Discussion Paper No. 975

THE IMPACT OF PRE-MARITAL SEX RATIOSON HOUSEHOLD SAVING
IN TWO ASIAN COUNTRIES:THE COMPETITIVE SAVING
MOTIVE REVISITEDCharles Yuji Horioka
Akiko Terada-Hagiwara

July 2016

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

The Impact of Pre-marital Sex Ratios on Household Saving in Two Asian Countries: The Competitive Saving
Motive Revisited*
Charles Yuji Horioka** and Akiko Terada-Hagiwara***July 5, 2016
Abstract: This paper estimates a household saving rate equation for India and Korea using long-term timeseries data for the 1975-2010 period, focusing in particular on the impact of the pre-marital sex ratio on thehousehold saving rate. To summarize the main findings of the paper, it finds that the pre-marital sex (orgender) ratio (the ratio of males to females) has a significant impact on the household saving rate in both India
and Korea, even after controlling for the usual suspects such as the aged and youth dependency ratios andincome. It has a negative impact in India, where the bride’s side has to pay substantial dowries to the groom’s
side at marriage, but a positive impact in Korea, where, as in China, the groom’s side has to bear adisproportionate share of marriage-related expenses including purchasing a house or condominium for the
newlywed couple.
Key words: Age structure of the population; competitive saving motive; dowries; gender ratio; household saving
rate; life cycle hypothesis; marriage expenses; pre-marital sex ratio; population control; saving for education;saving for marriage; saving rate; sex ratio; son preference; wedding expenses; Korea; India.

Journal of Economic Literature classification numbers: D12, D14, D91, E21, J11, J12, O16*We thank Jiro Akita, Chetan Ghate, Pedro Gomis-Porqueras, Shikha Jha, Shoshana Grossbard, Tatsuo Hatta,
Aziz Hayat, Yoshihiko Kadoya, Takamitsu Kurita, Jaewoo Lee, Seunghwan Leem, Debdulal Mallick, Keunkwan
Ryu, Kwanho Shin, Xueli Tang, Hideki Toya, Shinsuke Uchida, Midori Wakabayashi, Junmin Wan, Shang-Jin
Wei, Tansel Yilmazer, seminar participants at the Asian Growth Research Institute, Deakin University,
Fukuoka University, the International Monetary Fund/Bank of Korea Conference on “Asia: Challenges of
Stability and Growth,” Korea University, Nagoya City University, Seoul National University, Tohoku University,and the University of the Philippines, Diliman, two anonymous referees, and especially Yoko Niimi for theirvery helpful comments, Elenita Pura and Shiela Camingue-Romance for superb research assistance, and JSPS
KAKENHI Grant Number 15H01950, the Asian Growth Research Institute, and the Joint Usage/ResearchCenter at the Institute of Social and Economic Research, Osaka University, for their financial support. The
views expressed in this paper are those of the authors and do not necessarily reflect the views or policies of the
Asian Development Bank, its Board of Directors, or the governments they represent.
**C. Y. Horioka, Asian Growth Research Institute, 11-4, Ohtemachi, Kokurakita-ku, Kitakyushu, Fukuoka
813-0814, Japan. Email: horioka@iser.osaka-u.ac.jp; National Bureau of Economic Research, Cambridge, MA,
USA; Institute of Social and Economic Research, Osaka University, Osaka, Japan***A. Terada-Hagiwara, Economic Research and Regional Cooperation Department, Asian Development Bank,
6 ADB Avenue, Mandaluyong City, Metro Manila 1550, Philippines. Email: ahagiwara@adb.org

1. Introduction

As documented by Wei and Zhang (2011a), Du and Wei (2013), and Golley and Tyers(2014), the introduction of the one-child policy and other population control measures in
the People’s Republic of China (hereafter China), combined with strong son preference, led
to an increasingly unbalanced sex (or gender) ratio (ratio of males to females) in the
pre-marital cohort.

And in two widely cited papers, Wei and Zhang (2011a) and Du andWei (2013) argue that the increasingly unbalanced pre-marital sex ratio, in turn, required
the groom’s side to save increasingly more to ensure his success in an increasinglycompetitive marriage market and that this elevated the saving rate of the household
sector as a whole (what they call the “competitive saving motive”).

Wei and Zhang (2011a) and Du and Wei (2013) verify this effect using household-level dataand provincial panel data for China, cross-country data for a sample of about 160
countries, and numerical calibration methods and show that the sharp increase in the
pre-marital sex ratio can potentially explain about 60% of the sharp increase in China’s
household saving rate during the 1990-2007 period (from 16% to 30%) and about half ofboth the current account surplus of China and the current account deficit of the UnitedStates (see Wei and Zhang (2015) for a useful survey).

While the “competitive saving motive” may be applicable outside of China given theunbalanced sex ratios and conventions regarding marriage-related expenses in othercountries, empirical investigations have been limited (but see Horioka (1987) for ananalysis of saving for marriage in Japan).

The purpose of this paper is to contribute to1the literature by determining whether or not a similar mechanism has led to a significant
relationship between the pre-marital sex ratio and the household saving rate in India andthe Republic of Korea (hereafter Korea), two countries in which, as in China, sex ratios areunbalanced and marriage-related expenses are considerable, and to determine whether or
not trends over time in the pre-marital sex ratio can explain trends over time in thehousehold saving rate in these two countries. In order to accomplish these objectives,
this paper estimates a household saving rate equation for India and Korea using
long-term time series data for the 1975-2010 period, focusing in particular on the impactof the pre-marital sex ratio on the household saving rate.

