Dept of Real Estate and Construction Management
Div of Building and Real Estate Economics
Master of Science Thesis no. 435
Price Analysis of Chinese Real Estate Market
Author:
Yukun Han
Supervisor:
Abukar Warsame
Stockholm, 2008
Master of Science thesis
Title:
Authors
Department
Master Thesis number
Supervisor
Keywords
Price Analysis of Chinese Real Estate Market
Yukun Han
Department of Real Estate and Construction
Management
Division of Building and Real Estate
Economics
435
Abukar Warsame
Price, Chinese Real Estate Market, Carey Model
Abstract
Based on the Carey (1990) model, this paper attempted to give some explanations for the
increase of real estate price in China, provide the methods to drive the real estate prices into
the reasonable level, and bring out some countermeasures to prevent and control the real
estate bubbles of China. From the econometric results, it was indicated that in the real estate
market of China, the supply in the real estate market is negatively related with the real estate
price, and the number of investors involved in the market and the available financial resources
from banks both have positive correlations with the real estate price. According to the current
situation of China’s real estate market, these three factors in some degree can explain the
extremely high real estate price in China, which would make the real estate market vulnerable
to the bubble crisis. Additionally, the price-income ratio and the vacancy rate were introduced
and calculated in this paper in order to give a comprehensive analysis to China’s real estate
market. Increasing the reasonable supply, adjusting the number of investors and regulating the
credit scale can benefit for the balanced development of real estate market and avoiding the
real estate bubbles.
Acknowledgement
After five months continuous hard work, this paper has been finished, this is not only my
master thesis in the program of Real Estate Management, but also the benchmark in my life.
Firstly, I want to thank my supervisor Abukar Warsame. Without his careful and constructive
helps, I cannot finish this paper so successfully.
Secondly, I want to thank Yuqi Yao, my beloved wife forever. She always gives me
encouragement, confidence, and selfless care, when we lived in Sweden. And I also want to
thank our mother, Yunhua Li, who encouraged us to go abroad for further study. And I want
to thank my parents and all of family members. I love you all forever!
Finally, I also want to give thanks to my lovely classmates, I can’t achieve success without
your help and concern. Thank you very much!
Yukun Han
May, 2008, Stockholm
3
Table of contents
1 Introduction............................................................................................................................6
1.1 Real Estate Bubbles in Asian Countries...........................................................................6
1.1.1 Japan.................................................................................................................................6
1.1.2 Thailand............................................................................................................................7
1.1.3 Malaysia............................................................................................................................8
1.1.4 China.................................................................................................................................9
1.2 Purpose...............................................................................................................................11
1.3 Structure............................................................................................................................11
2 Methodology.........................................................................................................................13
2.1 Methodology of Science....................................................................................................13
2.2 Data Sources......................................................................................................................13
2.3 Related Researches...........................................................................................................14
3 Theory and Analysis............................................................................................................16
3.1 General Economic Analysis of Chinese Real Estate Market........................................16
3.1.1 Information Asymmetric...............................................................................................16
3.1.2 Externalities....................................................................................................................18
3.1.3 Imperfect Competition..............................................................................................…19
3.1.4 Restriction of Supply.....................................................................................................20
3.1.5 Government's Improper Intervention.........................................................................21
3.2 Carey Model......................................................................................................................21
3.2.1 Introduction of Carey Model........................................................................................21
3.2.1.1 Total Amount of Supply in the Real Estate Market (Z)...........................................23
3.2.1.2 Deviation between Reservation Price and Fundamental Price (h).........................24
3.2.1.3 The Number of Investors in the Market (N).............................................................24
3.2.1.4 The Available Financial Resources to Investors (L)................................................25
3.2.2 Test of Carey Model.......................................................................................................25
3.2.2.1 Hypothesis....................................................................................................................26
3.2.2.2 Definition of Variables................................................................................................26
3.2.2.3 Sample and Data.........................................................................................................26
3.2.2.4 Econometric Model.....................................................................................................27
3.2.2.5 Regression Results.......................................................................................................27
4
3.2.3 Analysis...........................................................................................................................28
3.2.3.1 Restriction of Supply in Real Estate Market--Z......................................................28
3.2.3.2 Diversification of Investors in the Real Estate Market--N......................................30
3.2.3.3 The Effects of Banking Credit on the Real Estate Market--L............................... 31
3.3 Indicators to Measure the Real Estate Bubble...............................................................33
3.3.1 Price-income ratio..........................................................................................................33
3.3.1.1 Definition......................................................................................................................33
3.3.1.2 Price-Income Ratio in China's Real Estate Market.................................................34
3.3.1.3 Limitations of Price-income Ratio.............................................................................34
3.3.2 Vacancy Rate..................................................................................................................35
3.3.2.1 Definition......................................................................................................................35
3.3.2.2 Vacancy Rate in China's Real Estate Market..........................................................36
3.3.2.3 Limitations of Vacancy Rate......................................................................................36
3.4 Countermeasures to Control and Prevent Real Estate Bubbles...................................38
4 Conclusions...........................................................................................................................41
Appendix..................................................................................................................................43
References................................................................................................................................52
5
1 Introduction
With the modernization of society, the world economy, especially the modern market
economy, has continually been plagued by economic bubble, and bubble has become a
widespread economic phenomenon in the world. From the beginning of the establishment for
market economic system, the Dutch Tulip Bubble in 17th century, the Mississippi Bubble of
France and the South Sea Bubble of London in the early 18th century already cast a shadow of
bubble to the world economy. Then with the development of modern market economy, the
international capital flows, the currency exchange and the increased credit loans have also
provided the adequate conditions to the formation of economic bubble. The economic bubble
makes it difficult to distinguish between investment and speculation, which would cause the
irrational expectations of investors and easily trigger an economic crisis. Also, the inherent
cyclical fluctuations of market economy would aggravate the damage of economic bubble
further.
1.1 Real Estate Bubbles in Asian Countries
The real estate industry in Asian countries has developed rapidly in the recent 100 years,
which makes a large contribution to the world-wide economic growth in the 20th century.
However, due to various complicated reasons, some countries and regions have undergone a
terrible real estate bubble, such as Japan, Thailand, Malaysia, and Hong Kong, which left
nothing but poverty to millions of investors.
1.1.1. Japan
The latter half of the 1980s was an extraordinary period in Japanese economic history.
Future historians will call it "the age of the bubble." Stock and land prices showed
remarkable increases and the economy enjoyed an investment and consumption boom.
Overseas investment from Japan increased very rapidly and Japan become the world's largest
creditor country.（Noguchi, 1994）
The real estate bubble of Japan started with the "Plaza Agreement" signed in 1985, which was
represented by a significant appreciation of the Japanese Yen. According to the data released
by the Ministry of Land, Infrastructure and Transport of Japan, by the end of 1991, the prices
of commercial land in six major cities of Japan increased by more than three times in such a
short period. During this period, the demand in the whole real estate market was quite strong,
6
and the speculation was prevalent, which stimulated the sustained increase of the real estate
prices.
However, with the burst of the bubble, from1990 to the present, the real estate prices in most
cities of Japan have dropped continually, which resulted in an extremely high ratio of nonperforming assets. Until the March of 2003, seven major Japanese banks have written off
about 5.6 trillion yen bad debts totally, and the Nikkei Stock Index also dropped below 8000
points (Japanese Economic and Fiscal Report, 2003), the lowest level in history. The burst of
the economic bubble, especially the lasting decline in real estate prices led to a serious
financial crisis, and destroyed the Japanese economy wholly. Japanese economy has entered a
long term recession period and in the following 10 years, the economic growth has always
been wandering at the state of stagnation, which is called as the “lost decade” by economic
circle.
1.1.2 Thailand
The East Asian Financial Crisis in 1997 started in Thailand. Since the 1980s, Thailand has
adjusted its overall industrial structure; it followed the experience of Asia “Four Small
Dragons” to abandon import substitution policies and took the export-oriented industries as
the key industries to develop, which brought the temporary prosperity to Thai Economy. On
the other hand, in order to improve the poor infrastructure construction and solve the shortage
of funds, Thai Government adopted series of preferential financial and monetary policies to
accelerate the reform of financial liberalization, and expand offshore financial business (Li,
2004). However, this blind pursuit of economic growth expanded the domestic investment
and credit scale rapidly in Thailand, and most personal loans did not flow into the production
sectors but the non-tradable sectors, such as real estate market and the stock market.
Particularly, in the late 1980s, due to the appreciation of the Yen and the collapse of the
economic bubble in Japan, Japan began to export large-scale capital to Southeast Asian
countries. Because of the adequate labour resources, the relative low land prices and labour
costs, as well as the various preferential policies in Thailand, large amounts of capital has
been easily attracted to Thailand, following with the constantly increased demand for foreign
capital in Thailand.
7
Therefore, with the expansion of banking credit, the real estate prices in many major cities,
such as Bangkok, increased remarkably, and the high profits in the real estate industry
attracted a large amount of international capital. Moving in cycles, the real estate bubble
expanded sharply. In 1989, the amount of the housing loans in Thailand was 45.9 billion baht,
which increased by more than seventeen times to more than 790 billion baht in 1996. At the
same time, the real estate prices also increase rapidly. During the period from 1988 to 1997,
the average annual growth rate for land prices was 20% from 1988 to 1992, and 40% from
1992 to 1997; especially, in some areas, the land prices increased by more than 14 times. Till
1997, there are 850,000 vacant residential units in Thailand, almost half of which were
located in the city of Bangkok, and the vacancy rate reached to 21% (Xu et al. 2002). The
excessive expansion of bank credit inevitably resulted in large bubbles accumulated in the real
estate industry of Thailand.
According to Collyns and Senhadji (2002), from the end of 1995, the once high-flying stock
market of Thailand began to slump, which dropped more than 70% until April of 1997.
Particularly, the cumulative decreasing range in the real estate stocks was about 85%. Many
international Investment Funds have retreated capital from Thailand, which created
tremendous pressure to Thai exchange rate. At last, the Thai government had to give up the
fixed exchange rate system, then both the stock index and real estate price declined sharply;
only in the second half of year 1997, Thai baht was devalued by about 50%, and the real
estate price decreased by nearly 30% (Li, 2004). Real estate bubbles in Thailand burst finally.
