Masters Degrees (Geography and Environmental Studies)

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Browsing Masters Degrees (Geography and Environmental Studies) by browse.metadata.advisor "Bloom, Z. J."

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    Determinants of house prices in Hout Bay
    (Stellenbosch : University of Stellenbosch, 2010-03) Van der Walt, Stephan; Van Niekerk, Adriaan; Bloom, Z. J.; University of Stellenbosch. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: The research problem addressed in this study is how to ascertain the primary determinants of house prices in Hout Bay. This overarching aim encompasses three interwoven aspects. The research attempts first to determine which factors generally affect property prices in Hout Bay; second, to assess the extent to which individual factors affect house prices; and third, to discover the role variables collectively play in determining house prices in Hout Bay. Four objectives emerge from this subdivision of the aim, namely identify potential house priceinfluencing factors in Hout Bay; quantify the selected locational variables; statistically analyse the variables to distinguish the significant and insignificant ones; and use regression analysis to deduce the collective and individual influences of the significant factors on house prices. Structured interviews were conducted with representatives of 12 estate agencies in Hout Bay to uncover factors affecting the local property market. Through insights gleaned from the literature, manipulation of municipal valuation and cadastral data and the structured interviews, 39 structural and site-related variables, 18 distance variables and 11 socioeconomic variables were constructed. Several preliminary and descriptive analyses performed on the variables gave a general impression of the distribution of data and assisted in identifying statistically significant variables for determining house prices. These analyses included measures of central tendency (mean, median and mode); measures of dispersion (minimum and maximum values, range, standard deviation, skewness and kurtosis); the compilation of histograms for each variable; analysis of variance (ANOVA) on nominal data variables; and the creation of 2D scatterplots for ordinal data variables. Spearman rank order correlation was performed on the nominal and ordinal data variables. Statistically weak variables and those exhibiting signs of multicollinearity were eliminated. A best-subsets regression analysis was executed on the remaining variables. The regression model performed adequately, explaining close to 54% of the variation in house prices in Hout Bay. Among the individual factors, the size of the erf was the strongest predictor of the house price dependent variable, house size was the second most important factor, while distance to busy roads and quality of the house shared similar importance. Regression residuals were also mapped to expose spatial patterns. It is recommended that comparable research be conducted on a citywide scale, that variables be quantified differently and that new GIS techniques be incorporated in future studies.