Download Confucianism, Social Norms and Household Saving Rates in China

 1 Confucianism, Social Norms and Household Saving Rates in China
Yvonne Jie Chen, National University of Singapore1
Zhiwu Chen, Yale School of Management2
Shijun He, Peking University3
Feb 25th, 2014
ABSTRACT
We study the effect of (declining) Confucian social norms on human capital
investment and saving rates in China. In our simple two-period model, parents have the
option to invest in both a risk-free asset and the human capital of their child. We assume that
social norms, and hence enforcement mechanisms, for supporting old-age parents may differ
in each region and that these cultural norms for acceptable filial piety determine the
probability of non-performance by children on their repayment obligations to parents and
hence the variation of return that parents can expect to receive from investing in children.
Modeling default by children as a function of the prevailing social norms gives us the
flexibility to study the impact of the declining Confucian influence on China’s
consumption-saving trends. Based on our large survey data across 11 provinces, this paper
adds to the current literature in several ways. First, we provide evidence supporting the key
assumption in the life-cycle hypothesis - that parents do view their children, especially sons,
as a source of retirement income. Thus, parents’ investment in children’s human capital is not
altruistic neither are intergenerational transfers from adult children to old-age parents.
Second, we offer an alternative explanation for the high household savings in China. That is,
in addition to the One Child Policy- and the gender imbalance-induced pressure to save more
(Wei and Zhang, 2011), the lack of financial development and the declining influence of
Confucianism are also significant contributors to China’s ever-growing saving rates.
1
Contact: [email protected]
2
Contact: [email protected]
3
Contact: [email protected] 1 1
2 Introduction
Household saving rates in China have been growing fast over the past three decades.
Hypotheses have been proposed to explain this as well as the changing-shaped age profile of
savings. Based on the life-cycle hypothesis framework, Modigliani and Cao (2004) point out
that the increased employment-to-minor ratio as a result of the post-1979 One Child Policy is
a main contributor to the increasing saving rates. This effect of the One Child Policy arises
due to both the “fewer mouths to feed” and the cultural reason that Chinese families view
children as a substitute for life-cycle saving. Empirically, Banerjee et. al. (2010) show that
families with sons tend to save less than those with only daughters, a finding that’s consistent
with the life-cycle hypothesis and in line with the Confucian tradition in which adult sons
have more obligations to care for parents.
Intergenerational transfers from adult children to elderly parents are common and
widely documented in China and other developing countries (Oliveira, 2013). However, their
motives and working mechanisms are still short of clear understanding. When Chinese
household savings are studied, it is usually assumed that parents view children as a form of
investment for old-age insurance and future risk events. Parents decide how much to invest in
children’s human capital based on the perceived return from such investments, while children
will determine how much to repay their elderly parents based on the human capital
investment they received while young (Ge et. al., 2012; Choukhmane et.al, 2013). One piece
that is missing from such economic models is whether the enforcement mechanisms needed
for such intra-family risk-sharing arrangements between parents and children are reliably
provided. If not, the implicit intertemporal financial exchange may not be enforceable
between parents and children. Previous research suggests that the sense of guilt and explicit
sanctions against children who ignore such obligations function as mechanisms through
which the intra-family exchange is made whole (Cox 1998). But, existing studies have
overlooked the impact of the still prevalent but weakening Confucian social norms on saving
behavior in China. After all, for a self-interested adult, she will always be evaluating the costs
and benefits of honoring her obligations to her old parents versus not. As the prevailing social
norms change, the optimal decision can be for her to default on the children-to-parents
repayment obligations.
In this paper, we study the effect of Confucian social norms on human capital
investment and saving rates. We build a simple two-period model in which parents have the
option to invest in both a risk-free asset and the human capital of their child. We assume that
2 3 social norms, and hence enforcement mechanisms, for supporting old-age parents may differ
in each region and that these cultural norms for acceptable filial piety determine the
probability of non-performance by children on their repayment obligations to parents and
hence the variation of return that parents can expect to receive from investing in children.
Modeling default by children as a function of the prevailing social norms gives us the
flexibility to study the impact of the declining Confucian influence on China’s
consumption-saving trends.
This paper adds to the current literature in several ways. First, we provide direct
evidence supporting the key assumption in the life-cycle hypothesis - that parents do view
their children, especially sons, as a source of retirement income. Our survey data thus show
that parents’ investment in children’s human capital is not altruistic neither are
intergenerational transfers from adult children to old-age parents. Second, we offer an
alternative explanation for the high household savings in China. That is, in addition to the
One Child Policy- and the gender imbalance-induced pressure to save more, the lack of
financial development and the declining influence of Confucianism are also significant
contributors to China’s ever-increasing household saving rates. When external financial
products such as retirement funds and insurance products are not richly available, individuals
have to find other ways to hedge future risks and uncertainties. Traditionally, the main
reliable way was to have more children, especially more sons, for old age and sickness
insurance. But, the One Child Policy since 1979 narrowed this option to one. In addition, the
declining influence of Confucianism, especially in cities, and the increased population
mobility across regions have both increased the non-performance rate of children on their
obligations to parents and hence made children unreliable investment instruments. Filial piety
is no longer a guaranteed value shared by younger generations. As a result, young and
mid-aged parents have to save more than prior generations, even if they have a son.
Our research is based on survey data collected from the 2011 Finance and Society
Survey conducted by a team at Yale School of Management and the Tsinghua University
Center for Market and Society. The survey was funded by the Citi Foundation, covering nine
provinces in China -- Zhejiang, Jiangsu, Liaoning, Ningxia, Xinjiang, Sichuan, Guangxi,
Guangdong and Hunan -- and two cosmopolitan cities -- Beijing and Shanghai.
A crucial innovation in our research is the construction of an Old-Age Support
Perception Index (henceforth the perception index), which is the percentage of respondents in
a given city or town that choose “For old age support” as an answer to the survey question
3 4 “Why do you want to have children?”. This index captures at least two elements about the
local region’s values. First, it indicates the degree of Confucian influence in the local culture
and acceptable social norms. In this sense, the higher the perception index, the more reliable
the return from investing in children and hence the less likely for children to default on their
repayment obligations to parents in the future. That is, a high perception index value implies
a low default probability on children-to-parents obligations. If this is the case, we expect
parents with a son or sons to save less in regions with a high perception index than in regions
with a low perception index. Second, the perception index may measure the extent of “need”
for children to be a reliable investment instrument for old age because other alternatives such
as financial products are not available or reliable. If this is the case, a high perception index
city may endogenously develop a culture that is more Confucian and emphasizes filial piety
more heavily, serving to reduce the default probability of the implicit financial contract
between parents and children. Thus, we interpret the perception index as measuring the
reliability of the implicit intra-family financial contract in a given community.
Using our unique data set, we investigate how saving rates are affected by Confucian
social norms or by the declining trend thereof. We focus on three questions. First, do
households living in regions with a high perception index save less? Second, do households
in such regions invest more in children’s human capital? Third, do parents in such regions
receive more intergenerational transfers from their adult children? Our results indicate that
for households with a son, the saving rate is negatively associated with the region’s
perception index: other things equal, families with a son save less in regions with stronger
Confucian influence than in regions with less Confucian influence. However, the negative
correlation is not significant for households with daughters. Overall, families invest more in
children’s human capital if they live in a strongly Confucian region, regardless of the gender
of the family’s child. Using data on intergenerational transfers, we also find that sons from
regions with a higher perception index do provide more monetary support to their elderly
parents. This is possibly evidence that the high prevalence of Confucianism may be a result
of strong financial needs by parents to rely on their children for old age, implying the
endogeneity of culture.
Our survey data further show that the bigger the city, the lower the old-age support
perception index and the less influence of Confucianism. Furthermore, the trend is for
Confucian filial piety to continue to decline in influence. This trend means that as time goes
by, even parents with sons will have to save more than prior generations, in anticipation that
their implicit financial contract with children will be less likely to be performed. Therefore,
4 5 Chinese household savings have been on the rise partly due to the declining influence of
Confucianism.
The remainder of the paper is organized as follows. We provide a literature review on
saving rates and Confucian social norms in section 2. In section 3, a simple two-period model
is presented and testable predictions are derived. In section 4, we discuss the data and
preliminary analyses. Empirical results are presented in sections 5 through 8. Concluding
remarks are in section 9.
2
2.1
Literature Review
High Saving Rates in Developing Countries
Household savings have increased significantly over the past three decades in China.
Rural household saving rates went from 15% to 32%, while urban saving rates went from
15% to 28%.4This dramatic trend has remained a puzzle for economists (Kraay, 2000;
Chamon and Prasad, 2008). Many theories have been proposed to explain the sharp change in
Chinese household saving behavior. Modigliani and Cao (2004) offer two key insights from
the life-cycle theory of savings. First, the aggregate saving rate is a function of the country’s
long-term income growth. As China’s growth trend continues to be strong, Chinese
households are incentivized to save more in order to take advantage of long-term growth.
