Thesis (B.Sc)--University of Hong Kong, 2006. / Includes bibliographical references (p. 131-141)

Thesis (B.Sc)--University of Hong Kong, 2006. / Includes bibliographical references (p. 89-94)

Thesis (B.Sc)--University of Hong Kong, 2005. / Includes bibliographical references.

Eutrophication is the accelerated aging process of a lake which generally decreases the water quality in terms of aesthetic and recreational uses. At Liberty Lake, near Spokane, Washington, eutrophication has become a problem. Many individuals and agencies are interested in the benefits that occur when the lake's water quality has improved. In this research the benefits to private property owners were measured at Liberty Lake. Three methods — present sales, appraised value and personal interview — were compared and empirically tested to determine the economic benefits to private property owners as well as the overall community impact. For this study property was defined as land, buildings and other improvements. Current market sales and appraised values at six different lakes, each with different water quality levels, were used as the dependent variables for the present sales and appraised value methods. The dependent variables were regressed against several factors including physical (.housing, neighborhood, accessibility, and environmental characteristics) to estimate the effect water quality had on property values. A quadratic and double logarithmic function were examined. In the results a positive relationship was found between water quality and the dependent variables. A 100 percent increase in the water quality ranking resulted in a $3,800 increase in the sales price per lot and $884 increase in the appraised value per lot for the quadratic function. Separate equations were determined for vacant lots. The dependent variables were the same, but only neighborhood, accessibility and environmental characteristics were used to estimate the effect water quality had on property values. In the quadratic form with a 100 percent increase in the water quality ranking, sales price increased $556 per lot and appraised value increased $782 per lot. In the personal interview method home owners at Liberty Lake were interviewed and asked for how much they would be willing to buy and sell a particular home at different water quality levels. The differences between the two buying and selling prices were the estimated impact of a change in water quality and totaled $4,795 and $5,679, respectively. Both differences were significant at the one percent level. The buying price difference was used when comparing the personal interview method to the other methods, since it was less likely to overestimate the water quality effect. This research used the best water quality index available, but there is a definite need for future research to develop a uniform water quality index. / Graduation date: 1980

Thesis (B.Sc)--University of Hong Kong, 2005. / Includes bibliographical references (p. 87-100)

Thesis (B.Sc)--University of Hong Kong, 2006. / Includes bibliographical references (p. 128-137)

Thesis (B.Sc)--University of Hong Kong, 2006. / Includes bibliographical references (p. 177-195)

Thesis (B.Sc)--University of Hong Kong, 2006. / Includes bibliographical references (p. 79-87)

The role of liquidity in asset pricing model has attracted much attention in recent financial studies; however there is a paucity of literature with respect to liquidity risk and asset pricing in the direct housing market. The housing market is characterized by costly searching, inelastic supply and short-sale constraints. It is expected that the housing market should incur more significant illiquid effects, since it is much more illiquid than stock market. Motivated by this intuition, this thesis aims to explore 1) whether and to what extent liquidity can explain variations in over-time/crosssectional housing returns; and 2) whether liquidity factor plays a role in explaining the second moment (i.e. volatility) of housing price. We employ the panel regression and Fama-MacBeth two-stage procedure to investigate over-time and cross-sectional relations between liquidity and housing return. Liquidity asset pricing theory suggests that assets with lower degree of liquidity offer higher expected returns. Consistent with this prediction, the panel regression results suggest that housing return is a decreasing function of liquidity in previous year, while it is positively relative to contemporary liquidity shocks. For the cross-sectional asset pricing tests, housing estate specific betas are estimated using rolling time-series regressions of a three-factor asset pricing model. We investigate the proposition that housing estates with greater return sensitivity to market liquidity earns higher expected return. Using a disaggregate dataset of 55 popular housing estates, we find (1) both market liquidity beta and housing estate specific liquidity risk are significantly priced in the cross-sectional housing estate returns, implying that cross-sectional differences in estate premium partially represent the liquidity premium. (2) The market beta, sentiment beta and market liquidity beta explain 14.36% of variations in cross-sectional estate returns. The results are robust across different specifications. (3) Investors are less willing to bear liquidity risk during the down markets, which shed new light on the positive price-volume correlation. These findings complement the cross-sectional liquidity-return relationship in the financial literature. Measuring housing price volatility is fundamental to the study of the dynamics of housing price risk. We investigate the effects of liquidity on housing price volatility in different housing classes (classified by size of the housing unit according to the Rating and Valuation Department’s definitions). Housing price volatility is measured as the conditional variance of a GARCH model under the Adaptive Expectations framework. We reveal that volatility transmits from small housing units to large housing units, which indirectly supports the trade-up effect in previous literature. Besides, the starter and high-end housing classes are extraordinarily sensitive to negative and positive liquidity shocks respectively. Consistent with the friction search theory, we find that the pricing errors are alleviated as the trading volume increases, since the valuated price tends to be more accurate as more information arrives. Lastly, the variance decomposition and impulse response results imply that the positive liquidity shock accounts for a large proportion of variations in housing volatility. / published_or_final_version / Real Estate and Construction / Doctoral / Doctor of Philosophy

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