To summarize the main findings of this paper, it finds that the pre-marital sex ratio (ratioof males to females) has a significant impact on the household saving rate in India andKorea, even after controlling for the usual suspects such as the aged and youth
dependency ratios and income.

It has a negative impact in India, where the bride’s side

has to pay substantial dowries to the groom’s side at marriage, but a positive impact inKorea, where, as in China, the groom’s side has to bear a disproportionate share of
marriage-related expenses including purchasing a house or condominium for the
newlywed couple.

The findings of the paper imply that trends in the pre-marital sex ratio

can explain trends in the household saving rate during the first half of the sample period
but not during the second half in both countries and that the level of the pre-marital sex
ratio can partly explain the high level of Korea’s household saving rate but not the highlevel of India’s household saving rate.

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The remainder of this paper is organized as follows:

Section 2 contains a theoretical

discussion of the impact of the pre-marital sex ratio on the household saving rate, section
3 presents and discusses data on trends over time in the pre-marital sex ratio and thehousehold saving rate in India and Korea, section 4 presents the estimation model used inthis paper, section 5 discusses the data sources used, section 6 presents the estimation
results, and section 7 summarizes, concludes, and explores the policy implications of ourfindings.

2. Theoretical Considerations

In this section, we discuss the theoretical impact of the sex (male-to-female) ratio of the
pre-marital cohort on the household saving rate (this exposition is based on
Grossbard-Shechtman (1993), Wei and Zhang (2011a), Du and Wei (2013), and Grossbard(2015)).1

If the pre-marital sex ratio is unbalanced, families with a child who belongs tothe overrepresented gender will presumably increase their saving in order to ensure that
their child is able to secure an “attractive” spouse, especially if the custom in that country
is for families with a child who belongs to the overrepresented gender to bear adisproportionate share of marriage-related expenses. At the same time, families with achild who belongs to the underrepresented gender may or may not reduce their saving due
to the presence of two mutually offsetting effects.

On the one hand, they may reduce

their saving because of their favorable bargaining position in the marriage market, but on
the other hand, they may increase their saving to ensure that their child does not suffer an
1

See Lafortune (2013) for a very similar analysis of the impact of sex ratios not on the household savingrate but on pre-marital educational investments and Wei and Zhang (2011b) for a very similar analysis of
the impact of sex ratios on the occupational choice of parents.

3erosion of his or her bargaining power vis-à-vis his or her spouse (assuming that therelative wealth levels of the two sides affects the relative bargaining power of the husband
and wife vis-à-vis one other after marriage). Thus, families with a child who belongs tothe overrepresented gender will unambiguously increase their saving, but it is not
immediately clear whether families with a child who belongs to the underrepresented
gender will increase or decrease their saving and whether the saving of the household
sector as a whole will increase or decrease, on balance.

However, Du and Wei (2013) show that a higher pre-marital sex ratio will unambiguously
raise the saving rate of the household sector as a whole for at least two reasons.

First,

families with a child who belongs to the overrepresented gender will save more not only
because of the child’s disadvantaged position in the marriage market but also because theyknow that families with a child who belongs to the underrepresented gender will save lessdue to the child’s advantaged position in the marriage market and want to compensate forthe reduced saving from the other side.

Thus, the increase in the saving of families witha child who belongs to the overrepresented gender will more than offset the decrease in
the saving of families with a child who belongs to the underrepresented gender.

Second,the more unbalanced the pre-marital sex ratio is, the higher will be the proportion of the
pre-marital cohort that needs to save more for marriage due to its disadvantaged positionin the marriage market.

These theoretical considerations generate the prediction that the saving rate of thehousehold sector as a whole will be lowest when the pre-marital sex ratio is balanced andthat it will be higher, the more the pre-marital sex ratio is unbalanced in either direction.

4

In other words, the pre-marital sex ratio will have a negative impact on the householdsaving rate if the pre-marital sex ratio is below the biologically normal sex ratio of 1.05 to
1.06 and a positive impact on the household saving rate if the pre-marital sex ratio is
above this threshold.

However, as shown later, the pre-marital sex ratio is unbalanced infavor of males (exceeds the 1.06 threshold) in both India and Korea (except in Korea
during the 1975-1983 period).

This implies that we would expect the pre-marital sex

ratio to have a positive impact on the household saving rate in both countries because thegroom’s side will have to save more and more as the pre-marital sex ratio increases andbrides become in increasingly short supply.

However, the foregoing discussion ignores the issue of which side bears the brunt ofmarriage-related expenses, and it is to this issue that we now turn.

Since the custom in

China is for the groom’s side to bear a disproportionate share of marriage-related expenses
including purchasing a house or condominium for the newlywed couple, this in turn bid up
the cost of securing a bride, led families with sons to save more than before, and caused
the overall household saving rate to increase over time.

Similarly, in the case of Korea,

the bride’s side is expected to pay a (cash) dowry and to pay for the furnishings of the
newlywed’s home, but the groom’s side is expected to return half of the dowry and to pay
for the newlywed’s home, which has become a more and more onerous burden over time
due to the rapid rise in housing prices (see Onishi (2007)).

Thus, wedding customs in

Korea are very similar to those in China, with the groom’s side being expected to bear adisproportionate share of marriage-related expenses, and moreover, housing prices haveincreased sharply in Korea, as they have in China, thereby further increasing the groom

5

side’s burden.2

By contrast, in the case of India, the bride’s side must pay enormous dowries to thegroom’s side.

