From Singlehood to Marriage
Elizabeth Ong Ling Lee
Lee Kuan Y ew School of Public Policy
National University of Singapore
469 C, Bukit Timah Road, Singapore 259772
65166873
elizabethong@ nus.edu.sg
Abstract
Marriage is a key factor in Singapore’s fertility crisis: increasing marriage rates and
lowering the median age at first marriage have a direct bearing on the birth rate. However,
the trend of Singaporeans not marrying or marrying later has persisted for several years.
The two reasons most frequently cited for not marrying are: not having met a suitable
partner, and choosing to concentrate on studies or career. To explore the dynamics of
available singles in search of a life partner, System Dynamics modeling is used to find the
answers to the following questions: What goes on in the search for someone eligible? What
factors influence the success of such a search? What are the variables affecting decisions to
get married or wait for a better match? What is the relative importance of different sets of
variables in influencing such decisions? Some of the findings are that ample supply and
consumption of match-making services is counter-productive; and that engaging the help of
external parties such as employers, community and religious bodies, educational
institutions, professional associations and others to create group participation opportunities
for singles can do much more for the marriage rate than relying predominantly on private
dating agencies.
Key words: singlehood, marriage, life-partner, match-making, Singapore
1. INTRODUCTION
Like many countries in Asia, Singapore has experienced rapid decline in the total
fertility rate (TFR)! of its resident population since the 1950s. For more than three
decades now, the TFR has been below the replacement rate of 2.1. In 2013, the TFR of
this island-state in Southeast Asia was 1.29.
This persistent low fertility, coupled with increasing life expectancy’, has led to a
shrinking and ageing citizen population. Out of a total population of 5.4 million as of
June 2013, there were only 3.31 million Singapore citizens. 0.53 million permanent
residents and 1.55 million non-residents, comprising mainly foreign workers and
students, formed the remainder of the population (Department of Statistics, 2013). The
natural growth in citizen numbers has been decreasing steadily over the years, and will
begin to decline from around 2025.
While the government has been successful in attracting immigrant labour and new
citizens to help sustain the economy and keep the population decline in check, their
efforts to increase its TFR have been far less successful.
Marriage - a Key Factor in Singapore’s Fertility Crisis
The TFR, while a useful indicator for tracking fertility trends, may not be a suitable
measure for population planning. Even if it could be increased to 2.1, the population
would not be able to replace itself unless the TFR was maintained at 2.1 over a long
period of time. It has been suggested, by Cheung (2009) that a more accurate measure
would be to look at the number of births by birth cohorts and to study inter-cohort
changes, and that the key to increasing the birth rate lay in increasing marriage rates and
lowering the median age at first marriage.
However, the trend of Singaporean citizens not marrying or marrying later has persisted
for several years. From 2000 to 2011, the proportion of citizens who remained single in
the 30 to 34 age group increased from 33% to 44% for males and from 22% to 31% for
females. Those who got married did so later: in the same period, the median age at first
marriage increased from 28.5 to 30.1 for males and 26.1 to 27.8 for females. (National
Population and Talent Division, 2012)
Singapore is not alone; this trend is indeed regarded as a “regional transition to new
behavior” in Asia, triggered by social and economic changes. These include the erosion
of traditional practices such as arranged marriages, greater opportunities for education
for young people, changing aspirations and expectations and an increase of females in
the labour force. These have led to changes in attitudes towards singlehood, marriage
and parenthood, resulting in sharply declining fertility levels in Asia, where
childbearing occurs primarily within marriage.
Singapore’s Solution: The Social Development Network
Yet, marriage remains desirable to Singaporeans. The Marriage & Parenthood (M&P)
Study 2012, a survey commissioned by NPTD (2012) to understand the attitudes and
motivations behind Singapore residents’ marriage and parenthood trends, reported that
83% of the single respondents indicated their desire to get married. The two reasons
most frequently cited for not marrying were: (1) not having met a suitable partner, and
(2) desire to concentrate on studies or career.
In 2008, the budget promoting marriage and parenthood was doubled with the
introduction of the enhanced M&P Package (Ministry of Finance, 2009). This package,
which was further enhanced in 2013, mostly included incentives and initiatives to
encourage married couples to have more children and to support better work-life
balance.