Second, there is a causal relationship between demographic changes and aggregate saving
rates. Many empirical studies have attempted to estimate the impact of demographic structure
on savings. Using the One Child Policy as an instrument for fertility, Banerjee et. al. (2010)
find that the number of children is negatively correlated with a household’s saving rate. The
effect is more profound for households with boys. However, most of these studies suffer from
the common weak-instrument problem. While the national saving rate is associated with the
age composition of its population, household saving rates are determined by each
household’s lifetime utility maximization process, together with other household economic
matters including fertility and human capital investment decisions (Becker, 1973; Schultz,
2007). Unraveling the causal effect of demographic structure on saving behavior is hence
challenging. For example, using provincial data and a dynamic panel analysis, Horioka (2007)
does not find the age structure to have an impact on household saving rates.
Wei and Zhang (2011) propose that the high saving rate is driven by gender
imbalance. Using both census and household survey data, they find that when the
4
China Statistical Year Books of various years.
5 6 male/female ratio is abnormally high, parents have to save more in order to increase their
son’s competitiveness in the marriage market. In a recent paper, Ge et. Al. (2012) use a
three-period overlapping-generations model to show the effect of the One Child Policy on
saving rates. They demonstrate that older households save more for old-age security reasons,
while middle-age households save more due to the decreased burden of child bearing.
2.2
The Role of Social Norms on Saving
Existing theories are compelling and have helped us understand the drivers of
increasingly higher saving rates in China. But, these studies have taken the cultural and social
norms in China as a given that does not change. The reality is that social norms have been
endogenously evolving in response to changes in the social, cultural and economic conditions
of China. Such changes in social norms should impact the reliability of intra-family
intertemporal risk-sharing arrangements, which in turn affects the saving behavior even for
families with sons.
Traditionally, households in developing countries have relied heavily on
intergeneration transfers from adult children to parents as old-age insurance. The
old-age-security hypothesis dates back at least to Leibenstein (1957), in which parents view
children as an investment/insurance asset. This view is supported by household surveys of
developing countries where parents typically indicate old-age security as the key motive for
having children (Choukhmane et.al, 2013).
In the classic Becker model, however, intra-family transfers are assumed to be
altruistic with the family continuing through an infinite sequence of dynasties. In this setting,
the current parents are to make their consumption-saving-investment decisions to maximize
the total household utility of consumption not only of the current generation but also of their
children’s and children’s children’s generations and so on. The altruistic dynastic-household
model focuses on transfers from parents to future generations, whereas the old-age-security
hypothesis focuses on the repayment obligations of children to parents and treats children as
personalized instrument of intertemporal risk hedging. The latter hypothesis is supported by
evidence and practice in many countries of adult children having to repay their elderly
parents (Cox, 1998).
For children to be an acceptable instrument of insurance and risk-hedging, there have
to be reliable institutions or social norms that serve to minimize the default probability of the
implicit intra-family intertemporal contract and to ensure compliance by the children. For an
6 7 egoistic adult, he will evaluate the costs and benefits of repaying the obligations and
maintaining membership in the intra-family risk-sharing system, as opposed to defaulting and
exiting the system. Due to the fact that a person cannot choose which family to be born into,
he will choose to stay in the given household system only if the return from intra-family
exchange is higher than the external market rate (Cigno,1992) or if the external financial
markets simply do not exist. As Cigno (1992) argues, a middle-aged person can choose to
default and have no children of his own or stay in the system and have as many children as he
could. Thus, the social norms and the associated penalty functions for defaulting behavior are
key in determining where the optimal cost-and-benefit tradeoff lies.
The issue of compliance is particularly challenging in the Chinese context for two
reasons. First, when the number of children per household is fixed at one under the One Child
Policy, there is no way to increase the risk-hedging effectiveness through having more
children. Even for the sole child a couple can have, there is no certainty for filial piety or
future repayment to parents by the child unless the social norms are extremely constraining
and punitive. Second, in China and many developing countries, financial markets are still
under-developed and unreliable; As a result, intra-family transfer arrangements prevail as a
better insurance option (Cox,1992). Parents will likely continue to mix and optimize over a
portfolio of both financial assets and children (as personalized insurance instruments). But,
whether children continue to represent a more cost-effective and more reliable hedge against
old age and sickness depends on the extent to which the cultural values and social norms can
continue to internalize high enough costs for violating the implicit intra-family financial
contract. Otherwise, if filial piety is no longer a valued and practiced virtue and if financial
markets remain under-developed, parents will have no alternative but save more and consume
less.
In this paper we hypothesize that parents’ expectations of the future return from
investing in children are a function of changing social norms for old-age support. In order for
them to raise children as a way to engage in intra-family financial exchange as opposed to
relying on external markets, they have to believe with enough confidence that their children
will follow through on the implicit contract and repay the investment in the future. In our
model, parents decide on the following: 1) whether or not to invest in their children and 2)
how much to invest.
Traditionally, the implicit intra-family financial contract has been enforced via the
Confucian value system which predominantly emphasizes the children-to-parents obligations
as well as the younger brother’s obligations to elder siblings. These values and the resulting
7 8 behavioral norms are internalized both psychologically and through the male-line property
inheritance system. Psychologically, as Young (2008) points out, social norms function in
such a way that if one deviates from the norms, he not only has to feel a strong sense of guilt
but also faces the prospect of social exclusion and punishment. Economically, Kandori (1992)
argues that social norms come with community-level penalties that apply to those who do not
conform. In addition, as property and land were traditionally owned at the family level
instead of at the individual level and the most senior surviving male was the head of the
family until he dies, adult children were, no matter how old they are, forced to honor
Confucian filial piety norms for fear of losing the expected property or land ownership.
Therefore, several conditions were met to make the intra-family financial contract work:
internalized guilt, economic incentives re-enforced by the land property system, and
population immobility across regions (so as to make the community static).
But, since about three decades ago, industrialization has really picked up speed,
resulting in both fast urbanization and large-scale population mobility to far-away cities.
Coupled with the public ownership system of all land in China, these changes have led to the
fast decline of Confucian influence and its core social norms. As both the psychological and
economic costs of deviations from filial piety norms have declined, the implicit intra-family
financial contract has become less and less enforceable. Even though the continuous decline
of Confucian influence is an overall national trend in China, there are, as our data will show,
vast differences across regions, which offers us enough variations to study the impact of this
trend on both household-level and aggregate saving rates.
3
Social Norms and Saving Behavior: Theory
In this section, we build a two-period model to illustrate how social norms on filial piety
can impact human capital investment and household saving behavior, by extending the model
of Ge et. al. (2012) to our present context. Suppose an agent lives for two periods and she
receives an income of Y1and Y2, respectively in periods 1 and 2. In period 1, the agent decides
on the amount to save, S, and the number of children to have, n. The financial savings are
assumed to earn a risk-free gross return, R(.), over period 2 and the return from investing in
children is g(.) if the children do not default on the implicit financial contract. First, we
consider the case where there is no uncertainty. For simplicity, assume there is no credit
constraint between periods. Suppose the agent wants to maximize the following lifetime
utility:
8 9 (1)
Max u(c1 ) + β Eu(c2 )
s.t. c1 + S = Y1 − qn
c2 = (Y1 − qn − c1 )R + r(γ )g(qn) +Y2
where c1 and c2 are the respective consumption of periods 1 and 2; u(.) the period utility of
consumption; β the subjective discount factor; n the number of children5; q the human
capital investment per child such as wedding gifts and college tuition; and R the gross
risk-free interest. Parents are expected to receive r(γ) g(qn) from their adult children when
they retire in the second period, where γ is the old-age-support perception index in the region
where the agent lives and g(qn) is the promised return function from investing in children
(which is increasing in qn and concave) provided that there is no future default by the
children. As discussed above, the perception index γ captures the local social norms for
supporting elderly parents. In our model, we use r(γ), increasing in γ, to represent the parents’
subjective discount function which is applied to the return, g(qn), from investing in their
children.
Due to the strict birth-control policies in China, households are allowed to have no more
than n children, i.e. n ≤ n . Suppose a corner solution for fertility is obtained and the
household chooses to have n children. With a log utility function, the optimal period-1
consumption is
c1* =
⎤
Y2 r (γ ) g (qn)
1 ⎡
− qn ⎥
⎢Y1 + +
1 + β ⎣
R
R
⎦ (2) Hence the period-1 saving rate is
⎡
⎤
Y1 − c1*
Y2 r (γ ) g (qn)
1
s1 =
= 1−
− qn ⎥ (3) ⎢Y1 + +
Y1
(1 + β )Y1 ⎣
R
R
⎦
In this model, parents are profit-maximizing when they decide how much to invest in
their children. They will keep investing more in children until the marginal return from such
investment equals the marginal cost. Optimal period-1 consumption is increasing, while
optimal saving rate is decreasing, in the prevalence level of Confucian filial piety or the
region’s perception index γ.
