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The Wealth Effect of Chinese Household Assets and Its Influence on
Consumption Demand
ZHI Dalin, HAN Jianyu
School of Economics, Northeast Normal University, P.R.China, 130117
Abstract
At present, the rapidity of economic growth in China is slower. The weakness of
economic growth driving of consumption demand emerges. Based on consumption function, this paper
uses cointegration theory and Vector Error Correction model which are based on VAR model and
combines Granger Causality Test to conduct an empirical study on the wealth effect of Chinese
resident’s assets that mainly include the aspects of stock market and real estate market in China. The
research results show: the wealth effect of Chinese stock market is relatively feeble because of Chinese
stock market existing problems in scale, operation and managing policies; compared with stock market,
the wealth effect of real estate market is comparably significant, with 1% increase on real estate market
wealth, there will be 1.36% increase in consumption expenditure. Currently, dispensable income is the
main factor influencing the consumption demand in China, so the fundamental ways to promote
consumption increase in China are promoting the increase of income of households and stabilizing
income expectation.
Key words Cointegration, Consumption function, Granger test, VEC, Wealth effect
1 Introduction
Western conventional economists ignored study on the issue of demand, and few questioned
consumption theory that belongs to demand issue ahead of Keynes. In the book of The General Theory
of Employment, Interest and Money published in 1936 Keynes [1] studied consumption function firstly
and held the opinion that actual consumption expenditure is the stationary function of actual income
through studying the relation between consumption and income on the basis of absolute income
hypothesis.
Pigou [2], in his book Employment and Equilibrium published in 1941, introduced the principle of
wealth effect, which is that: when price decreases in recession stage, households’ actual surplus will
increase, and wealth net value will increase. Subsequently, the consumption desire of consumers will
grow. In The New PalGrave: A Dictionary OF Economics (Q-Z) (1996) [3], wealth effect is strictly
defined as follow: if other conditions being the same, changes in currency surplus will lead to changes in
aggregate consumption expenditure. Because this wealth effect was firstly advocated by Pigou and
Haberler, it was also called Pigou effect or actual surplus effect.
With continuous development of consumption theories, more attention was paid to wealth effect
and it is validated ulteriorly. Friedman [4] connected consumption and persistent income in his Persistent
Income Hypothesis and thought that “people’s consumption expenditure is related to their ‘persistent
income’ which can be predicted, but not to their current income. ‘Persistent income’ is the sum of all
income in the predicted period and payable interest of loans as well as receivable interest of
interest-bearing assets”. Modigliani[5] treated assets (including stock, securities, savings, heritage, etc.)
as the second factor influencing consumption to explain consumption expenditure together with
dispensable income in his consumption function based on life cycle hypothesis. Through using
American data during the world war to fit their consumption function equation, Aodo and Modigliani
[6]
(1963) found that the coefficient of assets was near to 0.06(that is the size of wealth effect), and then
proved the existence of wealth effect.
Now one of the factors which restrict the rapid development of economy in China is consumption
demand, especially the weak increase of household expenditure demand. Hereby studying the
consumption theory and consumption function form has important practical significance in guiding the
establishment of consumption policies. In the process of studying consumption function form, one issue
that can not be ignored is the relationship between consumption expenditure and wealth assets, and
Ⅱ
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whether wealth assets have an impact on household consumption expenditure. That is the issue of the
existence of wealth effect. Broad wealth effect refers to the impact of changes in household assets
(including cash, savings, securities, stock, and properties, etc.) on household consumption demand. But
this paper simplifies it by cutting out the superfluous and only considers the wealth effect of stock
market and real estate market owing to the stability of national debt, company securities, and interest.
Chinese scholars conducted meaningful theoretical and empirical research on the wealth effect of
stock market on base of analysis of Chinese consumption function. Zang Xuheng (1994) analyzed the
influence of financial assets (mainly savings and cash) on expenditure when he studied expenditure
function. He Juhuang (2000) studied the impact of financial assets (mainly savings and cash) on
consumption before 1996. Gao Li (2001) found that there was no significant wealth effect of Chinese
stock market, and there was relatively big instability at different stages. Li Zhenming (2001) thought
that the wealth effect of stock market should be lower than 0.044. Li Xuefeng (2003) concluded that the
wealth effect of Chinese stock market was feeble by using regression analysis and analyzed the reason
for the weakness of wealth effect. Mao Dingxiang (2004) studied the wealth effect of stock market from
1992 to 2002 by using causality test and cointegration analysis method and thought that there was only
substitution effect of Chinese stock market. By using cointegration method, Ma Hui (2006) concluded
that Chinese stock market had no significant wealth effect within full-sample period. But from analysis
of data since 1996, the wealth effect had a weak existence. Li Yushan (2006) studied the wealth effect of
Chinese household securities assets and housing assets by establishing ECM model and research showed
that the wealth effect of securities assets was weak.
