Essays on real estate markets in Hong Kong

Abstract

This thesis consists of two chapters. The first chapter studies the dynamics of office market in Hong Kong, while the second chapter investigates the relationship between the initial public offerings and real estate markets in Hong Kong. It attempts to relate the stocks’ performance to the commercial real estate market. The pervious literatures focus on the interactions among the relevant economic variables, including the office rents, employment growth, construction rate, sectoral output, interest rate, and the quality of offices. This thesis complements the literature by relating the commercial real estate market to the stock market and liquidity variables. The first chapter attempts to reproduce the results from the previous literature with 20-year data in Hong Kong. Using Wheaton model as the basic one, our paper first tries to improve it by adding stock market and interest rate variables in the model. Through applying Vector Autoregression (VAR) Model, normality tests, and Granger Causality Tests, we find that these additional variables are incapable to explain at the highest class of office market, but are valuable to explain at lower classes of office market. The result has important implications to the modeling and monitoring of office market. The second chapter examines empirically the relationship between the real estate market and initial public offerings in Hong Kong. “Production theory”, “psychology theory” and “underlying factor theory” are the three plausible reasons accounting for their relationship. By running different VAR models and granger causality tests, strong evidences were found to support “psychology theory”, while the other two theories were not supported. It also has implications to policymakers because it highlights the investors’ interest towards Chinese economy.

Date of Award	2 Oct 2008
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Lixin HUANG (Supervisor) & Ka Yui Charles LEUNG (Supervisor)