5
For simplicity, assume that parents do not derive utility directly from raising a child. 9 10 If we further assume, following the Confucian tradition, that only sons are obligated to
provide old-age support but not daughters, then we can rewrite the return function from
raising children as
()
( ) , where
z[1son ]r γ g qn
z[1son ] is the characteristic function that equals
to 1 if a household has a son and 0 otherwise. For households with only daughters, we shall
not expect to see a correlation between social norms γ and optimal saving rate because
investing in daughters is not profitable. A resulting prediction is that households with a son
will save less than those with only daughters. For households with sons, the parents’
profit-maximizing human-capital investment in children is determined by
max q
()
(5)
( ) − qn
z[1son ]r γ g qn
R
Let the optimal investment level derived from the above equation be q* (γ ,n,R ) . Then
the marginal effect of social norms
on the period-1 saving rate can be written as
(
+
" '
'
'%
∂s1
1 * z[1son ]$#r γ g qn +r(γ )g (qn)qγ '& ' =-nqγ *
∂γ
Y1 (1+β ) *
R
)
,
()
( )
(6)
Rewriting (6), we get
z[1son ]!#r ' γ g qn +r(γ )g ' (qn)qγ' $&
∂s1
1
1
"
%
=+
nqγ'
∂γ
Y1 (1+β )
R
Y1 (1+β )
()
( )
The first term in the above equation is the income effect, and the second term the substitution
effect. Note that qγ' > 0 due to the concavity of g(.). This means that the higher the
perception index or the more prevalent the Confucian values, the more the parents are willing
to invest in children. However, an improvement in social norms γ has two effects on the
household saving rates. The income effect leads parents to save less because they expect to
receive more transfers from their children in period 2, but the substitution effect leads them to
save more because investment in children is now more profitable and hence they will
sacrifice some current consumption to increase their future consumption.
From equation (6) we know that at q=q*, we have
( )
z[1son ]r γ g ' qn n
()
R
=n
10 11 (7)
( )
⇒ z[1son ]r γ g ' qn =R
()
Substituting equation (7) into equation (6), we obtain
(8)
( )
z[1son ]r ' γ g qn
∂s1
1
=∂γ Y1 (1+β )
R
()
Equation (8) captures the aggregate effect of γ on saving decisions. The sign of (8) is
always negative, which means the income effect of rising Confucian influence outweighs its
substitution effect. Thus, households with sons will save less and consume more as the social
norms become more Confucian and the return from investing in children is hence more
reliable. But, households with only daughters will not benefit from a more Confucian cultural
environment. Therefore, households with sons will save less in the first period compared to
households with daughters. It is also clear from (8) that when the risk-free interest rate R
offered by bank saving accounts goes higher, the prevailing social norms being Confucian
will have lower impact on household savings. At the extreme when R is infinitely high,
Confucian values will have no effect on household savings.
We hence have the following testable predictions from this model without uncertainty:
•
The social norms or perception index shall have no effect on the optimal saving rate
of households with only daughters but a negative effect on that of households with a
son. Everything else equal, households with a son will save less than households with
only daughters.
•
Other things equal, households with a son will save less in region A than in region B,
if region A is more Confucian in values and social norms.
Next, we assume that human capital investment return is risky, i.e., g(.) is a random
variable. This certainly affects parents’ decisions. Due to the One Child Policy, we assume
that the number of children in each household is exogenously fixed at one. Assume the gross
1
return for every dollar of human capital investment on children is denoted by Ri = R + ε ,
γ
where ε is a random variable with mean 0 and variance 1 R > R and is the expected gross
return from children. Note that in regions where the social norms are less Confucian (i.e., a
low value for γ), the risk of human capital investing in children will be higher as the children
are more likely to default in future repayment obligations.
11 12 The maximization problem for the parents then becomes:
Max u (c1 ) + β Eu (c2 )
(9) s.t. c1 = (1 − s)Y1
c2 = sY1 (θ R + (1 − θ ) Ri ) + Y2 = (Y1 − c1 )(θ R + (1 − θ ) Ri ) + Y2
where θ is the fraction of period-1 savings to be invested in the risk-free asset. The first-order
conditions for the above yield
u ' (c1 ) − β E[(θ R + (1 − θ ) Ri )u ' ((Y1 − c1 )(θ R + (1 − θ ) Ri ) + Y2 )] = 0
and the second-order condition yields
H = u " (c1 ) + β E[(θ R + (1 − θ ) Ri ) 2 u " ((Y1 − c1 )(θ R + (1 − θ ) Ri ) + Y2 )] < 0
Assuming a log utility, we arrive at the following equation:
⎡
⎤
(θ R + (1 − θ ) Ri )
1
= β E ⎢
⎥
c1
⎣ (Y1 − c1 )(θ R + (1 − θ ) Ri ) + Y2 ⎦
The effect of γ on human capital investment and saving rates can be derived as follows.
From the first-order conditions, we know that c1 is a function of θ , and
∂c1 E[{u ' (c2 ) + u" (c2 )(Y1 − c1 )(θ R + (1 − θ ) Ri )}( R − Ri )]
=
∂θ
H
Substituting the optimal solution for c1 (θ , γ , β ) into the objective function, we have
V = u(c1 (θ , γ , β )) + β E[u((Y1 − c1 (θ , γ , β ))(θ R + (1 − θ ) Ri ) + Y2 )]
If an interior solution is obtained, then we must have 0 < θ < 1 , which means parents will
invest in both risk-free asset and their child. Then the optimal choice of θ satisfies the
following first-order and second-order conditions:
∂V
= β (Y1 − c1 ) E[u ' (c2 )( R − Ri )] = 0
∂θ
∂c
∂ 2V
D = 2 = − β E[{u ' (c2 ) + u" (c2 )(Y1 − c1 )(θ R + (1 − θ ) Ri )}( R − Ri )] 1 + β (Y1 − c1 ) 2 E[u " (c2 )( R − Ri ) 2 ]
∂θ
∂θ
'
"
2
− β E[{u (c2 ) + u (c2 )(Y1 − c1 )(θ R + (1 − θ ) Ri )}( R − Ri )] + H gβ (Y1 − c1 ) 2 E[u " (c2 )( R − Ri ) 2 ]
=
<0
H
Therefore the optimal portfolio choice satisfies
12 13 *
∂θ
=
∂γ
1
− β (Y1 − c1 ) E[u ' (c2 ) ε ]
γ
D
(10)
<0
See Appendix A for derivation. We have
∂(1 − θ * )
> 0.
∂γ
By equation (10), the optimal investment in children is still increasing as the social
norms γ become more Confucian. It also implies that there exists a lower threshold on γ , say
γ , such that if the social norms fall lower than this, that is, if children become too unreliable
as an investment instrument (i.e., γ is too low), then parents will opt out of investing in their
children’s human capital and put all the savings in the risk-free asset. If and when this
happens, the children will no longer be an investment asset but a pure consumption good as
in the standard Becker model and the parents are purely altruistic.
A mixed portfolio of
both the riskfree asset and children will be optimal only if γ > γ , i.e. 0 < θ < 1 only if γ > γ .
As γ approaches zero, the risk with investing in children’s human capital becomes very
large. In the extreme, parents might choose not to invest in children’s human capital at all and
only hold the riskfree financial asset.
The effect of γ on period-1 consumption is
∂c1*
=
∂γ
−β
⎡ Y ⎤ ∂θ * ⎛
∂θ * ⎡ Y2 ⎤
1 ⎡ Y ⎤ ⎞
E ⎢ 22 ε ⎥
( R − R)
E ⎢ 2 ⎥ + (1 − θ ) 2 E ⎢ 22 ε ⎥ ⎟
⎜
γ ⎣ c2 ⎦ ∂γ ⎜
∂γ ⎣ c2 ⎦
γ
⎣ c2 ⎦ ⎟
+ −β
(11)
⎜
⎟
H
H
⎜⎜
⎟⎟
⎝
⎠
1
⎡ 1 ⎤
∂θ *
Because E ⎢ 2 ε ⎥ < 0 ,
< 0 and H < 0 , the first term in the above equation,
c
∂
γ
⎣ 2 ⎦
−β
⎡ Y ⎤ ∂θ *
E ⎢ 22 ε ⎥
, captures the income effect of an increase in γ. When the social norms
γ ⎣ c2 ⎦ ∂γ
>0
H
1
become more Confucian, the return from investing in children will be less uncertain and
hence the parents are willing to consume more in period 1. As in the certainty model, the first
part of equation (11) is the income effect and it is always greater than zero. The second part is
the substitution effect: as the return uncertainty of human capital investment decreases, the
parents will want to invest more and spend less in period 1. And the substitution effect is
13 14 always less than zero. The sign of the overall effect of γ on period-1 consumption is thus
ambiguous. Therefore, in the presence of uncertainty, the effect of γ on household saving
⎛ Y − c * ⎞
∂ ⎜ 1 1 ⎟
rates, ∂s
Y ⎠ , is also ambiguous.
= ⎝
∂γ
∂γ
Our results indicate that when human capital investment is perceived as a risky asset,
parents in more Confucian regions will invest more in their children than in less Confucian
regions. But the impact of social norms on the optimal saving rate is ambiguous.
For families with daughters, their optimal saving rate under uncertainty is equivalent to
the case when θ = 1 . As
∂c1
θ
< 0 (see appendix B), it means that families with just daughters
will, regardless of the social norm level γ, have the lowest period-1consumption and the
highest saving rate but put all their savings in the risk-free asset and invest nothing in their
daughters’ human capital. This is indeed the common behavior of families for their daughters
in China. As in the model without uncertainty, families with daughters would save more than
those with sons because daughters are not considered an investment for old age and sickness.