According to Anderson (2007), dowries are paid in 93 to 94% of cases inIndia and amount to 4 to 6 times annual male income, 7 to 8 times annual per capita
income, and 68% of total household assets before marriage, and the amount of dowries
increased at the phenomenal rate of 15% per year during the 60-year from 1921 until 1981.
The Dowry Prohibition Act was enacted in 1961 and it was further strengthened in 1983
and 2005, but the payment of dowries is still common in many parts of India and theaforementioned laws are primarily concerned with preventing and punishing the crueltreatment, harassment, and even murder of brides in connection with dowry demands
rather than with the payment of the dowry itself.

Thus, the situation in India is the

opposite of that in China.

If the social custom is for the groom’s side to bear a disproportionate share of
marriage-related expenses (as in China and Korea), the positive impact of the pre-maritalsex ratio on the household saving rate will be actualized because the groom’s side has tosave for marriage-related expenses even when the pre-marital sex ratio is balanced andwill have to save even more for marriage-related expenses if the pre-marital sex ratio is
unbalanced and they are disadvantaged in the marriage market.

By contrast, if the social custom is for the bride’s side to bear a disproportionate share of
2Note, however, that there is an endogeneity issue here, with the higher housing prices in China andKorea being caused in part by the increased demand for housing caused by the unbalanced pre-maritalsex ratio (see, example, Wei, Zhang, and Liu, 2015).

6

marriage-related expenses (as in India), the positive impact of the pre-marital sex ratio on
the household saving rate may not be actualized because it is the bride’s side that bears
the burden of marriage-related expenses, and even if the pre-marital sex ratio increases(the ratio of grooms to brides increases), the groom’s side will not necessarily have to saveany more than before for marriage-related expenses despite their disadvantaged positionin the marriage market.

Indeed, as the pre-marital sex ratio increases, the shortage ofbrides will become increasingly acute, which in turn might bid down dowries, reduce themarriage-related saving that the bride’s side has to do, and thereby reduce overallhousehold saving.

Thus, the impact of the pre-marital sex ratio on the household savingrate is theoretically ambiguous, but it could well have a negative impact on the householdsaving rate, the opposite result from countries such as China and Korea where the groom’s
side bears a disproportionate share of marriage-related expenses.

To summarize, even though the pre-marital sex ratio is unbalanced in favor of males inboth India and Korea, we would expect the impact of the pre-marital sex ratio to bedifferent in the two countries due the differences in social customs regarding which side
bears the brunt of marriage-related expenses. We would expect the pre-marital sex ratio
to have a positive impact on the household saving rate in Korea where the groom’s side
bears a disproportionate share of marriage-related expenses, and it could well have anegative impact on the household saving rate in India, where the bride’s side bears a
disproportionate share of marriage-related expenses.

7

3. Data on Pre-Marital Sex Ratios and Household Saving Rates in India and Korea

In this section, we present data on the sex ratio of the pre-marital cohort and thehousehold saving rate in India and Korea during the 1975-2010 period.

In India, the average age at first marriage was 22.7 for males, 17.7 for females, and 20.2
for both sexes in 1971 and 26.0 for males, 22.2 for females, and 24.1 for both sexes in 2011(all data were taken from Medindia, 2016), and thus the average age at first marriage forboth sexes presumably averaged about 22 during the 1975-2010 period as a whole. By
contrast, in Korea, the average age at first marriage was much later--26.7 for males, 22.8
for females, and 24.75 for both sexes in 1966 and 32.2 for males, 29.6 for females, and 30.9
for both sexes in Korea in 2013 (the data for 1966 were taken from Lapierre-Adamcyk andBurch (1974) while the data for 2013 were taken from Statistics Korea (2013)), and thus
the average age at first marriage for both sexes presumably averaged about 28 during the
1975-2010 period as a whole.

We therefore define the pre-marital cohort as the 10 to 19

age group in India and the 15 to 24 age group in Korea, reflecting differences in the
average age at first marriage in the two countries, and calculate SEXRATIO (the sex ratioof the pre-marital cohort) as the ratio of males to females for the 10 to 19 age group in thecase of India and for the 15 to 24 age group in the case of Korea.

It would have been

preferable to use a different definition of the pre-marital cohort in each year to reflectincreases over time in the average age at first marriage in the two countries, but we were
not able to do so because the population data are available only for 5-year age groups.
Moreover, it would have been preferable to take account of the age difference between
males and females at first marriage (about 4 to 5 years in India and about 3 to 4 years in

8

Korea), but we were not able to do so for the same reason.

Figures 1-1 and 1-2 show data on trends over time in SEXRATIO (the pre-marital sex ratio,
the ratio of males to females) in India and Korea, respectively, during the 1975-2010
period, taken from United Nations (2016), and as can be seen from these figures, this ratio
was relatively stable in India during this period, fluctuating in the 1.080 to 1.103 range.
It showed a slight downward trend during the 1975-93 period, declining from 1.094 in
1975 to 1.080 in 1993, remained stable at 1.080 during the 1993-98 period, and showed aslight upward trend during the 1998-2010 period, increasing from 1.080 in 1998 to 1.103
in 2010.

In Korea, by contrast, the pre-marital sex ratio showed a sharp upward trend

throughout the 1975-2010 period, increasing from 1.045 in 1975 to 1.127 in 2010. There
are at least two possible explanations for this trend.

One is the increasing availability

and/or affordability of sex determination technology (ultrasonography and amniocentesis)
and sex-selective abortions (see Guilmoto (2009) and Du and Wei (2013)), and the other isthat the sharp decline in fertility, combined with strong son preference, caused parents tocare more about the gender of any given child (see Golley and Tyers (2012) for a discussionof the population control policies that were largely responsible for the sharp decline infertility).

