Abstract:The aim of this study is to identify whether there is a common house price trend across provincial capitals in Poland. The log t regression is the main method of analysis. Additionally, traditional convergence tests based on the concepts of β- and σ-convergence are used. The obtained results indicate that the cities do not share a common price in the long-run. There are, however, convergence clubs on both primary and secondary markets. In each club, house prices across cities tend to converge to their own stea… Show more
“…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%
“… Fig. 6 Spatial distribution of convergence clubs: in the Polish rental housing market identified based on the trend component of time series extracted using a the Hodrick–Prescott filter, b the boosted Hodrick–Prescott filter, c the Butterworth filter and d the Christiano–Fitzgerald filter; e in the Polish sales secondary housing market according to estimates by Tomal ( 2019a , b ) …”
Section: Resultsmentioning
confidence: 99%
“…The literature review indicated that the key predictors on the demand and supply side may be variables describing the level of unemployment (Leszczyński and Olszewski 2017 ; Tomal 2019a , b , 2021 ; Cellmer et al 2020 ), wages (Cellmer et al 2020 ), housing stock (Kokot 2018 ; Matysiak and Olszewski 2019 ; Tomal 2019b ), population size and density (Tomal 2019a ), city area (Tomal 2019a ) and sense of security (Źróbek et al 2015 ). The list of explanatory variables was supplemented with additional covariates characterising the specificity of the residential rental market in Poland, i.e.…”
Section: Resultsmentioning
confidence: 99%
“…The empirical research to date in this area is not very extensive, and to the best of the author's knowledge only several such analyses have been developed. In particular, studies on the presence of convergence clubs in the residential market have been conducted in the USA (Kim and Rous 2012 ; Apergis and Payne 2012 , 2019 , 2020 ; Montañés and Olmos 2013 ), China (Meng et al 2015 ; Lin et al 2015 ; Zhang et al 2017 ; Hu et al 2020 ), the UK (Montagnoli and Nagayasu 2015 ; Holmes et al 2019 ), Spain (Blanco et al 2016 ), Australia (Awaworyi Churchill et al 2018 ), South Africa (Apergis et al 2015 ) and Poland (Matysiak and Olszewski 2019 ; Tomal 2019a , 2020a ). It should be noted that almost all of the above studies analysed the convergence of sales prices in the residential market.…”
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.
“…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%
“… Fig. 6 Spatial distribution of convergence clubs: in the Polish rental housing market identified based on the trend component of time series extracted using a the Hodrick–Prescott filter, b the boosted Hodrick–Prescott filter, c the Butterworth filter and d the Christiano–Fitzgerald filter; e in the Polish sales secondary housing market according to estimates by Tomal ( 2019a , b ) …”
Section: Resultsmentioning
confidence: 99%
“…The literature review indicated that the key predictors on the demand and supply side may be variables describing the level of unemployment (Leszczyński and Olszewski 2017 ; Tomal 2019a , b , 2021 ; Cellmer et al 2020 ), wages (Cellmer et al 2020 ), housing stock (Kokot 2018 ; Matysiak and Olszewski 2019 ; Tomal 2019b ), population size and density (Tomal 2019a ), city area (Tomal 2019a ) and sense of security (Źróbek et al 2015 ). The list of explanatory variables was supplemented with additional covariates characterising the specificity of the residential rental market in Poland, i.e.…”
Section: Resultsmentioning
confidence: 99%
“…The empirical research to date in this area is not very extensive, and to the best of the author's knowledge only several such analyses have been developed. In particular, studies on the presence of convergence clubs in the residential market have been conducted in the USA (Kim and Rous 2012 ; Apergis and Payne 2012 , 2019 , 2020 ; Montañés and Olmos 2013 ), China (Meng et al 2015 ; Lin et al 2015 ; Zhang et al 2017 ; Hu et al 2020 ), the UK (Montagnoli and Nagayasu 2015 ; Holmes et al 2019 ), Spain (Blanco et al 2016 ), Australia (Awaworyi Churchill et al 2018 ), South Africa (Apergis et al 2015 ) and Poland (Matysiak and Olszewski 2019 ; Tomal 2019a , 2020a ). It should be noted that almost all of the above studies analysed the convergence of sales prices in the residential market.…”
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.
“…Other studies have in turn shown that in the fifteen Polish urban markets there are three groups of cities distinguished by the convergence of residential prices on the primary market that tend to approach the respective common price levels in these groups, but are not geographically distributed (Matysiak & Olszewski, 2019). Similar conclusions, though referring to both the primary and secondary markets, have also been drawn from other independent studies (Tomal, 2019). Some similarities and convergence in housing prices can also be observed between voivodeships; however, studies using this approach do not give unambiguous results and should be interpreted with caution (Żelazowski, 2019).…”
Property prices, including, in particular, residential properties, vary across local markets. For example, according to the National Bank of Poland, in late 2018, the average unit price of an apartment on the secondary market stood at PLN 8,700 in Warsaw, 6,100 in Poznań, 4,800 in Szczecin, and 3,800 in Kielce and Zielona Góra. The level of prices on particular markets is affected by a variety of factors, primarily those of a social and economic nature. Earlier research work on the influence of such factors on the level of apartment prices was carried out on a random basis, and their results were also published in the Real Estate Management and Valuation journals (Kokot 2018). This article presents study results that help deepen and broaden such analyses, seeing as how the research work:
–covers a period of 12 years (2006-2018),–proposes and then applies a city wealth synthetic measure (SMZM) in the analyses,– classifies cities according to the criterion of socio-economic factors and of average housing prices,–examines relationships within the groups of cities identified via classification.The obtained results indicate that it is justified to consider the impact of socio-economic factors on housing prices precisely in the context of their appropriate classification. Moreover, they may be an indicative tool of identifying so-called comparable or parallel real property markets.
This article aims to check whether there has been a price bubble in the Polish major housing markets in recent years. To accomplish this goal, the log price-to-rent ratios in Polish provincial cities were analysed. In order to avoid incorrect conclusions, the log price-to-rent ratio using the instrumental variable estimation and ordinary least squares methods was decomposed into two components: fundamental and non-fundamental. The latter was then examined using the Phillips, Shi, and Yu procedure to detect explosive and downward movements. The results of the study showed that, in general, over 2011, actual log price-to-rent ratios in the analysed cities were below their fundamental values, i.e., a negative price bubble existed. However, more or less since the beginning of 2013, the surveyed markets have seen an increasing level of the non-fundamental component of the index under study, and its particularly explosive movements are visible in the first quarters of 2014. Finally, this analysis indicated future research directions and study implications for Polish policy-makers, housing investors, and households.
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