4
Data and Construction of the Perception Index
This paper uses the data set from the 2011 Finance and Society Survey conducted by
a team at Yale School of Management and the Tsinghua University Center for Market and
Society and funded by the Citi Foundation. The survey covers nine provinces and two
municipalities, including Zhejiang, Jiangsu, Liaoning, Ningxia, Xinjiang, Sichuan, Guangxi,
Guangdong and Hunan, and Beijing and Shanghai. Within each province, four tiers of
communities are sampled: the provincial capital city, two prefectural cities, three county
towns and three rural villages. The purpose is to understand the impact of financial
development on social structure and cultural values. The questions asked of each respondent
cover seven categories: family values, old-age arrangements, transfers among family
members, access and use of external financial instruments, plus demographic information
such as education, age, income, savings, and siblings.
The complete sample contains responses from 11,170 respondents, approximately
equally distributed across the four tiers of community. Each of the 11 provinces and
municipalities contributes about 1,000 observations, with roughly 250 respondents randomly
14 15 drawn from each of the four tiers within a given province or municipality and subject to the
sample age distribution approximately matching the overall age/gender distribution of China.
The survey is administered by intercept interviews, which may result in sample selection
biases. We will discuss issues with non-random sampling and correction strategies in section
6.
A perception index that measures the local region’s filial piety attitudes is constructed
for each locality based on the following multiple-choice question: "What is the purpose of
having a child?", to which respondents can answer by choosing any number of five choices:
a) to continue the family blood line, b) out of love for children and for personal connections,
c) for old-age insurance, d) because everyone else does it, and e) other reasons.
Two different methods are used to form the perception index. In the first method, we
set the old-age support indicator, Yij, for respondent i in region j to 1 if c) is one of her
choices and 0 otherwise. The perception index for each region j is calculated as follows:
𝐼𝑛𝑑𝑒𝑥! = 100 ×
!
!!! !!"
(12)
!
In the second method, we use principle component analysis (PCA) to combine
information revealed by choices b) and c).
6
Principal component is a linear combination of
the variables that enters the index. Because both choices b) and c) reflect an individual’s
intention to invest or not invest in children for old age support and her expectation about
whether her children should honor the implicit financial contract, the combined value should
better reflect the respondent’s attitudes towards raising children.
Table 1: Perception Index by Region Type
City Type
Municipalities
Provincial
Prefectural
County
Rural
Capital
City
Town
Villages
Perception Index
17.5
22.1
25.8
29.6
48.9
Perception Index 2
-32.8
-22.3
-21.1
-15.1
6.6
Note: Municipalities include Beijing, Shanghai, while provincial capitals include Shenyang, Yinchuan,
Chengdu, Nanning, Changsha, Guangzhou, Nanjing, Hangzhou, and Urumqi. Perception Index for each city
type is calculated using equation (12)
6
Choosing b) means parents consider children as a consumption good and choosing c)
means parents consider children as an investment good, although b) may also be interpreted
as implying children being an investment in future emotional security. 15 16 Table 1 summarizes the average perception index by region or city type respectively
according to equation (12) and the principle-component analysis method. The first row of
Table 1 shows the perception index using Method 1. It is clear that large cosmopolitan
municipalities like Beijing and Shanghai have the lowest perception index of 17.5, being the
least Confucian societies. On average, 17.5% of people living in these mega cities view
children as old-age security investment. Going from the top-tier mega cities to provincial
capital cities, to prefectural cities and then to county towns and rural villages, the perception
index shows a clear rising trend, implying Confucian norms are the most emphasized and
needed in villages for economic security reasons where the perception index has a value of
48.9.
Since external financial products are the most available in the mega cities and the
least available in rural villages, this indicates a strong negative correlation between access to
modern finance and dependence on children for old-age insurance (hence, a negative
correlation between modern finance and prevalence of Confucianism in a society).
Perception Index 2 is constructed using the PCA method. We use the eigenvector from
the biggest eigen-values to combine choices b) and c) into one indicator. The closer to zero
the index is, the more people in a given locality consider children as an investment good
rather than a pure consumption good. The corresponding coefficients for these two choices
are -0.71 and 0.71. Because individuals choosing b) outnumber those choosing c) in most
localities, the average perception index is negative for all top four tiers of region in Table 1,
except rural villages. As shown in Table 1, Perception Index 2 also increases as we go from
mega cities to rural villages. This trend indicates that as we move away from the metropolitan
areas, more people consider their children as an investment good.
Due to concerns of measurement errors and sample selection biases, we only include
localities with more than 80 observations. Following Wei and Zhang (2011), we exclude
families with more than one child, single-parent families as well as families with three
generations living together. Only families with respondents aged between 30 to 45 are
included in our study. Due to concerns of missing values in village surveys, we exclude rural
villagers from our main regressions. In the robustness check section, we will repeat the
regressions with rural village families included and the results will be shown to remain
unchanged.
Following the convention in the literature, we define saving rate as the logarithm of
the income-to-expenditure ratio. In the questionnaire, we ask respondents about annual
income per adult and average monthly consumption per person in the family.
16 Because only
17 nuclear families are included in our regression sample, we multiply the average per-adult
annual income by two to get the annual household income. The average monthly
consumption is multiplied by three and then by twelve months to arrive at the annual
household expenditure.
We use the 2000 China Census Data to construct the local region-level sex ratio,
which is the male/female ratio among children between 0-9 years old as of the year 2000
(who would be between 11 and 20 years old as of 2011).
Summary statistics are presented in Table 2. Three sets of perception index are
reported. Row 1 reports the perception index calculated using equation (12), excluding the
village level observations. The numbers suggest a large variation for the perception index,
ranging between 7.8 and 54.4. Row 2 reports the perception index when the village level
observations are included. Row 3 reports the perception index calculated using the PCA
method.
Table 2 reports the average saving rates respectively for all respondents, for families
with sons, and for families with only daughters. The average saving rate for the full sample is
59%, whereas households with only a daughter save 4% more than those with a son. The
average saving rates for each category are significantly higher than the respective rates in
Wei and Zhang (2011), perhaps due to the difference in sampling time and also in sampling
design (we shall come back to this in section 6).
Rows 8-11 report other characteristics. Education level is re-coded as a binary
characteristic taking a value of 1 if the respondent has finished at least a high school
education. Then, 60% of our participants have a high school diploma, which is consistent
with the population average. However, the fraction of participants with a college degree is
significantly higher than the national average, mainly due to our focused sample being
restricted to the age range of 30-45 years. Risk attitude is measured by the respondent’s
choice between two lotteries. We set a respondent’s risk attitude at 1 if he is risk-loving and 0
otherwise. Information on insurance purchases and pension participation is also collected.
The variable, Insurance, is set to equal 1 if the respondent has voluntarily purchased
commercial insurance policies. Similarly, the variable, Pension, is coded as 1 if the
respondent has public/government pensions. As shown in Table 2, 72% of the respondents
have external insurance policies while 44% have pension plans. In terms of the gender
distribution, 51% of the respondents are male.
17 18 Table 2: Descriptive Statistics
All
Son Family
Obs
Mean
Obs
Panel A: Perception Index and Household Saving Rate
Perception
1530
0.167
826
Index
(0.373)
Perception
Index 2 (PCA)
Saving Rate
1530
0.627
826
(0.652)
Daughter Family
Mean
Obs
Mean
0.207
(0.405)
704
0.119
(0.324)
0.596
(0.637)
704
0.665
(0.668)
37.31
(4.497)
5.491
(5.505)
0.550
(0.498)
0.352
(0.478)
0.721
(0.449)
0.276
(0.447)
0.500
(0.500)
0.512
(0.500)
704
37.40
(4.634)
6.507
(8.721)
0.615
(0.487)
0.374
(0.484)
0.729
(0.445)
0.262
(0.440)
0.511
(0.500)
0.516
(0.500)
Panel B: Respondents’ Demographic Variables
Age
1530
Income (RMB
‘0000)
Education
1531
Risk Attitude
1530
Insurance
1529
Pension
1530
State_emp
1530
Gender
1530
1530
37.35
(4.559)
5.959
(7.183)
0.580
(0.494)
0.362
(0.481)
0.725
(0.447)
0.270
(0.444)
0.505
(0.500) 0.514
(0.500)
826
826
826
826
825
826
826
826
705
704
704
704
704
704
704
Note: Sample of non-village nucleus families with only one child. Respondents’ age between 30 and 45. Saving
Rate is calculated as log(income/expenditure).
Education = 1 if the respondent has completed high school or beyond.
Risk Attitude = 1 if the respondent is risk loving. Risk assessment is based on a survey question that asked
respondents to choose from two lotteries. The first lottery have 100% chance of winning 2000, the second
lottery has 50% of winning 5000 and 50% nothing. Respondents choose the second lottery is classified as risk
loving.
Insurance = 1 if the respondent has purchased commercial insurance.
Pension = 1 if the respondent has purchased pension, either public or private.
Gender = 1 if the respondent is a female.