1.1.3 Malaysia
Malaysia, like other Southeast Asian countries, implements export-oriented economic policies
all along, and the international trade plays an important role in the national economic
development. According to the World Bank Database, from 1990 to 1996, the export in
Malaysia grew at an average annual rate of 18%, which was 10 percent points higher than the
growth rate of GDP, and stimulated the rapid economic growth in Malaysia. Furthermore, in
order to keep a sustained economic development, the government investment of Malaysia
increased rapidly to an extremely high level in the 1990s, and the demand for capital became
very great. Therefore, Malaysia government adopted series of policies to accelerate the
financial liberalization and facilitate the capital flows, which caused large amounts of
international capital inflows and imposed a heavy burden of foreign debt on the government.
Till June of 1997, the total foreign debt had reached to 45.2 billion US dollars, 30% of which
8
was short-term foreign debt. Similar as Thailand, most of this foreign debt did not flow into
the real economic production, but was invested into the real estate market and stock market,
which would speed up the formation of bubbles.
With the expansion of investment and credit scale, an unusual prosperity appeared in the
entire real estate market. The Government of Malaysia invested lots of capital and labour
resources to improve the infrastructure construction and to build "vanity projects", such as the
Multimedia Super Corridor Project, the Artificial Island Project, the Malacca Strait Bridge,
and other large-scale construction projects, which led to the overheated development of the
entire real estate and construction industries. Additionally, because of the inefficiency of
Malaysian financial supervision system and the "moral hazard" problem existing in the
deposit insurance system, amounts of speculative capital flowed into the domestic real estate
industry and stock market, which led to the rapid increase in real estate price. For instance, in
Kuala Lumpur, the capital of Malaysia, during the year of 1995, the residential rental rose by
55% and housing prices rose by 66%; on the other hand, the vacancy rate increased from the
normal level 5% in 1990 to the extremely high level 25% in 1998 (Xie, 2002).
However, the economic bubble in Malaysia collapsed rapidly with the outbreak of the Asia
Financial Crisis. Malaysia exchange rate slumped from one dollar to 2.5247 ringgit in July of
1997 till one dollar to 4.88 ringgit in January of 1998 (ASEAN Annual Report, 1999),
devalued in half. Furthermore, more tragic collapse happened in the stock market; the Kuala
Lumpur Composite Index shrank from1077.3 points on June 30th, 1997 to 594.44 points on
December 31st, 1997, and the financial and real estate stocks dove by 70% to 90%; nearly
225 billion dollars’ value was vaporized from the Kuala Lumpur Stock market in such short
period. Then the real estate bubble bursted; average daily trading volume in Malaysian real
estate market fell by 37% in the second half of 1997, and various housing price index began
to drop substantially (Li, 2004). So far, economic bubble in Malaysia also collapsed finally.
1.1.4 China
China's real estate industry has developed rapidly in recent 20 years. Especially from the
1990s, the Housing Reform and fast development of urbanization have created large new
demand for lands. The increased labour income, the advanced construction techniques, plenty
of new urban population, and the improved bank credit scales contribute to upgrade the
quality system in real estate enterprises, and have gradually transferred the demand for
9
building-style from commercial buildings to residential buildings. The main body of
consumption in real estate market has shifted from the Groups to the individuals, and the real
estate productions have changed from consumer goods to investment goods, which attracts
not only large amounts of domestic investors but also lots of international investors to invest
in China’s real estate market.
Since 1998, the growth rate of Chinese real estate development & investment has always been
higher than the growth rate of total investment in fixed-assets. During the period from 2000 to
2006, both the floor space under construction and floor space completed have increased
greatly (China Statistical Yearbook, 2006); furthermore, within the real estate supply
structure, the total supplies for economically affordable houses, the luxury apartments and
villas have declined quite a lot; instead, the share of the ordinary residential buildings has
enhanced gradually.
The supply-demand relations attribute to the fluctuation of real estate prices eventually.
Corresponding to the large increase of the land prices in 2002 and 2003, the residential
building prices have risen distinctly since 2003. According to China Real Estate Statistics
Yearbook 2004, during the period from 2000 to 2004, within the 35 major cities of China,
there are 19 cities where the housing price index increased by more than 5%, thirteen of
which locate in southeastern China, the most economic developed regions in China.
Meanwhile, with the continuous RMB (Chinese yuan) appreciation expectation, great
amounts of international hot money keep flowing into China, especially the China’s stock
market and real estate market, which provide the possibility for economic bubbles.
The real estate bubbles occurred in many major cities of the world, such as London, New
York, Tokyo and Hongkong. According to Ren (2007), different degree of real estate bubbles
exist in some of China’s major cities. These cities can be devided into four types.
1.
Cities in the formation stage of bubbles. The real estate prices in these cities had kept low
and stable for a long time before, but the land and housing prices increased rapidly in
recent years, such as Tianjin.
10
2.
Cities entering the expansion stage of bubbles. In the recent 10 years following the
overheated real estate investment from 1992 to 1993, the real estate prices in these cities
have increased fluctuantly and the speculation phenomena seldom occur in these cities,
such as Beijing.
3.
Cities in the expansion stage of bubbles. The real estate prices in these cities have
increased rapidly and sustainedly, and the emergence of speculation has accelerated the
rise of real estate prices, such as Shanghai and Hangzhou.
4.
Cities in the stage of bubble collapse. In these cities, the speculation has reduced
gradually, the demand is apparently less than the supply, the real estate transaction
volumes fall sharply, and the collapse of real estate bubble would happen at anytime,
such as Wenzhou.
1.2 Purpose
The purpose of this paper is to analyze the factors which affect the real estate prices, and the
relationship among each factor with the real estate bubbles. Based on the Carey (1990) model,
empirical methods are used to find out the practical application of this model in the reality of
China, and this paper hopes to find the reasons for the increase of Chinese real estate prices.
Then this paper will introduce some real estate ratios which can measure the real estate
bubbles existing in China’s real estate market, such as price-income ratio and vacancy rate.
According to these ratios and some lessons from real estate markets in Southeast Asia
countries, this paper also can provide the countermeasures in control and prevention of real
estate bubbles to the Chinese government.
1.3 Structure
This paper is divided by four parts; the first part of this paper will give some examples of
economic bubble which happened in some Asian countries, and introduce the status of
China’s real estate market, then propose the main purpose of this paper. The second part is
methodology part. The third part introduce the basic ideas of Carey model, then according to
the this model, the paper will give the explanations for the increase of real estate price in
China from three aspects combined with the current situation of China’s real estate market; in
11
addition, some ratios to measure whether the bubbles exist in real estate market will be
discussed in this part. Last part is conclusion.
12
2 Methodology
2.1 Methodology of Science
The scientific methodology is the guide of an article in the economic studies, and ambiguous
and unscientific methodology often leads to chaotic logic and reasoning.
When a hypothesis is tested, it can be either verified (shown to be true) or falsified (shown to
be false). In order to be useful in science a hypothesis has to be testable, i.e. possible to verify
or falsify. But which is most important, verification or falsification? In the 20th century two
schools of thought emerged, one of which gave absolute preference to verification and the
other to falsification. The first of these schools was, logical empiricism, also called logical
positivism or the Vienna school. Its proponents claimed that a sentence cannot be at all
meaningful unless it is possible to verify......The other school was founded by Karl Popper
(1902 – 1994). He proposed that we should stop trying to verify theories or hypotheses. His
major argument for this was that theories and hypotheses consist of universal statements, and
such statements, he maintained, are not possible to verify. (Sven Ove Hansson, 2007)
According to The Oxford Dictionary of Philosophy, 1994, the Hypothetico-deductive method
is associated with a philosophy of science that stresses the virtues of falsification. A
hypothesis is proposed, and consequences are deduced, which are then tested against
experience. If the hypothesis is falsified, then we learn from the attempt, and are in a position
to produce a better one. If not, then we can try other tests. This is a process of hypothesis
proposing, deduction, and falsification
2.2 Data Sources
The data files in this paper are collected from the China Statistical Yearbook (1999-2007),
and the Beijing Statistical Yearbook (1990-2006). The data used here focuses on economic
indicators of Chapter 6 in Statistical Yearbook: Investment in Fixed Assets in 31 functional
Provinces, Autonomous Regions and Municipalities of China which exclude Hong Kong and
Taiwan. The period from the late 1990s to 2006 is the research focus in this paper, because on
the one hand, this period is the golden period of rapid growth and development in China’s real
estate industry; on the other hand, there still has the heated debate on whether the real estate
bubbles exist in China during this period.
13
2.3 Related Researches
In a paper released by the International Monetary Fund (IMF) in 2002, Collyns et al. studied
that the relationship among lending booms, asset price cycles and financial crisis across the
East Asian countries. With theoretical arguments and empirical evidence, it suggested that the
asset prices inflation, the real estate bubbles and subsequent financial crisis in East Asian
countries can be largely explained by bank lending booms; furthermore, the effect is
considerably stronger in real estate market than in the stock market. In addition, the response
of property prices to credit is asymmetric in the sense that the response during period of
rising property prices is three time the response during periods of declining prices.
In another paper released from IMF, Hilbers et al (2001) showed that unbalanced
development in real estate prices is an important factor contributing to vulnerabilities and
possibly crisis in the financial sector. There exists significant positive correlation between
real estate prices and bank credit scales. The authors indicated that the bank plays a key role
in real estate market through many channels:
a) Lending for real estate purchases, financing of developers and construction companies.
b) Lending to non-bank financial intermediaries (finance companies) that engage in real
estate lending.
c)
Use of real estate as collateral for both real estate and other lending.
d)
Direct investment in real estate.
Therefore the long cycles in real estate, the insufficient data and assessments for the recent
real estate values, the weak supervision and regulation on real estate market, and moral hazard
problems, all of these would lead the financial sector to be mired in crisis. Additionally, the
real estate market has some specific characteristics:
a) Heterogeneity of supply.
b) The absence of a central trading market.
c) Infrequent trades.
d) High transaction cost.
e) Prices that are often determined by bilateral negotiation.
f)
Rigid and constrained supply.
g) Financing through borrowing.
h) The use of real estate as collateral.
14
i)
Large differences between countries in the legal, prudential, taxation and financing
framework within which real estate is produced and traded.
These would further complicate the analysis for real estate prices development.
Herring and Wachter (1998) analyzed the relationship and dynamic mechanism between the
real estate cycles and banking crises. Firstly, an increase in the price of real estate may
increase the supply of credit to the real estate industry, which in turn, is likely to lead to
further increases in the price of real estate. The bank credit would reinforce the increase of
real estate prices; Secondly, when the real estate prices begin to collapse, the bank behavior
would hasten this decline. According to this paper, moral hazard problem plays an important
role in increasing the risk of financial system’s collapse, especially when bank shareholders
have little to lose and bank depositors believe they will be protected by the safety net. Also,
the poor information and inadequate analysis result in the growing vulnerability of banking
crises.