Note that the biologically normal sex ratio at birth is 1.05 to 1.06 (105 or 106 males forevery 100 females).

Thus, the sex ratio in both India and Korea is higher than thenatural ratio (except until 1983 in Korea), as it is in many, if not most, Asian countries (seeGuilmoto (2009) for comparative data on sex ratios at birth for a large number of Asian
countries), suggesting that parents have a strong preference for sons in both countries.

9

Parents presumably operationalized their preference for sons via female infanticide inearlier times (observed in some northern Indian states such as Delhi, Haryana, andRajasthan) and by sex-selective abortions (made possible by sex determination technology
such as ultrasonography and amniocentesis) in more recent times. 3

The crucial

difference between India and Korea is in trends over time, with Korea showing a much
more pronounced upward trend in its sex ratio throughout the period of analysis for thereasons noted earlier.

Turning to data on the household saving rate, we defined HHSR (the household savingrate) as the ratio of net household saving to net household disposable income, where net
household saving is calculated as the difference between net household disposable income
and household consumption) (see section 5 for data sources).

Figures 2-1 and 2-2 show

data on HHSR for India and Korea, respectively, during the 1975-2010 period, and as canbe seen from these figures, India’s household saving rate has shown a long-term upward
trend over time, increasing from 9.6% in 1975 to 26.9% in 2010.

By contrast, Korea’s

household saving rate has been highly volatile over time, fluctuating between 0.4% in2002 and 26.0% in 1988 but generally high (above 10%) until 1999 and generally low(below 10%) thereafter.

We now compare trends over time in the pre-marital sex ratio to trends over time in thehousehold saving rate in India and Korea.

In the case of India, the pre-marital sex ratio

and the household saving rate showed opposite trends during the 1975-96 period, with the3

Indeed, Chen, et al. (2013) find using variations across counties in China that access to ultrasound had

a significant impact on sex ratios at birth, with 40-50% of the increase in sex ratios at birth in China
being due to improved access to ultrasound.

10former showing a downward trend and the latter showing an upward trend, whereas they
showed similar trends during the 1996-2010 period, with both of them showing upward
trends.

Since we hypothesized that the pre-marital sex ratio may have a negative impact

on the household saving rate in the case of India, trends in the pre-marital sex ratio may
be able to explain trends in the household saving rate during the 1975-96 period but notduring the 1996-2010 period.

In the case of Korea, the pre-marital sex ratio showed an upward trend throughout the
1975-2010 period but the household saving rate was volatile during this period.

Since wehypothesized that the pre-marital sex ratio will have a positive impact on the householdsaving rate in the case of Korea and since the household saving rate showed an upward
trend during the 1975-78, 1980-88, 1997-98, 2002-04, and 2008-09 periods, trends in the
pre-marital sex ratio may be able to explain trends in the household saving rate during
these periods but not during other periods.

However, we cannot be certain about the impact of the pre-marital sex ratio on thehousehold saving rate in the two countries unless we conduct a rigorous regression
analysis and control for the impact of other factors.

It is to this type of analysis that weturn in the remainder of this paper.

4. Estimation ModelIn this section, we discuss the estimation model we use in our econometric analysis of thedeterminants of household saving rates in Korea and India.

11

We start with the mostcommonly used specification deriving from the life cycle/permanent income hypothesisthat posits that the household saving rate is a function of the age structure of the
population, income levels, corporate saving, etc. and add to it the pre-marital sex ratio(see, for example, Modigliani (1970), Feldstein (1977, 1980), Modigliani and Sterling(1983), Horioka (1989, 1997), Edwards (1996), Higgins (1998), Loayza, et al. (2000), Chinn
and Prasad (2003), Luhrman (2003), Bosworth and Chodorow-Reich (2007), Horioka and
Wan (2007), Kim and Lee (2008), Park and Shin (2009), and Horioka andTerada-Hagiwara (2012) for more details; Fafchamps and Pender (1997), Kochar (1999),
and Athukorala and Sen (2004) for papers on India; and Hurd (1995), Kwack and Lee(2005), and Park and Rhee (2005) for papers on Korea).

Thus, the estimation model we use is as follows:(1)

HHSR(t) = a0 + a1*DEP(t) + a2*AGE(t) + a3*SEXRATIO(t) + a4*PCY(t) +a5*CORPSAV(t) + a6*POP1519(t) + a7*TREND(t) + e(t),where HHSR = the household saving rate (defined as the ratio of net household saving to
net household disposable income)
DEP = the youth dependency ratio, defined as the ratio of the young population (thepopulation aged 0 to 14 in the case of India and the population aged 0 to 19 in the case of
Korea) to the working-age population (the population aged 15 to 59 in the case of India
and the population aged 20 to 64 in the case of Korea)
AGE = the aged dependency ratio, defined as the ratio of the aged population (thepopulation aged 60 and older in the case of India and the population aged 65 and older in12the case of Korea) to the working-age population
SEXRATIO = the sex ratio (the ratio of males to females) of the pre-marital cohort(defined as the 10 to 19 age group in India and the 15 to 24 age group in Korea, for thereasons explained earlier).
PCY = per capita real net household disposable income
CORPSAV = the ratio of net corporate saving to net household disposable income
POP1519 = the ratio of the pre-college population (the population aged 15 to 19) tothe working-age population (the population aged 20 to 64) (included only in the case of
Korea for the reasons given below)
TREND = a time trend
e = an error term

DEP and AGE are meant to capture the impact of the age structure of the population andare included in virtually all aggregate saving rate regressions.

