# RECORD 129023b53e859d480f057e1aa633ff7548d6c727
# TITLE: Anchoring Effect in Chinas Real Estate Market
# YEAR: 2023.0  VENUE: Advances in Economics, Management and Political Sciences  DOI: 10.54254/2754-1169/14/20230815
# AUTHORS: Siyu Chen; Wenhao Wang; Lu-Hong Zhong
# PAGES: 8  CANDIDATE TABLE PAGES (1-based): [4]
# ABSTRACT: Since the reform and opening up, China's real estate industry has prospered rapidly and has become an important force driving rapid economic growth and promoting urbanization. In recent years, China's real estate industry has entered an inflection point of development, and real estate bubbles and cyclical sharp fluctuations in the real estate market have occurred from time to time. Behavioral finance has provided a new research direction for how to explain this fluctuation. Based on this, this essay uses the classic anchoring effect theory in behavioral finance theory to study the existence and characteristics of anchoring effect in China's real estate market from the micro level, and explains the entire mechanism through three applications. The first application empirically tested the existence of the anchoring effect in China's real estate market, and analyzed the difference between the anchoring effect in the eastern and western regions of China. It verified that the decision of housing prices in the central region was affected by the anchoring effect of the micro subject, while the anchoring effect in the eastern and western regions was not significant. The second application analyzed Hong Kong's secondary residential market, and a statistical model including anchoring effects was also presented in order to study the dynamics of house prices. The third application provides an improved Hedonic model, which combines various literature data to study the influence of age, growth area and other characteristics of home buyers on real estate prices under the anchoring effect.


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Anchoring Effect in China’s Real Estate Market 
Siyu Chen 1, a, †, *, Wenhao Wang2, † and Luhong Zhong3, † 
1 School of Economics, Fujian Normal University, Fuzhou 350108, China 
2 Suzhou Foreign Language School, Suzhou 215000, China 
3 Ulink College of Shanghai, Shanghai 201600, China 
a. 104022020006@student.fjnu.edu.cn 
*corresponding author 
†These authors contributed equally to this work.  
Abstract: Since the reform and opening up, China's real estate industry has prospered rapidly 
and has become an important force driving rapid economic growth and promoting 
urbanization. In recent years, China's real estate industry has entered an inflection point of 
development, and real estate bubbles and cyclical sharp fluctuations in the real estate market 
have occurred from time to time. Behavioral finance has provided a new research direction 
for how to explain this fluctuation. Based on this, this essay uses the classic anchoring effect 
theory in behavioral finance theory to study the existence and characteristics of anchoring 
effect in China's real estate market from the micro level, and explains the entire mechanism 
through three applications. The first application empirically tested the existence of the 
anchoring effect in China's real estate market, and analyzed the difference between the 
anchoring effect in the eastern and western regions of China. It verified that the decision of 
housing prices in the central region was affected by the anchoring effect of the micro subject, 
while the anchoring effect in the eastern and western regions was not significant. The second 
application analyzed Hong Kong's secondary residential market, and a statistical model 
including anchoring effects was also presented in order to study the dynamics of house prices. 
The third application provides an improved Hedonic model, which combines various 
literature data to study the influence of age, growth area and other characteristics of home 
buyers on real estate prices under the anchoring effect. 
Keywords: anchoring effect, real estate market, house price 
1. 
Introduction 
One of the great lessons of the 2008 international financial crisis is the harmfulness of house price 
bubbles to the macro economy. As an important asset for enterprises and residents, real estate 
possesses the dual characteristics including consumer goods as well as investment goods, and its price 
fluctuations may have a greater impact on the real economy and financial system in depth and breadth 
than stocks and other financial assets. 
Since the policy of reform and opening-up introduced, China's real estate industry has undertaken 
tremendous changes. However, its development in China has not been smooth sailing, and some 
serious problems have been exposed beneath the surface of the property market boom. From a 
nationwide perspective, the development of China's real estate market has shown an overheated trend, 
Proceedings of the 2nd International Conference on Business and Policy Studies
DOI: 10.54254/2754-1169/14/20230815
© 2023 The Authors. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0
(https://creativecommons.org/licenses/by/4.0/).
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the change of the real estate market transaction volume preceded real estate price, and the final VAR 
estimation result was used to test the lagged positive correlation between real estate market 
transaction volume and real estate price to test whether the anchoring effect exists. 
Table 1: Descriptive statistics of the data. 
 
Variate Sample 
AVG 
Variance 
MIN 
MAX 
the 
National 
P 
2652 
4374.511 
3410.051 
650.3289 
22209.08 
V 
2652 
24159956 
2496963 
5100 
23800000 
East 
P 
1404 
5769.426 
4043.801 
1076.983 
22209.08 
V 
1404 
2729427 
2733150 
5100 
23800000 
Mid 
P 
624 
2711.298 
1332.947 
650.3289 
6195.997 
V 
624 
2168816 
2204528 
47600 
16300000 
West 
P 
624 
2899.171 
1242.315 
741.91 
6417.433 
V 
624 
1957955 
2086896 
7450 
13100000 
Table 2: Results of panel unit root tests on economic variables. 
 