Qu and Li (2004) examined the relationship between real estate prices and bubbles. Combined
with the incomplete competition market structure and the supply constraint of the housing
market, a theoretical model was built to explain the phenomena of the rapid increase in recent
China's real estate prices. Results indicated that the increasing market demand, the easy
access to financial resources and the oligopoly competitive market are the major factors
leading to the increase of real estate prices and the formation of real estate bubbles.
15
3 Theory and Analysis
According to Eatwell et al. (1998), A bubble may be defined loosely as a sharp rise in price of
an asset or a range of assets in a continuous process, with the initial rise generating
expectations of further rises and attracting new buyers - generally speculators interested in
profits from trading in the asset rather than its use or earning capacity. The rise if usually
followed by a reversal of expectations and a sharp decline in price often resulting in financial
crisis. A boom is a more extended and gentler rise in prices, production and profits than a
bubble, and may be followed by crisis, sometimes taking the form of a crash (or panic) or
alternatively by a gentle subsidence of the boom without crisis. In theory, real estate prices
depend on the economic returns and utilities of real estates; so when prices have been inflated
too much and seriously deviate from the true values, bubbles will inevitably exist in the
markets.
3.1. General Economic Analysis of Chinese Real Estate Market
Milgrom and Roberts (1992) have stated that the resulting allocation of goods and services is
Pareto-efficient when
a) Each firm maximizes its profits, knowing the prices and its own production technology.
b) Each consumer maximizes utility, knowing the prices and his or her own preferences.
c) Income and prices are such that demand equals supply for every good and service.
However, this conclusion is based on a series of strong assumptions, which cannot be strictly
satisfied in real world, because the real market structure is imperfect and the market
mechanism always fails in the allocation of resources. Therefore, the real economic operation
mechanism, which cannot satisfy the Pareto optimality, will inevitably cause the inefficient
allocation of resources and the loss of social welfare. Particularly, because of some special
characters of real estate market, there always exist the market failure phenomena in real estate
market, which could be liable to trigger bubbles. These market failures mainly include the
information asymmetry, the negative externalities, incomplete competition markets, the
supply restrictions and government's improper intervention.
16
3.1.1. Information asymmetric
The model of perfect competitive market assumes that the market works with the complete
information, which means all the participants, including both supply-side and demand-side in
the market, can access to all relevant information; however, in the real world, especially in the
financial market, the information is often incomplete. The "information asymmetric" (MasColell et al. 1995) refers to the asymmetric distribution of information in transaction, that is
one party holds more information than the other party, which would affect the decisionmaking behaviours of each participant. Furthermore, even facing the same information, if two
parties have significant difference in the ability for processing and analyzing information, this
also can be taken as a kind of information asymmetry.
In a sound market system, real estate price should be equal to its replacement cost, that is the
sum of the present value for rents in each period (Yang et al. 2005), which is largely affected
by the relationship between market supply and demand. In the situation of information
asymmetric, excessive speculations would lead to overestimate or underestimate the future
returns of real estate investments. When the investors are over-optimistic about the future
economic situation, a large amount of capital would be attracted into the real estate market by
high rate of returns, large parts of which mainly come from the banking credit loans or
mortgage loans. However, the real estate market is inevitably affected by many factors. Even
in the circumstance of complete information, although investors can adjust their investment
strategies to minimize the risk and maximize the profit according to the different economic
situation, the complicated economic operation make it difficult for investors to give rational
judgment, and they always believe that the real estate prices would never drop before they
retreat capital from the market, which would cause the formation of the real estate bubble
eventually.
Asymmetric information would lead to "adverse selection" problem before the transaction,
and create "moral hazard" problem after the transaction (Mas-Colell et al. 1995). Real estate
industry is a capital-intensive industry, which cannot be developed without support of
financial resources. However, because of the imperfect financial system in China, information
asymmetric would create the serious problem of adverse selection. The investors who are
risk-seeking and in poor credit often can obtain loans from banks; on the contrary, those who
are risk-averse and have ability to return the loans with good reputation have to be driven out
from the lending market. Then the "adverse selection" problems take place. On the other
17
hand, currently, the Chinese government bear the complete secured responsibility for stateowned financial systems, so there would exist the serious "moral hazard" problem in the
decision-making process of financial institutions. Banks blindly pursue the expansion of
market share, and ignore the credit examination for enterprises and individuals and the
profitability assessment for projects, which would make the financial institutions greatly
underestimate the potential risk of investment projects. Once a high-risk project succeeds, the
exclusive benefits belong to banks; however, if borrowers default, banks often only need to
bear a small part of the loss, and the government has to pay the bill for banks ultimately. The
risk of moral hazard is quite difficult for people to realize during the period of market
prosperity, and the increasing loans from banks would speed up the expansion of bubble in
real estate market. Once the bubble burst, the value of collateral would depreciate sharply, and
the banks have to dispose of a large amount of non-performing assets, which would not only
damage the financial systems, but also destroy the sound development of entire economy. In
the Southeast Asian Financial Crisis, the value of real estate in Thailand, Hong Kong, Japan,
Korea, Singapore has shrunk by 30% -70% (ASEAN Annual Report, 1997-2006). And the
overheated real estate investment of China in 1993 also left large amounts of non-performing
assets to the Chinese banking systems, especially the state-owned banks. All of these are the
profound lesson from real estate bubble.
3.1.2 Externalities
Externalities refer to the action of one party can affect the welfare of other parties, but there
are no corresponding incentive/constraint mechanisms to make the party take the influence on
other parties into consideration during decision-making process. Hendrikse (1992) stated that
Market may have problems with externalities and public goods, externalities and public goods
entail collective consumption or production. If these effects are not accounted for in the
prices, then prices signal the wrong information. In such situation, costs are not paid for by
the party generating the costs (negative externality) or the benefits are not received by the
person creating the benefits (positive externality). In order to achieve the Pareto Optimality in
resource allocation, it's required that the marginal revenue of production should be equal to
the social marginal cost, rather than the individual marginal cost; otherwise, it will lower the
efficiency of resource allocation systems.
There also exist positive and negative externalities in the real estate market. On the one hand,
the developments of real estate industry can create better business environments, provide
18
more employment opportunities, and enhance the differential rent level on surrounding area,
which can contribute to the local economic prosperity. On the other hand, with the increased
demand for lands in China, and the imperfect compensation policies for land, plenty of
farmers have to abandon their lands and crowd into cities, which become the barriers for
urban development. Furthermore, the real estate development inevitably generate large
amounts of construction waste, the temporary traffic jam and so on, all of which would result
in the direct reduction for local residents’ utility levels and become the typical negative
externalities in real estate development. When a resource has the features of scarcity,
ambiguity in property rights, easy access to public and low price, the transfer of this resource
always lead to the tremendous resource waste. Due to a large number of occupations of
cultivated lands at extremely low cost, or even free, by the end of 2006, the total cultivated
land in China has decreased sharply to only 121.8 million hectare, which results in the
continual decrease in food supply and affects the people’s living standards directly.
3.1.3 Imperfect Competition
According to the number of enterprises in the market, the nature of products, the influence of
enterprises to the prices and the possibility of market access, the market can be divided into
four kinds of structures: the perfect competitive market, the monopolistic competitive marker,
the oligopoly market and the monopoly market respectively. Moreover, the variety of
products is greater and the prices are lower in the perfect competitive market than in other
three market structures; therefore, the imperfect markets would decline the efficiency of
production and reduce the social welfare levels wholly.
Real estate industry has the characters of high-risk and capital-intensive, and Chinese
government implements a series of strict market access policies all along, so there exist some
degree of entry barriers in Chinese real estate market, and the number of enterprises in real
estate industry is much less than that in perfect competitive industry. Furthermore, the
products of real estate industry have the distinctive feature of heterogeneity, such as the
differential land rent and the difference in product quality between economically affordable
housing and villas; however, this differentiation is not significant in the same type of real
estate products. Therefore, the real estate market in China is not a perfect competitive market,
and it should be monopolistic competitive or oligopoly market.
19
From the respect of products’ nature, Kuang (2003) investigated 27 different real estate
enterprises in Beijing. The author found the purposes of advertisement for most enterprises
were to express the information of their products to consumers, and only four of them wanted
to differentiate their products’ qualities and characteristics from other enterprises.
Furthermore, during the process of product-pricing, according to this investigation, only one
enterprise wanted to adopt the open price competition strategy, two acknowledged that they
had negotiated the price with other enterprises, and the rest enterprises set price by
themselves, which almost formed a collusive pricing mode.
3.1.4. Restriction of Supply
In a perfect market system, price is decided by the interaction of supply and demand. As
shown in Figure 2a, to most common commodities, when the supply increases, that is the
upward-sloping supply curve shifts rightward from S1 to S2, then the competition of products
would be more intensive, and the price will be driven to decline from P1 to P2 and the
willingly supplied quantities will increase from Q1 to Q2 at new equilibrium E2. On the
contrary, when the demand increases excessively, that is the downward-sloping demand curve
shifts rightward from D1 to D2, price will be bid up from P1 to P3 and the willingly supplied
quantities will move upward from Q1 to Q3 at new equilibrium E3. Therefore, in the situation
of perfect market mechanism, excessive supply would decrease the price, which in turn can
restrain the supply; excess demand would enhance the price, which in turn would suppress the
increasing degree of price.
The development of real estate industry is highly related with the supply of lands, which is
typical kind of scarce and nearly non-renewable resource. So the supply of real estate
commodities is very rigid, and the equilibrium price in the market is mostly decided by
demand side, as shown in Figure 2b (Wu, 2007). The increased demands in real estate market,
which include the consumption demand, the investment demand, as well as the speculative
demand, will inevitably lead to a direct rise in price. People believe that the real estate prices
always keep rising in the long term, and when the return rates in stock market or other market
are lower than that in real estate market, speculation would be prevalent in the real estate
market; additionally, because the short-term supply of real estate commodities cannot be
adjusted largely, it would result in a further sharp rise of prices in real estate market. Investors
and speculators make profits from the real estate market, and then in turn it would create more
irrational expectation and attract more capital to flow into the real estate market, which can
20
further push the demand curve upward and increase the price. Moving in cycle, the prices of
real estate would be kept in a sustained increasing process. The speculative behaviours result
in the emergence of bubbles eventually.