To boost marriage rates, the package had enhanced programmes for singles. This
involved the merging of the 25-year-old Social Development Unit (SDU) and Social
Development Services (SDS) into the Social Development Network (SDN). SDN
would be “the centre of the entire dating network”, responsible for developing,
accrediting and collaborating with private match-making agencies to support singles in
their search for life partners. With SDN, it was hoped that the decline in marriage rate
and delay in marrying could be reversed.
. PURPOSE OF THE INVESTIGATION
To explore the dynamics of available singles in search of a life partner, System
Dynamics modeling is used to find the answers to the following questions:
e What goes on in the search for someone eligible? What factors influence the
success of such a search?
e What are the variables affecting decisions to get married or wait for a better
match? What is the relative importance of different sets of variables in
influencing such decisions?
e What suggestions can be offered in support of SDN’s role as the centre of
Singapore’s dating network?
. CONCEPTS & CAUSAL RELATIONSHIPS
The system dynamics model in this paper was created in 2008 based on my mental
model — my knowledge and understanding, gained through observation, personal
experience and reflections. Through these, I developed the concepts relevant to the
dating process. These concepts centred on the enquiry “What is the role of
introductions, dating and match-making services in the search for a life partner?” and
“What factors influence delays in making a life partner selection after an eligible
candidate has been found?”
From a survey of the available literature then, I could not find studies or secondary data
that were sufficiently relevant to the line of inquiry that I sought to pursue. In addition,
a fairly extensive search was made then for papers presented at past years’ Intemational
System Dynamics Conference, with the hope of finding fairly similar models on the
search for a life partner, but none were found that dealt with this topic.
3.1 DATING DYNAMICS
Introductions, Dating Services & Social Groups
Firstly, any two persons would not become acquainted without either being introduced
through a third party or one of them first taking the initiative to introduce himself /
herself. Introductions are an essential precursor to relationships, regardless of whether
they occur naturally or are obtained by engaging the services of a match-making
agency.
A group-dating activity is comparable to a job fair that brings potential employers and
employees together, while a one-to-one arranged date for enrolled members of a dating
agency is like job interview, with both sides having initiated the encounter by signaling
their search intention. Chance meetings rarely occur, as one would not know which of
the strangers he/she passes is also looking for a life partner and the occasion for an
introduction is unlikely to arise.
A social group consists of two or more people who interact with one another and who
recognize themselves as a distinct social unit. Membership in social groups could occur
naturally such as through kinship’ or through voluntary or involuntary enrolment
(junior college, Philosophy class, prison, Residents’ committee, SDN, private dating
agency). They could be relatively long-term or middle-term (neighbourhood, place of
worship, place of work, gym membership) or short-term (1-week training workshop,
library talk, hospital stay).
In every age cohort of singles, a certain proportion would choose to remain single for a
period of time or even indefinitely. Other life priorities (studies/career), not having
enough money, not being ready or prepared for marriage and considering oneself too
young for marriage were among the top 5 reasons cited by single respondents in the
2012 M&P Study.
Available singles make up the rest of the cohort. Of these, those whom one finds
eligible would possess a set or sub-set of characteristics pertaining to educational level,
economic status, religious affiliation, beliefs, attitudes, values and aspirations.
Not every available single male (ASM) would be desirable as a life partner to a female
and vice-versa. Physical, emotional, intellectual attributes, personality traits and inter-
personal affinity play a part in affecting how desirable a person is to another.
[The model and explanation of Dating Dynamics is given on page 9.]
3.2. DYNAMICS OF SELECTING A LIFE PARTNER
When a single female (SF) meets an eligible male (EM) who in tum finds her eligible,
she may decide to wait for someone better to come along rather than pick him if she
believes that: (1) she can afford to wait, (2) she is likely to meet a reasonable number of
EM from whom she can find a better match and (3) she is likely to be desirable to future
EM whom she meets.
These three factors are captured in the following variables, which have been created for
the purpose of this model: (1) fertility lifespan category, (2) perceived personal
desirability and (3) expectations of cohort introductions to EM.
