This study analyses the housing price volatility in metropolitan areas in South Africa, particularly Port Elizabeth and East London residential housing markets. This study uses secondary statistical data, obtained from secondary sources. The study uses quarterly time series data for the period 1981:1 to 2015:3 giving 139 observations. The data will be collected from different sources. The main sources of data are real estate agencies (Trafalgar, Harcourts and Property24), the South African Department of Trade and Industry (dti) and supplemented by the South African Reserve Bank (SARB) and Statistics South Africa (Stats SA). The study shall use the ordinary least squares (OLS) method to estimate its results. Ordinarily, this is a generalised linear modelling technique that may be used to model a single response variable which has been recorded on at least an interval scale. This method requires that the underlying stochastic processes of the variables are stationary. That is, explanatory variables should exhibit constant means and variances over time. If the stochastic processes are not stationary, OLS produces unreliably significant coefficients. Results showed that household savings, household income and total growth in household buildings (TGH) are statistically significant in explaining changes in house prices. Jointly, all the explanatory variables can account for almost 52% of the changes in the dependent variable. The Durbin Watson statistic showed that there is no autocorrelation in the model. This shows that the model is good. Results from the regression show that there is a negative relationship between house prices and household savings. A one-unit increase in household savings leads to a 0.407 decrease in house prices. This relationship makes economic sense because when households save, there is less income available to buy houses. When there is less income available to buy houses, it would mean there is less demand for houses.

This study sought to empirically investigate trends and volatility in residential property prices in South Africa using quarterly data over the period 1980Q1 to 2011Q4. The empirical analysis uses a range of unit root and stationarity tests as well as a number of ARCH-family of models. The results from the trend analysis suggest that the behaviour of house prices in South Africa follows a random walk process. The randomness in the behaviour of house prices could be attributed to permanent effect of shock. Investigation into the dynamic behaviour of the house prices supports the existence of conditional volatility that is time-varying and highly persistent. Moreover, volatility is found to be asymmetric in news suggesting evidence of anti-leverage effects. These findings have important portfolio implications especially, considering the fact that large-scale losses are possible if house prices exhibit the type of persistent in behaviour as captured in this study. Also, the existence of asymmetric effects in volatility suggests that more caution needs to be placed on news arrival as they may have significant impacts on the house price behaviour. Accordingly, this study suggests the need for residential property market to be treated like other asset markets with regards to risk.

Sports facilities increasingly feature amongst the most expensive development projects world-wide. One such facility includes world-class stadia. Such facilities tend to commit a considerably large amount of a country's public funds to the project. This public expenditure on new stadia, and the required public taxation, may be economically justified if the benefits from the new stadia outweigh the costs. 15 May 2004 saw South Africa winning the bid to host the FIFA 2010 Soccer World Cup tournament. This mega-event was played in 10 stadia across nine chosen host cities. Five of these stadia were newly constructed, while the other five needed upgrading. Both South Africa's national government and local governments of host cities bore the expenses of the new stadia construction and the upgrading to the existing stadia. This amounted to a total public expenditure of R13.5295 billion on the stadia alone. The Nelson Mandela Bay Stadium on the banks of the North End Lake in Port Elizabeth was amongst the five newly constructed stadia costing R1.7 billion. Many international studies have been conducted to assess the impact of new stadia on the economies of host cities. One particular aspect which has received a lot of attention as far as empirical research is concerned is the impact of stadia on residential property prices (Carlino & Couslon, 2004; Davies, 2005; Tu, 2005; Coates & Humphreys, 2006; Ahlfeldt & Maennig, 2007, 2010; Dehring, Depken & Ward, 2007; Feng & Humphreys, 2008, 2012; Kavetsos, 2010; Ahlfeldt, Maennig & Scholz, 2010; Kiel, Matheson & Sullivan, 2010; Ahlfeldt & Kavetsos, 2011; Coates & Matheson, 2011). The majority of the studies conducted have indicated that the presence of a new stadium in an area has a significantly positive effect on surrounding house values that decays with distance from the facility. As no study has yet been done in South Africa to investigate the impact of the announcement of the construction of new stadia on nearby residential property values, this study examines, by means of the hedonic pricing model, the effect of the announcement to construct the Nelson Mandela Bay Stadium on the banks of North End Lake on adjacent residential property values. The study period for this study was 2004 - 2006. This time period captured the stadium announcement effect. The residential properties in North End that were traded at least once during the period 2004 to 2006 made up the target population. According to the South African Property Transfer Guide (SAPTG), a total of 417 property transactions (excluding repeat sales) took place over the study period (2004 - 2006). The 417 transactions were deemed to be the size of the target population and a list of 100 property transactions were used as the sampling frame. As the study period was from 2004 - 2006, it was necessary to adjust the market prices to constant 2006 prices. For this purpose, data from the Port Elizabeth and Uitenhage section of the ABSA house price indices were used so as to eliminate any inflationary effects on the property values over the study period. The results of the study revealed that the stadium has a statistically significant positive effect on adjacent residential properties situated within a 1 200 metres radius from the stadium. The average owner of a residential property in North End would be willing-to-pay between R10 7898 and R11 704.6 to be situated 435 metres closer to the stadium.