There was relatively little research on the wealth effect of real estate market by Chinese scholars,
but their views were the same: that was, the wealth effect of real estate market was relatively significant.
Li Yushan (2006) found in his research that in short term, the wealth effect of housing assets was
negative, but in long term it was positive. Liu Jianjiang (2005) made an in-depth analysis about the
functioning mechanism of the wealth effect of real estate market through LC-PIH model and held the
opinion that the wealth effect of real estate market had a stronger influence than that of stock market.
Only Zhu Xinling (2006) thought that Chinese real estate market had no wealth effect but only
substitution effect.
The research results of scholars offer much accumulation which can be used as reference for
knowing better about wealth effect and making further study about consumption theories. Nevertheless
compared with the same kind of research abroad, research in China lags apparently, which can be seen
from the following two aspects: (1) the research methods drop behind relatively, and modern
econometrical methods are rarely used. The direct fitting with nonstationary economic data results in
false regression issues, or there are inappropriate uses of modern econometrical methods, such as the
sample period is too small, etc. (2) Research is not adequate in depth and is not sub divisional enough.
According to different effect of different kinds of assets we should conduct sub divisional research and
make dynamic analysis about the short term and long term effect of wealth in studying wealth effect.
Generally speaking, research in China only makes econometrical analysis of single assets. Besides, on
the wealth effect of stock market and real estate market there isn’t simultaneous research and the
differences of short term and long term effect are often ignored. In order to solve the above two points,
this paper tries to make an in-depth research on the wealth effect of Chinese stock market and real estate
market by using cointegration theory and Vector Error Correction model which are based on VAR model
combined with Granger Causality Test.
2 Empirical Analysis
2.1 Selected variables and the data
This paper mainly studies the wealth effect of stock market and real estate market, that is, the
impact of stock price and real estate price index on household consumption. By integrating the research
practice of previous scholars and the reflection of the writers, this paper tries choosing the total
consumption (TC) of a society as the index of household consumption demand in China. Because the
holders of stock and real estate wealth are mainly urban residents, it is reasonable and representative to
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use dispensable income of urban residents (Y) as income. The main index for measuring stock market
changes are Shanghai (Shenzhen) stock index, total stock market value, and circulation market value,
etc. This paper chooses the closing stock price (SP) of Shanghai stock comprehensive index to represent
the change of stock wealth. In considering that REP can better represent increase (decrease) in real
estate wealth, the real estate change is represented by national real estate price (REP) not real estate
fixed assets investment.
Because the development time of stock market in China is relatively short, and the announcement
of real estate data is relatively late, choosing annual data will result in a too small number of observed
variables, which will reduce the validity of methods used. So this paper adopts the quarterly data of
index in order to make the research deep and extensive. The time span is from first quarter in 1996 to
second quarter in 2006. Among the data, the total commodity (TC) data of social consumer goods are
mainly from China macroeconomic database and have gone through simple calculation; the urban
household dispensable income (Y) data are from The people’s bank of China quarterly statistical
bulletin; the closing price of Shanghai stock comprehensive index are got from China financial
statistical yearbooks from 1997 to 2006, data of 2006 are from The people’s bank of China quarterly
statistical bulletin; national real estate price index (REP) are mainly obtained from China
macroeconomic database and China real estate statistical yearbooks. Because our country do not
announce quarterly real estate price index data until the year 1998, after careful consideration, for the
real estate price index data in 1996 and 1997, we draw references from data of 1998 in the same quarter,
and do calculations based on the same base according to the fixed assets investment index in 1996, 1997
and 1998.
The total commodity (TC) of social consumer goods and urban household dispensable income (Y)
sequence show significant quarterly fluctuation, and we adjust it by adopting X11 method
(multiplication model) and the adjusted sequence numbers are recorded as TCSA and YSA respectively.
The change in natural logarithmic of the data does not alter its former cointegration relation; besides, it
makes it have linear tendency and eliminates the existing heteroskedasticity in the time series. We make
natural logarithmic of the selected variable serial, and the changed serial are recorded as LTCSA, LSPA
and LREP respectively.