The life cycle hypothesis

predicts that both coefficients will be negative since the aggregate household saving rateshould be lower, the higher is the ratio of the dependent (young or aged) population to theworking-age population.

The dependent and working-age populations are defineddifferently in India and Korea to reflect differences in college entrance rates (higher in
Korea than in India) and retirement ages (later in Korea than in India).

Turning to the other explanatory variables, one would expect the coefficient of PCY to bepositive since households should be able to afford to save more if their income levels arehigher, and one would expect the coefficient of CORPSAV to be negative if households see
through the corporate veil and reduce their own saving in response to increases in13

corporate saving.

Yet another demographic variable of possible importance in societies that place value on
education is POP1519 (the ratio of pre-college children (the population aged 15 to 19) tothe working-age population (the population aged 20 to 64)).

More specifically, in a society

in which college expenses are high, one would expect parents with pre-college children to
save for their children’s college expenses and therefore that the aggregate householdsaving rate will be higher, the higher is the share of parents with pre-college children.

Bycontrast, in a society in which pre-college expenses such as the expenses of cram schools,
private tutoring, etc., are high, one would expect parents with pre-college children to haveto draw down their savings in order to pay for such expenses and therefore that theaggregate household saving rate will be lower, the higher is the share of parents withpre-college children (see Horioka (1985) for an analysis of saving for education in Japan).
This variable was included only in the case of Korea because its coefficient was not
significant when included in the regressions for India, perhaps because educational
expenses are not as important in India as they are in Korea, which in turn may be due
partly to the fact that the practice of sending pre-college students to cram schools, hiring
private tutors for them, etc., is far less common in India and partly to the fact that a much
lower proportion of the young go to college in India.4

As of 2010, 39.8% of the population

aged 25 and above had completed tertiary level education in Korea whereas thecorresponding figure for India was still only 9.1%, according to data from Barro and Lee(2016).

4

The regression results for India with the POP1519 variable included are available upon request fromthe authors.

145. Data Sources

In this section, we describe the data sources from which our data were taken.

National accounts data for Korea on the net saving and net disposable income ofhouseholds and non-profit institutions serving households and net corporate saving(needed to calculate HHSR, PCY, and CORPSAV) were taken from Organisation for
Economic Co-operation and Development (2016), while similar data for India were takenfrom CEIC data manager, WEB (New York, N.Y.), which in turn were taken from Central
Statistics Office (2016).

In both countries, PCY was calculated by dividing net household disposable income bytotal population, then deflating by the price deflator for private consumption expenditure.
In the case of India, the price deflator was obtained by dividing nominal private
consumption expenditure by real private consumption expenditure using data fromCentral Statistics Office (2016).

In the case of Korea, the price deflator was taken

directly from Organisation for Economic Co-operation and Development (2016).

DEP, AGE, SEXRATIO, and POP1519 were calculated using data taken from United
Nations (2016).

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6. Estimation Results

In this section, we present our estimation results.

6.1. Time Series Properties of the Variables

We tested the variables used in our analysis for unit roots using the Dickey-Fuller test,
Augmented Dickey-Fuller test, KPSS test, and Zivot-Harvey test (see Dickey and Fuller(1979), Kwiatkowski, et al. (1992), Zivot and Andrews (1992), and Harvey, Leybourne, andTaylor (2013)).

The detailed test results are not shown due to space limitations, but wefound that all of the variables used in our analysis are non-stationary.

In particular,

most or all tests showed that HHSR, PCY, and CORPSAV are I(1) and that DEP, AGE,SEXRATIO, and CREDIT are I(2) or I(3) in the case of India.

Similarly, most or all tests

showed that HHSR, CORPSAV, and CREDIT are I(1), that SEXRATIO and FINA are I(1)or I(2), that DEP and AGE are I(2) or I(3), and that the degrees of integration of PCY and
POP1519 are not clear in the case of Korea. Thus, there is a real danger that ordinary
least squares will lead to spurious correlations, and the use of cointegration techniques isclearly warranted.

6.2. Results of the Tests for Cointegration

We tested for cointegration using the Engle-Granger test (Engle and Granger (1987)), the
KPSS test (Kwiatkowski, et al. (1992)), and the Johansen test (Johansen (1988, 1991) andJohansen and Juselius (1990)).

Looking first at the results of the Engle-Granger test and16the KPSS test (see Tables 1-1 and 1-2), the results for all specifications for both countries
indicate the presence of cointegration, implying the presence of a long-term relationshipamong the variables.

Turning to the results of the Johansen test (not shown due to space limitations), the trace
test as well as the maximum eigenvalue test indicate the presence of cointegration in bothcountries for all specifications.

As for the number of cointegrating vectors, the trace test

as well as the maximum eigenvalue test indicate the presence of 2 to 5 cointegrating
vectors in the case of India and 2 to 4 cointegrating vectors in the case of Korea.

A priori

we would expect to find only one cointegrating vector and it is well-known that the
Johansen test will lead to an upward bias in cointegrating rank in small samples (see, forexample, Cheung and Lai (1993) and Johansen (2002)).

Thus, when estimating thecointegrating vector, we constrained the number of vectors to be one.

6.3. The Determinants of Household Saving Rates in India and Korea

In this subsection, we present our estimates of the cointegrating vector, which shed lighton the determinants of the household saving rate in India and Korea.

