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.

published_or_final_version / Housing Management / Master / Master of Housing Management

published_or_final_version / Housing Management / Master / Master of Housing Management

Housing is a dual commodity, which means it is not only a consumption, but an investment, good as well. Investors prefer larger units to smaller ones because larger units with higher ratios of the land-to-property-value will experience higher appreciation rates during a boom and enjoy higher liquidity. Therefore, changes in investment demand have a greater impact on the prices of larger units than on smaller units. Meanwhile, observations have revealed that buyers of smaller units are mostly prospective owner-occupiers driven by consumption demand. Thus, changes in consumption demand have a greater impact on the prices of smaller units than on larger ones. The aim of this study is to investigate the reasons for variations in the price movements of larger and smaller units. If the theory of the investment and consumption submarket holds true, the price differentials between larger and smaller units should capture the changes in investment and consumption demand. The changes in investment demand are measured by capital flows (the proxy of which is the LIBOR-to-HIBOR ratio) and the investment sentiment of the stock market (proxy: Hang Seng Index), whereas changes in consumption demand are measured by unemployment (proxy: unemployment rates). Three hypotheses are derived from the theory of the investment and consumption submarket: 1) The influx of large venture capital into Hong Kong should enlarge the price differentials, while the outflow of large venture capital should narrow them; 2) there is a positive relationship between investment market sentiment and the price differentials; and 3) the unemployment rate should positively affect the price differentials. In the empirical analysis, the price differentials between larger and smaller units are regressed on the variables of the LIBOR-to-HIBOR ratio, the Hang Seng Index, the unemployment rates, and other control variables. Quarterly data from 1985 to 2009 in Hong Kong is employed. The results of the ordinary least squares (OLS) method confirm the three hypotheses of capital flows, investment market sentiment, and unemployment. The empirical results of this study have potentially important practical and policy implications. The findings on the different effects of investment and consumption demand on the prices of larger units versus those on smaller units will offer homebuyers guidance on what to buy and when to buy it. Besides, studies on housing price should distinguish the price movements of larger and smaller units when different investment and consumption demands are concerned. Meanwhile, this study should shed light on investment activities. Other than conventional investment indicators, investors can predict price changes in larger units by tracking the influx or outflow of large amounts of capital to and from Hong Kong, respectively. The findings of this study should also help the government take action to influence the prices of larger units without affecting the smaller unit market, and vice versa. / published_or_final_version / Real Estate and Construction / Master / Master of Philosophy

