One of the main pillars of sustainable urban development at the local scale is to control the social aspect of urban equality of socio-economic systems. A number of studies confirm that poverty in urban space is accompanied by negative phenomena, such as high unemployment, social pathologies, increased crime rate, or the high level of the decapitalization of space, including the poor condition of housing and municipal infrastructure. However, there is a gap in defining the relation between urban poverty and city structure to control and preferably minimize social inequalities. The aim of the study was to empirically verify the impact of the location of residential properties in relation to poverty-stricken areas in the city. The research covered the housing market in one Polish city (Kalisz) in the years 2006–2018. By applying GIS technologies, we identified the location of each property in relation to poverty areas. The data was subjected to regression analysis, with the use of the hedonic approach based on exponential models. The analysis of data allowed us to conclude that location in a poorer area does affect the prices of new flats, which is not only a contribution to the development of science, but is also information that could be used by developers or property valuers to establish the prices of flats, as well as city managers to avoid pauperization of urban districts.
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Research background: The processes of economic convergence observed in many devel-oping countries are characterized by reduction of economic differences on the cross-country level, which are accompanied by growing internal economic inequalities. This may stem from the fact that in the catching-up countries a more dynamic growth pattern is observed in the economically strongest regions, which is initially reflected in spatial polarization and increasing regional inequalities. However, just as the countries reach higher levels of devel-opment, the diffusion of growth-inducing impulses to less-developed areas should lead to the spatial equalizing of the development levels and reducing regional inequalities. Purpose of the article: The aim of the paper is to determine the relationship be-tween the level of economic growth and observed economic inequalities in Central and Eastern European (CEE) countries. The theoretical framework adopted to describe and explain those relations is the so-called Williamson’s hypothesis in which the relationship between the scale of regional inequalities and economic growth is illustrated by a curve shaped like an inverted U. Methods: The research procedure was intended to verify William-son’s hypothesis by estimating parabolic econometric models. Indicators of economic growth along with measure of regional inequalities (Williamson’s coefficient of variation) were used in the regression modeling. The research period spanned the years 1995-2014. Findings & Value added: In the light of the study of CEE countries, it was possible to observe both convergence symptoms as well as divergence tendencies. It can be thus stated that the analyzed CEE countries followed a similar path to the one observed earlier by Wil-liamson in other developing countries. However, the analyses conducted by the authors at the national and regional levels of CEE countries were equivocal and did not fully support the theoretical assumptions of Williamson’s hypothesis.
Celem artykułu jest próba czasowej i przestrzennej analizy rynku nowych samochodów osobowych w Polsce (zakupionych przez indywidualnych użytkowników), wykorzystującej różnorodny aparat metodologiczny. Analiza ta obejmuje trzy główne grupy problemów: -ogólną charakterystykę rynku samochodów osobowych w Polsce w wymiarze czasowym i przestrzennym, –identyfikację czynników wpływających na sprzedaż nowych samochodów osobowych klientom indywidualnym oraz ich przestrzenne zróżnicowanie, –wyróżnienie różnych typów zmienności popytu na nowe samochody osobowe w wymiarze przestrzennym i prognozowanie przyszłego popytu. Na podstawie przeglądu literatury zidentyfikowano czynniki, które mogą wpływać na wielkość popytu na samochody, a następnie określono ich rolę za pomocą modeli ekonometrycznych. Regresja wielokrotna wykazała, że na wielkość efektywnego popytu na nowe samochody w Polsce w latach 2008–2015 największy wpływ miały: poziom dochodów konsumentów, uwarunkowania demograficzne, poziom rozwoju lokalnego oraz poziom nasycenia rynku. Dalsze analizy dokonane za pomocą lokalnych modeli geograficznie ważonej regresji ujawniły ogólne trendy przestrzenne oddziaływania zidentyfikowanych czynników. W ostatnim etapie badań za pomocą analizy harmonicznej dokonano próby typologii powiatów z punktu widzenia zmienności popytu na nowe samochody osobowe oraz estymacji przyszłego popytu.
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