Fertility Lifespan Category (FLC)
This is an indicator of the amount of time a SF has before it is too late (in terms of
willingness and/or capability) for her to bear a child. For the purposes of this model,
we assume that a woman would be unwilling or unable to bear a child beyond 50
years of age. The FLC has three values: 5.44, 3.22 and 1, corresponding to the
median fertile no. of years of 24.5 for the age cohort 20 to 29, 14.5 for cohort 30 to
39 and 4.5 for cohort 40 to 49 respectively. The higher the SF’s FLC is, the longer
her fertility lifespan. The FLC as also conversely proportional to the Probability of
SF Making a Life Partner Selection: the higher the FLC (that is, the younger the
SF), the more likely the SF is to wait for a better match, and therefore the less likely
she is to make a life partner selection.
Perceived Personal Desirability (PPD)
This refers to the degree of desirability a SF perceives herself to have for EM in
mutually eligible introductions. Her self-perception is likely to be influenced by the
set of personal attributes that she has, and how much value she thinks males (and
society in general) value them.
The PPD has continuous values, from 0° to 1. In this model, a relatively high
average PPD of 0.7 is assumed for SF in the 20 to 29 age group®, and means “out of
10 EM, 7 will find me desirable”. The PPD initial value used in this model is a
cohort average. It is possible to obtain this average through survey methods. Like
the FLI, the PPD is also conversely proportional to the Probability of SF Making a
Life Partner Selection. The higher the PPD, the more desirable to future EM she
considers herself to be. An SF with high PPD would expect to have high chances of
pairing off with someone more eligible than any of those EM she has already met,
and is thus less likely to make a life partner selection from among them.
Expectations of Cohort Introductions to EM (ECI)
This is a multiplier reflecting the number of introductions to mutually eligible single
males that a SF expects she is likely to have while in the current age cohort. Her
estimation could be shaped by information available to her, or observations she has
made.
The ECI has continuous values from 0 to 1, and the ECI initial value used in the
model is a cohort average. Unlike FLC and PPD, it is directly proportional to the
Probability of SF Making a Life Partner Selection. An ECI of 0.1 or 1/10 indicates
an expectation of having 10 mutually eligible introductions while in the cohort,
while an ECI of 0.05 or 1/20 indicates an expectation of having 20 mutually eligible
introductions. Thus, the smaller the ECI, the less likely the SF would be ready to
commit to selecting as her life partner one of the EM that she has met.
[The model and explanation of Dynamics of Selecting a Life Partner are given on
page 9.]
4, MODELLING APPROACH
The dynamics of dating, life partner selection and marriage are highly complex. It
becomes many times more complicated when both sexes are included in the model.
Each sex may have unique variables affecting them. Single males, for instance, may
delay marriage due to army conscription, or opt for foreign brides or a homosexual
partner. Marriage is also not static. With divorce or the death of a spouse, one goes back
to singlehood and may or may not re-enter the marriage stock.
This model is designed with the possibility of it being used at a later stage to explore
Birth Dynamics. Thus, it focuses on stocks and flows affecting the Female Population,
as there is a natural progression from being single to being an ever married female with
no child, one child,
two children and so
on.
“From Singlehood to
Marriage” Model
Stage 1
Using 2008 statistics,
cy the model consists of
Single Female pen 2 stocks — the Single
soit Oe Female (SF)
Female Population population stock and
the Ever Married
Female (EMF)
population stock.
(Refer to STELLA
model on page 7.)
Each stock has inflows and outflows of birth, migration, ageing and death.
The 2 stocks are connected by one-way flows as SF in each age cohort (starting from 10
to 19 and ending with 40 to 49’) marry and thereby leave the SF stock to enter the same
cohort in the EMF stock. The EMF cohorts of reproductive ages 10 to 19 up to 40 to 49
contribute to the birth of new females going in the 0 to 9 cohort.
The accuracy of the model was checked by running it from 2008 to 2050 to determine if
the size of the Total Resident Population matched official projections. The graph and
its results are given below.
