Dissertation: Is There A Housing Bubble In Hong Kong (Dissertation Sample)

Abstract
This study uses the PSY (Phillips, Shi, and Yu, 2011) method to detect the presence of housing bubbles in Hong Kong for all house classes (A, B, C, D and E) (based on the area) as identified by the Ratings and Valuation Department, Government of Hong Kong for the period January 2003–November 2016. On analysing the monthly price-rent ratio, multiple bubbles were observed over the observation period, the frequency of which increased with the area of the houses. While, most of the bubbles observed in the last decade are negative bubbles (because of the global economic uncertainty), most of the bubbles observed in this decade are positive bubbles (recovery by the global economy). Despite the housing price in Hong Kong falling down drastically in 2016, a housing bubble is still found to be present, as observed for November 2016.
Table of ContentsIntroduction………………………………………………………………..……6-8Background to the studyResearch overviewStructure of the dissertationLiterature Review……………………………………………………………9-19Mechanism of the property bubbleMethods of bubble detectionOverview of Hong Kong real estate marketResearch Methodology…………………………………………….………20-24Sampling & data collectionResearch approach & analysis techniquesFindings…………………………………………………………………..…25-42Price indicesRental indicesPrice-to-rent ratioDetection of bubblesTime stamping of bubblesDiscussion……………………………………………………………………43-45Observation 1Observation 2Observation 3Observation 4Conclusion……………………………………………………………………46-48Summary of the researchRecommendation to stakeholdersLimitations of the studyValidity of the studyReferencesAppendices
List of Figures
Figure 1: Structure of this dissertation
Figure 2: Asset bubble mechanism
Figure 3: Price Index for All Classes
Figure 4: Rental Index for All Classes
Figure 5: Price-rent ratio for Class A
Figure 6: Price-rent ratio for Class B
Figure 7: Price-rent ratio for Class C
Figure 8: Price-rent ratio for Class D
Figure 9: Price-rent ratio for Class E
Figure 10: BSDFr2 (r0) statistics for Class A
Figure 11: BSDFr2 (r0) statistics for Class B
Figure 12: BSDFr2 (r0) statistics for Class C
Figure 13: BSDFr2 (r0) statistics for Class D
Figure 14: BSDFr2 (r0) statistics for Class E
List of Tables
Table 1: Class of houses based on the area
Table 2: Descriptive statistics for price-rent ratio for Class A
Table 3: Descriptive statistics for price-rent ratio for Class B
Table 4: Descriptive statistics for price-rent ratio for Class C
Table 5: Descriptive statistics for price-rent ratio for Class D
Table 6: Descriptive statistics for price-rent ratio for Class E
Table 7: sup sup DF statistics for all the classes
Table 8: No. of bubbles for all the classes
1 Introduction
1 Background to the study
Over the last two decades, both the advanced and the emerging economies have been plagued by several financial crises- the Asian financial crisis, the Dot-Com crisis, the European debt crisis and the global financial crisis. Despite the asset being different in each of these crises, these crisis were characterised by the collapse of asset pricing bubbles (Yui et al., 2013). One such asset, real estate is a very important asset class especially for the investors in the Asian economies as the Asian investors are known to buy the properties for price appreciation instead of simply dwelling purpose (Tsai & Peng, 2011), which results in the dynamics of the housing market in the Asian economies potentially impacting the global financial stability (Hui, 2011). Based on the above severity of the crises as a result of bubble implosion, the economists and the policymakers search for ways to detect bubbles early, so that appropriate measures can be taken to deflate the asset bubbles before they implode.
Over the period, 2003-2015, the inflation-adjusted price of the apartments in Hong Kong rose by a factor of 3.8, which is much higher than the observed growth in the United States, prior to the 2007 subprime crisis (Richmond & Roehner, 2016). This rapid growth in the housing prices can either be a result of the high demand or be an indication of the presence of a bubble. Of late, there are contrasting views on the housing prices and the presence of a bubble in the housing sector in Hong Kong - In April 2016, Richter (2016) highlighted that the housing bubble in Hong Kong has imploded as characterized by the collapsing sales and the prices falling down by 11.7% over the period September 2015 – March 2016. Property analyst Nomura added that over the next two years the fall in price will continue. Nomura also estimated the housing prices to fall by approximately 19.7% till the end of 2017. However, in September 2016, Zheng (2016) referred to the finding by UBS that Hong Kong has the highest price-to-income value in the world. Although the rent prices in Hong Kong have decreased by 8% since the peak value which was achieved in 2015, the price-to-rent ratio is still considered to be at an unsustainable level, which shows that the risk of a bubble is still there, thus a possibility of further implosion of the bubble still remains.
The need for this research arises because of these contrasting views on the presence of a bubble in the housing market in Hong Kong.
2 Research overview
This research attempts to answer the following research question-
Is there a bubble in the real house price in Hong Kong?
Stiglitz (1990) defined an asset bubble to be present if there is a dramatic increase in the price of the asset followed by an immediate dramatic fall in the price. He was of the opinion that the investors’ perception about the asset’s price rising in the future is the reason that the current asset price also increases.
The most popular method to identify the presence of a bubble is the present value method, which is difficult to use with accuracy, as a result several indirect methods like the bubble proxy and forewarning indices are recommended to detect a bubble using several indicators which have strong correlation with the bubbles. The bubble proxy method uses one indicator whereas the forewarning method creates an index using several indicators. The widely used indicators are price–income ratio, price–rent ratio and vacancy rate (Yu, 2015).
This research uses the bubble proxy method suggested by Phillips et al. (PSY) (2011) which is a modification of the method suggested by Phillips et al. (PWY) (2011)) to determine the presence of the bubble in the housing market in Hong Kong. The observation period for this research is 2003-2016, the rationale behind the selection of the observation period is discussed in the third chapter.
3 Structure of the dissertation
This dissertation is structured in six chapters which are demonstrated below:
Figure 1: Structure of this dissertation
2 Literature review
In this chapter, the relevant literature on the mechanism of the property bubble, methods of bubble detection and the Hong Kong real estate market will be reviewed.
2.1 Mechanism of the property bubble
Brunnermeier (2008), further added to earlier-mentioned definition of Stiglitz (1990) that the investors’ expectation about the asset prices to increase in the future, results in a price deviation from the fundamental value. However, the supporters of efficient markets denied the possibility of a bubble, as they believed that the market price is justified (Smith & Smith, 2006). Blanchard & Fisher (1989) identified that the price of the asset is made up of two components — the bubble price and the fundamental price. Stiglitz (1990) also found that if the current asset price cannot be justified by the fundamental factors, then it could be an indication of presence of an asset bubble. The difference between the market price and the price estimated by the fundamentals cannot sustain for long, and as a result the bubble bursts and the price drops (Hui, 2011). However, it needs to be understood that the increasing asset prices or high prices of the asset are not necessarily a sign of the bubble (Feng & Wu, 2015).
Lind (2008) identified three kinds of bubbles. The first are the purely speculative bubbles, where the buyers believe that the current asset price is high and will eventually fall. However, they also believe that the fall will not be immediate and that they will be able to sell the asset at a profit before the price of the asset falls. The second type are the irrational expectations bubbles, where the investors are over-optimistic and expect the price of the assets to grow rapidly and to keep doing so for a long time. The estimated future price being much higher than the historical average price, results in the investor paying a higher price when he purchases. The third type are the irrational institutions bubbles, which are attri...