variables, dependent on the eigenvalues-related percentage of explained variation.
... Fuzzy logic theory is currently used in many sciences and is often applied as the main support tool in decision-making systems (e.g. Bello & Verdegay, 2012;Chi, Yeh, & Lai, 2011;Renigier-Biłozor, 2011;Renigier-Biłozor, Wiśniewski, Biłozor, & Kaklauskas, 2014;Zavadskas & Turskis, 2011). It is a common situation that real estate analysts (appraisers) have problems with insufficient information to carry out econometric modelling or they have problems determining the causal relationships between real estate variables. ...
... In the approach based on the fuzzy set theory, decisions are made based on "raw data" in line with the principles of Boolean logic, that is, a given decision (real estate value) is made if given conditions (real estate attributes) are fulfilled. The literature analyses indicated that hybrid solutions have a number of advantages in automated property valuation approaches (D'Amato, 2008;McCluskey et al., 2013;Renigier-Biłozor et al., 2014, 2019. ...
This article proposes the possibility of applying fuzzy logic theory to perform the tasks of determining the market value of agricultural lands. These tasks are of a multi‐criteria character, as multiple factors are taken into consideration during the land value valuation process. The market value of agricultural land plots, calculated using fuzzy logic methods, can provide a basis for further use in the processes that are directly related to their turnover, that is, during auctioning, setting of a land tax, determining of the value of pawn in the land bank. Methodic approach to the determination of the market value of agricultural lands with the application of the methods of fuzzy logic and the package Fuzzy Logic Toolbox of the computing system Matlab is universal. It can be used for assessment of the value of a land plot with any number of indices, having no crisp mathematic model. The proposed method is particularly useful for countries where the agricultural real estate market is still in its early stages of development and will contribute to making it more transparent and thus it can be a significant tool supporting the sustainable development of the agricultural real estate market. Agricultural land market is a vital ingredient of the system for sustainable development of rural areas.
... Currently, the apartment market is developing strongly and is becoming somewhat a city-forming factor (Yai-Hungh and Chun-Kei, 2006;Renigier-Biłozor and Wiśniewski, 2014), especially in the seaside regions or places with significant natural and tourist (historical) values. Natural qualities are particularly valued, i.e. the views (landscapes) and the proximity of nature, creating an added value that attracts investors to purchase apartments and perform development activities. ...
... Modern real estate markets respond more flexibly to macroeconomic changes. These reactions are driven not only by changes in the real estate sector, but mainly by macroeconomic and microeconomic data received from other markets (Yai-Hungh and Chun-Kei, 2006;Wolniak and Skotnicka-Zasadzień, 2018;Renigier-Biłozor and Wiśniewski, 2014). ...