{9 EVERMARRIED FEMALES 2: TOTAL RES..NTPOPULATION 7 SINGLE FEMALES
;| st
Lae
ONDA 2 retain of EMF: SF od Tot Reet Pope en
The graph obtained from has output data consistent with official projections. The total resident
population increases by 23.75% from 3,679,402 in 2008 to 4,553,369 in 2050. Some reports have
predicted a population of 5 million in 2050, but this model is more accurate as its birth rates are
those of Ever Married Females. Most models, including Ruth-Hannon, base their birth rates on
all females
“From Singlehood to Marriage” Model — Stage 2
Next, taking the age cohort of 20 29, a sub-model is created to map out the interaction
of variables influencing single females’ decisions to get married. (See initial values in
Table 1 and STELLA model on page 8.)
STOCKS & CONVERTERS INTHE MODEL
VALUES
T_|NoofSF 248300
2 |NoofEMF 0
3_| Noof Smgle by Choice 0
T_| Noof Social Groups; Social Group Size 3,50
3 | Average Fraction of ASM Introduced to SF; Fraction of EM among ASM | 05:03
© _| Noof Introductions to ASM Outside of Social Groups 30
7 _| Probability of Staymg Single O15
[S| Fertility Lifespan Category 3
9 _| Perceived Personal Desirability 07
10 | Expectations of Cohort Introductions to EM O1
Table 2: Initial Values im the “From Singlehood to Marriage - Stage 2” model (#2008 data)
Items 4-6 are assigned estimated values based on what might be reasonably reflective of
the social contexts of SF. The model was run several times (using a 10-year period),
each time with the values of items 4-6 adjusted incrementally until a marriage rate close
to that of 2008 was reached. (Refer to graph below.)
@ 1: EVER AES 20.29 2: SINGLE. HOICE 20 29 3 SINGLE..ALES 20 29 4: Mertiage Rate
1
2
3
rt
—
; |
z] 150000 3
rs 006 + 3
+
By ae
1
z a
:] 9 =
i
] 250 5.00 7.50 19.00
Paget Years 11:46 PM. Thu, Nov 26, 2009
asf ? No of EMF, SF. S by Cnobe & Mantage Rate
The graph shows what happens to the initial cohort of 248300 SF im the 20 to 29 age group after|
10 years. The no. of SF is reduced by half to 121274. The no. of EMF (Ever Married Females)
rise from 0 to 100492 and the no of SC (Singles by Choice) rises from 0 to 26534 — 40.5% and
10.5% of the 20 to 29 SF population respectively. The Marriage Rate is 0.07] fallimg to 0.05 at
the end of 10 years, due to the no. moving into the SC stock.
STAGE 1: Two-cohort EVER MARRIED
Model of Single Females even ansieD ee
and Ever Married co
Females
BIRTHS
FRACTIONOF FEMALE BABIES
BIRTH RATE
NET MIG
RATE OS
NET MIG
09
DEATH RATE
COEFF FEMALES
09
RAT
TIME 09 e
019
EVER MARRIED
FEMALES 40.49
TOTAL PAPULATION Pecan
OF FEMALES IN
POPULATION
RATIO OF EVER MARRIED FEMALES
TO FEMALES
EVER MARRIED oO
FEMALES 1019,
Terme
1019 MARRYING 10 29
our 019
DEATH RATE DIE 2029 NET MIG
COEFF FEMALES 2029 MARRYING 20.29
Time 209
“_, NET
DIE EM EM 20 2
DEATH RATE
COEFF FEMALES
AME EM
2029
ouTem
2029
N
EVER MARRIED
FEMALES 30 39
MARRYING 20 39
DEATH RATE
COEFF FEMALES
3039
The model maintains the
same pattern throughoutand
ends with the age 80 & up.
ime 30 39
Our 30 39
O 9
RATE 40 49 MARRIAGE RATE
COEFF FEMALES 40 49
STAGE 2: From DYNAMICS OF SELECTING A LIFE PARTNER
Singlehood to Marriage
Model for Age 29 to 29 The marriage rate is influenced by the probability of
Cohort the single female making a life partner selection,
which is in tun influenced by FLC, PPD and ECI.
