In our study, we refer childbearing subsidiary policies as child-care subsidies and baby bonus (Child Development Co-Savings Scheme). Most would agree that these subsidy policies, which reduce parent’s costs to raise babies, would lead to higher Total Fertility Rate. Total Fertility Rate (TFR) is defined as the number of children an average woman would have assuming that she lives her full reproductive lifetime [1]. Subsidy is generally defined as money granted especially by government to reduce the cost of service or of producing goods [2].

A study revealed that Australian Baby Bonus exerted a small positive effect on fertility [3]. The effect seemed to be stronger for second and possibly higher-order children. In addition the result showed that bonus effect is permanent. Other study conducted in United States evidently show that child-care is positively associated with the intentions to have further children among couples [4]. It is expected that by providing subsidies, number of children an average woman would have, would increase. However, the conclusion from past study could not determine that the result would be similar in local context since the researches are conducted in different demographical area. Our report will investigate the short-term and long-term effect of the policies and aim to provide a comprehensive solution to improve the fertility rate in Singapore.


For the past 30 years, Singapore has faced a serious problem of declining TFR (total fertility rate). With TFR of 1.16 in 2010 [5], Singapore is ranked 170th [6] in the world and arguably one of the lowest TFR in the world. This issue will lead Singapore to be an ageing society. Currently Singapore has 344,069 elderly residents in 2010; this amount is estimated to increase by 20% the year 2030. The situation causes some serious problems in productivity, national defence, and will be detrimental to the economy. Nowadays the Singapore government strongly encourages the Singaporeans to get married and have at least 2 children. To support the campaign, the country has provided various subsidies to help parents in raising their children.


Though subsidies have been given to the parents, the general statistics show that the Singapore TFR declines over the years. Several revisions such as increasing baby bonuses are done to make the subsidies even more helpful, but the result is still negative. Therefore, in our project, we would like to analyze in greater depth relating to Singapore subsidiary policies, investigate its short and long term impacts and research more about the perspective of our future generation with regards to government policy.

Scope of study:

Our research will focus primarily on the different government policies that are implemented to increase TFR. Other factors such as the environment, psychological-thinking, social factors which may affect TFRs will not be included. To make our research clearer and an all-rounded study, we have our attention only on childcare subsidies, baby bonus, educational subsidies, housing loans, maternity and paternity leave, and hospitalisation subsidies. To prevent discrepancy in interpretation, TFR is defined as the number of children an average woman would have assuming that she lives her full reproductive lifetime and the policies that we are looking at are pertaining to those implemented by the Singapore government only.

Research Methods:

Our study will focus on evaluating the effectiveness of government subsidy policies. Some of these policies had been revised over the years, to ensure that our analysis will be as accurate as possible, we will divide the discussion into 3 parts: short term, long term and future estimation. Short term is defined as 3 year after policy is implemented, long term will represent the general trend of the policy since it is implemented till present. Short and long term impacts will be analysed using data compiled from administrative records. Future estimation will be done through analyses of our obtained data from the survey.

In this study, a two-part survey will be conducted as well. The first part will identify the important factors that affect people’s decision to give birth. Subsequently, the second part will address the perspective of the young generation towards childbearing.

The survey questionnaire will include close –ended as well as open-ended questions. The target of our survey will be NTU students. The target sample size will be 100, of which 50 will be males and 50 will be females, after which the results will be collated and be analyzed further. With the results we will propose suggestions that will mould the policy towards greater effectiveness for the new, upcoming generation of Singaporeans.

The expected result for our analysis is that government-based policies are effective in the short term, after which ineffective in the long term. We will then review the suggested solutions in hope that the policy can work better.


Much research has been done to explore the effectiveness of government’s policies in increasing the fertility rate as the Singapore government found that they had a serious problem such as ageing population. Although many policies were conducted and revised many times, the fertility rate seemed to decline slightly recently. Therefore, our paper hopes that by investigating the various polices Singapore government has used to impact TRF, we can find out the root of the problem to Singapore’s persistent low TFR and propose reasons for it.

References: Biology-Online Dictionary (2007), Online dictionary.

2. Oxford Learner’s Pocket Dictionary (2008), Oxford University Press.

3. Drago, R., Sawyer, K., Sheffler, K., Warren, D., and Wooden, M. (2009), “Did Australia’s Baby Bonus Increase the Fertility Rate?,” Melbourne Institute Working Paper No. 1/09, University of Melbourne, Melbourne Institute of Applied Economic and Social Research.

4. Lehrer, E. L. and Kawasaki, S. (1985), “Child Care Arrangements and Fertility: An Analysis of Two-Earner Households,” Demography (Vol 22; no.4), pp. 499-513.

5. Department of Statistics Singapore (2011), Online statistics.

6. Total Fertility Rate 2010 (2010), CIA World Factbook 2010.