Real estate economists and practitioners have been cognizant of spatial autocorrelation in housing prices for more than three decades. In the early days, they relied to a huge extent on techniques developed in statistical science and focused exclusively on its identification and quantitative assessment in housing studies. It has been well-acknowledged that the presence of spatial autocorrelation in housing prices will compromise the applicability of conventional hedonic statistics, which may lead to biased and inconsistent estimates. In light of this, recent studies in the area have spawned an immense literature aimed at devising sophisticated econometric models such as hedonic spatial lag model and hedonic error model as correction methods. Interestingly, the underpinning factors attributing to its existence remain relatively theoretically unexplored due perhaps to a paucity of quality goereferenced housing data as well as the indifferent attitude espoused by the researchers. Although some general propositions regarding its causes have been proposed, they are accused of lacking inferential basis. Acknowledging the above research gap, this thesis attempts to investigate the underlying factors affecting the formation of, and change in, spatial autocorrelation in housing prices. Specifically, we conjecture that spatial autocorrelation is crucially determined by one of the economic workings of the housing market—price determination process. It is posited that the occurrence of the spatial phenomenon is a direct consequence of how market participants in search of past information in the market ascertain current housing prices. Specifically, spatial autocorrelation is deemed to be established, or increase, when property traders infer current housing prices from past sales of properties (i.e. comparables) located in the same neighborhood as the subject houses. Based on the above information search framework, we put forward three hypotheses to facilitate our examination. First, it is hypothesized that market volatility depresses spatial autocorrelation. As in any other commodity market, past sales transactions in real estate are important sources of price information, which become more obsolescent, and hence, fail to be a good price signal when the market is more volatile. Traders are compelled to rely less on past sales in establishing the current prices of the housing units. Accordingly, spatial autocorrelation will be diminished; following broadly the same line of logic, the second hypothesis is constructed, which states that market liquidity (defined as total market transaction volume) dampens spatial autocorrelation. Given that market liquidity reflects the amount of price information being circulated in the market, traders in accessing property values in a “thick” market do not have to necessarily infer from comparables that are located further away from the subject properties. Hence, a weaker spatial autocorrelation relationship between prices is resulted; third, building age is a critical factor in assessing a house’s redevelopment potential, whose value is largely independent of the transaction prices of the surrounding housing units. Given that a house’s total value can be perceived as an addition of its use value and redevelopment value (i.e. real option value of redevelopment), and that the former’s role decreases whereas the latter’s increases with building age in appraising its total value, it is therefore hypothesized that spatial autocorrelation decreases as building age increases. Several spatial autoregressive hedonic models are developed, with which the three hypotheses are tested using geo-coded open market transaction data in Hong Kong for the period of 1997 to 2008. The results indicate no contrary evidence rejecting any of the hypotheses at the 1% significance level. They soundly confirm the roles market volatility, market liquidity and building age played in the price determination process in real estate, as well as in the formation of spatial autocorrelation. The research findings of this thesis carry several straightforward but far-reaching implications beyond the theoretical literature, among which is the significance to, and impact on, property valuation and economic analysis of local housing systems. A better conceptual understanding on the causes of spatial autocorrelation in housing prices can greatly prompt the development of more parsimonious hedonic models, which are econometrically appealing. In this sense, statistical problems and complications (e.g. loss of degrees of freedom) associated with traditionally-used models, which generally routinely incorporate a long list of locational variables, can be circumvented. In addition, hedonic models derived based on our research findings, which give a simpler yet more realistic representation of the housing market, make real estate mass appraisals much less computationally-intensive. Real estate mass appraisals are used for a variety of purposes, including but not limited to taxation, mortgage assessment, government policy-making, and investment. They are of specific interest to accountants, bankers, real estate developers and investors, government authorities and economists. / published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

Ever since the tax reform in 1994 in China, local governments have to rely more and more on land and real estate related fees as a major source of revenue. With the rapid development of the financial sector in China, local governments also rely more on bank loans with real estate assets as collaterals to finance capital expenditure projects and other government expenditure. Many theoretical studies have suggested that the reliance of local governments on land and real estate related revenue has fuelled housing prices and rendered the central government’s policy to contain housing price escalation ineffective. However, so far there has been little vigorous empirical analysis that supports this argument. This study use panel data from 31 provinces over the period 1999 to 2010 to analyses empirically the role of provincial governments’ behavior in determining housing price levels in China. Our empirical results suggest that the behavior of provincial governments has contributed significantly to regional housing price disparity after controlling for social and economic factors. In particular, we found that the level of fiscal autonomy (local government revenue as a percentage of GDP) has an overall positive impact on housing prices and that such impact is stronger for provinces that are geographically more distant from Beijing. We also found that although the central government’s policy on the RMB exchange rate reform in 2005 has an overall positive impact on real housing prices due to inflow of speculative hot money, such impact varied across different provinces and thus also contributed to regional housing price disparity. Our empirical results suggest that speculative hot money tended to flow into housing markets in provinces with a more developed tertiary sector. This is because regions with more developed tertiary sector usually have more mature real estate markets, lower information costs, better financial and legal services, which facilitates flow of fund into and out of the housing market. This study contributes to the body of knowledge on regional housing price disparity. Unlike previous studies that only focused mainly on the impact of economic, social and government planning policies, this study also aimed at studying the role of fiscal and monetary policies in China. The results have important policy and practical implications. First, while the financial incentives and responsibility given to provincial governments may increase economic efficiency, they may also lead to conflicting goals between central and local governments. In addition such financial incentives and responsibility may unexpectedly lead to housing price bubbles that are economically and socially undesirable. Second, the central government’s policy to reform the exchange rate formation mechanism of the RMB in 2005 has also contributed to housing price escalation which may not be desirable from both social and political perspectives. Even worse still, the impact was not uniform but stronger in provinces with a more developed tertiary sector, which are usually wealthier provinces. Increase in housing prices in these provinces may lead to faster regional economic growth and thus contributing to even more sever regional income disparity, which contradicts the central government’s goal of reducing income polarization. / published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

