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Singapore's fertility rate is currently below 1.2, raising concerns about population ageing and long-term sustainability. The fertility decline is characterized by falling birth rates among women in their 20s with almost no recuperation among women in their 30s. This project explores a) whether informational imperfections help to account for high intended ages at childbearing in Singapore, b) whether informational interventions significantly affect ideal and expected ages at marriage and childbearing, and expected probability of undergoing social egg freezing, and c) whether informational interventions significantly affect expected and actual educational outcomes and labor market outcomes.
Our hypotheses are:
Full description
The project conducts a randomized controlled trial involving 1000 full-time undergraduate students at NUS. The trial has three stages.
In the first stage, participants will be recruited through campus advertisements.
In the second stage, participants who meet the eligibility criteria will complete a 30-40 minute online survey. The survey includes the following:
In the third stage, the students' responses are linked to the Educational Data Lake managed by ALSET, Provost's Office, NUS, which collects data on students' module choices (whether within the same major, in a different major within the same faculty or in a different faculty) and CAP in the following academic semester and at graduation, graduation status, and starting salary and employment status six months after graduation. All participants are informed and these linkages are mentioned in the consent form.
After the data collection is completed, we will analyse the data using a difference-in-differences econometric model. Our model compares three sets of dependent variables at different points in time:
The results are compared by gender, faculty, educational and career expectations, and other background characteristics, including dating history and mental wellbeing.
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1,000 participants in 3 patient groups, including a placebo group
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Data sourced from clinicaltrials.gov
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