Thesis (MA (Geography and Environmental Studies))--University of Stellenbosch, 2010. / 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. / AFRIKAANSE OPSOMMING: Die navorsingsprobleem wat hierdie studie aanspreek, is hoe om vas te stel wat die primêre
faktore is wat huispryse in Houtbaai bepaal. Hierdie oorkoepelende doelwit vervat drie
onderling verwante aspekte. Eerstens, poog die navorsing om te bepaal watter faktore in die
algemeen huispryse in Houtbaai beïnvloed; tweedens, om te assesseer tot watter mate
individuele faktore huispryse affekteer; en derdens, om te ontdek watter kollektiewe rol
veranderlikes in die bepaling van huispryse in Houtbaai speel. Vanuit hierdie onderverdeling
van die navorsingsdoelwit het vier doelstellings ontstaan, naamlik identifiseer die potensiële
faktore wat huispryse in Houtbaai beïnvloed; kwantifiseer die geselekteerde
liggingsveranderlikes; voer verskeie analises uit op die veranderlikes om die beduidende en
onbeduidende veranderlikes te identifiseer; en benut regressie-analise om die kollektiewe en
individuele invloed van beduidende faktore op huispryse in die studiegebied vas te stel.
Gestruktureerde onderhoude is met verkoopslui van 12 eiendomsagentskappe in Houtbaai
gevoer om die faktore te bepaal wat die plaaslike eiendomsmark beïnvloed. Deur middel van
insigte verkry uit die akademiese literatuur, manipulasie van munisipale waardasie- en
kadastrale data en die gestruktureerde onderhoude is 39 strukturele en liggingsverwante
veranderlikes, 18 afstandsveranderlikes en 11 sosio-ekonomiese veranderlikes geskep.
Verskeie analises wat op die veranderlikes uitgevoer is, het ‘n algemene indruk van die
verspreiding van die data verskaf en het die identifisering van statistiesbeduidende
veranderlikes bevorder. Hierdie analises het maatstawwe vir sentrale neiging (rekenkundige
gemiddelde, mediaan en modus); maatstawwe vir dispersie (minimum en maksimum,
variasiewydte, standaardafwyking, skeefheid en kurtose); die samestelling van histogramme
vir elke veranderlike; die analise van variansie (ANOVA) op veranderlikes met nominale
data; en die skep van 2D-spreidingstippe vir veranderlikes met ordinale data behels. Spearman
se rangorde korrelasie is op beide die nominale en ordinale data uitgevoer.
Statistiesonbeduidende veranderlikes, of dié wat tekens van multikollineariteit met ander
veranderlikes getoon het, is geëlimineer. ‘n Beste deelversameling regressie-analise is
uitgevoer op die oorblywende veranderlikes.
Die regressiemodel het gepaste resultate behaal deurdat dit byna 54% van die variasie in
Houtbaai se huispryse verklaar het. Van die individuele veranderlikes was die grootte van die erf die sterkste voorspeller van die huisprys afhanklike veranderlike, huisgrootte was die
tweede belangrikste faktor, terwyl afstand van besige paaie en die kwaliteit van die huis
soortgelyke invloed gedeel het. Die regressiemodel se residu’s is gekarteer om ruimtelike
patrone vas te stel. Dit word aanbeveel dat soortgelyke navorsing op ‘n stadswye skaal
uitgevoer word, dat die veranderlikes op ander wyses gekwantifiseer word en dat nuwe GIStegnieke
in toekomstige studies aangewend word.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/4250 |
| Date | 03 1900 |
| Creators | Van der Walt, Stephan |
| Contributors | Van Niekerk, Adriaan, Bloom, Z. J., University of Stellenbosch. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | Unknown |
| Type | Thesis |
| Format | 64 p. : ill., maps |
| Rights | University of Stellenbosch |
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