SINGLE BY CHOICE
20 29
Probability
of SF Staying Single
seal Expectations of
Tntroductions to EM
while in Cohort
SF Making]Life Partner
Sejection
STAYING SINGLE
Time in Cohort
20 29
EVER MARRIED
FEMALES 2029
i=
li r Fraction of Intros
WORRY, Where EM Finds SF Eligible
AVAILABLESF Time in Cohort
‘Stal No of Mutually —With|Mutual
Eligible Intros
Available SF
Social Group
Size
No of Intrgs to ASM
in All Social Groups
Actual No of Intros
toEM
All Zocial Groups
Actual No of Intros to AGM
Social Groups
Fraction of EM
No of Intros among ASM
‘Average Fraction to ASM Outside of
of ASM Social Groups
DATING DY NAMICS
A single female’s chances of marrying depend on the no of mutually eligible introductions she has,
which is influenced by the no of social groups she belongs to, the size of the groups, the fraction of
available single males she meets, and so on.
10
5. HY POTHESIS-TESTING & ANALYSIS OF RESULTS
Sensitivity analyses are carried out with the .... to compare the effect of the variables on
following variables...
¢ Perceived Personal Desirability (PPD) © The Number of Ever Married Females at the end
¢ Fertility Lifespan Category (FLC) of 10 years
. of Cohort Introductions (ECI) © The Fraction of Ever Married Females in the
* No of Social Groups (NSG) Female Population at the end of 10 years
* Fraction of Eligible Males Among Available ¢ The Marriage Rate
Single Males Introduced to SF (FEM)
To set up a basis for comparison, each of the variables is assigned a pair of values with a percentage
difference of 444%. This figure is chosen as the percentage difference between the 2 end values of
FLC, which are 5.44 and 1. At any one time, only one variable was changed to see its effect on the
number and fraction of ever married females and the marriage rate.
5.1 EFFECT OF VARIABLES ON THE NO. OF EVER MARRIED FEMALES
@ EVER WARRIED FEMALES 2029: 1-2-2-4-5-8-
t
229157 << ived personal desirability
oi
wa 3——— “ __ Fertile time running out
194091 ; — ing
1
2 Moderate perceived desirability
120142 Es i .
10002 a +-—— Expect 10 more intros while in cohort}
ee + Many fertile years ahead
66307 ae :
eee bg Expect 54.4 more intros
23083 t Se :
0 2 5. 7.0 10.00
Paget Years 10:28 PM Thu, Nov 28, 2009
=} ? Effect of 444% increase n ECI, FLC and PPD on No of EMF
Figure 1: Comparing the effects of PPD, FLC and ECI on the number of EMF
11
§@ EVER MARRIED FEMALES 2029: 1-2-2-4-
t
148802 4: +— 54.4% of ASM are eligible
ae
ing to 5.44 social
105660 + Pas pee Po tees Semen
La eo
Oe a Belonging to 1 social group
42430 ae ; et 10% of ASM introduced are eligible
40098 7 es
0 2. 5 7 10,
Paget Years 10:10PM Thu, Nov 28, 2008
ear ? Effect of 444% increase mn NSG & FEM on the no. of EMF
Figure 2: Comparing the effects of NSG & FEM on the number of EMF
5:2 EFFECT OF VARIABLES ON THE MARRIAGE _ RATE
@ Mariage Rate: 1-2-3-4-5-6-
1 0.
Low perceived personal desirability EF
ee
1
Fertile time running out 0.
-——1
Moderate perceived desirability “Ft
Expect 10 more intros ——— ; — ae =
Many fertile years ahead S
i 00 2h0 5. 7. 10.
EeeS OE Arms Baws Yeas 10:57 PM. Thu, Nov 28, 2008
aaF 2? Effect of PPD, FLC & ECI on Marriage Rate
Figure 3} Comparing the effects of PPD, FLI and ECI on the Marriage Rate
12
@® Mariage Rate: 1-2-2-4-
0.
54.4% of ASM are eligible in
|
Pp
a
Belonging to 5.44 ai
a
2
Belonging to 1 social group
10% of ASM introduced are eligible L =
00 2 5.00 7. 10.
Paget Yeas 11:02 PM Thu, Nov 28, 2008
3a ? Effect of NSG & FEM on Marriage Rate
Figure 4} Comparing the effects of NSG & FEM on the Marriage Rate
6. SUMMARY OF RESULTS
The System Dynamics modeling of the journey from Singlehood to Marriage reveals
interesting insights and counter-intuitive findings. The results are presented in Table 3 and
4 below.
