Download The Effect of Imbalance of Regional Economic Development on the

The Effect of Imbalance of Regional Economic Development on the
Price of Real Estate: An Empirical Study of China
XU Feng, SU Yong
School of Management, Jilin University, P.R.China, 130022
Abstract: Based on monopolistic competition of different products, this paper analyzes market effect
and social effect of totally differential mechanism of real estate and believes that the differential
products can strengthen the monopolistic force of land agents then to improve their ability of monopoly
pricing, which can harm social welfare. This paper, based on Chinese practice, finds that imbalance of
regional economic development pricks up the differences of the real estate products and reinforces the
land agents´ market force, which causes the increase of housing price, the difference of regional housing
price and the bad effect of related policies. So some suggestions are discussed at the end.
Keywords: regional economy, real estate price, product difference, Lerner index
1 Introduction
Since 1990s, China has been on the way to market economy, and Chinese real estate market came
into being at that time. The price in Chinese real estate industry increases gradually every year. But
since 2004, the housing prices have been rising greatly, which is higher than the per capita income. In
Beijing, Shanghai and Guangdong, the price increased by 12314%、3814%、7311% in past three years
but the middle cities increased a little, which shows that regional difference of price is enlarging. The
practices in developed countries and many researches show that abnormal continuous increase of
housing price will bring many economic and social problems, such as overheated economy, real estate
financial risk and unstable society [1]. Since 2006, the rapid price increase in real estate has caused many
problems, which have been the focus of all circles. The government has taken some measures to control
and leverage the real estate market, but the effects are not evident.
Real estate is the combination of building and land, and is composed of house property and land
property [2]. In China, under the system of state-owned urban land, the key problems of real estate
industry development lie in the government management, which is the main entry barrier of land agents
and forms the incomplete competition in real estate industry. Many domestic scholars study real estate
price mechanism via monopolistic piecing. What is more, the lands are immovable, and cannot be
copied, so they are complete different. Generally speaking, product difference hypothesis is the base of
imperfect competition theory, so complete differences of real estate products impact the housing prices.
But the difference degree is unsure. On one hand, land agents can strengthen the differences via varieties,
quality and service, on the other hand, imbalance of regional economic development can objectively
influences product differences. Based on the internal feature of complete differences of real estate
products, this paper studies the effect of imbalance of regional economic development on the price of
real estate products and provides some pragmatic suggestions for the government.
2 Market effect and social influence of complete difference of real estate products
Entry barrier is the base of incomplete competition market. If the barriers don’t exist, a firm can
enter and quit an industry, then the market will be in the state of complete competition. Monopolistic
force is not only determined by the numbers and sizes of the firms, but also by the products differences
of all firms. So we will analyze the market effect of complete difference of real estate products
according to the model of monopolistic competition of different products [3].
Suppose two land agents provide two different products and their costs are zero. The demand for
land agent one (q1) is not only determined by its price (p1), but also by that of land agent two (p2).
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Obviously, according to demand law, q1 will fall when p1 increase. According to the substitution
features of the products, if p2 of land agent two increases, the demand for land agent one will increase
because its price (p1) is relatively cheaper. The following two equations can be used to express the
demands for land agent one and two.
q1 = a - bp1 + cp2
q2 = a - bp2 + cp1
(1)
where a > 0, and it is capacity parameter; b > 0, and it stands for the sensitive degree of output of two
products to each price; c > 0, and it stands for the substitution degree of one product to another one; b >
c, and this means each product is more sensitive to its own price, that is to say, if p1 increase a little, the
demand for land agent one will not change when p2 increase more. If the differences between b and c
are big, then the same to the differences between the two products. In equation (1), the demand is
expressed by price function, and then the following is the reverse functions:
p1 =m - nq1 - rq2
p2 =m - nq2 - rq1
(2)
where m = a / (b - c), n = b / (b2 - c2), r = c /(b2 - c2 ); n > r, and this means each price is more sensitive
to its own output. According to equation (1), we can get p1 when land agent one (l1) maximizes its
profit.
