Real Estate lnvestments: Principles and Evidence - The Cases of Spain and China

Abstract

With the years ahead promising few certainties, limited growth and challenges from every direction to the investment assumptions of old, commercial real estate is taking on new relevance. Both listed and unlisted commercial real estate investments have come of age. This thesis will look at the opportunities which direct property and REITs offer to investors, and consider the wide-ranging contribution the sector makes to society and the entire economy. The dissertation consists of a general introduction and three independent but relevant chapters to deeply analyze the Spanish and the Chinese cross-border real estate investment issues from diversified perspectives. The thesis involves both listed and unlisted real estate questions that are unexplained well in existing literature yet. The general introduction broadly presents a big picture of the globe, the Spanish, and the Chinese real estate investment environments and status, respectively. Also, the research background and significance, as well as the theoretical foundation for this study and methodologies adopted for each chapter are lined out here. Chapter 1 aims to figure out those potential determinants for international capital flow towards the Spanish unlisted real estate and construction sectors. By applying the Stock-adjustment model developed by William H. Branson in 1968, and via the Vector Autoregression (VAR), Vector Error Correction Model (VECM), as well as the Pooled Engle and Granger Least Square (Pooled-EGLS) regression method, the empirical results demonstrated that the Spanish GDP growth rate, the M3 money supply, housing prices, country risk, as well as interest rates have a strong correlation with foreign real estate capital flow towards the Spanish property sector. Besides, cross-border capital flows into the Spanish construction sector is also estimated by utilizing the same indicators for real estate study. But less evidence is found through the same pattern. Chapter 2 focuses on the analyses of risk and returns relationship far the Spanish REITs. The celebrated Fama and French Three-Factor (FF3) model developed by Eugene Fama and Kenneth French in 1993 is applied in this case. Based on the Autoregressive Distributed Lag Model (ARDL), the results indicate that the Spanish REITs yields can be explained well by the Market, Size, and Value three standard Fama-French factors, which are in line with the previous research on common shares. By comparison purposes, the Carhart four factors model that expanded from the FF3 model also employed. However, the momentum indicator is not significant in this case. Chapter 3 analyzes what drivers that likely drive the Chinese real estate capital outflows to the main European cities. This article adopts the Gravity Model of trade to do the research, which has been extensively utilizing far FDI studies. Due to the zero-investment issue that exists during the sample period, the Heckman model is utilized to avoid the sample selection bias. Both Maximum Likelihood and Two-Step regression methods are run but paying attention to the results from the ML method. The first-step regression results indicating that push factors such as China's foreign exchange reserves and the Chinese government investment policy (Belt & Road lnitiative), as well as a set of pull factors including the host cities inflation, real estate transparency, housing prices index, and the total resident population, affecting the probability that China sends its real estate capital to the recipient cities. For the gravity model that corrected by the lnverse Mills Ration, the second-step regression results tell that only the Chinese GDP affects the real estate capital outflows in the destinations in this case.