The results for

India are shown in Table 2-1, and as can be seen from this table, the coefficient of
SEXRATIO is negative and significant in both variants, as expected.

As for thecoefficients of the other variables, the coefficients of AGE and DEP are negative andsignificant, as predicted by the life cycle hypothesis, the coefficient of PCY is positive andsignificant, as expected, the coefficient of CORPSAV is negative and significant, as
expected, and the coefficient of TREND is negative and significant, indicating a downward

17

trend in the household saving rate.

The results for Korea are shown in Table 2-2, and as can be seen from this table, thecoefficient of SEXRATIO is positive and significant in every variant, as expected.

As forthe coefficients of the other variables, the coefficient of DEP is always negative andsignificant, as expected, but the coefficient of AGE is always positive and significant in all
but one variant, contrary to expectation.

Perhaps this is because Koreans continue tosave even after retirement because they are risk-averse (and concerned in particular about
longevity risk) and/or because they want to leave a bequest to their children.

Thecoefficient of PCY is positive and significant, as expected, the coefficient of CORPSAV is
positive and significant, contrary to expectation, the coefficient of POP1519 is negativeand significant, presumably because the cost of cram schools, private tutoring, and otherexpenses of pre-college students lowers the saving rate of households with pre-college
children, and the coefficient of TREND is negative and significant, indicating a downward
trend in the household saving rate.

Thus, the results are highly satisfactory, in general, and provide support for the life cycle
hypothesis in both India and Korea, and in particular, the coefficient of SEXRATIO has
the expected sign (negative in India and positive in Korea) and is always significant inboth countries.

This suggests that the “competitive saving hypothesis” of Wei and Zhang(2011a) and Du and Wei (2013) applies not only in China but also in India and Korea andthat unbalanced pre-marital sex ratios elevate the household saving rate.

We turn now to the implications of our findings for whether trends over time in the18

pre-marital sex ratio can explain trends over time in the household saving rate in India
and Korea.

Looking first at the case of India, the negative impact of the pre-marital sex

ratio on the household saving rate implies that the downward trend in the pre-marital sex
ratio until 1993 can explain the upward trend in the household saving rate until 1993 butthat the upward trend in the pre-marital sex ratio after 1998 cannot explain thecontinuing upward trend in the household saving rate after 1998.5

Looking next at the case of Korea, the positive impact of the pre-marital sex ratio on thehousehold saving rate implies that the upward trend in the pre-marital sex ratio
throughout the 1975-2011 period can explain the upward trend in the household savingrate until 1998 but not the downward trend therein after 1998.6

Turning next to whether the level of the pre-marital sex ratio can explain the level of thehousehold saving rate in India and Korea, the fact that the pre-marital sex ratio has anegative impact on the household saving rate in India and the fact that the India’s
pre-marital sex ratio is higher than average imply that India’s household saving rate
5

If the coefficient of the pre-marital sex ratio became positive after 1998, the upward trend in the

pre-marital sex ratio after 1998 would be able to explain the upward trend in the household saving rate,
but when we tried introducing an interactive term between SEXRATIO and a dummy variable that
equals one for all years after 1997 and zero otherwise, we found that the coefficient of SEXRATIO not
only remained negative after 1997 but that its absolute magnitude increased even further.

6

If the coefficient of the pre-marital sex ratio became negative after 1998, the upward trend in the

pre-marital sex ratio after 1998 would be able to explain the downward trend in the household saving
rate, but when we tried introducing an interactive term between SEXRATIO and a dummy variable that
equals one for all years after 1997 and zero otherwise, we found that the coefficient of SEXRATIO not
only remained positive after 1997 but that its absolute magnitude increased even further.

19

should be lower than average. Thus, India’s pre-marital sex ratio cannot explain India’s
higher than average household saving rate.

Turning to the case of Korea, the fact that the pre-marital sex ratio has a positive impact
on the household saving rate and the fact that Korea’s pre-marital sex ratio was below
average until 1983 and above average thereafter implies that her household saving rateshould have been below average until 1983 and above average after 1983.

Thus, thepre-marital sex ratio can explain the high level of Korea’s household saving rate during
the 1984-2000 period but not the high level thereof before 1984 nor the low level thereof
after 2000.

As for the impact of the age structure of the population, since DEP was found to have anegative impact on India’s household saving rate, the steady decline in DEP during theperiod of analysis can help explain the steady increase in India’s household saving rateduring this period.

AGE was also found to have a negative impact on India’s householdsaving rate, but since it increased only slowly during the period of analysis, it did not havean appreciable impact on trends over time in India’s household saving rate during thisperiod, and India’s household saving rate showed a steady increase despite the slightdownward pressure exerted on it by the slow increase in AGE.

In the case of Korea, both DEP and AGE exerted upward pressure on the household savingrate during the period of analysis because DEP declined over time and has a negative
impact on the household saving rate while AGE increased over time and has a positive
impact on the household saving rate.

Thus, trends in the age structure of the population20

can explain the upward trend in Korea’s household saving rate during the 1975-78,
1980-88, 1997-98, 2002-04, and 2008-09 periods but cannot explain trends in Korea’s
household saving rate during other periods.7

7. Conclusions

In this paper, we estimated a household saving rate equation for India and Korea using
long-term time series data for the 1975-2010 period, focusing in particular on the impactof the pre-marital sex (or gender) ratio (the ratio of males to females) on the householdsaving rate.

To summarize the main findings of the paper, it found that the pre-maritalsex ratio has a significant impact on the household saving rate in both India and Korea,
even after controlling for the usual suspects such as the aged and youth dependency ratios
and income.