2.2 Unit root test
In practice, economic and financial data are mostly nonstationary time series, and before a specific
empirical equation estimation and relevant test, we generally need to do unit root test to ascertain
whether the selected variables has time tendency. If the data are nonstationary time series, then we need
to apply cointegration analysis method. This paper adopts the often-used ADF test and all the operations
are finished in Eviews5.0. The test results are as follows in Table 1:
Table 1 Unit root test result
Variable
ADF value
1% critical value
5% critical value
LTCSA
1.629188
-4.2165
-3.5312
LYSA
-1.673232
-4.2023
-3.5247
LSP
-2.437255
-4.2092
-3.5279
LREP
-1.875100
-4.2242
-3.5348
D LTCSA
-4.154349
-4.2165
-3.5312
D LYSA
-4.827058
-3.6171
-2.9422
D LSP
-3.080763
-2.6261
-1.9501
D LREP
-4.722643
-3.6067
-2.9378
Note: D reprents first difference of variables; critical value is Mackinnon value.
Result
Nonstationary
Nonstationary
Nonstationary
Nonstationary
Stationary
Stationary
Stationary
Stationary
、
、
From the test result of Table 1, we can see that under an significance level of 1%, LTCSA LYSA
LSP and LREP can not deny null hypothesis, that is, they are all nonstationary time series, but in their
first difference sequence, expect that D LTCSA can only deny null hypothesis under an significance
level of 5%, D LYSA D LSP and D LREP can deny null hypothesis under an significance level of 1%.
So we think that LTCSA LYSA LSP and LREP are all first order integration series, that is I 1 .
、
、
、
（）
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2.3 Cointegration test
If two (or more) time series are nonstationary, while their certain linear combination is stationary,
we say that among them there exists cointegration relations, and it reflects long-run equilibrium
relations among variables. This paper adopts Johansen maximum likelihood method of estimation to do
cointegration test with variables. We first define VAR (Vector Autoregression) model and according to
AIC and SC we find that the optimal lag length of VAR is seven, and all kinds of index show that the
model is benign. See Table 2 for test results:
Table 2 Johansen cointegration test result
Likelihood
0.05
0.01
Hypothesized
Ratio
Critical Value
Critical Value
No. of CE(s)
0.954618
165.4676
47.21
54.46
None **
0.615933
57.22541
29.68
35.65
At most 1 **
0.472638
23.73254
15.41
20.04
At most 2 **
0.037484
1.337171
3.76
6.65
At most 3
Note:Trace test indicates 3 cointegrating eqn(s) at the 0.05 level ** denotes rejection of the hypothesis at the
0.05 level.
Eigenvalue
；
The result in Table 2 shows that: there are three cointegration equations among the total commodity
of social consumer goods, the urban household dispensable income, the closing price of Shanghai stock
comprehensive index and the real estate price index under 5% significance level. But this paper is more
concerned with the first cointegration equation that contains all variables, and the standardized
cointegration equation form is (numerical value in the brackets is inch standard error):
VECM=LTCSA-0.815724LYSA-0.137516LSP-1.357116LREP+5.058044 (1)
(0.00441)
(0.00139)
(0.00966)
From equation (1) we can see that the MPC of the urban household dispensable income is 0.815724,
and the t statistic is very significant, which means that between the urban household dispensable income
and consumption there is a long-run stationary equilibrium change relation. In the equation, the
coefficient of closing price of Shanghai stock comprehensive index is 0.137516, and the t statistic is also
very significant. It means that after 1996, due to the initial development of stock market in China, the
wealth effect of stock assets emerges. Although it is relatively small, Chinese stock market has
influenced consumption in recent ten years, despite the influence is feeble. This is consistent with the
conclusions of certain scholars. The coefficient of real estate price index is 1.357116 and the t statistic is
very significant, which shows that real estate industry has significant positive wealth effect of
consumption demand, and in view of the long run the coefficient of impact is relatively big.
2.4 Granger causality test
Granger causality test is actually to test whether the lagged variable of a variable can be introduced
into other variable equations, and if one variable gets lagged influence from other variables, we call that
they have Granger causality relation. This paper mainly considers the lagged influence of stock, real
estate and income on consumption. The test result is listed in Table 3:
Table 3 Granger causality test result
Null Hypothesis
F-Statistic
Probability
LYSA does not Granger Cause LTCSA
3.49175
0.02389
LTCSA does not Granger Cause LYSA
5.17285
0.01076
LSP does not Granger Cause LTCSA
1.77603
0.18423
LTCSA does not Granger Cause LSP
0.39123
0.67915
LREP does not Granger Cause LTCSA
5.57781
0.00789
LTCSA does not Granger Cause LREP
4.70355
0.01552
Result
Refuse original hypothesis
Refuse original hypothesis
Accept original hypothesis
Accept original hypothesis
Refuse original hypothesis
Refuse original hypothesis
Table 3 shows that between consumption and income there is a causality relation, that is, increasing
in income will drive increase in consumption, and increasing in consumption will promote economic
growth and finally promote income increase. This is the benign circulation of economic development.