State_emp = 1 if the respondent works for a public sector or state owned enterprise
18 19 Figure 1: Scatter Plot of Perception Index and Saving Rate
1.5
1
saving
.5
0
0
.5
saving
1
1.5
Left: Binary Perception Index; Right: PCA Perception Index
10
20
30
oldsupport
40
50
-40
-20
oldsupport2
0
20
To provide an intuition for the relationship between aggregate perception index and
saving rate at city level, Figure 1 provides a scatter plot between the two variables. The graph
on the left uses the binary perception index and the graph on the right uses the index
constructed using the principal component analysis. We can see a clear negative relation
between the two variables. This pattern indicates that each locality’s average saving rate
decreases with the locality’s perception index.
The question of whether parents perceive children as a form of investment has been
debated for a long time. Surveys in developing countries sometime have attempted to address
this question and parents often indicate that children are a form of investment (). To our
knowledge, this has not been studied in China. In our survey we ask participants whether they
perceive children as a form of investment. In response, 17.11% of the respondents view
children as a form of financial investment, whereas 82.56% disagree. But, this outcome is
inconsistent with their answers to the question of “Why do you want to have children?” as
summarized in Table 1, where more than 23% of them choose “For old-age insurance” as a
reason. To further understand their views on raising children, we ask them what form of
support they would desire to receive from children when they retire. To this, 26% of the
respondents choose “Nothing” as the answer, 32.2% “Economic support and time”, 39.5%
“They come to visit and spend time with us”, and 1.9% “Just economic support”. This
finding indicates the vast majority have future emotional-support expectations from children,
whereas a minority has mostly or some economic expectations....This
19 20 5
Econometric Analysis
Next, we seek to understand the determinants of household saving rates. To this end, we
rely on the following multivariate regression in which the dependent variable is the saving
rate for household i living in city j:
𝑠𝑎𝑣𝑖𝑛𝑔𝑟𝑎𝑡𝑒!" = 𝛼! + 𝛼! 𝑃𝑒𝑟𝑐𝑒𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥! + 𝛼! ∗ 𝑃𝑒𝑟𝑐𝑒𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥! ∗ 𝑠𝑜𝑛!" + 𝛼! ∗
𝑠𝑜𝑛!" + 𝜃𝑋!" + 𝜀 !"
(13)
Where 𝑃𝑒𝑟𝑐𝑒𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥! is the perception index of city j, measuring the percentage of
respondents in the given city who choose “For old-age insurance” as a reason for having
children, that is, the city’s intensity of Confucian prevalence; 𝑠𝑜𝑛!" equals 1 if household i
has a son and 0 otherwise; and 𝑋!" is a set of individual characteristics of household i living
in city j. It was noted in sections 2 that under Confucian social norms parents expect to
receive more old-age support from sons than daughters. Therefore we include the interaction
term, 𝑃𝑒𝑟𝑐𝑒𝑝𝑡𝑖𝑜𝑛 𝐼𝑛𝑑𝑒𝑥! ∗ 𝑠𝑜𝑛!" , to capture the possible joint effect of a son and the
locality’s Confucian prevalence intensity on savingrate. Given that the perception index
constructed in equation (12) might be endogenous to measurement errors, we performed the
Hausman test to determine the endogeneity of Perception Index and its interaction terms. We
could reject the hypothesis (at a P value of 0.00) that these variables are exogenous7.
It is
therefore necessary to take this into account in the upcoming regression analyses.
To further address this issue, we exploit the exogenous variation of the distance
between the surveyed cities and their provincial capital. We use the distance as an instrument
for Perception Index and its interaction term. This instrumental variable should be correlated
with the perception of raising children for old age support, but uncorrelated with the error
terms in equation (13). The distance to provincial capital is a good proxy for Confucian
influence on social norms as we expect localities closer to the provincial capital to be less
Confucian in terms of social norms and family values. Hence a city’s perception index should
be positively correlated with its distance from the provincial capital. However, the distance
per se should not directly correlate with saving rates after economic conditions and other
household and individual characteristics are controlled for. Results using both the ordinary
least squares (OLS) and the two-stage regressions are reported next.
7
The results are available upon request.
20 5.1
21 The OLS Results
In Table 3, we present the OLS regressions after excluding the highest and lowest 1%
saving rate observations from the sample. The first four columns are regressions using the
simple Perception Index1 and column 5 reports results using the PCA Perception Index 2.
Columns 1 and 3 are based on the baseline specification without controlling for sex ratio,
whereas columns 2 and 4 are specifications in which sex ratio is controlled for. The last three
columns report results with both provincial and city type dummy variables included. All
regressions control for family income, individual characteristics (gender, education, risk
attitude) as well as pension participation and insurance purchase.
The coefficient of Perception Index on household saving rate is positive but not
statistically significant. This shows that the Perception Index variable has no significant
effect on saving decisions for families with only a daughter (i.e., son = 0). For families with a
son, the coefficient of son is negative, meaning that other things equal, families whose single
child is a son save significantly less than those with a daughter. This is in line with our
hypothesis and consistent with the findings by Banerjee et. al. (2010). It also provides
evidence that parents possess different expectations of financial returns from sons than
daughters. The interaction term of son and Perception Index is also negative (though
statistically insignificant except for column 5), meaning that in localities with stronger
Confucian influence, the saving rate differential between families with a son and those with a
daughter will be even bigger than in localities with a lower Perception Index. Thus, stronger
Confucian influence leads son families to save even less than otherwise.
The coefficient signs for sex ratio and the interaction term between sex ratio and son
are all consistent with Wei and Zhang (2011). The interaction term of sex ratio and son is
positive, indicating that having a son and living in a region with a high sex imbalance leads to
a higher saving rate for competitive reasons as hypothesized in Wei and Zhang (2011).
Interestingly, in the original regression presented in Wei and Zhang (2011), the coefficient of
sex ratio is negative and insignificant. In our regressions, it is still negative but becomes
significant. This means that families living in a high gender imbalance region in general save
less, which is true even for families with a son because the combined coefficient on sex ratio
is negative even when son = 1. If this is the case, aggregate saving rates in China should go
lower as a result of increasing gender imbalances in various regions, a prediction contrary to
that of Wei and Zhang (2011).
Observe that risk attitude has a negative impact on saving rates. If an individual is
risk loving, she will save less. Insurance use and pension participation both have a positive
21 22 impact on saving rates, but the effect is not statistically significant. This is contrary to the
expectation that the use of external financial products will help reduce the need to save.
Table 3b reports the regression results of individual level perception index on
household saving rate. Different from Table 3a, the perception index used in this table does
not reflect the strength of the local Confucianism social norm. It solely reflects respondents’
own perception on the issue of raising children for old age security purposes. The variable
Perception Index takes on two values in this regression. We set the individual perception
index to be 1 if the respondent chooses “for old-age insurance” as an answer for the question
“why do you have children”. The individual level perception index is very likely to be
endogenous in the regression. Household saving rate and individuals’ perception on children
could be jointly determined by some unobserved individual or household characteristics.
There could also be reverse causality between these two variables. Individuals with higher
saving rate depend less on their child hence their perception on children might be a function
of their saving rates as well. Therefore results in Table 3b should be interpreted with caution.
It only shows that there is a negative correlation between household saving rate and
individual perception on raising child for old age support. Regression results indicate that
household saving rates for those that treat their children, at least partially, as an investment
good are at least 3.3% lower than those do not.
22 23 Table 3a: OLS Results of Perception Index on Saving Rate
Dependent Var =
Saving Rate
Son
Perception Index
Son x Perception
Index
(1)
(2)
(3)
Base line
w/sex ratio
w/ more
controls
(4)
w/ sex ratio
and more
controls
-0.065
(0.082)
-0.002
(0.003)
-1.316**
(0.617)
-0.001
(0.003)
-0.037
(0.063)
0.004
(0.003)
-0.827*
(0.484)
0.003
(0.003)
-0.838*
(0.483)
-0.004**
(0.001)
-0.000
(0.003)
-0.001
(0.003)
-1.874***
(0.382)
1.123**
(0.557)
-0.001
(0.003)
-0.001
(0.003)
-0.749*
(0.386)
0.713
(0.432)
0.092***
(0.004)
-0.001***
(0.000)
-0.084
(0.053)
0.001
(0.001)
-0.136***
(0.032)
-0.065**
(0.029)
-0.018
(0.032)
-0.034
(0.032)
-0.178***
(0.028)
0.009
(0.031)
2.657**
(1.110)
0.003
(0.002)
-0.883*
(0.377)
0.641
(0.430)
0.090***
(0.004)
-0.001***
(0.000)
-0.090*
(0.053)
0.001*
(0.001)
-0.140***
(0.032)
-0.063*
(0.028)
-0.021
(0.032)
-0.036
(0.032)
-0.176***
(0.028)
0.007
(0.031)
2.831**
(1.048)
1,530
0.373
1,530
0.376
Sex Ratio
Son * Sex Ratio
Income
0.699***
(0.062)
2.783***
(0.424)
0.092***
(0.008)
-0.001***
(0.000)
-0.087
(0.053)
0.001
(0.001)
-0.134***
(0.032)
-0.065**
(0.029)
-0.023
(0.034)
-0.034
(0.033)
-0.176***
(0.027)
0.003
(0.030)
1.852*
(0.995)
1,531
0.003
1,531
0.023
1,530
0.371
Income ^2
Age
Age ^2
Education
Risk Attitude
Insurance
Pension
Gender
State_emp
Constant
Observations
R-squared
Note that robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05,
p<0.1.