l1 (p1, p2) = p1 q1 = p1 (a - bp1 + cp2)
(3)
Its one-stage condition is p1* (p2) = (a + cp2) /2b
(4)
Equation (4) can be regarded as responding function, that is to say, when p2 is fixed, equation
(4)will be the best response of land agent one. According to symmetry theory, Bertrand Equilibrium is
as follows:
qib = ab/ (2b - c)
pib = a / (2b - c)
b
2
li = a b / (2b - c)2 i = 1, 2
If two firms undergo Cournot competition, we can get q1 when land agent one (l1) maximizes its
profit according to equation (1):
l1 (q1, q2) = p1 q1 = q1 (m - nq1 - rq2)
Its one-stage condition is q1*(q2) = (m - rq2) /2n
Similarly, according to symmetry theory, we can get Cournot Equilibrium of different products as
follows:
qic =m / (2n + r) = a (b + c) / (2b + c)
c
pi =mn / (2n + r) = ab/ [ (b - c) (2b + c) ]
lic =m2n / (2n + r)2= a2b ( b + c) / [ (2b + c)2 ( b - c) ] i = 1, 2
According to the above analyses, we can get the following results: dpib /dc > 0, dpic /dc > 0, dlib /dc
> 0, dlic /dc >0. The results show that if the product differences augment, the substitution between
products will decrease, price competition between firms will trail off and the profit will increase. qic - qib
< 0, pc - pb = ac2 / [ (4b2 - c2 ) ( b -c) ] > 0, lc >lb > 0, and these show that Cournot competition of
different products can lead to lower output, higher price and profit. At the same time, in Bertrand
competition, the price and profit are all more than zero, which avoids Bertrand Paradox. Difference
degree of the products is positively related to firms´ market force, that is, the greater the differences, the
stronger the market force, the more monopolistic the market, so the products are quite different. Even if
there are several land agents in the market, they can exert almost monopolistic force on their products.
Contrariwise, even if there are a few firms, their market force will be weak if their products are
homogeneous.
Next, we will analyze the social effect of different products [4]. As shown in Table 1(a) and (b),
when the product differences are strengthened, the demand elasticity of real estate products will lessen,
MV - P* will increase, and the firms will have more monopolistic force, so they will snatch more
consumer surplus and the social loss (shadow part) also increases.
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P ric e
P ric e
ME
ME
M V -P
P*
S=A E
S= A E
M V -P *
PP
P*
PP
MV
MV
Q*
Q*
Q u a n tity
Q u a n t ity
(b )
(a )
Table 1 Social effect of products difference
Note: ME, AE and MV stand for marginal expenditures, average expenditures and marginal value respectively.
In China, there are three regional economic zones and they are East, Middle and west Zones. After
the open-door reform, the disparities among the three zones increase greatly (see table 2), and the most
developed areas are Beijing, Shanghai, Jiangsu, Zhejiang and Guangdong. The imbalance of regional
economic development strengthens the difference of real estate products, market force of land agents
and their ability of monopolistic pricing, which causes the bad effect of government’s policies of
controlling the housing prices. We will analyze quantitatively the relation between the imbalance of
regional economic development and monopolistic force of land agents to study the effect of Chinese
monopolistic pricing mechanism on the housing prices.
Table 2 GDP in East, Middle and West of China from 1995-2007
Source: Chinese Economic Website
3 Empirical studies
3.1 The imbalance of regional economic development and monopolistic force of real estate
Lerner index [5] and regional economic development indexes are introduced for analysis. Lerner
index (L) measures monopolistic force and can be expressed by the following equation: L = (P - MC) /P,
where P stands for product price and MC is marginal cost; Lerner index fluctuates between 0 and 1, and
the bigger its value, the stronger the market monopolistic force. Under the state of complete competition,
price equals to marginal cost, so Lerner index is 0. But in monopolistic market, price is higher than
marginal cost, Lerner index fluctuates between 0 and 1. This index can measure forestallers´ behavior
and price deviation from the marginal cost. Logarithm model of selling cost (SC) of real estate products
and selling quantity (SQ) are built to get price elasticity coefficient then to analyze marginal price of
real estate products. The result is as follows: SC = - 6.45E+ 10 + 1916.663SQ. The model has passed
test and the data comes from Chinese Economic Website (CEW). The result shows that when real estate
adds one square meter, the total price of the house will add RMB 1916.663, that is, the marginal price of
real estate product is RMB 1916.663 (constant). K is used to express balanced indexes of regional
economic development. In this paper we use three economic zones (East, Middle and West) to estimate
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these balanced indexes. Suppose the total economic gross of East, Middle and West of China can be
expressed by GE, GM and GW, and the ratio between them and GDP can be expressed by GE /GDP,
GM /GDP and GW /GDP respectively. When three zones develop absolutely equally, the ratio will be
1/3, so K can be expressed as follows: K=Abs (GE /GDP - 1 /3) +Abs (GM /GDP - 1 /3) +Abs (GW
/GDP - 1 /3), where Abs ( ) stands for absolute value. The bigger the value of K, the more imbalanced
regional economy. If regional economy keeps balance, then the value of K is 0. Empirical studies are
done according to the data of 1994 to 2007 and all data (i.e. annual selling price, building price, regional
GDP, etc.) are from CEW. GDPs of three zones equal to the total amount of every district in the zone.
