Translocality on the real estate market: A new extended approach

Wiśniewski, R.; Brzezicka, Justyna

doi:10.1016/j.landusepol.2020.104731

Cited by 7 publications

(4 citation statements)

References 36 publications

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“…Summarising the overall convergence analysis, it should be stressed that all research methods used in this study rejected the possibility of its occurrence across the Polish residential rental markets, which is in line with other analyses studying convergence or differentiation in the Polish real estate market; see, for example, Żelazowski ( 2019 ), Gnat ( 2016 ), Dittmann ( 2014 ), Wiśniewski and Brzezicka ( 2020 ), Tomal ( 2019a ), Tomal and Gumieniak ( 2020 ).…”

Section: Resultssupporting

confidence: 83%

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

Tomal

2021

Empir Econ

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The aim of this paper is to test for overall and cluster convergence of housing rents across Polish provincial capitals and to identify drivers of convergence club formation. In order to achieve the goal of the study, several novel convergence tests were used, including the Kong et al. (J Econom 209:185–207, 2019. https://doi.org/10.1016/j.jeconom.2018.12.022) and Phillips and Sul (Econometrica 75:1771–1855, 2007. https://doi.org/10.1111/j.1468-0262.2007.00811.x) approaches. Moreover, club convergence analysis was carried out in four different configurations, varying in the technique of trend component extraction from the data. In particular, three well-known methods of time series decomposition were used, i.e. the Hodrick–Prescott, Butterworth and Christiano–Fitzgerald filters, as well as the most recent boosted Hodrick–Prescott filter. The results indicated that rental prices across the studied cities do not share a common path in the long run. It is possible, however, to identify convergence clubs where rents are moving towards a club-specific steady state. Detailed analysis of the structure of estimated clusters showed that data filtering using the boosted Hodrick–Prescott method leads to the most reliable allocation of cities to convergence clubs. Moreover, the estimation of logit models revealed that the likelihood of any two cities belonging to the same convergence club depends mainly on similar levels in terms of the unemployment rate, housing stock, city area, and the number of students. Finally, recommendations for local and national policy-makers concerning the development of the rental market have been formulated, particularly in the areas of urban land-use planning policy, housing legislation and public–private partnerships.

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Section: Resultssupporting

confidence: 83%

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

Tomal

2021

Empir Econ

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“…Each group of variables can directly or indirectly influence the functioning of the entire market mechanism because real market transactions are conducted based on a theoretically infinite amount of information and, consequently, an infinite number of variables. The infinite set of data is composed of information that is directly acquired by market participants (each market participant can process a potentially infinite set of directly observable data) and information that reaches market actors indirectly (each market participant can process a potentially infinite set of data from the surrounding environment) (Wi sniewski and Brzezicka, 2020).…”

Section: Methods and Data 41 Glocal Real Estate Market Indexmentioning

confidence: 99%

Glocal real estate market: evidence from European Countries

Wiśniewski

Brzezicka

2020

JERER

Self Cite

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Purpose This paper aims to analyse globalisation, localisation and glocalisation on the real estate market and define the characteristic features of a glocal real estate market (GREM). The GREM involves real estate properties and real estate products, as well as linking the local and global dimensions of real estate market. Further aims of the study were to provide a methodology for developing the glocal real estate market index (GREMI), and compare selected European markets by analysing their glocalisation potential. Design/methodology/approach A novel method of identifying and assessing the GREM was prepared in the work. The methodology provides tools for calculating the GREMI. This is an index based on a few dozen variables from various thematic scopes, describing the glocalisation potential of a selected market, calibrated to a range <0, 1>. GREMI values were calculated for 12 countries, which accessed European Union (EU) in 2004. The sample covers period from 2004 to 2017. Findings The study shows that the GREMI continues to increase in all countries over time and the results are becoming synchronised. Romania is a country with the highest number of minimum GREMI values in all years (2004–2017). The highest values of the GREMI were determined in Estonia over the period of nine years (2004–2006, 2008 and 2013–2017). Research limitations/implications The prepared index may be applied to analyse different real estate markets, though the necessity to select an identical set of variables for analysis to allow for comparing between markets is a limitation for applying the method. The actual selection of variables is also a study limitation, which was of an opening nature to research in this scope and may be disputable. Originality/value This paper provides the original methodology of the GREMI index for countries joining the EU from 2004 onwards.

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“…One of the key problems in real estate market analyses is the identification of real estate characteristics (their occurrence, extent, and relevance) affecting the reasoning [13][14][15][16][17]. The accurate identification of problems and limitations in the area of real estate information analyses determines the direction of the search for solutions that better reflect market reality.…”

Section: The Problem Of Real Estate Feature Significance Assessmentmentioning

confidence: 99%

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

Walacik,

Chmielewska

2024

Sustainability

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As the global imperative for sustainable development intensifies, the real estate industry stands at the intersection of environmental responsibility and economic viability. This paper presents a comprehensive exploration of the significance of sustainable solutions within the real estate sector, employing advanced artificial intelligence (AI) algorithms to assess their impact. This study focuses on the integration of AI-powered tools in a decision-making process analysis. The research methodology involves the development and implementation of AI algorithms capable of analyzing vast datasets related to real estate attributes. By leveraging machine learning techniques, the algorithm assesses the significance of energy efficiency solutions along with other intrinsic and extrinsic attributes. This paper examines the effectiveness of these solutions in relation to the influence on property prices with a framework based on an AI-driven algorithm. The findings aim to inform real estate professionals and investors about the tangible advantages of integrating AI technologies into sustainable solutions, promoting a more informed and responsible approach to industry practices. This research contributes to the growing interest in the connection of the real estate sector, sustainability, and AI, offering insights that can guide strategic decision making. By implementing the random forest method in the real estate feature significance assessment original methodology, it has been shown that AI-powered algorithms can be a useful tool from the perspective of real estate price prediction. The methodology’s ability to handle non-linear relationships and provide insights into feature importance proved advantageous in comparison to the multiple regression analysis.

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Translocality on the real estate market: A new extended approach

Cited by 7 publications

References 36 publications

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

Testing for overall and cluster convergence of housing rents using robust methodology: evidence from Polish provincial capitals

Glocal real estate market: evidence from European Countries

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

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