A housing market analysis for the city of Krakow

Adamkiewicz, Dagmara; Radziszewska–Zielina, Elżbieta

doi:10.4467/2353737xct.19.102.10884

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…The results showed that house prices, income, and credit accessibility significantly influence housing investors' purchase decisions in a positive direction. Adamkiewicz & Radziszewska-Zielina (2019) conducted an online survey on a group of 104 persons who were currently searching for an apartment. Based on the outcomes, they concluded that the perceived need for persons to have their apartment is the most common reason for purchasing a house.…”

Section: Theoretical Basicmentioning

confidence: 99%

Factors affecting housing purchase decision in Vietnam

Loan¹

2023

JFM

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Housing is an essential asset for households, and owning a home is a dream of many people, For a country with one of the largest populations in the world such as Vietnam, owning a house for low-income employees is even more desirable to low-income people. Many low-income people are disadvantaged groups in society, so building houses that meet the needs of disadvantaged groups always has a positive impact on socio-economic development. The article uses a survey method combined with regression analysis to identify factors affecting the decision to buy housing in Vietnam, including income, location, quality of work, living environment, prices, and references. These are factors associated with the character and local characteristics of Vietnamese people

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Section: Theoretical Basicmentioning

confidence: 99%

Factors affecting housing purchase decision in Vietnam

Loan¹

2023

JFM

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Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland

Tomal

2020

IJGI

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The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scraping technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR-SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors shaping housing rents. However, one can identify some determinants that are ubiquitous for almost the entire city. This concerns mainly the variables describing the area of the flat and the age of the building. Moreover, the Monte Carlo test indicated that the spatial autoregressive parameter also changes significantly over space.

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A housing market analysis for the city of Krakow

Cited by 2 publications

References 16 publications

Factors affecting housing purchase decision in Vietnam

Factors affecting housing purchase decision in Vietnam

Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland

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