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The study used Google search query data on real estate interest for several countries in the Baltic area. The dynamics of public interest in housing have been compared to the dynamics of the COVID-19 infections in Lithuania, Latvia, Poland, and Sweden. This study uses the Vector autoregressive (VAR) model to forecast such time series. VAR is a multivariate linear time series model in which the endogenous variables in the system are lagged functions of the values of all endogenous variables. The increase in COVID-19 infections negatively affected society’s interest in housing. The study used Google Trends and R software.

Motives: Using Points-of-Interest (POIs) data and GIS software, the spatial heterogeneity of different types of accommodation could cheap, easily and quick be analyzed. Aim: The use of kernel density estimation (KDE) of Points-of-Interest data to shown spatial distribution of different types of accommodation in Poland. Results: There is a close relationship between the type of accommodation and the type of tourist attraction.

The COVID-19 pandemic represents a combined supply and demand shock to the financial and housing market but also an unusual negative shock in terms of the health of society (households) and national economy. The fall in housing demand was initially assumed together with price decreases as a consequence of the uncertainty of the health of society, significant falls in stock markets and corporate solvency. However, the results of research in selected Polish cities do not indicate such a significant market recession. This article examines the housing price dynamics and forecasting in Polish cities during the COVID-19 pandemic. The TRAMO/SEATS and ARIMA models were used for the decomposition and forecasting of dwelling time series. The Polish housing market, represented by selected local housing markets, still shows a growing trend despite the COVID-19 pandemic throughout 2020. The housing market may slow down in 2021, but the strong forecasted growth trends in Warszawa and Poznan suggest that there will be no significant price decline in Poland in the near future. © 2021, AGH University of Science and Technology Press. All rights reserved.

The real estate market, as an open, complex and dynamic system, responds to changes in the environment of economic, legal or social conditions, although the pace and direction of these changes depends on the level of inertia of this system. At the same time, this market stimulates the market environment through prices. This study attempts to identify cause-and-effect relationships in the scope of the impact of selected economic and social indicators on prices of residential premises, as well as to identify the effects of price changes on these indicators. The time horizon of the study covered the years from 2008 to 2018. In the studies, to assess the stationarity of time series, an extended Dickey-Fuller test was used for the model with a free expression and linear trend, a vector autoregression model (VAR) was then constructed and Granger tests and impulse response analysis were performed using the Impulse Response Function (IRF). As a result, it was demonstrated that the response of real estate prices to the impulse from explanatory variables appears between the first and the fourth quarters, and expires after about three years.

The aim of this study is to identify the factors that significantly determine the regional spatial differentiation of housing prices as well as housing market activity in Poland. The present research makes the assumption that average housing prices and market activity (number of transactions) are regionally shaped by economic, social, infrastructural and environmental conditions which can be described as a set of diagnostic features ascribed to a given area, constituting a statistical unit. Furthermore, it is assumed that individual effects may appear, being tied to the idiosyncrasies and significance of the given area. The time horizon of the research is 2008-2018. Based on data sourced from the Central Statistical Office a panel data was prepared for each of 380 Polish districts (poviats). Next, parameters were estimated for a single-factor panel model, as well as a two-factor model in which the constant term is different for different time periods and different units. This resulted in a model encompassing both average price determinants, and individual effects which reflect certain regularities of their spatial distribution. Moreover, the research will result in a set of cartograms made with Geographic Information System tools, depicting the random effects resulting from estimates of panel models using the Nerlove and Swamy-Arora transformations.

The main part of the study will be to demonstrate that models taking into account spatial heterogeneity (Geographically Weighted Regression and Mixed Geographically Weighted Regression) which reproduce housing market determinants better reflect market relationships than conventional regression models. The spatial heterogeneity of the housing market determinants results in the spatial diversity of the market activity, as well as of real estate prices and values. The main aim of the study was to analyse an effect of these socio-demographic and environmental factors on average housing property prices and on the number of transactions in a spatial approach. In previous research conducted on a national scale, usually all variables were treated in a similar way, i.e., as global or local variables. During the research, an attempt was also made to answer the question of which of the variables adopted for analysis have a local impact on prices and market activity, and which are global. The study was conducted in Poland and used data from the year 2018 on 380 counties (Local Administrative Units). The study showed that determinants both for average prices and for the housing market activity show spatial autocorrelation with high&ndash, high and low&ndash, low cluster groups. Owing to these models, it was possible to draw specific conclusions on local determinants of flat prices and the market activity in Poland. The study findings have confirmed that they are an extremely effective tool for spatial data analysis.