The regional plot is based on CEW. In order to overcome heteroscedasticity, logarithms of L and K are
used in the latter analyses.
3.1.1 Stationary test of variables
When analyzing time order data, we should firstly exert stationary test of variables to reduce
falsehood. ADF test is utilized to test unit root of lnL and lnK. The results are as follows by using
Eviews5.0.
Table 1 ADF unit root tests of variables
Variables
Test form
ADF statistics
5% critical value
Stable or not
lnL
(C,0,2)
-0.767265
-3.259809
Not
lnK
(C,0,2)
-1.131972
-3.144920
Not
∆lnL
(C,0,2)
-5.049807
-3.320969
Yes
∆lnK
(C,0,2)
-4.131283
-3.175352
Yes
Note: ADF test form (c,t,k) stands for the equation of unit root test, and includes constant, time trend and lag order.
0 means c and t are not included, and “∆” stands for differential sampling parameter.
3.1.2 Co-integration test and error correction model
Engle and Granger put forward co-integration theory [6] and believed that although some economic
variables are not unstable, their linear combination may be stable, and this stable combination is called
co-integration equation. In this paper we utilize residuals of regression equation to test co-integration
relation. The co-integration equation are as follows:
lnL = - 0.322181 + 1.665190 lnK
( - 0.911399) (5.007346)
R2 = 0.758115 R2´ = 0.727879 DW = 1.307148 F = 25.07351
(Note: the values in bracket are t-statistics)
According to the regression results, the equation is valid. Then ADF test is done to estimate residual et
to test whether it is stable. The results are shown in table 2.
ADF statistics
ADF critical value
Table 2 ADF test of residual et
t-statistics
-2.575496
1% level
-2.847250
5% level
-1.988198
10% level
-1.600140
Prob. values
0.0166
From table 2 we know that hypothesis 0 is rejected at the level of 5% (that is, et—I(0)), which
shows that residual order is stable. Co-integration relation exists between lnL and lnK and the regression
coefficient is 1.665190 (>0), which shows that a long-term stable and positive balanced relation exists
between the imbalance of regional economic development and monopolistic force of real estate.
Error correction model means when co-integration relation exists between variables, then this relation is
realized in the course of short-term fluctuation and modification. Because co-integration relation exists
between lnL and lnK, then error correction models of ∆lnL、∆lnKare as follows:
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∆lnL = 0.226359 + 0.224468∆lnK – 0.356157et ( - 1)
(3.485613) (0.796871)
( - 1.984627)
R2 = 0.398352
R2´ = - 0.197803 DW = 2.745455 F = 1.986306
(Note: the values in bracket are t-statistics)
As shown in the results, error correction coefficient is significant at the level of 10% and it is
0.356157, which shows that the degree of reverse correction of last imbalanced state is 35.162%,and it
means when long-term balance deviates the speed of adjustment from imbalanced state to balanced state
is slow.
3.1.3 Granger causality test
We use Granger causality test to study the cause-and-effect relation between imbalance of regional
economic development and monopolistic force of real estate. Granger causality test comes down to the
selection of lag order. Here the selection of best lag order is based on the residual analysis of
unrestricted VAR model, that is AIC order selection criteria and finally the best lag order K = 1.
Hypothesis 0
InL is not Granger cause of InK
InK is not Granger cause of InL
Table 3 Results of Granger causal test
Samples
F-statistics
10
1.64420
10
2.37054
P-value
0.24706
0.17457
According to Granger causality test, we know that the probability of lnL Granger cause lnK is
75.1294%, and that of lnK Granger cause lnL is 82.1543%. The ratios show that the imbalance of
regional economic development causes monopolistic force of real estate, and this force can strengthen
the imbalance of regional development reversely.