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There is no Granger causality relation between stock index and consumption, but the probability of
refusing null hypothesis and making mistakes is only 0.18423, which means that there probably exists a
weak link between the two in actual economic operation, but it is not adequate to say that there is
Granger causality relation. This is in accordance with the conclusion that “Chinese stock market has
influenced consumption in recent ten years, though the influence is feeble” in the cointegration test.
Reflecting upon the test result of real estate and consumption, there is significant Granger causality
relation between them, and the relation is very significant, which means that the wealth effect of
Chinese real estate industry is relatively significant, in compliance with the cointegration test results and
research conclusions of some scholars.
2.5 Vector error correction model
Cointegration equation reflects the long-run equilibrium relation between variables, and VEC
(Vector Error Correction Model) can reflect that when the equilibrium relation between variables departs
from long-run equilibrium state, it will be adjusted to the adjusting speed in equilibrium state. Because
we have proved that there is cointegration relation between the selected variables, then we can utilize
VEC to watch short-run departure equilibrium. According to the VAR model lagged stage established in
cointegration test, we are sure that the VEC lagged stage is six, and the analysis results are in table 4:
variable
coefficient
standard deviation
t statistic
variable
coefficient
standard deviation
t statistic
variable
coefficient
standard deviation
t statistic
variable
coefficient
standard deviation
t statistic
D(LTCSA(-1))
0.879318
(0.30739)
[2.86059]
D(LYSA(-1))
1.068637
(0.40510)
[2.63798]
D(LSP(-1))
-0.094234
(0.06376)
[-1.47794]
D(LREP(-1))
1.523297
(0.83923)
[1.81512]
Table 4 VEC analysis results
D(LTCSA(-2)) D(LTCSA(-3)) D(LTCSA(-4))
1.688125
1.782676
1.407313
(0.44892)
(0.56552)
(0.48274)
[3.76039]
[3.15225]
[2.91524]
D(LYSA(-2))
D(LYSA(-3))
D(LYSA(-4))
0.537715
0.529758
0.934666
(0.33808)
(0.16887)
(0.25369)
[1.59051]
[3.13705]
[3.68422]
D(LSP(-2))
D(LSP(-3))
D(LSP(-4))
-0.013838
0.103075
0.146606
(0.04549)
(0.02852)
(0.04405)
[-0.30418]
[ 3.61442]
[ 3.32808]
D(LREP(-2))
D(LREP(-3))
D(LREP(-4))
0.956802
0.628001
0.284135
(0.55949)
(0.37364)
(0.28246)
[1.71015]
[1.68076]
[1.00593]
D(LTCSA(-5))
0.666998
(0.39705)
[1.67989]
D(LYSA(-5))
0.888290
(0.35580)
[2.49657]
D(LSP(-5))
0.151582
(0.04732)
[ 3.20302]
D(LREP(-5))
0.326699
(0.23978)
[1.36248]
D(LTCSA(-6))
0.187764
(0.21285)
[0.88213]
D(LYSA(-6))
0.360475
(0.25231)
[1.42871]
D(LSP(-6))
0.057876
(0.03902)
[ 1.48316]
D(LREP(-6))
0.020356
(0.27031)
[0.07531]
Result in table 4 shows that in the current stage of China, income is still the main reason for
determining consumption expenditure. In the first, third, fourth and fifth lagged period, the coefficient
reaches its lowest point of 0.53, and the t statistics are also very significant. In the second and sixth
lagged period the coefficient of estimation are negative, but the t statistic are not significant, in the third,
fourth and fifth quarter of lagged period the coefficient are stationary and remain above 0.10 and the
statistic are also significant, which mean that with increase in wealth, investors have the tendency of
using stock market income as permanent income, and subsequently the consumption expenditure desire
is strengthened. This is in agreement with permanent income hypothesis. The fluctuation in the sixth
stage of the lagged period can be explained by unstable stock market in China and over fluctuation. In
general, the wealth effect of stock assets on consumption expenditure in China is weak. Real estate
assets have relatively stable effect on consumption expenditure. But after the fourth stage of the lagged
period, there are signs showing the effect tending to be smaller and the statistic is also insignificant.