Thesis (MBA)--Stellenbosch University, 2008. / ENGLISH ABSTRACT: Internationally, a number of studies on property cycles have been undertaken. In contrast very little academic research has been undertaken in South Africa. The importance of the subject is once again become evident given the recent global turbulence in both property and credit markets. The central hypothesis of this study is that there exists a residential property cycle in South Africa and that it can be identified and that furthermore there are indicators that can identify the various stages that the property market finds itself in and that these indicators can be used to forecast the property cycle. A number of potential drivers of the property cycle were identified and analysed. These drivers collectively propel the property cycle through its various cycle stages. Not one of the drivers in isolation has the ability to move the cycle; it is rather the correct combination of drivers at the right time that have the necessary impact to make the changes in property price levels. The study has identified the historical residential property cycle in South Africa and identified the primary drivers of the property cycle. It was found that Interest Rates, GOP, Population, Household Debt to Disposable Income ratio, Quantity of Building Plans Approved and Building Cost Escalation are all material drivers in defining the property cycle. A statistical analysis in the form of multiple regression was applied to the above variables and a statistical model was developed to forecast the property cycle. It was found that the model has significant explanatory powers when the goodness of fit was tested. / AFRIKAANSE OPSOMMING: Die sentraal onderstelling van hierdie studie is dat daar 'n residensiele eiendom kringloop in Suid-afrika bestaan en dat dit geidentifiseer kan wees en dat bowendien daar aanwysers wat die verskeie stadiums van die eiendom mark kan identifiseer vind en dat hierdie aanwysers gebruik kan word vir voorspelling van die eiendom kringloop. 'n Aantal potensiele drywers van die eiendom kringloop was geidentifiseer en gean ali seer. Hierdie drywers gesamentlik dryf die eiendom kringloop deur sy verskeie kringloop stadiums voort. Nie een van die drywers in isolasie het die vermoe om die kringloop te beweeg nie; dit is liewer die korrekte kombinasie van drywers op tyd wat die nodige impak het om die veranderinge in eiendom prys vlakke te maak. Die studie het die historiese residensiele eiendom kringloop in Suid-afrika geidentifiseer en die primere drywers van die eiendom kringloop. Dit was gevind dat Rentekoerse, GOP, Populasie, Huishouding Skuld tot Weggooibare Inkomste Verhouding, Hoeveelheid van Gebou Pia nne Goedgekeur en Gebou Kos Eskilasie is almal materiaal drywers in definieer van die eiendom kringloop. 'n Statisties analisering was aangewend aan die bo onkonstante en 'n statistiese skema was ontwikkel om voorspelling van die eiendom kringloop te bepaal. Dit was gevind dat die skema beduidende verduidelike kragte het wanneer die goedheid van pas getoets was.

A great deal of research has been carried out on residential property values and numerous factors have been identified as having an effect on residential property values. The physical characteristics of properties of properties are the primary factors that determine the market value of residential property. However, factors concerning location are also thought to influence the value of residential properties. These locational factors include, among others, accessibility to highways, airports, schools, parks and public transportation centres. This study examines the effect of another locational factor, namely proximity to a newly built shopping centre. Shopping centres have been increasing in numbers throughout South Africa over the past few decades. These shopping centres are usually situated in close proximity to residential properties. As such, shopping centres that are in close proximity to residential properties can influence property prices. This study makes use of the hedonic price model to assess the price impact of the newly constructed Baywest Mall on the residential properties in the western suburbs of Nelson Mandela, namely Sherwood, Rowallan Park and Kunune Park. On 21 March 2012, the construction of the Baywest Mall was officially announced. This announcement created an area of interest as to whether its construction and completion would have an impact on the prices of residential properties situated in close proximity to the mall. The study period for this study was from 2004 – 2015. This time period is thought to be sufficient to assess the effect of the Baywest Shopping Mall on the residential property prices before and after the announcement of the construction of the mall. As the study period ranged from 2004 – 2015 it was necessary to adjust the sales prices over the years to constant 2015 prices. As such, the ABSA house price index was used in order to eliminate any inflationary effects on the property values over the study period. The results of the study revealed that the newly built Baywest Mall has a statistically significant positive effect on properties in close proximity to the shopping mall. This result enhances the scientific understanding of the effect of commercial land uses, such as, shopping centres, on the value of adjacent residential properties.

This study exammes the impact of macroeconomic and financial variables on the performance of the housing property market in South Africa using monthly data for the period January 1996 to June 2008. Orthogonalised and non-orthogonalised house price returns and real estate returns are utilised as proxies for the housing property market in separate models. Three main issues were empirically analysed in relation to the linkage between selected variables and the housing property market. The first aspect examined the relationship between selected macroeconomic and financial factors and property returns. Secondly, the study examined the influence that a unit shock to each variable has on property returns over a period of time. The third aspect focused on determining the proportion of property returns variation that results from changes in the macroeconomic and financial variables. VAR modelling was thus adopted to empirically analyse these three aspects. The results reveal that house price returns are influenced by most of the macroeconomic and financial variables used in this study. Specifically, the real effective exchange rate, interest rate spread and manufacturing production positively impact on house price returns while the domestic interest rate, the dividend yield and expected inflation have a negative effect. Furthermore, manufacturing production has a lagged effect on house price returns while the real effective exchange rate and domestic interest rate have a contemporaneous effect. Real estate returns are not influenced by most of the variables except for the domestic interest rate and dividend yield which have a negative effect.

PhD / Department of Development Studies