3.1.5 Government's Improper Intervention
In fact, the Chinese government has indeed adopted some intervention measures in the real
estate market from many aspects, such as urban planning, land policies, Interest Rate polices,
taxation policies and direct government's investments, etc., which can effectively compensate
for the inadequacies of market to some extent. However, the government's intervention will
also lead to the phenomena of market failures, such as the inefficiency of government
regulatory agencies and serious waste of resources. Furthermore, the operation of
government's intervention also have the problem of transaction costs; since all participants in
government intervention are rational economic men, who have the internal instinct to pursue
the individual profits; when there lacks the efficient supervision, it would result in the RentSeeking phenomena during government interventions, which deviate from the main purpose
of government interventions that maintain the market development.
3.2 Carey Model
3.2.1 Introduction of Carey Model
Carey (1990) has developed a dynamic model, which reveals the inner mechanisms of land
pricing driven by financing and expectations about future land prices. Carey originally applied
this model to analyze the agricultural land of United States, and then Herring and Wachter
(2002) extended the Carey model in the analysis of the commercial real estate bubbles due to
the strong explanation of some variables in this model for the real estate markets. This model
mainly analyzes the cyclic process of the real estate market with rigid short-term supply.
Herring (2006) applied the Carey model to analyze the real estate market of New Zealand,
and found that the net immigration flows and the financial liberalization in New Zealand
would attribute to the increase of demand for housing, and the very tight regulation on new
construction of New Zealand would attribute to the decrease of supply of buildable land, all
of which could lead to the national or regional house-price booms in New Zealand.
In this model, it’s assumed that the supply in real estate market is fixed in a certain period of
time, at least in a short run this assumption is reasonable, which is defined as Z; and there are
21
N homogenous potential investors in the real estate market, but these investors can access to
different degree of information about the market and their expectation to the market return are
also diverse, so the reservation prices are not identical for all investors. This reservation price
(P) is assumed to be a continuous closed convex function and is subject to uniform
distribution with a mean of fundamental value (P*) and a deviation (h) of P from P*, that is
P ~ F (P*, h). So those who have the higher reservation price than P* will become the
demanders in the real estate market; furthermore, the fundamental price (P*) is decided by the
proportion of this kind of investors, and the reservation price (P) is also the market clearing
price. At any arbitrary P’ in the market, the real estate demand is (N (1-F (P’)) L), of which
1- F (P') is the proportion of investors with the reservation price P ≥ P', N is the number of
investors, and L is the available resources, especially the financial resources, to each investor,
which is assumed to be identical to each investor in this model. Therefore, in equilibrium,
which is at the clearing price P, the total demand in real estate market (N (1-F (P)) L) is equal
to the value of total supply in real estate market PZ.
P Z = N (1-F (P)) L
then
P = N (1-F (P)) L / Z
(1)
P is subject to the uniform distribution under the interval of 〔P* - h, P* + h〕, so:
1 - F (P) = (P*+h-P) / 2h
Then (1) can be rewritten as:
P = (N (P*+h) L) / (2hZ+NL)
(2)
Here:
P:
the equilibrium price in the real estate market
P*:
the fundamental price in real estate market
N:
the number of investors in the market
F (P):
the distribution function of P
h:
the deviation between P and P*
L:
the resources available to investors
Z:
total amount of supply in the real estate market
N (1-F (P)):
the number of demanders in the real estate market
N (1-F (P)) L: total value of demand in the real estate market
PZ:
total value of supply in the real estate market
22
Above is the basic form of Carey model, and the real estate price (P) depends on five
variables, including the number of investors (N), the available financial resources to investors
(L), the fundamental price (P*), the total amount of supply in real estate market (Z ), as well
as the deviation between investors' reservation price and the fundamental price (h).
Through calculating the partial derivatives for equation 2, it’s clearly shown the relationships
between the real estate price and other parameters.
∂P / ∂N = 2hZ (P*+h) / (2hZ+NL)2 > 0
∂P / ∂L = 2hZN (P*+h) / (2hZ+NL)2 > 0
∂P / ∂P* = NL / 2hZ+NL > 0
∂P / ∂Z = -2hN(P*+h) / (2hZ+NL)2 < 0
∂P / ∂h = NL (NL-2P*Z) / (2hZ+NL)2
Because N, L, P*, Z, h are all positive, the real estate price is an increasing function to the
number of investors, the total financial resources available to investors, such as bank loans,
and the fundamental price; and the real estate price declines with the increase of the total
amount of supply in real estate market; all of these are consistent with the reality. Moreover,
when NL / 2 > P*Z, which means the total value of financial resources owned by half of
investors in the market exceed the total value of supply calculated by the fundamental price in
real estate market, then the real estate price will rise with the increase of h; on the contrary,
when NL / 2 < P*Z, the real estate price will decline with the increase of h. In addition, when
h = 0, that is to say P = P*, it means the information is symmetric and the market expectation
of all investors are identical.
An obvious advantage of this model is that it is very convenient and easy for analyzing the
real estate price movement through examining the total amount of supply in real estate
market, the investors’ expectation to market, the total number of investors, and the amount of
financial resources available to the investors. In other words, study for these variables can be
very helpful to analyze the future movement tendency of real estate prices.
3.2.1.1 Total Amount of Supply in the Real Estate Market (Z)
According to the general investment theories, asset price depends on the replacement cost,
which is the present value of total rents, i.e. P = ∑ R / (1+r)n, R is rent for each period, r is
the discount rate. When the current real estate price is higher than its replacement cost,
23
developers will have strong incentive to invest in more real estate projects, which would
enhance the real estate stock level in the market, and improve the amount of supply in the real
estate market (Z). In a long run, the real estate market will arrive to equilibrium eventually
and the actual real estate price will be driven to be equal to the replacement cost. However,
this adjustment is a long-term process. According to Rosen (1984), new construction,
however, takes a substantial amount of time- perhaps two or six years- and so the adjustment
process is likely to be slow. Moreover, developers have imperfect information about future
demand and limited knowledge about forthcoming supply and so the amount of new
construction is likely to differ from that which would take place with perfect foresight.
Therefore, because of the imperfect information, the forecast error and the time lag problem
in the adjustment of supply, during a long period the real estate market works in an
unbalanced situation, which can give explanations for why the bubbles are more liable to
occur in the real estate market.
3.2.1.2 Deviation between Reservation Price and Fundamental Price (h)
The deviation between investors' reservation price and the fundamental price (h) may vary in
different circumstances. According to the former assumptions, h changes with the diverse
available information to each investor and the various market expectation of each investor. So
when some important information or events happen, which can affect the judgement of
investors on the trend of future market, the investors' reservation price is bound to change.
Furthermore, according to Herring and Wachter (1998), in general h is likely to increase
when vacancy are low and new information regarding the determinants of demand causes
price to rise, investor may believe that they have special insight into how the new information
will affect the demand and future price increases or they may make errors in interpreting the
new information. On the other hand, h is likely to fall when vacancies are high and prices are
falling, at least in part because the most optimistic investors are likely to suffer financial
distress or failure and be obliged to leave the market.
3.2.1.3 The Number of Investors in the Market (N)
Generally speaking, in a mature and stable real estate market, it is impossible for the number
of investors in the market to change rapidly in a short time, which decides that N could not be
a very important determinant affecting the real estate price movement in such perfect market.
However, in an imperfect and changeable market, the number of investors still plays a key
role to the real estate price. For example, in the 1980s, many countries have deregulated
24
economic and financial controls, which attracted lots of foreign investors into the domestic
capital market; in some countries, such as Thailand and other Southeast Asian countries, the
foreign investors can be allowed to invest in real estate market directly; in some other
countries, such as the United States in the 1980s, all types of investors were allowed to invest
to real estate market directly (Li, 2004). The increased number of investors involved in the
market would stimulate the rise of real estate prices greatly. Moreover, it’s assumed that all
investors are homogeneous in this model, and each investor can access to the same amount of
resources, which is to simplify the analysis of the theory; however in the reality, especially in
an open financial circumstance, the new investors can obtain larger amount of resources than
the old ones, so the appearance of new investors can stimulate the further increase of the real
estate prices.
3.2.1.4 The Available Financial Resources to Investors (L)
The financial resources available to investors are mainly from the banking loans, which may
be the important reason leading to the prosperity or the bubbles of the real estate market.
Especially during the period of financial innovation and financial liberalization, on the one
hand, with the deregulation of financial controls, plenty of new financial products have
emerged, which can facilitate the availability of financial resources to the investors; on the
other hand, large scale of international capital have flowed into the domestic market, which
can provide more financial resources to the investors. Furthermore, the support from the
financial sector, particularly the banking sector, would inevitably result in the lasting increase
of real estate price and the continuous expansion of real estate bubble crisis. However, when
the scale of banking credit drops suddenly, the real estate prices will decline consequentially,
then the collapse of bubbles would occur.
3.2.2 Test of Carey Model
The basic form of Carey (1990) model is: P = (N (P* + h) L) / (2hZ + NL), which means that
there are at least five variables affecting the real estate prices: the number of investors (N), the
available financial resources to investors (L), the total amount of supply in real estate market
(Z), the deviation between investors' reservation price and the fundamental price (h), as well
as the fundamental price (P*). Through the partial derivatives to these parameters
respectively, it has already indicated the relationship between the real estate price and other
parameters clearly; Particularly, the model has shown that the real estate price (P) is
25
negatively correlated with Z, and positively related with other parameters: N, L, P*. The
relationship between P and h is quite complex, because h is jointly affected by other
parameters: N, L, P*, Z, and decided by the difference of investors' available information and
expectation for the future market. In order to simplify the model, it’s assumed that each
investor' available information and expectation for the future market are the same, and the
fundamental price (P*) is taken as given and exogenous. Thus, the test of Carey model
focuses on the other three variables, which are N, Z and L respectively.
3.2.2.1 Hypothesis
According to Carey Model, ∂P / ∂N > 0, ∂P / ∂L > 0, ∂P / ∂Z < 0, the hypothesis is:
The real estate price of China would increase with the improvement of the number of
investors involved in China’s real estate market and the available financial resources to
investors, that is to say the number of investors and the available financial resources have
positive correlations with the real estate price. The expansion of total amount of supply in
China’s real estate market will drive down the real state price of China, that is to say the total
amount of supply in China’s real estate market is negatively related with the real estate price.
3.2.2.2 Definition of Variables
P:
Average Selling Price of Houses (yuan/sqm)
N:
Number of Real Estate Development Enterprises (unit)
Z:
Floor Spaces of Buildings under Construction (ten thousand sqm)
L: Funds of Enterprises for Real Estate Development (ten thousand yuan)
3.2.2.3 Sample and Data
This paper uses the data of 31 regions in China from 2002 to 2006, and establishes a panel
data file for these 155 observation samples. The data is collected from China Statistical
Yearbook from 2002 to 2006, and focuses on the Chapter Six: Investment of Fixed Assets.