6.1 RELATIVE IMPACT OF VARIABLES ON NUMBER OF MARRIED FEMALES
The results shown in Table 3 reveal that of the factors that decrease the number of Ever
Married Females, FLC has the greatest impact, followed closely by PPD and ELC. The
significant degree of impact generated by these variables means that these are strong
motivating factors for SF to either postpone or commit to selecting a life partner from the
mutually eligible males available to her.
This suggests that younger SF, as well as those who regard themselves as more attractive to
the opposite sex are significantly more likely to delay marriage decisions. Those who
expect to meet many eligible men while in their current cohort would also postpone
committing to any of those they have already met.
While belonging to more social groups renders SF more likely to get married, the fraction
of eligible males among the single and available men in these groups has almost double the
impact on pairing off.
13
With a 444% increase in Change in the No of Ever Percentage of
Married Females Female Population!!
Fertility Lifespan Category (FLC) 127784 (decrease) 51.5%
Perceived Desirability (PPD) 109015 (decrease) 43.9%
Expected Cohort Introductions (ELC) 77409 (decrease) 31.2%
Fraction of Eligible males among ASM Introduced 108704 (increase) 43.8%
No of Social Groups 63230 (increase) 25.5%
Table 3: Relative Sensitivity of Each of the 5 Variables in Influencing the Number of EMF
6.2 IMPACT OF VARIABLES ON FRACTION OF MARRIED FEMALES &
MARRIAGE RATE
It can be seen from Table 4 overleaf that the highest fractions of EMF (0.78 and 0.92
respectively) and correspondingly higher marriage rates (0.20 and 0.43 respectively) can be
attained with the following profiles of SF:
e Those in the older age cohorts (30 to 39 and 40 to 49).
¢ Those who regard themselves as being less desirable to males with whom they have
mutual eligibility.
In addition, if slightly more than half of the available single males introduced to SF are
eligible, the fraction of EMF in the total female population would be high — at 0.60, with a
correspondingly high marriage rate at 0.11. (Note: the marriage rate of SF 20-29 was 0.065
in 2012, and 0.07 in 2008)
14
‘Variables used in Sensitivity Analysis Noof Fraction | Marriage
(Applicable to all SF in the Cohort) EMF ofEMF® | Rate
FLC 1 194091 | 0.78 020
Fertility Lifespan Median of 4.5 fertile year: igf
Category 522 66307 027 0.04
Median of 24.5 fertile years left
[ 2D oI 229157 [092 a
Perceived Personal | Perceive themseivesas desirable toon 10%of
Desirability males with whom they Arve mutual eligbiity
0.544 120142 048 0.08
Perceive themselvesas desirable to ony 52.2%
of males with whom they have muna eligi
ECT Ol 100492] 04 0.06
Expectations of Expect to meet 10 more males with whom they
Cohort Introductions | Aave mutual eligbiiy while inthe cohort
to Eligible Males O01 Toss [009s [on |
Expect to meet 54.4 more eligible males while in
‘the cohort
[ NSG T 42430 [017 002
No of Social Groups | Belong to J social group
344 105660 043 0.07
Belong to 5.44 social groups
FEM ol 40098 016 0.02
Fraction of EM There is mutual eligidilip with 10%ofthe
amongASM available single males invoduwed to them
Introduced 0544 148802 | 0.60 on
There is mutual eligidilip with 54.4% ofthe
available singie males invodwed to them
Table 4: Comparison of the Effects of Specific Values of each of the 5 Variables on
(1) the Number & Fraction of EMF and (2) the Marriaze Rate
7, ANALYSIS OF RESULTS & RECOMMENDATIONS
7.1 Higher Chances of Match-making Success with Older SF
The results suggest that, all things being equal (i.e., with the rest of the assigned data in
the model being unchanged), the chances of success with SF in the 30 to 39 and 40 to
49 age cohorts are substantially and progressively (with advancement in age) higher
than those with younger cohorts. This is counter-intuitive, as there is a strong tendency
for private matching-making agencies and even goverment marriage promotion units
to neglect these age groups (especially those nearing and above 40) as they consider
their chances of success to be very low.