3.1.4 Impulse response analysis
We use impulse response function to analyze the dynamic relation between the imbalance of
regional economic development and monopolistic force of real estate. In VAR model, disturbing term is
also called innovation. Impulse response function describes how a variable’s disturbance affects other
variables via model then feed back to itself [6]. Table 3 is drawn to explain the relation between the
imbalance of regional economic development and monopolistic force of real estate. Real line stands for
calculative values and broken line is the confidence belt, which equals to response function plus (or
minus) doubled standard deviation. As shown in table 3, the imbalance of regional economic
development is positively related to the monopolistic force of real estate. The effect increases from
period one, then peaks at period two, and from then on the monopolistic force of real estate keeps stable.
Table 3 Response of InL to the standard deviation of InK
3.2 Monopolistic pricing in real estate industry [3]
After the above analyses, we build monopolistic pricing model of real estate industry to study the
effect of monopolistic force on pricing. Theoretically, demand and supply are two factors affecting
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pricing of real estate products. In order to analyze their effect on the price, we use cost and per capita
income as variables in regression analysis. Because of the incomplete data in real estate industry, we use
the housing selling prices, building cost and per capita income from 31 districts or provinces ranging
from 2000 to 2007 in Eviews. All data are from CEW. In order to overcome heteroscedasticity,
logarithms of P, C and Income are used in the analyses. The regression results are as follows:
lnP = 1.776672 + 0.185917 lnC + 0.499254 lnIncome +[AR (1) = 01844056 ]
(1.231170) (2.208723)
(3.641586)
(15.66469)
R2 = 0.933477 R2‘ = 0.931814 DW = 2.229866 F = 561.2994
We can see from the results that house pricing is positively related to building cost and per capita
income respectively. But building cost and per capita income have different effects on the price.
Building cost increases by 1%, then the price will only increase 0.185917%, but per capita income
increases by 1%, then the price will increase 0.499254%, which means the cost is not the main factor
affecting the price. In China, monopolistic force of land agents is very strong, so they snatch customer
surplus, which causes house price rise. In developed areas, such as Beijing, Shanghai and Guangzhou,
this effect is greater and the vicious circle of economic development-continuous house pricing rise
continues, which embitter residents´ economic burden[7].
Besides, per capita income is only one of the factors measuring regional economic development,
other factors, such as development quality, environment and potential, are also can be used to measure
regional economic development.
4 Conclusions
As shown in the results of empirical study, complete differences of real estate products lead to
incomplete competition in this industry, then forming monopolistic and competitive market. The
imbalance of regional economic development reinforces products differences, strengthens the
monopolistic force of land agents and improves their ability of pricing, which can help them snatch
more consumer surplus, especially in developed areas, where the economy develops quickly and the
house price are higher than other underdeveloped districts. In China, the price of real estate products rise
continually and the regional differences are enlarging. At present, pricing-control policies are focusing
on macro-controlled level, ,such as implementing tight monetary policies, improving the loan interest
rate, inhibiting overheated demand and even if using administrative and economic ways to intervene
house price. But these policies didn’t work well. So, in order to control the real estate price sustaining
rise, the government should start with internal features of real estate products and market structure to
adjust macro policies, boost balanced development of regional economy, reduce the differences among
real estate products and inhibit monopolistic force of land agents to weaken their ability of house pricing.
Only by doing these, will policies of controlling house prices take effect.
References
[1]Liu Xiuguang. Inner paradox and price rigidity: an analytical framework in Chinese real estate.
Academic Research. 2007, (1): 1-10. (in Chinese)
[2]Tang Shuhua. Chinese Real Estate. Beijing: New Times Press, 1992. (in Chinese)
[3]Miao Tianqing. Chinese Real Estate: structure, conduct and performance. Beijing: Economic and
Science Press, 2004. (in Chinese)
[4]Pindik Rubinfield. Micro economy. Beijing: Chinese Renmin University Press, 2004. (in Chinese)
[5]Yang Jiangwen, Zhou Fengqi. Industrial organization. Shanghai: Learning Press, 2003. (in Chinese)
[6]Gao Tiemei. Statistical analysis and model building: usage of Eview. Beijing: Tsinghua University
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Financial and Economic University, 2007, (1):25-29. (in Chinese)
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