Through empirical analysis, it is helpful to find out the correlation between the real estate
price and other variables, including the number of investors, the available financial resources
and the total amount of supply in real estate market.
26
3.2.2.4 Econometric Model
According the panel data, the model was established, which is:
Yit = αi + β1 X it1 + β2 X it2 + β3 X it3 + ε it,
i = 1,2...... 31; t = 1,2......5. (1)
Here, the dependent variable Y is P, the independent variables
X1, X2, X3 are L, N and Z
respectively, and ε is the error term.
3.2.2.5 Regression Results
Number of
155
R-squared
0.8213
231.36
Adj R-squared 0.8178
Prob > F
0
Root MSE
variables
Coefficient Std. Err.
L
0.0003042
1.58E-05
N
0.0138766
0.1041908 2.26
0.0252
Z
-0.284393
0.0386927 -7.35
0
_cons
1876.261
75.18609
0
observation
F(
3,
151)
t value
19.25
24.95
524.21
P>t
0
Table2: Regression Results of Model
From Table 2, it shows that R-squared is 0.8213, which means that real estate price can be
well explained by those independent variables. And from the t values, it shows that the three
independent variables are all statistically significant at the significant level of 5%, that is to
say the available financial resources, the number of investors and the total amount of supply
are highly related with the real estate price. Keeping other variables constant, if financial
resources increase ten thousand yuan, the real estate price would increase 0.0003042 yuan, if
the number of investor increases one unit, the price would raise about 0.014 yuan, and if the
total supply of real estate increase 10000 sqm, the price would drop 0.284 yuan. The
coefficients of these three variables indicate the financial resources and the number of
investors are positively related with the real estate price, and the total amount of supply has
significant negative effect on the real estate price, which is consistent with the hypothesis and
27
can certify the Carey’s theory. Therefore, Carey model can be used to analyze the factors
affecting the Chinese real estate prices.
3.2.3 Analysis
Based on Carey model and taking Beijing as an example, the dynamics of real estate prices
affected by each variable in Carey model can be analyzed and the reasons for the increase of
real estate price in China will be introduced.
3.2.3.1 Restriction of Supply in Real Estate Market--Z
In Carey (1990) model, there exists negative correlation between total amount of supply and
real estate prices. When other conditions keep constant, the more supply in the real estate
market, the lower the real estate price is, which is consistent with the general principle of
supply and demand in common commodities. The limited land resources and the time lag
problem in the real estate market make the real estate supply is relatively inelastic compared
with the real estate demand. Therefore, the supply in real estate market cannot satisfy the
people’s growing demand on the real estates because of the improvement of income, the
increased population and the accelerated process of urbanization; moreover, the high priceearning ratio in real estate market may not increase the real supply in real estate market, but
lead to speculation and real estate bubbles.
Real estate industry is very liable to be affected by the restriction of supply. Taking Beijing as
an example, the city’s population has reached 15 million and still increases by the rate of
about 3% per year, which bring many problems to the development of Beijing, such as the
increased per capita consumption for water and lands. The statistical data released by the
Reference News (June, 2004) shows that the land resource is extremely scarce in Beijing,
except the agricultural land, the current available urban land in Beijing is only left to 10%20%. So the real estate development in Beijing has to transfer from centre areas to
surrounding and rural areas.
Real estate has the dual characteristic of durable consumer goods and investment goods, so
compared with general commodities, the income elasticity of demand in housing market is
quite larger. According to the panel data of China's real estate market from 1992 to 1997,
Chen (2000) has estimated that the income elasticity of demand in China's real estate market
is about 1.2, which means the demand and expenditure for housing will rise with the increase
28
of people's disposable income, and an increase of 1% in residents’ disposable income would
contribute to an increase of 1.2% in residents’ demand for housing, which requires a
corresponding increase of 1.2% in housing supply to achieve a market equilibrium.
Particularly, in 2004, the income elasticity of demand in China and Beijing city were 1.81 and
1.86 respectively, that is to say, if residents’ income increased by 1%, the corresponding
supply in real estate market should increased by at least 1.8%, that is, the growth rate of
supply in real estate market should be 1.8 times higher than the growth rate of income.
Furthermore, because the real estate commodities are durable consumer goods, the real estate
consumption and prices affect not only the welfare of current generation, but also the welfare
of next generation. The change of population and economic development will have significant
influence on the consumption demand of real estate. On the one hand, the population growth
will lead to the increase of housing demand; here, the growth of population includes the
natural growth of population, and the growth of immigrating population, which has already
become a major reason for the growth of cities, especially in some large cities, such as
Beijing, Shanghai, and Guangzhou (China Statistic Yearbook, 2007). If the growth rate of
supply in real estate market is less than the growth rate of demand caused by the increased
population, then the real estate prices will increase inevitably. On the other hand, the
economic development would stimulate the further increase of housing demand; the
accelerated urbanization process and large-scale city reconstruction in China will create more
demands for housing, which would enhance the real estate prices in China.
From Table 3, it is obvious that in recent years, the natural growth rate of population in
Beijing has maintained at a low level of around 1‰ since 1998, even in 2003, this rate was
negative. However, the total number of permanent population shows an increasing trend in
these years, which indicates that it’s mainly the immigrating population to cause the
population growth in Beijing; and in turn the increased population can stimulate more
demands for real estate products. Moreover, this table also shows that the proportion of nonagricultural population in total permanent population, which can be regarded as indicator for
the degree of urbanization, has increased continuously; the degree of urbanization has
increased from 73% in 1990 to 84% in 2006. The accelerated pace of urbanization and the
improved proportion of non-agriculture population in Beijing greatly promoted the growth of
housing demand in Beijing’s real estate market.
29
In the late 1990s, the housing price index including the Selling Price Index of Houses and the
Renting Price Index of Houses, increased under the economic background of deflation and
low, even negative growth rate of Consumer Price Index (CPI). Especially in recent years, the
increasing tendency has enlarged; from above table, in 2004 and 2005, the difference between
Selling Price Index of Residential Buildings and CPI were 5.5 and 6.6 percentage points
respectively, and in 2000, 2001 and 2003, the difference between Renting Price Index of
Residential Buildings and CPI were 13.8, 7.4, and 6.3 percentage points respectively, which
can clearly show that the serious inflation phenomena exist in China’s real estate market, and
maybe become a symbol for real estate bubbles. Worthy of mention, due to the macroregulation and control policies from 2004, the difference between CPI and Renting Price
Index of Houses, especially the residential buildings, began to decline in following years.
As mentioned before, asset price depends on its replacement cost, which is the sum of the
present value for rents in each future period. And the ratio of asset price to rents can be used
as the indicator for the general price-earning ratio of investment, because the rise of real estate
price can be taken as the capital gains, and the rental income can be regarded as the profits.
Currently in China’s real estate market, the ratio of real estate price to rents, that is the priceearning ratio, is so high that it would attract more speculation and affect the sound
development of real estate market.
From Figure 3, the price-earning ratio in China's real estate market has an increasing tendency
since1998, and reached the peak about 1.08 in 2004, then followed by a slight decrease till
1.04 in 2006. As we all know, excessive price-earning ratio will not really increase the supply
in real estate market, but lead to frequent speculation and generate the bubbles in the
economy. Because of the inelasticity of supply in real estate market, the large amount of
capital attracted into the real estate market cannot flow to the truly real estate construction,
and the investors only pursue for the capital gains generated by the price difference, which
would lead to the prevalence of speculation and real estate market confusion. Once prices
decline, speculative arbitrage opportunities would disappear quickly, and the burst of real
estate bubble will cause the financial and economic crisis.
3.2.3.2 Diversification of Investors in the Real Estate Market--N
According to Carey model, the relationship between real estate prices and the total number of
investors is positive (∂P / ∂N > 0), and the total investors assumed in Carey model should
30
include not only the direct real estate investors, but also the investors in the financial markets,
because the advanced secondary markets in the foreign developed countries have become the
major channels for real estate financing and transactions, such as mortgage -backed securities,
real estate investment trusts and so on. However, at this stage, the secondary market in China
is quite undeveloped, so the major financial resources of investors in Chinese real estate
market are still the bank loans.
Before the Economic Reform in 1978, the Chinese government or the state-owned enterprises
almost entirely owned the urban residential buildings, and the real estate market did not exist
really at that time. With the introducing of market mechanism after 1979, the Chinese
government began to reform the real estate system gradually, however the Chinese real estate
market in this period was in the start stage and the government and state-owned enterprises
were still the main participants in real estate market, which inevitably led to the inefficiency
of market investment bodies. Fortunately, from 1992, the Chinese government began to relax
the control for type and number of real estate enterprises. Especially the Housing System
Reform in 1998 and the corresponding financial reform further stimulated the rapid
development and standardization of the real estate market in China. From then on, the
participants of real estate investment have gradually become diverse, which include the
domestic funded enterprises, the foreign funded enterprises and the private investors.
The number of real estate development enterprises has increased since 1997, and this increase
was the result of two sources. Firstly, the number of stated-owned and collective-owned
enterprises has decreased continuously. Secondly, the number of other types of enterprises,
such as joint-stock enterprises and the foreign-owned enterprises, has increased sharply.
Therefore, the diversification of investment bodies would contribute to the more efficient
development of the Chinese real estate market from the late 1990s. Carey model shows that
the real estate price will increase with the growth of the number of investors, and the actual
status in China can confirm this model at least in this aspect.
3.2.3.3 The Effects of Banking Credit on the Real Estate Market--L
The real estate industry has highly related with the banking industry. The banks could have
incentives to increase the credits, even if the real estate market has expanded too much and
the risk of real estate bubbles exists in the market. However, the bank itself is very vulnerable
31
to the influence of Bank run, and then the close relationship with real estate industry would
aggravate this problem.
Currently, due to the imperfect financial system of China, the expansion of real estate bubble
crisis has a high degree of positive correlation with bank credit. About 80% of the China’s
financial assets have concentrated in banking sector, which plays an important role on the
allocation of the financial resources in China (China Statistic Yearbook, 2007). As the main
body of financial system, the banking institutions are the concentration of the financial risk
from enterprises and individuals. Once the economic situation reverses, the people's
expectation changes or some unforeseen incidents happen, the banking sector is always the
first one to be affected, and then followed by the banking crisis, currency crisis and economic
crisis, such as the collapse of economic bubbles in Japan, and the financial crisis in Mexico
and in Southeast Asian.
There are two major types of banking loans in China's real estate market, which include the
real estate development loan and the personal housing loan.