Testing 
Method 
LLC 
Breitung 
IPS 
ADF-Fisher 
PP-Fisher 
the 
National 
lnp 
-6.28901 
-4.85440*** 
-16.7042*** 
-365.591*** 
694.343*** 
Inv 
-13.4258*** -2.72818*** 
-13.5794… 
-304.871*** 
917.908*** 
East 
lnp 
-4.09745*** -5.46881*** 
-14.678*** 
238.82*** 
332.064… 
Inv 
-6.65464*** -1.70474*** 
-6.86672*** 
106.020*** 
446.246*** 
Mid 
lnp 
-2.79502*** -2.45001*** 
-9.46389*** 
101.508*** 
182.929*** 
Inv 
-19.0694*** 
-1.77311** 
-14.3103*** 
171.524*** 
249.731*** 
West 
lnp 
398539*** 
-1.78435*** 
-3.01980*** 
25.2604*** 
179.350*** 
Inv 
1.45726 
-1.28279* 
-3.43872*** 
27.3272*** 
221.931*** 
*, **, *** indicate stationary at the 10%, 5% and 1% significance levels respectively 
Table 3: Estimated results of panel VAR. 
 
Inp 
 
the National 
East 
Mid 
West 
Lnv(-l) 
0.301227*** 
-0.0702564** 
0.09416*** 
0.0082298 
Lnv(-2) 
---- 
-0.0522693 
0.0312033 
0.0320357 
Lnp(-l) 
0.627542*** 
0.57088*** 
0.403938*** 
0.5080872*** 
Lnp(-2) 
---- 
0.5300592*** 0.3984971*** 
0.4186571*** 
 
By analyzing the data and tables above [12], experimenters could draw the following conclusions. 
Table 1 indicates that the average real estate price in the central and western region were less than 
that in the eastern regions. The fluctuation range was a step-like decrease in the eastern, central and 
western regions, and from the perspective of the average transaction volume of real estate, the eastern 
region has the largest transaction volume, followed by the central region, and the western region has 
the least average transaction volume. Table 2 suggests that the nationwide variables lnp and lnv were 
both stationary at the 1% significance level and had no unit root. While the panel data of the two 
variables (except for individual cases) in the east, middle and west regions did not have a unit root, 
and they were all stationary time series. Table 3 verifies that from a national perspective, the current 
Proceedings of the 2nd International Conference on Business and Policy Studies
DOI: 10.54254/2754-1169/14/20230815
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housing price was affected by the transaction volume of the previous issue, and there was a positive 
correlation between them. That is, in China's commercial housing market, there was a lagging positive 
relationship between transaction volume and housing price. At the same time, the experimenters also 
found that the price has a strong autocorrelation, and investors would adjust the current price 
according to the historical price of the real estate. The rise in the past price would cause the current 
price to rise, which was caused by the psychological expectations of consumers. In other words, 
consumers set their own anchors through such expectations. As for the eastern, central, and western 
regions, the anchoring effect was dissimilar in different regions. The determination of housing prices 
in the central region was affected by the anchoring effect of the micro-subject, while it was not 
significant in the western and eastern regions. 
In summary, the anchoring behavior among the main part of consumers and the anchoring effect 
in the market are the manifestation of the imperfect operating mechanism and development of the 
real estate market. Targeted recommendations are put forward for investors, real estate developers 
and intermediaries, and the government. For investors, strengthening the skills of collecting and 
identifying information and the ability to control cognitive errors and psychological disorders are 
important. For real estate developers and intermediaries, though strengthening the construction of the 
credit system of real estate enterprises is tough to some extent, it is worth trying. The government 
should establish a transparent real estate market transaction information platform and evaluation 
mechanism. Furthermore, it is responsible to formulate differentiated policies for the development of 
real estate markets in different regions. 
2.2. Application in the Hong Kong Second-Hand Housing Market 
An appealing characteristic of Hong Kong’s secondary housing marketplace is its extreme 
competition [10]. There are a whole lot of customers and dealers with inside the marketplace [13]. 
Estate sellers' preferred fee is simply 2 according to cent of the acquisition fee (1 according to cent 
for every client and seller). The aggressive nature of the marketplace makes strategic conduct via way 
of means of customers, dealers or sellers much less likely, presenting best situations for checking out 
each cognitive bias. 
The assumption is that customers peg the cost of the house to its preceding buy fee. As a 
prerequisite for figuring out the anchoring impact, the client needs to recognize the preceding buy 
fee.  
In fact, the wants for these records are enormous. Between 2001 and 2010, the common quantity 
of searches according to year turned into 4.5 million (out of a populace of approximately 7 million 
primarily based totally on 2011 figures), at the same time as the quantity of second-hand transactions 
according to yr turned into much less than 200,000 [14]. This indicates that customers do take these 
records into consideration whilst creating a buy decision. The Internet has made it less expensive to 
get these records. The overall quantity of land sign in searches is at the rise. While the quantity of on-
line searches greater than doubled among 2001 and 2010, the quantity of counter searches declined 
step by step over the equal period. A direct implication of this fashion is that anchoring results have 
turn out to be more and more crucial over the years. 
Using housing transaction statistics from the Economic Property Research Center (EPRC) as the 
number one statistics source.  
Utilizing a pattern of repeat sales, researchers discover each anchoring and loss aversion with 
inside the Hong Kong secondary housing marketplace. then gifting an easy version to expose the 
effect of those cognitive biases on residence fee dynamics. In the version, because of those cognitive 
biases, each fee dispersion and quantity are definitely associated with common residence prices. In 
addition, taking into consideration loss aversion, a smaller anchoring impact reduces fee dispersion 
Proceedings of the 2nd International Conference on Business and Policy Studies
DOI: 10.54254/2754-1169/14/20230815
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