published_or_final_version / Housing Management / Master / Master of Housing Management

This thesis contains three empirical essays on the economics of house price dynamics. The first essay derives a forward-looking rational expectations house price model and empirically tests its ability to explain short-run fluctuations in real house prices. A novel approach to proxying imputed rents of owner-occupied housing, as a function of housing market fundamentals, is derived and combined with a housing market arbitrage relation to derive a present value model for real house prices. Tests of the rational expectations, nonlinear cross-equation restrictions reject the joint null hypothesis of rational expectations and the asset-based housing price model for quarterly, single-detached house prices in the city of Vancouver, British Columbia, over the 1979-1991 sample period. The model fails to fully capture observed house price dynamics in two real estate booms but tracks real house prices well in less volatile times, suggesting that prices may temporarily deviate from fundamental values in real estate market upswings. The second essay develops and applies a test of the joint null hypothesis of rational expectations, and no risk premium in the Vancouver condominium apartment market. The results show that, on average, ex post house price changes move in the opposite direction than their rational expectation under risk neutrality. This essay also documents the predictability of excess annual condominium returns using lags of annual returns and the rent/price ratio, and quarterly returns with short-term nominal interest rates. It further shows that deviations of house price changes from their (risk neutral) rational expectation are both stationary and related to the stage of the real estate price cycle. The third essay examines whether a time-varying housing market risk premium can explain deviations in house price fluctuations from those predicted by the rational expectations hypothesis under risk neutrality. If homeowners are risk averse and housing price risk is not completely diversifiable then housing market efficiency implies that re turns to housing investment should be positively correlated with a premium for bearing risk. The first part of the essay shows that, in theory, the finding of negative slope co-efficients in tests of unbiased house price expectations under risk neutrality (in chapter 3) is attributable to omitted risk considerations if two conditions are satisfied: (1) the covariance between the risk premium and expected house price appreciation under risk neutrality is negative, and; (2) the variance of the risk premium is considerably larger than the variance of expected appreciation under risk neutrality. The second part of the essay uses a conditional capital asset pricing model to investigate whether predictable returns in the Vancouver housing market are time-varying risk premia. The empirical results are inconclusive.

Since 1970, many inner-city neighbourhoods that were the domain of low-income groups occupying cheap, dilapidated housing have attracted higher socio-economic groups. As a consequence, capital invested has increased the condition and price of inner-city housing. This phenomenon is commonly called "gentrification." This thesis reviews the gentrification literature, analyzes gentrification within an economic framework, and uses regression analysis to test the following hypothesis: There is a lag between the first statge of gentrification, the start of demographic transition, and the second stage, rising real housing prices. An increase in real housing prices can, therefore, be predicted by observing which central neighbourhoods are beginning to undergo demographic change. The intra-urban gentrification model designed for this thesis regresses the change in real housing prices during the 1970s against the change in demographics during the 1960s. The sample is 95 inner-city census tracts from Vancouver, Ottawa-Hull, and Toronto. The conclusion from statistical analysis is that rising housing prices in gentrifying neighbourhoods can indeed be predicted by observing which inner-city neighbourhoods are starting to undergo demographic change. / Business, Sauder School of / Graduate