1.
Real Estate Development Loan
Real estate development loan is the most important channel for banking capital flowing into
the real estate industry, which refers to the loan granted by banks to real estate development
enterprises for housing construction and land development. Generally speaking, most of the
real estate development loans are short-term loans, and the loan repayment mainly depends on
the sales revenue of housings. Thus, the risk of real estate development loans focuses on the
effective supply and demand in real estate market. When the demand is greater than the
supply, and the real estate market is in the state of prosperity, the real estate development
loans can be regarded as high-quality assets for banks. On the contrary, the reversed economic
situation and the changed people’s expectation would cause the sudden decline of demand,
that is to say the actual demand in real estate market is less than the expected demand of
banks and developers, bubble risk will be accumulated in real estate market inevitably, and
the banking system have to withstand the impact of bank-run and asset-shrink eventually, then
the entire economy would face the serious financial crisis.
32
2.
Personal Housing Loan
The other type of major banking loan in China is the long-term personal housing loan. The
risk of default is relatively smaller for the long-term personal housing loan, which is a kind of
high-quality assets for banks; however, it must have the prerequisite of continuous
improvement of people’s income and stable real estate prices, which cannot be guaranteed in
a long term. Actually, the quality of personal housing mortgage loan can be affected by many
factors, such as the macroeconomic situation and the people’s income level. Once the
economic situation turns into recession, which would inevitably affect the people’s income
and drive the real estate price down, then the risk of default for borrowers will increase. With
the reduction of real estate bubbles, the banking assets would shrink. In addition, because the
personal housing loan is a kind of long-term loan, maybe in short period the market risk and
the probability of default are relatively low, but in a long run, with the increase of uncertain
factors in economy, the real estate industry, the banking system and the national economy
have to bear tremendous pressure.
Domestic loan is an important financial source to the real estate development. From 1999,
both in the whole country and in Beijing, the scale of domestic loans keeps in a steady
growing tendency. The domestic loans have increased rapidly from 111.157 billion yuan in
1999 to 535.698 billion yuan in 2006. Compared with the increasing tendency of the whole
country, the loaning scale in Beijing increased by a relatively stable rate, which reached
84.249 billion yuan in 2006. It indicates that the real estate enterprises have enlarged the
demand for financial resource gradually, the amount of loans kept rising in recent years not
only in the whole country but also in Beijing, and the real estate enterprises have received
strong support from banking sector. Combined with the Carey (1990) model, real estate price
rises with the increase of financial resources available to investors, so the improved bank
credit scale would give one explanation for the real estate price inflation in China.
3.3 Indicators to Measure the Real Estate Bubble
3.3.1 Price-income Ratio
3.3.1.1 Definition
The price-income ratio is the ratio of median house price divided by median household
income. The higher the price-income ratio, the lower of the purchasing power, and the greater
probability of real estate bubbles. Since real estate price depends on the resident's purchasing
33
power, the price to income ratio is one of the best indicators to reflect the real estate bubbles
accurately. Moreover, due to the easy access to data and a relatively simple calculating
method, this ratio is widely accepted in Chinese real estate industry.
3.3.1.2 Price-income Ratio in China's Real Estate Market
In this stage, the median data cannot be obtained in China, so the Chinese scholars generally
adopt the mean data in calculating the price-income ratio (Chen et al. 2007). The priceincome ratio of China can be calculated as following:
Price-income ratio = (P*S) /I
P: Average Selling Price per Square Meter
S: Per Capita Floor Space of Residential Building
I: Per Capita Annual Disposable Income
What is a reasonable range of this ratio? Different countries have different standards.
According to the book of " China: implementation options for urban housing reform "
published by the World Bank in 1992, the reasonable range of price-income ration in
developing countries is about from 4 to 6.1. However, from the table, the price-income ration
of China has increased gradually; especially in 2005 and 2006, the ratio has kept in the peak
of around 7.88. Based on the World Bank’s standard, the ratio is much higher than the
reasonable level, and a serious bubble has already existed in the Chinese real estate market for
a long time.
3.3.1.3 Limitations of Price-income Ratio
As a kind of indicator to measure the bubbles in the real estate market, price-income ratio also
has some limitations.
1.
The Price-income ratio is highly influenced by the level of income. From Table 7, when
the resident's average income is less than 1000 dollars, the range for price-income ratio is
from 6.3 to 30; when the interval of resident's average income is from 3000 to 3999
dollars, this ratio is from 2.1 to 20; and when the average income is large than 10000
dollars, the ratio would range from 0.8 to 12.3, especially in some developed countries,
this ratio is also higher than 10. The above information reveals that the income level has
an important effect on the value of price-income ratio, and the local income level is
34
highly related with the local price-income ratio; however, it cannot be shown that there
exists direct relationship between the income level and the bubbles, and the bubbles
cannot be completely identified only through calculating the price-income ratio.
2.
The price used to calculate the price-income ratio is the average selling price of
commercialized housing in a certain period of time, which is affected not only by the
fluctuation of the real estate price, but also by the difference among housing types. If
during a certain period, the proportion of the luxury houses is relatively higher, and the
selling revenue of this kind of housing takes a major weight of total selling revenue, then
the average selling price in this period would be high, and vise versa. So, the housing
type can impact the value of average selling price and have a significant influence on the
price-income ratio further. For example, according to the data from U.S. Census Bureau,
in the first quarter of 2001, the gap of price-income ratios in different U.S. cities is quite
large, ranged from 1.4 to 6.9. These figures, of course, can reflect the economic level, and
the gap between the housing price and local resident's income of each city in some
degree, however the actual disparity of real estate market in each city cannot be so great.
Therefore, the different price-income ratio caused by various housing types is unrelated
with the real estate bubble.
3.
As mentioned before, the local resident’s income level is highly related with the priceincome ratio. Different from some developed countries, China implemented the low-wage
policies for a long time; although after the economic reform, the Chinese government has
been making efforts to enhance the resident’s income level, this process needs a long
time. Currently, the average real estate price in China is relatively low compared with
some developed countries; however, because the income level in China is much lower
than these countries, the price-income ratio of Chinese real estate market is higher than
other countries. The high price-income ratio caused by the low resident’s income level
has no relationship with the bubble, and the only way to resolve the problem is to develop
the national economy and improve the resident's income continuously.
3.3.2 Vacancy Rate
3.3.2.1 Definition
The vacancy rate is an indicator to reflect the degree of demand in real estate market, and it
can affect the investors' expectation and judgement for the future real estate market. In
35
Chinese Economic Circle, generally the vacancy rate is calculated by the ratio of the current
vacant area of commercialized buildings to the total completed area in the past three years
(Zhang et al. 2004).
Vacancy rate = V / T *100%
V: Current Vacant Area of Commercialized Buildings
T: Total Completed Area of Commercialized Buildings in the Past Three Years
3.3.2.2 Vacancy Rate in China’s Real Estate Market
In theory, when the vacancy rate of a country is less than 3%, the real estate market is a
seller’s market, and it is difficult for the consumer to find an acceptable house in such market;
when the vacancy rate ranges from 3% to 10%, the relationship between supply and demand
in the market keeps stable, there would not exist the excess supply in the market, and the
buyers also have sufficient choice for real estate commodities; but when the housing vacancy
rate is greater than 10%, then the surplus housing supply would destroy the equilibrium in the
real estate market; Furthermore, when this rate increases to 15%, which means the excessive
supply cannot be relieved by the real demand for housings, the high vacancy rate can be used
to reflect the real estate bubble in the market.
Taking Beijing as an example, on the one hand, the total vacancy area of commercialized
housing has increased gradually from 4.087 million square meters in 2000 to 11.863 million
square meters in 2006; on the other hand, the vacancy rate in Beijing always fluctuates around
10%, which indicates that there exists the possibility of excess supply in Beijing’s real estate
market. Although in 2004 the vacancy rate declined to a safety level 7.04%, in the following
two years the rate started to rise again, and reach 11.6% at the end of 2006. If the vacancy rate
in Beijing has maintained an upward tendency, it is very likely for the bubble to occur in the
Beijing’s real estate market.
3.3.2.3 Limitations of Vacancy Rate
The vacancy rate can be used to reflect the current investment level and guide the future
investment decision, which must have the prerequisite of scientific and accurate calculation
method and unified measuring standard. Only with such prerequisite, the vacancy rate can
make a true reflection about the relationship between supply and demand for real estate
commodities. However, the prerequisite cannot be satisfied in current situation of China, and
36
there exist several problems during the calculating process of vacancy rate for Chinese real
estate market.
1.
The different statistical scope between numerator and denominator. During calculating
the vacancy rate, the numerator in the function: Current Vacant Area of Commercialized
Buildings is the vacancy area of ordinary commercialized housing, but the denominator:
Total Completed Area of Commercialized Buildings in the Past Three Years is the total
completed area of commercialized buildings, which not only includes the completed area
of buildings for sale, but also covers the completed area of the commercialized buildings
for rent, the completed area of the house rebuilding, as well as the public area of
commercialized buildings which cannot for sale. Therefore, the calculated result of
vacancy rate in this method is always smaller than the actual value (Jia, 2003).
2.
There is no international comparability among the judging standard of vacancy rate.
Usually in China, the judgement for the reasonable interval of vacancy rate is based on
the general international standard; however this international standard is calculated by the
ratio of total vacancy area to the total area of housing stock, which cannot be fully
utilized in Chinese real estate market, and make the Chinese vacancy rate lack of the
comparability. In addition, with the accelerated urbanization process in China and
different economic development level among cities, the judging standard for vacancy rate
will be different with cities.
3.
The imbalanced demand structure in China’s real estate market also causes that the
vacancy rate cannot fully be utilized in China. At this stage, the type of vacant housing in
China’s real estate market is mainly the luxury housing. Because the total price of this
type of housing is relatively high, and the return on investment is relatively great, many
real estate developers are willing to develop such type of housing, and reduce the
development for the ordinary or economically affordable housing. Moreover, the number
of consumers who have the consumption capacity to purchase the luxury housing is still
in minority. As mentioned before, the accelerated pace of urbanization and the improved
population in China have created more new demand for real estate products, however,
this demand largely concentrate in the ordinary and economically affordable housing,
which result in the unique characters of China’s real estate market that great demand and
low supply for ordinary and economically affordable houses, and low demand and great
37
supply for luxury houses. Therefore, the vacancy rate does not take the imbalanced
demand structure into consideration, and cannot really reflect the supple-demand relation
of China’s real estate market in some degree.
4.
The vacancy rate is not the only indicator to measure the situation of real estate market.