A recently emerged sustainable information society has ceased to be only a consumer and has become a web-based information source. Society’s online behaviour is tracked, recorded, processed, aggregated, and monetised. As a society, we are becoming a subject of research, and our web behaviour is a source of information for decision-makers (currently mainly business). The research aims to measure the strength of social interest in the housing market (Google Trends), which will then be correlated with the dynamics of housing prices in Poland in the years 2010–2021. The vector autoregressive model was used to diagnose the interrelationships (including Granger causality) and to forecast housing prices. The research showed that web searching for the keyword “dwelling” causes the dynamics of dwelling prices and is an attractive alternative to the classical variables used in forecasting housing market prices.

The assumption of a strong positive relationship between the specificity of an urban area and the operation of the housing market, which responds to megatrends in the market environment, has been the foundation of the research concept adopted for this study. The study treats the housing markets as complex, adaptive dynamic systems which develop through synergistic network responses. This paper employs a nonlinear critically-damped harmonic oscillator model and phase diagrams to describe the dynamics of housing prices (in the years 2006-2016) in order to demonstrate the synergistic network connections in selected Polish cities. In another important part of the study, the authors propose to employ non-classical dynamic measures, i.e. the absolute time of delay, relaxation time and a long-term level of equilibrium. The study has shown that network connections are strongly synchronized during periods of housing market instability (2006-2007), whereas the process of unsynchronization is observed during a period of stability (2008-2016). Moreover, phase diagrams have been used to demonstrate the similarity of trends in housing prices as well as the shapes of individual trajectories and the existence of multiple points of quasi-equilibrium.

This article presents the results of research on the effect of the customer&rsquo, s gender on the tenure choice (ownership or tenancy) on the housing market. In the study, an attempt has been made to investigate whether there is a significant role of women in making decisions in this market. The survey was conducted among residents of two cities&mdash, Olsztyn (Poland) and Vilnius (Lithuania). The obtained answers were subjected to a multi-dimensional categorical and quantitative analysis. The results showed, among others, that women generally have greater decision-making autonomy in residential issues than men, with Lithuanian women doing this much more often than Polish women. However, it should be noted that the dominant decision-making model in the housing market is the model of joint decisions taken by men and women. The results of the conducted analysis broaden the existing knowledge of the functioning of the housing market and may support the implementation of the pro-social and pro-sustainable spatial development policy of the given territorial unit. The results may also contribute to more sustainable development of enterprises in the housing construction sector. This is an important issue in a climate of intense competition between &ldquo, providers&rdquo, of flats and the gradual introduction of the idea of competition between them and the social environment.

Airports in Poland are obliged to observe the sustainable development principle and therefore to reduce their environmental impact by creating so-called limited use areas (LUA) related to aircraft-generated noise. The research authors analyzed airports&rsquo, impact on the prices of single-family homes located in the vicinity of airports. The LUA is therefore defined as the area designated to study the airport&rsquo, s specific impact on the single-family housing market. This is a formal limit which determines the examination of price changes and the decision-making conditions of market participants. This methodical approach is justified because no excessive noise is expected outside the LUA. Therefore, two markets in the vicinity of airports were examined. One is in an LUA which is closer to the airport, and the other market is outside the LUA where external noise effects are not present. Thus, we consider that real estate located outside the LUA is not subject to a significant negative impact from the airport. The study covered the Gdańsk Lech Walesa Airport and the Warsaw Chopin Airport in Poland in adjacent areas with the research time horizon of 2013&ndash, 2017. The study examined single-family house prices. We used a time series analysis, a classic multiple regression model, a spatial autoregressive model, and geographically weighted regression models in our research. Additionally, Geographical Information System (GIS) tools were used to visualize the results of our study. The research result was to demonstrate different impact levels of airports on the prices of single-family houses located in limited-use areas in Gdańsk and Warsaw. This research carries significant implications for the general public and airports&rsquo, economic decisions in resolving conflicts between the airport and residential property owners in airports&rsquo, vicinities.

