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Facing a rapidly ageing population, Singapore is presented with urgent policy challenges. Yet there is very little data on the economic, health and family circumstances of older Singaporeans. In response, the Centre for Research on the Economics of Ageing (CREA) at Singapore Management University has been collecting monthly data on a panel of Singaporeans aged between 50 and 70 years. We detail the methodology by which the Singapore Life Panel® (SLP) was constructed using a population-representative sampling frame from the Singapore Department of Statistics. Contact was made with 25,000 households through postal, phone and in-person canvassing. More than 15,200 respondents from over 11,500 households enrolled in the panel. Comparisons between SLP and official statistics show close matching on age, sex, marital status, ethnicity, education, labor force status, income and expenditure. This suggests that the panel is a representative of Singapore’s elderly population. Monthly surveys continue to be administered over the internet, supplemented by phone and in-person outreach to ensure the panel remains representative and hence reliable for informing policy makers. Response rates are remarkably stable at over 8,000 per month. The SLP contains rich data on demographics, health status, socio-economic indicators, contact with government programs and subjective perceptions and is likely to be a key resource for economic research into ageing in Singapore.

Small business owners use a variety of bootstrap financing methods to acquire the needed resources necessary to survive and eventually grow their businesses. One such method is to lease equipment and/or machinery. Leasing is a viable alternative to bank financing and for small businesses, leasing is a flexible strategy to preserve cash. In this study, we analyze the impact of asset specificity and growth opportunities on leasing decisions of a large cohort of startup businesses. To test our hypotheses, we use a unique dataset provided by the Kauffman Foundation.¹ Our longitudinal analyses show that startups with unique/specific assets have a lower propensity to lease whereas startups with high growth opportunities are more likely to lease their assets. We also argue that the owners’ demographic and socioeconomic characteristics are likely to impact their individual risk-taking behavior. Thus, factors such as owners’ experience, education, age, gender, and race are likely to impact the decision to lease assets. Our results show that owners’ characteristics do have a significant impact on these decisions. The findings reveal that female and older entrepreneurs as well as highly educated owners are less likely to lease. Our work advances prior research on the determinants of leasing in large, publicly traded firms and provides additional insights on entrepreneurial bootstrapping.