In China, the vacancy rate is widely used to reflect market situations, which always
causes the unprofessional consumers to misunderstand the real estate market; in their
opinions, high vacancy rate is equal to the low quality or overstock, which would
indirectly affect the sales for vacant houses. Therefore, the Chinese real estate market
should establish some positive indicators, such as the Sale Rate and Absorption Rate, to
give a comprehensive reflection for the supply-demand situation in Chinese real estate
market.
3.4 Countermeasures to Control and Prevent Real Estate Bubbles
The imbalance of supply-demand structure and the scarcity of land resources would result in
the irrational expectation, the speculation behaviours and the herd effect, and are the
fundamental reasons for real estate bubbles. Furthermore, the imperfect market mechanism,
and the asymmetric information in the China's real estate market make the banks and other
financial institutions pursue their own interests and underestimate the risk of loans, which
would further encourage the blind real estate development and expand the real estate bubble
crisis. Therefore, Chinese government should formulate some policies and measures to avoid
the irrational behaviours, to improve the land policies, to guide the rational investment and
consumption behaviours in real estate market, and to accelerate the information transfer in
banking sector. Moreover, the government should establish the risk early-warning system to
prevent and control the bubbles in real estate market.
Some of the Policies that could control or prevent real estate bubbles are:
1.
Adjust the real estate industrial structure, and balance the supply-demand relationship. In
the current Chinese real estate market, many developers have invested majorities of their
fund to develop the luxury buildings, which increased the vacancy rate of this type of
buildings, and declined the supply for economically affordable housing, which resulted in
the shortage for this type of houses in the market. Therefore, the government should
encourage the development for low-price and economically affordable houses through
38
some preferential policies, control the approval of land for luxury building construction,
and rebuild those buildings vacant for a long time to the economically affordable houses,
all of which would be helpful for real estate market to achieve the supply-demand
equilibrium again, and avoid the risk of bubbles.
2.
Another major problem in the development of Chinese real estate market is low degree of
industrial concentration and small scale of real estate enterprises, which would make the
market more vulnerable to the disorder and bubbles. Therefore, the government should
encourage the industrial acquisition and merger, form the large-scale real estate industrial
cluster, develop the real estate capital market to reduce the ratio of liabilities to assets of
real estate industry, and improve the ability for resisting the risk in real estate market.
3.
Develop the second-hand housing real estate market and the rental market. At present, the
Chinese government is lack of experience in managing the second-hand housing and
rental market, and most consumers prefer to purchase the new houses, which result in
high degree of vacancy in old houses. Moreover, the low purchasing power of medium
and low-income families would further increase the vacancy rate of new houses. Thus,
the government should offer some preferential policies to the second-hand housing
market, and attract more potential low-income consumers, which can make up for the
supply shortage in the new economically affordable housing market; on the other hand,
the development of rental market also can helpful to reduce the vacancy rate, slowdown
the increase in real estate prices, and relieve the crisis of real estate bubbles.
4.
Improve the financial system, control the capital resources. The emergence of real estate
bubbles is highly related with the large-scale capital inflow from banking sector to real
estate market. Thus, in order to avoid the bad assets and the expansion of credit, firstly,
the financial institutions should prudently grant the loans to the developers with high
quality and credit rank, and obey the principles of conservative, truth and safety during
the evaluation and review process for collaterals. Secondly, to those real estate enterprises
which have the ratio of equity to total project investment lower than 30%, and to those
which have the fraudulent business practices, the banks should not grant the loans to them
(Bai and Zhang, 2005). Thirdly, the banking sector should establish a perfect
information-sharing system to prevent the fraudulent practices in real estate market. At
39
last, the Chinese real estate industry and financial industry should develop the Real Estate
Investment Trusts (REITs) and propel the Mortgage-Backed Securitization (MBS).
5. Establish the risk early-warning system, and promote the rational behaviours in the
market. The rational decision is supported by complete information, so the incomplete
and asymmetric information can not only lead to the irrational behaviours for investors
and speculators, but also create real estate bubbles in the market. Compared with the
securities market and other common trading markets, the real estate market has the
features of slow information transmission and the lack of transparency; additionally, the
current statistic information system of China's real estate market is imperfect reflected by
the ambiguous indicators and poor data accuracy, all of which would lead to the irrational
investment and herd effect of government, investors and real estate developers. Therefore,
the government should improve the efficiency of information collection and distribution
in the real estate market, unify the Evaluation Index System, develop the risk earlywarning system, enhance the transparency of information, as well as actively guide the
real estate investment direction, such as regularly release the real estate data including the
fundamental price of real estate market and the vacancy rate, etc., and timely issue the
early warnings for the real estate market, which would benefit for encouraging the
people’s rational behaviours and controlling the bubbles in real estate market.
40
4 Conclusions
The real estate industry of a country is highly related with the people’s living standard, and a
sound development of real estate market can ensure the sustained economic growth of this
country.
The Cary model is utilizaed in this paper because this model can be understood easily and can
give the pertinent analysis to the real estate market; furthermore, according to the Popper's
theory of falsification, the hypothetico-deductive method is more suitable for the modern
economic research. Through econometric analysis of data from 31 regions of China, this
paper studies the effects of some factors, such as the supply in the real estate market (Z), the
number of investors in the real estate market (N) and the available financial resources from
banks (L), on the current Chinese real estate market.
It was found that the total amount of supply in real estate market is negatively related with the
real estate price, and both the number of investors and the available financial resources have
the positive correlation with the real estate price, which are consistent with the theoretical
hypotheses and can verify the Carey model.
Then combined with the special situation of real estate market in China and taking Beijing as
an example, this paper also gives the detailed analysis on the dynamics of Chinese real estate
price affected by the three variables and explains the reasons for the increase of real estate
price in China, including the restriction of supply in real estate market, the diversification of
investors and the expansion of credit scale, which would provide the possibility for the
occurrence of real estate bubbles. Additionally, as kind of supplementary indicators, the priceincome ratio and the vacancy rate are introduced in this paper, which would be helpful for the
deep understanding about the real estate market and bubbles. In the last part of theory and
analysis, five countermeasures to prevent and control the real estate bubbles in China have
been introduced.
Compared with general trading markets, the real estate market has some special
characteristics, and the major reasons for the market failure are the information asymmetric,
(negative) externalities and incomplete competition. Furthermore, the market cannot arrive to
the Pareto optimality, because of the restriction of supply and the government's improper
41
intervention.
Because of the incompleteness and difficulty in collecting the data, as well as the different
developing level in different cities, this paper only can introduce the price-income ratio and
the vacancy rate in China's real estate market. However, in order to give comprehensive
analysis about the real estate market, it’s necessary to include more indicators, such as GDPprice ratio and Tobin's Q, which can be the future research direction.
The paper provides the guidance for future real estate market development. The findings in
this paper can present some efficient strategies for the Chinese government to regulate and
control the real estate industry and prevent the irrational exuberance in the Chinese real estate
market. Increasing the reasonable supply, adjusting the number of investors and regulating the
credit scale are very important for the balanced development of real estate market and further
helpful for avoiding the crisis of real estate bubbles.
42
Appendix 1
Figure1: Annual Area of Cultivated Land
Annual Area of Cultivated
( million hectare )
Land
130.00
128.00
126.00
124.00
122.00
120.00
118.00
1999
2000
2001
2002
2003
2004
2005
2006
Date Source: Statistical Yearbook of Ministry of Agriculture of People’s Republic of China from 1999 to 2006.
Figure 2: The Supply and Demand in Different Markets
(a)Supply and Demand of Common Commodities (b)Supply and Demand in Real Estate Market
P
P
S
S1
P3
P1
P2
S2
E1
D2
E2
Q1 Q2 Q3
E1
P1
D1
0
E2
P2
E3
D1
D2
Q
0
43
Q1=Q2
Q
Figure 3: Price-earning Ratio in China’s Real Estate Market
Data Source: China Statistical Yearbook from 1999 to 2007
Figure 4: Loaning Scales of China and Beijing
Loan Scales of China and Beijing(100 million yuan)
6,000.00
5,000.00
4,000.00
3,000.00
2,000.00
1,000.00
0.00
1999
Domestic loans 1,111.57
Beijing
165.22
2000
2001
1,385.08 1,692.20
238.82
340.30
2002
2003
2,220.34 3,138.27
382.77
433.33
2004
2005
3,158.41 3,918.08
549.96
680.78
2006
5,356.98
842.49
Data Source: China Statistical Yearbook and Beijing Statistical Yearbook from 1999 to 2007
44
Figure 5: Vacancy Area of Beijing
Vacancy Area of Beijing (10000sq.m)
1400
1200
1000
800
600
400
200
0
Vacancy Area
2000
408.7
2001
502.4
2002
676.1
2003
697.9
2004
595
2005
967.7
2006
1186.3
Data Source: Beijing Statistical Yearbook from 2000 to 2006
Figure 6: Vacancy Rate of Beijing
Vacancy Rate Of Beijing
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
0.00%
2000
2001
2002
2003
Vacancy rate 11.96% 11.73% 12.39% 10.44%
Data Source: Beijing Statistical Yearbook from 2000 to 2006
45
2004
7.40%
2005
2006
10.26% 11.16%
Appendix 2
Table1: Comparison of Market Structures
Type
Perfect
Number of
Nature of
Influence of
Possibility of
enterprises
products
prices
market access
too much
same
no influence
no barrier
quite a lot
different
have short-term
easy
Competition
Monopolistic
Competition
influence
Oligopoly
two or
almost
always set a price
Competition
several
same
through
difficult
negotiation
Monopoly
one
unique
tremendous
impossible
influence
Data Source: "Modern Western micro-economic analysis" Zhu Shaowen, Yu Pingeng (1996).
Table2: Regression Results of Model
Number of
155
R-squared
0.8213
231.36
Adj R-squared 0.8178
Prob > F
0
Root MSE
variables
Coefficient Std. Err.