Wspolczesna debata naukowa wykazuje zasadnośc reorientacji ekonomii glownego nurtu w kierunku nurtow heterodoksyjnych pozwalających formulowac nowe aksjologiczne,doktrynalne i metodologiczne podstawy badan rynku nieruchomości. W artykule zwrocono uwage na proces zmiany ugruntowanych wlaściwości rynku nieruchomości i wylanianie sie nowych wlaściwości jako konsekwencji niedoświadczanych wcześniej w Polsce gwaltownych wzrostow cen w latach 2006-2007, a nastepnie stabilnych spadkow w formie gasnących oscylacji. W opracowaniu przedstawiono koncepcje paradygmatu badan rynku nieruchomości w duchu holizmu metodologicznego promującego dualizm ekonomii ortodoksyjnej i ekonomii heterodoksyjnej.

The objective of the study presented in the article is to determine the spatial diversification and determinantsof construction activity in Poland between 2006 and 2015. Theoretical hypotheses and observations of behaviour ofeconomic entities clearly show that their decisions depend both on the situation in local and regional markets, as wellas distances from other regions or local markets. The number and the surface area of completed residential units, as wellas the number of completed buildings and issued construction permits, were adopted as the measures of constructionactivity. The analysis also includes selected demographic, social and economic indices characterising the individualterritorial units in Poland on the basis of the local data bank maintained by the Central Statistical Office. In the courseof the study, spatial panel models were used, and as a result of the study, construction activity models were obtained,taking spatial interactions into account. DOI: https://doi.org/10.3846/enviro.2017.103

An immanent feature of the housing market is a large spatial dispersion of real estate prices along with their simultaneous high stratification. Application of classic methods of data interpolation results in an excessive simplification of the outcome because of a conversion of the dispersed data sets into areas of spatial continuity by reducing the above-average real estate prices. The main aim of the article was to search for spatial discontinuities of real estate prices’ distribution with 3D modeling using Voronoi diagrams as a method of irregular division of this space. Used methods of geospatial analyses with GIS tools enabled to identify clusters of high housing market activity and to avoid an excessive generalization of data resulting from the reduction of the above-average real estate prices. The research was conducted for over 7000 real estate transactions in years 2010–2017 in Olsztyn, the capital city of Warmia and Mazury in Poland, resulting in a 3D visualization of real estate prices for the chosen market, including the discontinuity in their spatial distribution.

Real estate market can be thought of as an open, dynamic system. It means that it is able to exchange stimuli with other open systems, and that its state evolves in a way that might be described mathematically. It turns out that two main processes contribute to the overall evolution of the real estate market: long-term, predictable evolution, interrupted by sharp changes of catastrophic origin. In this picture, national housing funds play an important role in supporting the housing finance: on one hand they could either stimulate or suppress the real estate market influencing the availability of the mortgage credit, but on the other hand, they could also help to stabilize prices. In this study, an attempt was made to determine the degree of relationship between the volume of mortgage financing from national housing funds and the dynamics of real estate prices.

This study examined similarities between local real estate markets in Poland from 2006 - 2013 by analyzing changes in housing prices. The analyses covered five cities - all of which are major centers of their regions: Warsaw (Mazovia - the center of Poland), Bialystok (Podlasie - the east of Poland), Cracow (Malopolska - the south of Poland), Poznan (Wielkopolska - the west of Poland) and Gdansk (Pomerania - the north of Poland). The time period was chosen so that it covered an interval of rapid changes in real estate prices (a housing bubble) and their subsequent relaxation to the equilibrium state. Firstly, a multi-dimensional analysis which took into account the Chebyshev distance was employed. This helped to conduct an analysis of the correlation of price changes over time, which revealed their concurrence and, moreover, showed specific propagation delays to external stimuli, and hence could be a measure of the market’s inertia. The degree of integration of the local markets under study changed only slightly over time; therefore, a thesis can be put forth in regard to the interrelation of local real estate markets, imagined as a system of communicating vessels. In the second stage, the damped harmonic oscillator model was employed to describe the observed evolution of real estate prices. This study exhibited high inertia in real estate markets, manifested during rapid structural changes in the system’s state occurring in conditions far from equilibrium. In long-term evolution, the pace of change is slow enough for the systems to remain close to equilibrium