15
7.2
7.3
Moreover, private match-making agencies are profit-driven, and would concentrate
their resources on younger clients. These clients would be easier to find dating partners
for, and this would generate revenue with clients of the opposite sex. Y ounger clients
are also likely to use their services for a longer time in their search for better matches,
as they have time on their side. Likewise, government agencies, driven by the need for
output figures and success rates as indicators of their performance, would be motivated
to reach for the low-hanging fruit — young single females whose marriage and child-
bearing would help lift the country’s low fertility rate.
The results indicate, however, that stepping up efforts to help this group of SF
overcome the challenges in their search of a life partner will pay off handsomely. Such
efforts could include connecting them with dating / social groups that more closely
match their age, economic status and interests, and ensuring that these groups have a
high fraction of single eligible males open to marrying someone in this age group.
Low Perceived Personal Desirability Raise Chances of SF Committing to Marriage
The finding that low perceived personal desirability makes SF more likely to commit to
marriage (instead of waiting for someone better) has interesting implications for the
way match-making programmes are designed.
One possible inference is that group-dating may be more effective than one-to-one
dating as the presence of other single and available females may have the effect of
lowering an SF’s assessment of her chances of being picked from among many, and
thus raise her willingness to commit when she does find someone mutually eligible (not
necessarily at this group-date event). Thus, a possible approach could be to promote
more group-dating activities by making them more accessible (through lower cost,
perhaps) and more appealing (through thoughtful, sensitive and creative programme
design).
Better Profile-Matching A mplify Chances of Match-making Success
From the findings, it is clear that a critical feature of such groups is that the higher the
fraction of eligible males there are among those introduced, the higher the chances of
marriage taking place.
This suggests that matching-making agencies would do well to focus on interests,
beliefs and values in programme planning to pool singles with similar profiles together.
Group-dating activities could be organized around special interests such as pet-care,
photography, an environmental cause, animal protection, bowling, golfing, dancing
lessons, camp-craft, and recycling efforts. In planning for group dating activities,
allowing time flexibility in leaving and joining such groups would have the effect of
increasing the number of introductions (those that go beyond the cursory and
superficial ones) to available single males in the group over time.
7.4 Ample Supply & Consumption of Match-making Services is Counter-productive
Another important finding that can be gleaned from the table is that the number of
mutually eligible males that SFs expect to be introduced to has an enormous impact on
16
life partner selection. Both the EMF fraction and the marriage rate are very low at
0.093 and 0.01 when the number of expected introductions is 54.4, for instance. Such
expectations of introductions are influenced by the one’s own social life (the frequency
of interactions with new people) and the membership flows and ebbs of the social
groups (those outside of match-making agencies) that one is in. For those who have
joined match-making agencies, the line-up of activities offered, the cost of
participation, the nature of promotional packages, and one’s expected extent of
participation combine to influence the ECI.
This has important implications for matching-making agencies. Possible applications of
the results from the model would be to:
Avoid offering “cheaper if you buy more” promotions. In this context, to match-
making agencies, “pay less for more introductions” deals may bring in funds to
cover running costs, but such a move would delay marriage decisions. Such
delays would last as long as the lifespan of the package, so if the deal is that the
20 introductions could be used within 18 months, the delay would last as long.
This finding is counter-intuitive. Agencies may think they are supporting the
nation’s policy of promoting marriage and lowering the median age of marriage
through such promotions but the effect would be just the opposite!
As the number of introductions a SF can get from various match-making
agencies is practically unlimited, accessibility is a lever that can be used to limit
her expectations of introductions. Accessibility could be controlled through
pricing. Naturally, the goal is not to restrict SF from meeting eligible males, but
to limit her expectations of introductions. The pricing should therefore be
carefully calibrated: it should be high enough to prevent over-consumption of
services and yet be “value-for-money” through effective profile-matching to
ensure a high FEM (Fraction of Eligible Males). Discounted pricing for
subsequent purchases of packages (“buy this package and get the next one at
half price”) should be avoided, as this would encourage delays in committing to
marriage with someone whom the SF has already met and found mutually
eligible.
