Housing Satisfaction in the Czech Republic: Results of Sociological Surveys in 2001 and 2013
Ladislav Kážmér, Irena Boumová Saturday, 30 July 2016
The article evaluates housing satisfaction and its development in the Czech Republic after 2000. Its goal is to help better understand the processes behind this phenomenon by identifying factors that influence how the level of housing satisfaction varies between population groups. In a comparative perspective on cross-sectional data from 2001 and 2013, the authors present the main findings of two waves of a quantitative sociological survey.
The article draws on two comparable datasets stemming from a nationwide sociological survey of attitudes to housing issues implemented in the Czech Republic as “Housing Attitudes 2001” and “Housing Attitudes 2013”. The analysis was conducted in two stages. In the first stage, pairwise correlation analysis was used to identify variables that are significantly associated with a measure of overall satisfaction with one’s current housing situation. In the second stage, multiple linear regression was used to test the significance of these variables. The goal was to find factors that independently predict the respondent’s overall housing satisfaction when controlling for other variables included in the regression model.
The article evaluates housing satisfaction and its development in the Czech Republic after 2000. Its goal is to help better understand the processes behind this phenomenon by identifying factors that influence how the level of housing satisfaction varies between population groups. In a comparative perspective on cross-sectional data from 2001 and 2013, the authors present the main findings of two waves of a quantitative sociological survey.
The article draws on two comparable datasets stemming from a nationwide sociological survey of attitudes to housing issues implemented in the Czech Republic as “Housing Attitudes 2001” and “Housing Attitudes 2013”. The analysis was conducted in two stages. In the first stage, pairwise correlation analysis was used to identify variables that are significantly associated with a measure of overall satisfaction with one’s current housing situation. In the second stage, multiple linear regression was used to test the significance of these variables. The goal was to find factors that independently predict the respondent’s overall housing satisfaction when controlling for other variables included in the regression model.