This article analyses the adverse impact of Chopin Airport in Warsaw on the prices of single-family houses located within the aircraft noise impact zone. The specific feature of the largest airport in Poland is its location within the city limits and the resulting direct surroundings of both multi- and single-family housing developments. Not only is the nuisance due to the proximity of the airport resulting from the actual exposure to an excessive noise level but also from legal restrictions associated with the Limited Use Area (LUA). The study used statistical modeling by applying a classic multiple regression model, spatial autoregressive model and geographically weighted regression model. Moreover, Geographical Information System (GIS) tools and geostatic modeling were used to visualise the results. The modeling results clearly show the significant impact of the neighborhood nuisance and the related spatial distribution of real estate prices. In addition, the geographically weighted regression model indicates that the proximity to an airport adversely affects the rate of price changes over time.

This article aims at testing the possibilities of applying hierarchical spatial autoregressive models to create land value maps in urbanized areas. The use of HSAR (Hierarchical Spatial Autoregressive) models for spatial differentiation of prices in the property market supports the multilevel diagnosis of the structure of this phenomenon, taking into account the effect of spatial interactions. The article applies a two-level hierarchical spatial autoregressive model, which will permit the evaluation of interactions and control spatial heterogeneity at two levels of spatial aggregation (general and detailed). The results of the research include both the evaluation of the impact of location on prices (taking into account non-spatial factors) and the creation of the average land price map, taking into consideration the spatial structure of the city. In empirical studies, the HSAR model was compared with classic LM (Linear Model), HLM (Hierarchical Linear Model), and SAR (Spatial Autoregressive) models to perform comparative analyses of the results.

Land value maps are generally used in mass appraisal for the determination of property taxes. In view of the complex nature of property management processes, land value maps may also serve a variety of purposes which are not dictated by legal requirements. This study proposes a concept for the development of a land value map which may be applied for non-tax purposes. The proposed map was developed with the use of statistical and geostatistical methods. A reference layer corresponding to a representative property was developed, and statistical models were used to determine coefficients that adjust property value in view of its non-spatial attributes. A theoretical concept was presented, and it was used to develop a land value map for the city of Olsztyn in northeastern Poland.

The real estate market is an open system, which implies that it is able to exchange signals with other open systems and dynamic systems. The evolution of a market system over time can be described mathematically. If the system's sensitivity threshold to external stimuli is exceeded, it becomes destabilized and moves from a near-balanced state to a state that is far from equilibrium. Those dynamic processes often induce key changes in the system's trajectory of evolution. In search of equilibrium, the system becomes transformed in a process of discontinuous and discrete changes in state variables. The above statement constitutes the research hypothesis in this article. In this study, an attempt was made to develop a mathematical model for visualizing the evolutionary path of the real estate market in the form of continuous changes interrupted by discontinuous changes. The qualitative transformation of the system will be evaluated with the use of the catastrophe theory.

Within the last decade, real estate prices in Poland have changed signi cantly. We believe that these prices inevitably re ect the dynamics of the real estate market, and therefore they can be used to track its evolution path. To study whether and how the prices (regarded as a state variable) change over time depending on such control variables as gross domestic product and central bank interest rates, the theory of discontinuous change (also known as the catastrophe theory) was used. Catastrophic model assumes that small price uctuations are associated with stable, long-term development of the market, whereas rapid changes are always due to short-term instabilities. In such a picture, the system evolution path draws a smooth curve within the stability area passing continuously between neighboring equilibrium states, and it rarely enters into the instability area to jump over the potential barrier to another equilibrium state.