Besides pricing, other barriers such as criteria for participation in activities
could be erected. SF of a younger cohort could be kept out of groups meant for
older SF. This would not only reduce expectations of introductions; it would
address the problem of older SF being left out of the marriage market due to the
phenomena of single men marrying down (females of same age or younger; of
same economic status or lower) and SF marrying up (males of same age or
older; of same economic status or higher), while it is much less socially
acceptable for SF to marry down (younger males; of lower economic status) and
SM manying up (older females; of higher economic status)
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7.5 Developing a Holistic, Society-based A pproach is the Best Way Forward
The findings indicate that belonging to more social groups with a high proportion of
eligible males boosts marriage rates for SF. This implies that investing more resources
in engaging the help of extemal parties such as both public and private sector
employers, community and religious bodies, educational institutions, professional
associations and others to create group participation opportunities for singles with
common interests, passions, beliefs and values can do much more for the marriage rate
than relying predominantly on private dating agencies.
8. CONCLUDING REMARKS
This exploration of the dating and mate-selection process has an important end-goal: to
boost Singapore’s fertility rate by lessening marriage delays and involuntary
singlehood. The fact that this quest is shared by many Asian countries plagued with
these marriage trends and declining populations underscores the relevance and
importance of such an investigation. There are many exciting possibilities for further
exploration into singlehood, marriage and birth using the tool of System Dynamics
modeling. Examples of such investigations include the dynamics of other marriage
contexts (e.g. marriage between citizens and foreigners), marriage dynamics for smaller
population groups (e.g. females of minority groups, such as the Malay community and
Indian females in Singapore), the dynamics of birth, family size and community support
systems, and the effect of societal and economic factors on these policy situations.
References
1. Cheung P. (2009). Population Planning in a Low Fertility, High Migration, Rapidly
Ageing Demographic Regime”. Lunch Forum, Civil Service College, Singapore, 13
January 2009. Accessed October 2, 2009 from http://www.cscollege.gov.sg (The
report on this lunch forum is no longer available in this website.)
2. Department of Statistics. (2013). Population Trends 2013. Singapore: Ministry of
Trade and Industry. Retrieved from
http://www.singstat.gov.sq/publications/publications_and_papers/population_and_p
opulation_structure/population2013.pdf
w
. Ministry of Finance. (2008) Government doubles budget to provide more support.
Singapore. Retrieved October 5, 2009, from
http://app.mof.gov.sg/newsroom details.aspx?news_sid=20090930890967894267
4. National Population and Talent Division. (2012). Marriage and Parenthood Trends
in Singapore (Occasional Paper June 2012). Singapore: Prime Minister’s Office.
Retrieved June 12, 2014, from
http://www. nptd.gov.sg/content/dam/nptd/O ccasional% 20Paper% 200n%20MP%20
Trends%20_For%20Media%20Briefing%2028%20Jun%202012_w%20annex.pdf
18
5. National Population and Talent Division. (2012). The Marriage & Parenthood
(M&P) Study 2012. Singapore: Prime Minister’s Office. Retrieved June 12, 2014,
from
http://www.nptd.gov.sg/content/NPTD/news/_jcr_content/par_content/download_9
O/file.res/mp-study-2012-press-release.pdf
+ Total fertility rate refers to the average number of live-births each female would have during her
reproductive years if she were to experience the age-specific fertility rates prevailing during the period.
are
°s life i by 10 years over the last 3 decades: from 72 years in 1980 to 82 years
in 2010. (Source: Our Population Our Future, Issues Paper July 2012, National Population and Talent
Division, Prime Minister’s Office, Singapore)
3 However, in the context of dating, we do not include families as social groups.
“Here, we disti sh between eligibility and desirabili
desirable to an EM.
: An eligible SF eligible may not necessarily be
° Not inclusive of 0, as the reciprocal of 0, which is used in the model equation, would have an indefinite
value.
® Depending on cultural and social norms and values, the average PPD for older age cohorts may be higher or
lower.
7 Marriage statistics stop at 40 to 49 cohort, ostensibly due to the insignificant occurrence of marriage in older
cohorts.
® Tt should be noted that these 2 characteristics of age and perceived desirability could well be linked, but we
should not presume that they necessarily go together. A successful and attractive SF in her forties may regard
herself as a good catch, and may have a PPD of 0.6, for instance.
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