L
0.0003042
1.58E-05
N
0.0138766
0.1041908 2.26
0.0252
Z
-0.284393
0.0386927 -7.35
0
_cons
1876.261
75.18609
0
observation
F(
3,
151)
46
t value
19.25
24.95
524.21
P>t
0
Table3: The Population of Beijing from 1990 to 2006
Year
Permanent
By Urban Area and Rural Area
Population
(10000 persons)
Urban Population
Rural Population
(10000 persons)
(10000 persons)
National
Degree of
Growth
Urbanization
Rate (‰)
1990
1086
798
288
7.23
73.48%
1991
1094
808
286
2.21
73.86%
1992
1102
819
283
3.11
74.32%
1993
1112
831
281
3.19
74.73%
1994
1125
846
279
3.20
75.20%
1995
1251.1
946.2
304.9
2.80
75.63%
1996
1259.4
957.9
301.5
2.68
76.06%
1997
1240.0
948.3
291.7
1.89
76.48%
1998
1245.6
957.7
287.9
0.7
76.89%
1999
1257.2
971.7
285.5
0.9
77.29%
2000
1363.6
1057.4
306.2
0.9
77.54%
2001
1385.1
1081.2
303.9
0.8
78.06%
2002
1423.2
1118.0
305.2
0.87
78.56%
2003
1456.4
1151.3
305.1
-0.09
79.05%
2004
1492.7
1187.2
305.5
0.74
79.53%
2005
1538.0
1286.1
251.9
1.09
83.62%
2006
1581.0
1333.3
247.7
1.3
84.33%
Date Source: Beijing Statistical Yearbook from 1990 to 2006
47
Table 4: Price Index for Real Estate
(preceding year=100)
Item
2006
2005
2004
2003
2002
2001
Consumer Price Index
101.5
101.8
103.9
101.2
99.2
100.7
105.5
107.6
109.7
104.8
103.7
Commercial Houses
105.8
107.7
109
105
Residential Buildings
106.4
108.4
109.4
101.4
101.9
101.4
Selling Price Index of
Houses
Renting Price Index of
Houses
Residential Buildings
2000
1999
1998
100.4
98.6
99.2
102.2
101.1
100
101.4
103.4
101.8
100.8
100.3
99.9
105.7
104
101.9
101.4
100.4
99.9
101.4
101.9
100.8
102.8
102.4
98.5
102.4
100.5
102.2
107.5
102
108.1
114.2
102.4
109.4
4
5.8
5.8
3.6
4.5
1.5
0.7
1.4
2.2
4.9
6.6
5.5
4.5
4.8
1.2
1 .0
1.8
0.7
-0.1
0.1
-2.5
0.7
1.6
2.1
2 .0
-0.1
3.2
-0.1
-1.3
-1.7
6.3
2.8
7.4
13.8
3.8
10.2
Difference between
Selling Price Index of
House and CPI
Difference between
Selling Price Index of
residential buildings
and CPI
Difference between
Renting Price Index of
Houses and CPI
Difference between
Renting Price Index of
residential buildings
and CPI
Date Source: China Statistical Yearbook from 1999 to 2007
48
Table5: Total Number of Real Estate Enterprises
(unit)
Year
Number of
Enterprises
Domestic
Funded
State-owned
Collective-
Enterprises
Enterprises
owned
Enterprises
Enterprises with
Foreign
Funds from Hong
Funded
Kong, Macao and
Enterprises
Taiwan
1997
21286
17202
N/A
N/A
1989
2095
1998
24378
19960
7958
4538
3214
1204
1999
25762
21422
7370
4127
3167
1173
2000
27303
23277
6641
3492
2899
1127
2001
29552
25509
5862
2991
2959
1084
2002
32618
28657
5015
2488
2884
1077
2003
37123
33107
4558
2205
2840
1176
2004
59242
53495
4775
2390
3639
2108
2005
56290
50957
4145
1796
3443
1890
2006
58710
53268
3797
1586
3519
1923
Data Source: China Statistical Yearbook from 1998 to 2007
49
Table6: China's Price-income Ratio from 1997 to 2006
Per Capita Floor
Per Capita
Average Selling
Price-income
Space of
Annual
Price of
Ratio
Residential
Disposable
Commercialized
Building in
Income of Urban
Buildings
Urban Areas
Households
(yuan/sq.m)
(sq.m)
(yuan)
1997
17.8
5160.3
1997
6.88
1998
18.7
5425.1
2063
7.10
1999
19.4
5854.0
2053
6.81
2000
20.3
6280.0
2112
6.81
2001
20.8
6859.6
2170
6.58
2002
22.8
7702.8
2250
6.66
2003
23.7
8472.2
2359
6.60
2004
25.0
9421.6
2778
7.37
2005
26.1
10493.0
3168
7.88
2006
27.5
11759.5
3367
7.87
Year
Data Source: China Statistical Yearbook of 2007
50
Table7: The Price-income Ratio of 96 Countries/Regions in 1998
The level of
The average of
Maximum of Price-
Minimum of price-
income(Dollar)
Price-income ratio
income ratio
income ratio
0-999
13.2
30
6.3
1000-1999
9.7
28
3.4
2000-2999
8.9
29.3
3.4
3000-3999
9
20
2.1
4000-5999
5.4
12.5
3.4
6000-9999
5.9
8.8
1.7
Above 10000
5.6
12.3
0.8
All
8.4
30
0.8
Data Source: “World Development Report 1999 and 2000", the World Bank.
Table8: Standard for Vacancy Rate in Commercialized Housing
Vacancy rate
Market preference
0- 3 ％
Scarcity of Supply
3 -1 0 ％
Equilibrium
1 0 - 15 ％
Excess Supply
Up to 15 ％
Serious Overstock
Data Source: “China Real Estate Business”, 15th of December, 1998
51
References
Akerlof, G.A. (1970) The Market for "Lemons": Quality Uncertainty and the Market
Mechanism, The Quarterly Journal of Economics, 84(3), 488-500.
ASEAN Annual Report, 1997-2006.
Bai, J. and Zhang, H. (2005) The Thinking of How to Control the Real Estate Bubble in
China. The Economic Review between China and America, 5(2), 33-25.
Bao, Z. (2005) The Price-income Ratio cannot Measure the Real Estate Bubble. Huaxia
Times.
Blackburn, S (1994). The Oxford Dictionary of Philosophy, 1rd Edn. Oxford University Press,
New York, pp. 281-282.
Carey, M. (1990) Feeding the Fad: the Federal Land Banks, Land Market Efficiency, and the
Farm Credit Crisis, Ph.D. Dissertation, University of California at Berkeley.
Chen, Z. (2000) The Housing Mortgage Loan: the Theory and Practise, Working Paper,
Fudan University.
Chen, Y. and Wu, X. (2007) The Analysis of Indicators in Real Estate Market: Price-income
Ratio, Working Paper, Nanjing Forestry University.
Collyns, C. and Senhadji, A. (2002) Lending Booms, Real Estate Bubbles and the Asian
Crisis, Working Paper, International Monetary Fund.
Eatwell, J., Milgate, M. and Newman, P. (1998). The New Palgrave: A Dictionary of
Economics, 3rd Edn. Macmillan Reference Limited, London, pp. 281.
Geltner, D.M. and Miller, N.G. (2001). Commercial Real Estate Analysis and Investments,
South-Western Educational Pub, U.S.A, pp. 164.
52
Hansson, S.O. (2007) The Art of Doing Science, Department of Philosophy and the History of
Technology, KTH.
Hendrikse, G. (2003). Economics and Management of Organisations: Co-ordination,
Motivation and Strategy, McGraw-Hill Education, UK, pp. 33-36.
Herring, R.J. and Wachter, S. (1998) Real Estate Booms and Banking Busts: an International
Perspective, Working Paper, University of Pennsylvania.
Herring, R.J. and Wachter, S. (2002) Bubbles in Real Estate Markets, Working Paper,
University of Pennsylvania.
Herring, R.J. (2006) Booms and Busts in Housing Markets: How Vulnerable is New
Zealand?, University of Pennsylvania.
Hilbers, P., Lei, Q. and Zacho, L. (2001) Real Estate Market Developments and Financial
Sector Soundness, Working Paper, International Monetary Fund.
Japanese Economic and Fiscal Report, 2003.
Jia, H. (2003) The Reform of Method to Calculate the Vacancy Rate in Commercial Housing,
Working Paper, National Bureau of Statistics of China.
Jin, S. (2007) The Gap of Price-income Ratio and the Adjustment of Housing Policies in
China, The National Study Report, 162(8), 44-56.
Kuang, W. (2003). Monopoly, Competition and Control: the Study of Residential Market in
Beijing, The Economy and Management Publishing House, Tianjin, pp. 73-77.
Li, H. (2004) Research on Real Estate Bubble and Real Estate Pricing Mechanism, Working
Paper, China Central Bank.
Lu, L. (2004) The Study of Real Estate Bubble, Finance and economics, 21(8), 19-30.
53
Mas-Colell, A.,.Whinston, M., and Green, J. (1995), Microeconomic Theory, Oxford
University Press.
Milgrom, P., Roberts, J. (1992), Economics, Organization and Management, Englewood
Cliffs: Prentice-Hall.
Noguchi, Y. (1994) The "Bubble" and Economic Policies in the 1980s, Journal of Japanese
Studies, 20(2), 291-329.
Qu, S. and Li, H. (2004) Market Structure, Supply Constraint and Financial Medium: an
Extension to the Housing Price Model of Carey (1990), Working Paper, China Central Bank.
Ren, J. (2007) How to Control the Real Estate Bubble in Main Cities, China Business Times.
Rosen, K. (1984) Toward a Model of the Office Building Sector, Real Estate Economics,
12(3), 261-269.
San, F. (2007) The Formation of Japan's Real Estate Bubble and the Pros and Cons of
Relevant Policies, Journal of Japanese Studies, 14(13), 33-46.
Tai, J. (2004) The Weekly News of International Real Estate, the Reference News.
Wang, Y. (2006) The Vacancy Rate of Commercial Housing and Real Estate Bubble,
Working Paper, Chongqing University.
Wu, L. (2007) Preventing the Real Estate Bubble and Financial Risk, Working Paper, Henan
Institute of Finance and Economics.
Xie, J. (2002). The Real Estate Bubble and Financial Crisis, 2rd Edn. The Economy and
Management Press, Henan, pp. 112-136.
Xue, J. (2007) The Enlightenment of "the Lost Decade in Japan" Because of the Real Estate
Bubble, International Business Times.
54
Xu, D, Yu, Z. and Wang, J. (2002) The Economic Bubble and Financial Crisis, Working
paper, China Renmin University.
Yang, F., Li, H. and Li, Y. (2005) The Theory of Economic Bubble and the China's Real
Estate Market, Working Paper, China Central Bank.
Ye, T. (2007) What Did the Japan's Real Estate Bubble Tell us?, Daily Economic News.
Zhang, D., Zhang, H. and Long, C. (2004) The Fluctuation of Real Estate Investment Caused
by the Vacancy Rate, Finance Centre, 1(14), 103-130.
Zhu, S. and Yu, P. (1996). Modern Western Microeconomic Analysis, 3rd Edn. The
Commercial Press, Hongkong, pp. 188-198.
55