The paper deals with the description of the issues related to the dynamics of the real estate market in terms of sharp, unexpected changes in the housing prices which have been observed in the last decade in many European countries due to some macroeconomic circumstances. When such perturbations appear, the real estate market is said to be structurally unstable, since even a small variation in the control parameters might result in a large, structural change in the state of the whole system. The essential problem addressed in the paper is the need to define and discriminate between the intervals of stable and unstable real estate market development with special attention paid to the latter. The research aims at modeling hardly explored field of discontinuous changes in the real estate market in order to reveal the bifurcation edge. Assuming that the periods of sudden price changes reflect an intrinsic property of the real estate market, it is shown that the evolution path draws for most of the time a smooth curve onto the stability area of the equilibrium surface, and only briefly penetrates into the instability area to hop to another equilibrium state.

PurposeClimatic conditions in Poland vary tremendously each year with temperatures exceeding 25°C in the summer and sub‐zero in the winter. Therefore the provision of adequate heating and cooling in residential, public and industrial buildings is essential. Poland has recently embarked on a refurbishment process known as “thermomodernisation”, which focuses on improving buildings' thermal and energy efficiency. This paper aims to present the results from a case study of refurbished apartments in Olsztyn, Poland, to determine whether this process increases market value.Design/methodology/approachThe research focuses on property in Olsztyn, Poland where residential property is typically situated in apartments within high‐rise and low‐rise buildings.FindingsThe majority of housing stock in Poland was built during the 1970s to 1990s when the thermal properties of building materials were not considered in the construction process, the thermal performance in most residential buildings is very low and heating costs unacceptably high. The results suggest both occupiers and professionals consider thermomodernisation benefits the occupiers by reducing energy and maintenance costs and improving the amenity value of a home. However, whilst both thought that property value was increased this increase was not significant.Practical implicationsThis paper provides information on the financial benefits to the occupier from “thermodernistion”, and encourages professionals to highlight these benefits when marketing property.Originality/valueNo published research has explored this issue. This paper addresses this situation.

The paper describes application of catastrophe theory for analysis of trends of real estate prices inPoznan. It turns out that the evolution of the real estate market is comprised of two main processes: long-term evolution in the area of a non-degenerate stability and discontinuous, rapid changes in the area of a degenerate stability. In the macro scale, the construction and developing branch contributes largely to the Gross Domestic Product affecting overall economic environment. In the micro scale, however, the knowledge about future price trends may help to decide whether or not to buy or sell the house property.

The paper deals with time series of housing prices on local real estate markets in Warszawa (WAW), Krakow (KRK) and Poznan (POZ) from 2006 to 2013 using a model of critically-damped harmonic oscillator to study underlying system dynamics. Performed analysis reveals the presence of housing bubble in 2007 that emerge from otherwise quasi-regular evolution around the equilibrium state. Time series of housing prices are fitted numerically to estimate important parameters of the system, for example: decay constant, delay time, and price equilibrium level, which help us to chose the leading market. Obtained results show reasonable matching of the model with housing prices in WAW and POZ, but less in KRK. The latter data, however, are found to agree well with the model of under-damped harmonic oscillator, which actually suggests that some trembling might occur in that market. Nevertheless, local real estate markets can be thought of as a system of interconnected damped harmonic oscillators with leading market in WAW that is about to change under aggregate macroeconomic fluctuations (exogenous factors) triggering changes in remaining markets.

The Presented research aims to analyze the Lithuanian and Polish housing markets in terms of the quality of life in new residential buildings. The article presents the concept of customer satisfaction in construction and criteria that define the quality of dwellings; the benefits, consequences, merits and demerits of the assessment of customer satisfaction are also named. A survey of customer satisfaction helps to evaluate the quality of dwellings according to their technical and functional parameters, as well as the degree of cooperation between customers and developers/contractors. The customer satisfaction index (CSI) was calculated for both countries. The results are useful for developers, contractors, facility management companies and building users.

The article aims to analyze the Lithuanian housing market and to look into the satisfaction of people with living conditions in new apartment buildings on this market. The article presents the concept of customer satisfaction in construction and the criteria that define the quality of dwellings; the benefits, consequences, merits and demerits of the assessment of customer satisfaction are also named. A survey of customer satisfaction helped to evaluate the quality of dwellings according to their technical and functional parameters, as well as the degree of cooperation between customers and contractors/builders. The customer satisfaction index (CSI) and the degree of loyalty were calculated, and then a customer satisfaction matrix was built up.