Please see Table 2 for the definition of other variables.
23 (5)
With PCA
perception
index 2
while * means
24 Table 3b: OLS Regression of Perception Index on Saving Rates - Individual
(1)
(2)
(3)
(4)
With PCA
Dependent Var =
w/ sex ratio and perception
Saving Rate
Baseline
w/ sex ratio
more controls
index 2
Son
Perception Index
Son * Perception
Index
-0.062*
(0.036)
-0.064
(0.078)
-1.297**
(0.622)
-0.050
(0.079)
-0.054*
(0.029)
-0.037
(0.068)
-0.760
(0.497)
-0.033
(0.068)
-0.007
(0.096)
-0.020
(0.098)
-1.842***
(0.381)
1.094**
(0.557)
0.023
(0.081)
0.016
(0.081)
-0.846**
(0.396)
0.630
(0.445)
0.091***
(0.008)
-0.001***
(0.000)
-0.082
(0.053)
0.001
(0.001)
-0.140***
(0.032)
-0.066**
(0.028)
-0.019
(0.034)
-0.034
(0.032)
-0.181***
(0.027)
0.007
(0.031)
2.811***
(1.086)
1,529
0.373
Sex Ratio
Son * Sex Ratio
Income
0.672***
(0.027)
2.738***
(0.429)
0.091***
(0.008)
-0.001***
(0.000)
-0.087
(0.053)
0.001
(0.001)
-0.141***
(0.032)
-0.065**
(0.028)
-0.026
(0.034)
-0.032
(0.033)
-0.180***
(0.027)
0.001
(0.030)
1.947**
(0.988)
1,530
0.004
1,530
0.024
1,529
0.371
Income^2
Age
Age^2
Education
Risk Attitude
Insurance
Pension
Gender
State_emp
Constant
Observations
R-squared
Note that robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05,
means p<0.1.
Please see Table 2 for the definition of other variables.
24 while *
6.
25 Two-Stage Regression Results
In this section we present the two-stage instrumental-variable estimations. Due to
concerns for the endogeneity of Perception Index and sample selection biases, we use the
distance of each given locality from the provincial capital as the instrument for the Perception
Index. Data on distance values for each locality are drawn from the Google Map. The Sargan
test (P-value = 0.16) and the Basmann test (P-value = 0.17) suggest that the instrument is
orthogonal to the error term in the regression model.
First-stage regression results are presented in Table 5. We instrument both Perception
Index and its interaction term Son * Perception Index using the distance variable and the
interaction of distance and son (son*dist). This is a standard technique of instrumenting
interaction terms with endogenous regressors. The coefficients of the instrumental variance
dist have the signs as expected and are highly significant. The first row of Table 5 shows that
as a locality is further away from the provincial capital, its Perception Index increases. This is
consistent with our expectation discussed above.
Table 6 presents the second-stage regression results when the Perception Index is
instrumented using the distance measure. All the regressions include a provincial and a city
tier dummy variable. Columns 2 and 4 have controlled for sex ratio and its interaction terms.
Columns 3 and 4 also include a set of individual characteristics
25 26 Table 5: First-Stage Effect of Distance from Provincial Capital on Perception Index
(1)
Dep Var =
Perception
Index
Dist
(2)
Baseline
Baseline
(3)
(4)
(5)
w/ sex ratio
w/ sex ratio
and more
controls
Dep Var =
Perception
Index 2
1.300***
2.201***
0.666***
0.684***
0.007
(0.243)
(0.327)
(0.225)
(0.224)
(0.296)
0.282
-0.127
-0.152
-0.448
(0.461)
(0.224)
(0.221)
(0.282)
0.252
14.962***
16.003***
7.838
(0.533)
(4.939)
(4.948)
(12.507)
-51.715***
-49.637***
-33.373***
(4.541)
(4.594)
(8.945)
-13.175***
-14.123***
-6.440
(4.380)
(4.389)
(11.303)
Son * Dist
Son
Sex Ratio
Son * Sex Ratio
City Size
Dummy
Y
N
Y
Y
Y
Y
N
Y
Y
Y
N
N
N
Y
Y
Provincial
Dummy
Individual
Characteristics
Observations
1,531
1,531
1,531
1,530
1530
R-squared
0.174
0.127
0.611
0.618
0.425
F Stat
96.06
34.89
136.0
89.85
123.3
Note: Robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05, while * means p<0.1.
Please see Table 2 for the definition of other variables. All regressions have controlled for provincial and city
type. The regression in column 4 also controls for individual characteristics including age, age squared, income,
income squared, education, purchase of commercial insurance, participation in public pension, risk attitude,
state employment status and gender. dist is the distance from the provincial capital city. The interaction term,
son*dist, is between son and dist, where son takes a value of 1 if the household has a son and 0 otherwise.
26 27 Table 6: 2SLS Effect of oldsupport on savingrate
DepVar = Saving
(1)
(2)
(3)
(4)
(5)
Base line
w/ sex
w/ more
w/ sex ratio
with PCA
ratio
controls
and more
perception
controls
index 2
Rate
Perception Index
0.007
-0.018
0.022
0.022
0.004
(0.390)
(-0.540)
(0.015)
(0.027)
(0.051)
-0.020*
-0.023**
-0.016*
-0.017*
-0.021
(-1.859)
(-2.064)
(0.009)
(0.009)
(0.015)
0.366
-0.130
-0.348
-1.584**
(1.553)
(-0.158)
(1.511)
(0.684)
-3.178*
0.971
-1.364
(-1.654)
(0.602)
(1.935)
Son*Perception
Index
Son
Sex ratio
Son*sex ratio
0.511
0.302
-0.770
0.791
(0.733)
(0.197)
(0.686)
(0.578)
0.093***
0.093***
0.092***
(0.008)
(0.008)
(0.009)
-0.001***
-0.001***
-0.001***
(0.000)
(0.000)
(0.000)
-0.081
-0.082
-0.104
(0.054)
(0.053)
(0.111)
0.001
0.001
0.001
(0.001)
(0.001)
(0.002)
-0.131***
-0.132***
-0.149*
(0.036)
(0.040)
(0.077)
-0.068**
-0.070**
-0.053
(0.030)
(0.034)
(0.043)
-0.008
-0.007
-0.012
(0.037)
(0.036)
(0.037)
-0.042
-0.044
-0.047
Income
Income^2
Age
Age^2
Education
Risk Attitude
Insurance
Pension
27 28 Gender
(0.035)
(0.040)
(0.055)
-0.172***
-0.175***
-0.173***
(0.027)
(0.027)
(0.038)
0.012
0.013
0.004
(0.033)
(0.035)
(0.049)
0.022
0.022
0.004
State_emp
Provincial Dummy
Y
Y
Y
Y
Y
City Size Dummy
Y
Y
Y
Y
Y
Observations
1,531
1,531
1,530
1,530
1,530
R-squared
0.062
0.351
0.352
0.328
Note that Robust z-statistics in parentheses. *** means p<0.01, ** means p<0.05, while *
means p<0.1.Please refer to Table 2 for variable definitions.
oldsupport is instrumented using dist, sonoldsupport is instrumented using sondist.
28 29 With the two-stage regressions, coefficient estimates for Perception Index are no
longer significant. However, coefficient estimates for the interaction term, Son*Perception
Index, are negative and statistically significant when the dummy variables are included. This
means that having a more Confucian influence alone does not decrease the saving rate for
families with only a daughter, but it does decrease the saving rate for families with a boy. The
coefficients of sex ratio and its interaction term, Son*Sex ratio, have the same signs, and the
same interpretations, as in Table 3 and 4. These results are consistent with our model
predictions outlined in section 3.
7.
Culture for old-age support and intergenerational transfers
Our hypothesis relies on the assumption that the return from parents’ investment in
children depends on the local social norms, or the probability of actual repayment by their
son after he grows up. In order to validate that parents do receive more transfers from sons,
we investigate the differences between transfers to retired parents from sons and from
daughters. We use a subsample of respondents whose mother is age 55 and older and whose
father is at least 60 years old.8 The interaction term, son * Perception Index, is included to
test whether son families living in regions with a high Perception Index would receive more
transfers.
Table 7 reports the probability of making monetary transfers to parents by gender of
the respondent. It is clear from the table that this probability is higher for sons than daughters.
Among those that do repay, the average annual transfer by sons is almost RMB 3,000 higher
than that by daughters. Old-age support from sons to their parents is not limited to monetary
transfers. We also find that sons are much more likely to live with their retired parents. The
probability for co-residence for sons is 23% while it is only 16% for daughters.
Table 7: Descriptive Statistics of Transfers to Retired Parents
Probability of
Average
Average transfer
Probability of living
transfer
transfer
excluding those who
with parents
(RMB)
did not (RMB)
65.3%
5059
7,769
22.9%
Daughter 59.7%
3502
5,881
16.3%
Son
8
These are the official retirement ages for women and men, respectively.