According to the analysis of the real development conditions on Chinese real estate market, it can be
regarded that it is influenced by real estate bubble which reduces the income expectations of investors
and accordingly the consumption expenditure decreases. But generally speaking, the wealth effect of
real estate on consumption expenditure is rather significant.
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3 Conclusions
3.1 The wealth effect of Chinese stock market is not significant
We can see that since 1996 the wealth effect of stock market has been relatively weak and marginal
propensity of consumption is basically around 0.10 through cointegration test and Vector Error
Correction model results. Considering the actual development on Chinese stock market, we think that
the reasons for weak effect of stock market are:
(1) In China the operation of wealth effect is basically restricted by the small stock market scale.
There are two levels of meanings about stock market scale: one is the depth of stock market, which is
denoted by stock market value/GDP; the other one is the width of stock market, which is measured by
the numbers of investors/whole households or families holding stock wealth/social total families.
Changes on stock market will have limited impact on family wealth without adequate market scale, and
there will be no mention of wealth effect. Table 5 lists the proportion of stock market value to GDP in
China and America since 1996, and we can clearly see from it that there is a relatively big gap between
the stock scale in China and America. Too small proportion of stock market value to GDP seriously
limits the operation of the wealth effect of stock market.
Table 5 comparison of proportion of stock market value to GDP in China and America (%)
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
country
China
14.50
23.44
24.52
31.82
53.79
45.37
37.43
36.38
27.14
17.70
America
109.5
137.3
154.6
181.8
n/a
288.5
243.3
142.0
n/a
n/a
Notes: Chinese data is from the annual China Financial Almanac, and America data are from International
Statistics Almanac.
(2) The operation of stock market in China is not stable and there is big wave. Mainly represented
by high stock transfer rate there is over speculation on Chinese stock market, see table 6. Continuous
fluctuations on stock market are not good for the persistent prosperity of stock market and the
expectations of investors over stock proceeds are not clear. Occasional proceeds can only be treated as
temporary income under this circumstance. This kind of proceeds will not have fixed relation with
consumption and the impact on consumption is only temporary according to permanent income theory.
Furthermore, stock assets are mainly manifested as the distribution of wealth among each investor under
the condition of big fluctuation on stock market. The total sum does not increase, and the consumption
increase of some investors is at the expense of decrease of consumption of other investors.
Table 6 Change of stock transfer rate (taking Shanghai as an example)
year
1996
1997
1998
1999
2000
2001
2002
2003
2004
transfer rate
590.78
701.81
453.63
471.46
492.87
269.33
214.00
250.75
288.71
Notes: the source is China Financial Almanac and China Securities and Option Statistics Almanac.
2005
274.37
(3) The quality of public companies is generally not high and the stock market is not standardized.
The basis of virtual economy is entity economy. Virtual economy can not develop well without the
growth of entity economy and the excellent performance support of public companies. Chinese stock
market is influenced by such factors such as policy, mechanism and administration factors, etc; and the
market operation is not standardized. What’s worse, the overall quality of public companies is not high,
so stock market has no support from excellent entity economy, which results that stock market proceeds
can not satisfy expectations of persistent income. This is the deep and vital reason for weak wealth effect
of Chinese stock market.
This paper holds the opinion that we should construct a stable mechanism in China to reduce the
policy fluctuation on stock market and attract investors to strengthen enduring expectations about stock
wealth proceeds concerning the weak wealth effect of Chinese stock market. We should guard the pass
strictly in order to enhance the quality of public companies and improve the basis of stock market
development; widen stock market scale step by step to create fundamental conditions for the exertion of
wealth effect; build up the concept of “promote economic growth through consumption in order to
determine stock market wealth” to support the development of stock market and exert its functions in
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resource distribution, fluid creation, and information transfer. But we should not hope that it will
stimulate consumption and overly emphasize the wealth effect of stock market. Instead, we should be
devoted to promoting benign cycle between stock market and consumption, that is, stimulating
economic growth through consumption, economic growth driving the increase of stock market wealth,
increase on stock market wealth further driving consumption expenditure and then economic growth.
