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

published_or_final_version / Housing Management / Master / Master of Housing Management

It is observed that there are many different models about housing price. Yet, this is relatively smaller number of studies about housing starts. This thesis is an empirical study to work out the relationship between housing starts, housing price and other economic and policy instrumental factors. To achieve this objective, a Vector Autoregression (VAR) model is built since there is inter-relationship between housing starts and housing price. By applying previous models filled with the research gaps, a new VAR model about the housing starts and housing price in Hong Kong is built. Four hypotheses are tested in the thesis. The first and second hypotheses are if housing starts and housing price are affected by the given exogenous variables. The third hypothesis is if the past movement of economic variables reliable in predicting future values of that variable. The last hypothesis is to test if the “high-land-price” policy really pushes up the housing price. The empirical results found in this thesis are a little bit different to previous studies in Hong Kong and overseas. Factors which are frequently proved to be statistically significant are not significant in this study (e.g. interest rate and tender price index). Developers in Hong Kong are found to care more about the future market rather than the current market conditions. Many factors do not exert an influence directly on housing starts but indirectly through their impact to the change of the change of the housing price. It is interesting to know that housing starts react negatively to a change in housing price. An increase in the change of housing price is a bullish signal for the developers. They will hold the land for a while until they expect the peak is coming upon the completion of a project. Therefore, the empirical results suggest the government has to introduce some policies which will lead to a fall in housing price in case that she wants to increase the supply of new private residential housing. Developers will accelerate the applications to commence construction when they expect there will be a downward trend in the housing price (which is shown by a negative change of the housing price.. / published_or_final_version / Real Estate and Construction / Master / Master of Philosophy

published_or_final_version / Housing Management / Master / Master of Housing Management

Disposition effect is one of the most documented trading anomalies studied in financial market. Its presence has been established over time horizons, time periods and market participants. This study will examine such trading behavior in the housing market. Using Mei Foo Sun Chuen estate, one of the largest and most frequent transacted estate in Hong Kong, we show that disposition effect is present in this market. A major difficulty in the statistical analysis is the presence of censored data problem, which is hard to circumvent in linear regression models. So we adopt a survival analysis approach, which can accommodate the issue and fit the data structure. The other difficulty is the possibility of omitted variables in the analysis. Instead of appealing to instrumental variables model approach, which is widely applied in many research studies on individual behavior but is extremely hard to be justified in a whole market case, we make use of partial identification approach to estimate bounds for the estimates rather than just a point estimate. Even though this seems offer us less precise information, it is still informative, especially when the bounds are narrow, and it is much less vulnerable to the validity of instruments. Besides the above techniques, we use bootstrapping method to estimate the standard errors throughout the analysis in order to make valid inference. There are three main results we have established in this study. First, the disposition effect is present in Hong Kong housing market. It shows up in both in pre-1997 and post-1997 periods, which suggest that it is a general phenomenon rather than a short-term trading pattern arising from a major macroeconomic event. Secondly, we show that it is the nominal perspective loss that matters, but not real loss. This confirms the validity of basic setup of both Prospect theory and most previous empirical studies on the disposition effect. Thirdly, the disposition effect is more significant for short term owner of less than 3 years. In fact, the disposition effect is absent or even reverses for those flat owners of more than 6 years. Comparing to the very first study on disposition effect by Shefrin & Statman (1985), our study makes a step forward in understanding trading behavior. We extend it applicability to housing market while their focus is only on financial market even though we are not the first to attempt the extension. We not only show the presence of disposition effect in the housing market, we also show that disposition effect is time dependent. Our results lead further support to disposition effect that its key component, loss, matters only in nominal term, not in real term. Instead of only applying ordinary least squared regression methods, which is widely used in the literature, we apply partial identification approach to tackle the endogeneity issue and apply duration models to deal with censored data and unobserved heterogeneity issues. All this makes our statistical results more robust. / published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

published_or_final_version / Real Estate and Construction / Master / Master of Science in Construction Project Management