29 30 In order to quantify the transfer patterns, we perform regression analyses using both
the probability of transfer and the amount transferred as the dependent variable. In Table 8,
the first three columns report results of the probit regressions. The first column indicates that
sons have a much higher probability to make monetary transfers to retired parents. When
Perception Index and the interaction term, Son*Perception Index, are controlled for, the
effect becomes less significant.
It is interesting to note that the Perception Index is negatively correlated with the
probability of repaying retired parents, indicating that daughters are less likely to pay for
parents retirement. Since the coefficient for the interaction term, Son * Perception Index, is
positive and the coefficient for son is also positive, sons are more likely to repay and pay
more in a region with a higher Confucian influence. The social working dynamics may be as
follows. Since the Confucian social norms put much more obligations on the son to repay and
care for his parents than on a daughter, parents are more willing to invest more in, and expect
to receive more in return in the future from, the son and hence families with a son will end up
with lower saving rates. In the future when the children are adults and their parents, a son will
repay his retired parents more than a daughter will, the observations of which will in turn
re-enforce the expectations and hence preferences of future parents for sons. This cycle will
continue so long as the Confucian influence does not go below a threshold level.
In addition, the higher the parents’ past income, the less likely for the children to
repay after the parents retire. Likewise, if the father used to be a government employee, he
likely has a good retirement pension, which reduces his children’s probability to offer
monetary transfers. Furthermore, the further away the children live from parents, the more
likely for them to honor the implicit financial obligations to their retire parents.
Columns 4-6 in Table 8 report the results of linear regressions with the amount
transferred as the dependent variable. The amount transferred from sons to their retired
parents is significantly higher than from daughters, and is related to the other characteristics
in similar ways as the transfer dummy variable is.
30 31 Table 8: Regression Results of Intergenerational Transfers
Probit Model
(1)
OLS
(2)
(3)
Dependent Var = transfer dummy
Son
0.17***
0.05
(3.85)
(0.49)
Oldsupport
Income
Parent_inc
Parent_med
Parent_dist
State_father
State_mother
Observations
(5)
(6)
Dependent Var = Amount
transferred to parents
1,300***
760.1
(3.53)
(0.82)
-0.01***
-0.01***
-37.8**
-24.5
(-3.36)
(-2.69)
(-2.28)
(-1.60)
0.01***
0.00
50.5***
22.9
(3.95)
(1.09)
(3.71)
(0.67)
0.06***
0.06***
0.06***
-376***
-375***
-374***
(4.07)
(4.18)
(4.18)
(-3.95)
(-3.92)
(-3.92)
0.00
0.00
0.00
0.01*
0.01*
0.01*
(1.61)
(1.59)
(1.58)
(1.93)
(1.92)
(1.92)
-0.03***
-0.03***
-0.03***
-9.28
-4.78
-6.06
(-4.61)
(-4.59)
(-4.60)
(-0.11)
(-0.06)
(-0.07)
0.00*
0.00*
0.00*
0.34*
0.34*
0.34*
(1.88)
(1.89)
(1.89)
(1.79)
(1.79)
(1.79)
0.06***
0.06***
0.06***
27.8
26.2
22.5
(2.86)
(2.76)
(2.74)
(0.18)
(0.17)
(0.14)
-0.19***
-0.20***
-0.20***
-923.7
-957.7
-955.1
(-3.13)
(-3.30)
(-3.29)
(-1.15)
(-1.19)
(-1.19)
-0.01
-0.01
-0.01
255.2
279.2
276.0
(-0.15)
(-0.13)
(-0.14)
(0.42)
(0.46)
(0.46)
3,932
3,925
3,925
3,932
3,925
3,925
0.18
0.18
0.18
Son*Oldsupport
Siblings
(4)
R-squared
Note that robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05, while *
means p<0.1. Please see Table 2 for the definition of other variables. Siblings = number of
siblings, parent_inc = parents’ income, parent_med = parents’ medical expenditure, parent_dist
= parents’ living distance from the respondent, state_father = 1 if the father used to be a state
employee and 0 otherwise, state_mother = if the mother used to be a state employee and 0
otherwise. All regressions also include provincial and city tier type dummies.
31 8.
32 Confucian Norms and Saving for Human Capital Investment
According to the model outlined in section 3, investment in children relative to the
risk-free asset shall increase as the Confucian social norms strengthen. In other words,
parents would be more willing to invest in their children if they perceive their children as a
more reliable source of income. We test this hypothesis using one of the questions asked in
the survey about saving intentions. In the questionnaire we ask parents “what are the
purposes for your savings”.
Individuals are prompted with the following choices: saving for
child education, saving for retirement, saving for medical expenses, saving for property
purchases, saving for child’s marriage, and other types of saving. Out of the 1237 valid
answers we obtained, 60.71% acknowledged that saving for child’s education is one of their
saving purposes. Summary data for saving motives are presented in Table 9.
A simple probit regression is used to analyze the effect of parents’ perception index on
their purpose of saving. Results are presented in Table 9. Coefficient of Perception Index is
positive and highly significant in all four model specifications. The regression results indicate
that as the Confucianism social norm strengthens in a region, parents are more likely to invest
in children in the form of education.
Table 9: Why do People Save – Self-reported Saving Motives
Saving Purpose
Self-Reported Saving Motive*
Child’s Education
60.71%
Retirement
29.31%
Medical Expenses
26.55%
Property Purchase
23.35%
Child’s Wedding
15.59%
Other Investment
20.62%
Other
1.63%
* % of individuals who choose the indicated reason as their motive of saving. Note that
respondents are allowed to choose multiple answers and hence the total exceeds 100%.
32 33 Table 10: Probit Regression of Perception Index on Saving for Education
(1)
(2)
(3)
Dependent Var =
(4)
w/ sex ratio
Pr(Saving for Child
and more
Education
Baseline
Baseline
w/ sex ratio
controls
Perception Index
0.009**
0.015**
0.015**
0.024***
(0.004)
(0.006)
(0.006)
(0.007)
-0.010
-0.011
-0.008
(0.008)
(0.008)
(0.008)
0.199
-1.821
-1.686
(0.189)
(1.352)
(1.377)
-1.033
-0.180
(0.775)
(0.841)
1.817
1.688
(1.211)
(1.228)
Son * Perception
Index
Son
Sex Ratio
Son * Sex Ratio
Income
0.047***
(0.012)
Income ^ 2
-0.001***
(0.000)
Age
0.359**
(0.146)
Age ^ 2
-0.005**
(0.002)
Education
0.251***
(0.086)
Risk Attitude
-0.006
(0.080)
Insurance
0.046
(0.089)
Pension
-0.314***
33 34 (0.086)
Gender
0.030
(0.077)
State_emp
0.126
(0.088)
Provincial Dummy
Y
City Size Dummy
Y
Constant
Observations
0.094
-0.022
1.129
-7.273**
(0.094)
(0.142)
(0.872)
(2.907)
1,223
1,223
1,223
1,222
Note that robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05, while * means p<0.1.
Please see Table 2 for the definition of other variables. 19.
Conclusions
The social norms are essential as an enforcement mechanism that ensures the fulfillment
of the implicit intra-family financial contract between parents and children. The family acts
as an implicit annuity market for the parents and a borrowing market for the children. The
gender imbalance increases the liquidity constraint of sons and increases the competitive
demand for wealth prior to the sons’ marriage. Hence the saving rate is jointly determined by
the gender of the child, gender imbalance, and the intensity of Confucian influence in the
region where the family lives.
The empirical results in this paper support the life-cycle view of saving. We find evidence
that households with a son save significantly less than those with a daughter. But, if the local
sex imbalance is severe or if the local Confucian influence is low, even parents with a son
will have to save more than those parents with a son in other regions. Our survey findings are
consistent with our theoretical model’s predictions, where the amount invested in the child is
derived from the parents’ life-time utility optimization. Our empirical evidence supports the
competitive-savings theory of Wei and Zhang (2011). We show that having a son in a region
34 35 with a strong sex imbalance would increase the household saving rate. However, the effect is
not statistically significant in the two-stage regressions.
Both our model and empirical results based on our survey indicate that a strong belief in
raising children for old age support and hence a strict adherence to Confucian values reduce
the saving rates for local families with a son but do not necessarily affect those parents with
only daughters. Our research shows that Chinese household saving rates have been on the rise
because financial products are not as readily available, children have become less reliable for
parents’ old age support due to the declining influence of Confucian values, and, to the extent
that parents have a son to raise, they have to save more for his education and for his future
marriage. As long as the influence of Confucianism continues to decline in China, the high
saving rate will likely persist unless financial development accelerates and social security
programs truly kicks in.