It has a negative impact in India, where the bride’s side has to pay

substantial dowries to the groom’s side at marriage, but a positive impact in Korea, where,
as in China, the groom’s side has to bear a disproportionate share of marriage-related
expenses including purchasing a house or condominium for the newlywed couple.

7

The

Finally, we estimated an error correction model to analyze the short-run dynamics of household saving

behavior.

The results are not shown in detail because they were not very satisfactory, but we provide abrief summary here.

In the case of India, virtually none of the coefficients including that of the error

correction term were significant.

In the case of Korea, the coefficient of the error correction term was

negative and significant in some cases, indicating some tendency to return to equilibrium after adeviation.

None of the other coefficients were consistently significant, and moreover, their signs were

almost always contrary to expectation.

These results suggest that the variables included in the analysis

cannot adequately explain short-run household saving behavior, which is not surprising because most of
the variables included in the analysis are variables that would be expected to have a longer-term impact
on household saving behavior.

21

findings of the paper imply that trends in the pre-marital sex ratio can explain trends inthe household saving rate during the first half of the sample period but not during thesecond half in both countries and that the level of the pre-marital sex ratio can partly
explain the high level of Korea’s household saving rate but not the high level of India’s
household saving rate.

In sum, unbalanced pre-marital sex ratios combined with excessive and asymmetricmarriage-related expenses have distorted the saving behavior of households in bothcountries. Du and Wei (2013) conduct a welfare analysis using numerical calibration
methods and show that, in China, the welfare of males decreases while that of females
increases and that social welfare (the sum of the welfare of all males and all females)
decreases as the sex ratio increases.

Thus, the welfare of males as well as social welfare

could be increased by bringing the sex ratio back into balance in Korea, where marriage
customs are similar to those in China, and conversely in India, where marriage customs
are the opposite of those in China.

Another policy implication relates to saving-investment imbalances and current accountimbalances.

Wei and Zhang (2011a) and Du and Wei (2013) show that more than half of

the increase in China’s household saving rate was due to the sharp increase in the
pre-marital sex ratio and that about half of China’s current account surplus was due to her
unbalanced sex ratio. Similarly, saving distortions caused by unbalanced sex ratios mayvery well affect saving-investment imbalances and current account imbalances in India
and Korea as well.

22

A related policy implication of our results relate to the so-called worldwide saving glut.
Our results imply that the imbalanced sex ratios in India and Korea are causing India’s
household saving rate to be lower than it would be otherwise and Korea’s householdsaving rate to be higher than it would be otherwise.

Thus, the net impact of imbalanced

sex ratios on worldwide saving is ambiguous.

Turning finally to how to reduce or eliminate the distortions in household saving behavior
caused by unbalanced pre-marital sex ratios in the first place, there are at least 3 possible
ways: (1) to eliminate son (or daughter) preference, (2) to relax or abolish population
control measures, and (3) to reduce excessive and asymmetric marriage-related expenses.

There is a long tradition of son preference in Asian societies because the eldest son
traditionally carries on the family line or the family business, and it is therefore not easy
to weaken this long-held tradition.

However, Das Gupta, et al. (2009) argues that Korea

did precisely that through direct policy measures although Hvistendahl (2011) disputes
this claim (see Golley and Tyers (2014)), and thus weakening son preference is apotentially effective way of eliminating the distortions in household saving behavior
caused by unbalanced sex ratios.

Turning to population control measures, they have been implemented in many developing
countries as a way of keeping population growth down and raising living standards, but
the most extreme example is the one-child policy in China (see Golley and Tyers (2012) foran excellent overview of population control measures in China and India).

Relaxing or

abolishing population control measures would enable parents to have the desired number23

of children and, at the same time, eliminate the distortions in household saving behavior
caused by unbalanced sex ratios, thereby enabling two birds to be killed with one stone.
The Chinese government’s relaxation of its one-child policy in rural areas and certain
cities in the early 1980s (see Golley and Tyers (2012)) and its sudden decision to abolishthe one-child policy altogether starting in 2016 are examples of policies that weakened orabolished population control measures.

Finally, the marriage customs that led to excessive and asymmetric marriage-related
expenses have a long tradition and hence would be hard to change, but abolishing suchcustoms would reduce the financial burden on parents of newlyweds and, at the same time,eliminate the distortions in household saving behavior caused by unbalanced sex ratios,
thereby enabling two birds to be killed with one stone.

India’s efforts to prohibit dowries

via legal means is one example of such a policy.

Moreover, policies to weaken son preference and policies to reduce excessive andasymmetric marriage-related expenses would also lead to greater gender equality, which
in turn would lead to a decline in sex-selective abortions and infanticide and in the
dowry-related harassment and even murder of women, and hence would be beneficial forthat reason as well.

Thus, policies to eliminate son (or daughter) preference, to relax or abolish population
control measures, and to reduce excessive and asymmetric marriage-related expenses arehighly beneficial because they would not only eliminate the distortions in householdsaving behavior caused by unbalanced sex ratios but also because they would allow

24parents to have the optimal number of children, reduce the financial burden of
marriage-related expenses, and achieve greater gender equality.