3.2 There exists significant wealth effect of Chinese real estate market
Compared with stock market our test results show that changes in real estate price have a bigger
impact on household consumption, and the wealth effect of real estate market is relatively significant,
which accord with the opinions of home and abroad scholars studying the wealth effect of real estate
market. In the cointegration equation, with 1% increase on real estate market wealth, there will be
1.36% increase in consumption expenditure. This means that the contribution on Chinese real estate
market to household’s consumption is big and it drives increase in consumption demand. But we should
see that there is much bubble on Chinese real estate market. There’re some reasons that lead to overheat
increase on real estate market price such as low interest monetary policy in China, backward financial
market development, relatively few financial products, narrow investment channels and continuous
downward stock market. Many consumers enter into real estate market out of the purpose of investment
and speculation. On one hand, it bids up real estate price, and on the other hand it brings about
substitution effects which partly counteract wealth effect which can be seen from abnormal phenomenon
in the VEC sixth lagged stage. At the same time of focusing on the wealth effect of real estate market,
we must have a clear recognition about the abnormal prosperity or even bubble on real estate market.
We should moderately develop housing consumption credit to promote stable growth in housing market;
make housing assets become securitized and strengthen the fluidity and profitability of real estate wealth;
at the same time establish reasonable housing price early-warning mechanism to prevent and control
harm and risks brought about by assets price bubble. We will ensure the continuous and stable
prosperity on real estate market and make it better exert wealth effect by taking these measures.
3.3 Income is still the main reason for determining consumption expenditure
The test results show us that the main factor determining consumption expenditure is still
dispensable income. The essential ways to stimulate consumption increase in China are promoting
increase of household income and stabilizing income expectations. Now our country is still in the
economic transferring stage and economic reform is in a key period. A serial of areas such as reform in
state-owned enterprises, medical insurance, housing, education system, and pension plans are all faced
with big difficulty. Because of unclearness about reform expectations, it is inevitable for residents to
show strong time preferences, and even when the nominal wealth increases, they still do not increase
consumption, which prevent the smooth operation of the wealth effect transmission channel and the
increase in wealth brought about by financial assets value rise will not result in correspondent
consumption increase.
In future, we should establish mechanism for stabilizing household income increase as soon as
possible to solve the problem of slow increase in household income, increase government transfer
payment strength, enhance the standard of “three guarantee lines”, improve income conditions of people
with low income, adjust household income gap, and raise household consumption level. Moreover, more
efforts should be made to promote social insurance system construction and stabilize household social
expectations; solve the problem of employment and unemployment of work force and re-employment of
people without jobs and stabilize the fundamentals of household income expectations.
4 Carry-over questions
In the process of studying wealth effect, the author think there is a question to be worth discussing
very much, namely at the beginning of the second half of the year 2006 the Market trend of the Chinese
stock market which continue to rise has created a problem that the wealth effect of stock market become
more remarkably. If we want to study this question, firstly I think I need to introduce two concepts the
，
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investment effect is the effect that stock price rise and the stock market scale expand, causes the stock
market's financing from enterprise increase, then stimulates the enterprise to invest, impels the economy
growth. This kind of effect generally has two aspects to display: accelerating the transformation from
folk deposit to the long term capital and guiding the capital diversion to the good development potential
industry. The substitution effect refers to that in the stage of the stock price rising persistently, the fund
possibly used to expend essentially enter into the stock market to get arbitrage in order to gain the stock
market income, causes the expenditure disbursement in the certain degree not to rise instead to fall. This
kind of effect frequently appears and partially counterbalances the effect of wealth effect in the initial
development period of stock market.
This paper believes that, looking from the short-term, the insane rise of the stock market in 2006
cannot cause the distinct enhancement of the wealth effect of stock market, on the contrary, more
possibly it has brought the investment effect and the substitution effect (maybe seen from that many
inhabitants raise money even apply loan in order to enter into stock market to get arbitrage), the wealth
effect possibly tends to reduce due to this; but looking from the long-term, the stock market rise reflect
the good development tendency of Chinese macroscopic economy movement, the exertion of the
investment effect can powerfully promote the national economy stable growth. Following there must be
unceasing expansion of the stock market scale, the virtual economic and the entitative economic basis
will form a more reasonable disposition, and promotes and develops mutually. The wealth effect of
Chinese stock market will change remarkably more and more.
This is the carry-over question of this paper. At present I have not collected the correlation data to
do empirical study, so later it needs to be studied further and thoroughly.
References
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[3]Edited by John Eatwell, Murray Milgate and Peter Newman. The new palgrave: a dictionary of economics,
volume 4, Q-Z. Economic science press. 1996:973-975.
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