35 36 References
A. Banerjee, N. Qian and Xin Meng, 2010 “Fertility and Savings: Micro Evidence from
Family Planning in China”,Working Paper
G. S. Becker and H. G. Lewis, 1973 “On the interaction between quantity and quality of
children”.The Journal of Political Economy, 81(2):S279-S288
M. D. Chamon and Eswar S. Prasad, 2010 "Why Are Saving Rates of Urban Households in
China Rising?," American Economic Journal: Macroeconomics, American Economic
Association, vol. 2(1), pages 93-130, January
A. Cigno, 1992 “Children and pensions.” Journal of Population Economics, 5(3):175-183
D. Cox and E. Jimenez. 1992 “Social security and private transfers in developing
countries:The case of Peru.” The World Bank Economic Review, 6(1):155-169
D. Cox, Z. Eser, and E. Jimenez, 1998 “Motives for private transfers over the life cycle:
Ananalytical framework and evidence for Peru.”Journal of Development Economics,
55(1):57-80, Feb
T. Choukhmane, N. Coeurdacierand Keyu Jin,2013 “The One-Child Policy and Household
Savings”, Working Paper
S. Ge, D. T. Yang, J. Zhang 2012 “Population Control Policies and the Chinese Household
Saving Puzzle.” Working Paper
C. Horioka and J. Wan, 2007. “The determinants of household saving in China: a dynamic
panelanalysis of provincial data.”Journal of Money, Credit and Banking, (18330068)
M. Kandori, 1992“Social Norms and Community Enforcement.”The Review of Economic
Studies, 59(1):63-80
A. Kraay, 2000.“Household Saving in China.” The World Bank Economic Review,
14(3):545-570,
36 37 F. Modigliani and S. L. Cao, 2004. “The Chinese Puzzle and Saving Life-Cycle
Hypothesis.”Journal of Economic Literature, 42(1):145-170
J. Oliveira,2013 “The Value of Children: Intergenerational Transfers,Fertility, and Human
Capital”, PhD Job market paper
T. P. Schultz. Fertility in Developing Countries.Yale University Working Paper 2007.
S.-j. Wei and X. Zhang, 2011. “The Competitive Saving Motive : Evidence from Rising Sex
Ratios and Savings Rates in China”,
Journal of Political Economy, 119(3):511-564
H. P. Young, 2008. “Social Norms.” In S. N. Durlauf and L. E. Blume, editors, New Palgrave
Dictionary of Economics. Macmillan, London, 2008.
Appendix A
⎛
⎞
⎜
⎟
⎛ ε ⎞
ε
⎟
E[u ' (c2 )ε ] = E ⎜ ⎟ = E ⎜
⎜ (Y − c )(θ R + (1 − θ )( R + ε ) ⎟
⎝ c2 ⎠
⎜ 1 1
γ ⎟⎠
⎝
1
ε
when ε > 0 ，
(Y1 − c1 )(θ R + (1 − θ )( R + )
γ
<
1
(Y1 − c1 )(θ R + (1 − θ ) R
ε
multiply both sides by ε ，get
ε
γ
<
(Y1 − c1 )(θ R + (1 − θ )( R + )
ε
Similarly, when ε < 0 ，we have
ε
γ
(Y1 − c1 )(θ R + (1 − θ )( R + )
37 ε
(Y1 − c1 )(θ R + (1 − θ ) R
<
ε
(Y1 − c1 )(θ R + (1 − θ ) R
38 ⎛
⎞
⎜
⎟
⎛ ε ⎞
ε
⎟ < 0
Therefore E[u ' (c2 )ε ] = E ⎜ ⎟ = E ⎜
⎜ (Y − c )(θ R + (1 − θ )( R + ε ) ⎟
⎝ c2 ⎠
⎜ 1 1
γ ⎟⎠
⎝
*
Because D < 0 , we have ∂θ
=
∂γ
1
− β (Y1 − c1 ) E[u ' (c2 ) ε ]
γ
D
<0
Appendix B ∂c1 E[{u ' (c2 ) + u " (c2 )(Y1 − c1 )(θ R + (1 − θ ) Ri )}( R − Ri )]
=
∂θ
H
⎡
⎤
Y2
E ⎢
( R − Ri ) ⎥
2
[(Y − c )(θ R + (1 − θ ) Ri ) + Y2 ]
⎦
= ⎣ 1 1
H
⎡
⎤
Y2
E ⎢
( R − Ri ) ⎥
2
[(Y − c )( R − (1 − θ )( R − Ri )) + Y2 ]
⎦
= ⎣ 1 1
H
When R − Ri > 0 ,
Y2
Y2
>
(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 (Y1 − c1 ) R + Y2
multiply both sides by
1
( R − Ri ) ,get (Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2
Y2
Y2
( R − Ri ) >
( R − Ri ) 2
[(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
[(Y1 − c1 ) R + Y2 ][(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
Similarly, when R − Ri < 0 ,we have Y2
Y2
( R − Ri ) >
( R − Ri ) 2
[(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
[(Y1 − c1 ) R + Y2 ][(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
Using ∂V
= β (Y1 − c1 ) E[u ' (c2 )( R − Ri )] = 0 , So we can ∂θ
38 39 ⎧
⎫
⎧
⎫
Y2
Y2
1
E ⎨
( R − Ri ) ⎬ >
E ⎨
( R − Ri ) ⎬ = 0 2
⎩[(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
⎭ [(Y1 − c1 ) R + Y2 ] ⎩[(Y1 − c1 )( R − (1 − θ )( R − Ri )) + Y2 ]
⎭
⎡
⎤
Y2
E ⎢
( R − Ri ) ⎥
2
It means ∂c1
[(Y − c )( R − (1 − θ )( R − Ri )) + Y2 ]
⎦ < 0 = ⎣ 1 1
∂θ
H
Appendix C Correction for Possible Sampling Biases Using Weighted OLS
As discussed in section 4, due to the wide locality coverage, the survey participants are
not selected in a totally random way. Biases may come from several channels. First, the
locations surveyed are chosen by design, rather than by randomizing over the counties or
provinces. The eleven provinces and eight cities of different sizes in each province are
carefully chosen in order to cover different and representative regions and segments of China.
Five tiers of city/locality are selected to represent different levels of development and offer
enough variations for our study.
Unequal selection probability and non-responsiveness are two other important sources of
possible sampling biases. Comparing the statistics in Table 2 to corresponding national
averages, we see that certain subpopulations are overrepresented in our sample. For example,
almost 40% of survey participants have a college degree, significantly higher than the
reported national average. The overrepresentation leads us to believe that there is an unequal
probability of selection among different education groups. This bias may have been due to
the choices of survey locations and times of day when our field workers are conducting the
survey. It is also possible that individuals with certain characteristics are more willing to
respond than others (e.g., those with higher education). Unfortunately, as we do not have data
about non-response target subjects, non-response biases are difficult to control for.
In order to correct for possible sampling biases, we use post-stratification to re-weight
each observation. The idea of post-stratification is to calibrate the sample so that it conforms
to a known population distribution. Weighted OLS regressions are then performed. Weights
are constructed using the 1% sampling of the 2005 population census, as follows. Step 1: the
population is first divided into 36 cells by marriage status, education level, and sex; Step 2:
the percentage of individuals falling into each cell is then computed using the population
39 40 census; Step 3: the percentage of individuals in our sample falling into each cell is also
computed; Step 4: the weight for each observation is then determined by the ratio between
these two percentages for the cell to which the observation belongs. By re-weighting each
individual respondent this way, we make sure that the distribution across these three
demographic dimensions of our sample conforms to the overall population profile at the
provincial level.
Results of the weighted regressions are presented in Table 4 below. The coefficient signs
for
oldsupport, son, and the interaction terms remain unchanged, while the magnitude of
these coefficients is close to their un-weighted counterparts reported in Table 3. Based on
Dumouchel and Duncan (1983), if the difference between the two estimates is close to zero, it
means the estimates are likely to be unbiased. Note that the coefficients for Insurance and
Pension are now negative though statistically significant, at the sign of which is consistent
with the expectation that financial development helps lift some saving pressure.
Table 4: Weighted OLS Regression Results
DepVar = Saving Rate
Son
Oldsupport
Son*oldsupport
(1)
(2)
(3)
(4)
Base line
w/ sex
w/ sex ratio
With PCA
ratio
and more
perception
controls
index 2
-0.041
-0.079
-0.007
-0.154
(0.134)
(1.079)
(0.095)
(0.829)
0.002
0.002
0.006
0.004
(0.004)
(0.004)
(0.005)
(0.005)
-0.002
-0.003
-0.003
-0.003
(0.006)
(0.006)
(0.004)
(0.004)
Sex ratio
Son*sex ratio
Income
40 -1.103*
-1.059*
(0.649)
(0.618)
0.037
0.137
(0.968)
(0.741)
0.098***
0.099***
(0.008)
(0.008)
41 Income^2
Age
Age^2
Education
Risk Attitude
Insurance
Pension
Gender
Constant
-0.001***
-0.001***
(0.000)
(0.000)
-0.066
-0.057
(0.073)
(0.074)
0.000
0.001
(0.001)
(0.001)
-0.227***
-0.224***
(0.039)
(0.039)
-0.108**
-0.104**
(0.045)
(0.044)
-0.089
-0.077
(0.060)
(0.058)
-0.014
-0.013
(0.047)
(0.047)
-0.203***
-0.205***
(0.040)
(0.040)
0.661***
1.880***
1.632
2.678*
(0.0959)
(0.714)
(1.348)
(1.508)
Province Dummy
N
N
Y
Y
City Size Dummy
N
N
Y
Y
Observations
1,530
1,530
1,530
1,530
R-squared
0.004
0.012
0.368
0.371
Note that robust standard errors are in parentheses. *** means p<0.01, ** means p<0.05, while *
means p<0.1. Please see Table 2 for the definition of other variables.
41