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Figure 1-1: Trends over Time in the Pre-Marital Sex Ratio in India

1.105

Pre‐marital sex ratio

1.100
1.095
1.090
1.085
1.080
1.075
1.070
1.065

Year

Figure 1-2: Trends over Time in the Pre-Marital Sex Ratio in Korea

1.140

Pre‐marital sex ratio

1.120
1.100
1.080
1.060
1.040
1.020
1.000

Year

Notes: The pre-marital sex ratio is calculated as the ratio of males to females in the
pre-marital cohort (defined as the 10-19 age group in the case of India and the 15-24 age
group in the case of Korea). The data are taken from United Nations (2016).
32

Figure 2-1: Trends over Time in the Household Saving Rate in India

Household saving rate (%)

30
25
20
15
10
5
0

Year

Figure 2-2: Trends over Time in the Household Saving Rate in Korea

Household saving rate (%)

30
25
20
15
10
5
0

Year

Notes: The household saving rate is computed as the ratio of net household saving to net
disposable household income (in percent).

The data are taken from Central Statistics

Office (2016) in the case of India and Organisation for Economic Co-operation andDevelopment (2016) in the case of Korea.

33

Table 1-1: Results o f Engle -Grange r and KPSS Co integratio n Te sts fo r India
Specification
Type of test
Time period
Number of obs
Statistic
DEP, AGE, SEXRATIO,
DF
1975-201035-3.389**PCY
ADF(1)
1976-201034-2.757*
ADF(2)
1977-201033-3.082**
KPSS0
1975-201035
0.0846
KPSS1
1976-201034
0.0581
KPSS2
1977-201033
0.0476
DEP, AGE, SEXRATIO,
DF
1975-201035-3.533**
PCY, CORPSAVADF(1)
1976-201034-2.773*
ADF(2)
1977-201033-3.088**
KPSS0
1975-2010
35
0.083
KPSS1
1976-201034
0.0583
KPSS2
1977-201033
0.048

Notes: This table shows the results of Engle-Granger and KPSS tests for cointegration for
India.

Refer to the main text for variable definitions, data sources, and details on thesetests.

*, **, and *** denote significance at the 10, 5, and 1 percent levels, respectively.

34

Table 1-2: Re sults of Engle -Grange r and KPSS Cointe gratio n Te sts fo r Ko rea
Specification
Type of test
Time period
Number of obs.
Statistic
DEP, AGE, SEXRATIO,DF
1976-201035
PCY-2.933*
ADF(1)
1977-201034-3.130**
ADF(2)
1978-201033-2.522
KPSS0
1976-2010
35
0.227
KPSS1
1977-2010
34
0.143
KPSS2
1978-2010
33
0.119
DEP, AGE, SEXRATIO,DF
1976-2010
35
PCY, CORPSAV-3.498**
ADF(1)
1977-201034-3.569**ADF(2)
1978-201033-3.340**KPSS01976-2010
35
0.156
KPSS1
1977-2010
34
0.106
KPSS2
1978-2010
33
0.094
DEP, AGE, PCY,DF
1976-201035
SEXRATIO, POP1519
0.094
ADF(1)
1977-201034-4.975***
ADF(2)
1978-201033-5.267***
KPSS0
1976-201035
0.0382
KPSS1
1977-201034
0.0291
KPSS2
1978-2010
33
0.0306
DEP, AGE, SEXRATIO,DF
1976-201035-3.938***PCY, POP1519, CORPSAVADF(1)
1977-201034-5.368***
ADF(2)
1978-201033-4.595***
KPSS0
1976-201035
0.0465
KPSS1
1977-2010
34
0.0342KPSS2
1978-2010
33
0.0363

Notes: This table shows the results of Engle-Granger and KPSS tests for cointegration for
Korea.

Refer to the main text for variable definitions, data sources, and details on thesetests.

*, **, and *** denote significance at the 10, 5, and 1 percent levels, respectively.

35

Table 2-1: The Determinants of Household Saving in India
Model 1Model 2
Variable
DEP-32.976 ***-10.949 ***-8.11-75.74AGE-176.326 ***-6.71-147.382 ***-116.67

SEXRATIO-95.957 ***-11.06-12.868 ***-45.81

PCY

500.234 ***13.60

164.063 ***162.06CORPSAV-1.621 ***-72.92

TREND-29.307 ***-11.30-4.748 ***-61.91

Constant

14394.880-3622.178

Sample period
No. of obs.

1979-201032

1979-201032

Notes: This table shows the cointegrating vector estimated using the Johansen methodwith 4 lags.

The dependent variable is the household saving rate. Refer to the main

text for variable definitions and data sources. *, **, and *** denote significance at the 10,
5, and 1 percent levels, respectively.

36

Variable
DEP

Table 2-2: The Determinants of Household Saving in Korea
Model 1Model 2Model 3-2.439 **-5.552 ***-14.466 ***-2.16-27.23-72.44Model 4-5.532 ***
-8.52

AGE

8.396
1.44

27.697 ***26.41

71.753 ***77.84

20.347 ***7.87

SEXRATIO

3.705 ***
2.72

8.740 ***
40.06

27.575 ***52.70

5.728 ***
4.15

PCY

50.533 ***3.69

117.770 ***45.97

255.900 ***76.30

111.328 ***11.69

CORPSAV

0.460 ***
15.26

POP1519

TREND

Constant
Sample period
No. of obs.

-9.962 *-1.89-635.572
1979-201032-28.600 ***-30.10-1452.321
1979-201032

0.450 ***
3.28
-0.035 ***-18.33-0.033 ***-5.42-72.134 ***-74.12-24.900 ***-8.64-3894.049
1979-2010
32-923.198
1979-201032

Notes: This table shows the cointegrating vector estimated using the Johansen methodwith 4 lags.

The dependent variable is the household saving rate. Refer to the main

text for variable definitions and data sources. *, **, and *** denote significance at the 10,
5, and 1 percent levels, respectively.

37