Gender Economics in Singapore
Herbert Au, Vice President (Special Projects & Innovation)
Applications of Gender-Disaggregrated Data in Gender Economics
Gender economics, the study of the role of gender in individual economic outcomes to provide a greater understanding of the world, has gained significant attention in recent years. This field has expanded to include studying the effects of financial crises on the different genders (Hozic et al., 2016), the causes and effects of the gender wage gap in America, and the effects of different levels of access to education on the labour market. With the advancements in econometric methods, economists have adopted multidisciplinary approaches like the collection of gender-disaggregated data to analyse phenomena.
Gender-disaggregated data is essential for studying gender issues and developing policies to alleviate them. Disaggregated data is data that is broken down into different demographic categories, such as gender, race, ethnicity, and occupation. Disaggregated data allows researchers to isolate the effect of specific variables on a variable of interest and control for other factors that might influence the outcome. For example, a researcher might be able to study the effect of education on a person’s income. Disaggregated data, used with techniques like machine learning and dual decomposition algorithms, enable the identification of causal relationships, helping develop more accurate financial forecasts and policy recommendations. Congruent with the growing recognition of the importance of disaggregated data, the International Monetary Fund (IMF) Executive Board approved the inclusion of gender in their key activities, “surveillance, capacity development, and lending” in June 2022. Through the collection of gender-disaggregated data, the IMF aims to assess the macroeconomic effects of gender gaps, evaluate the impact of events and policies on the different genders, and provide better “macroeconomic and financial policy advice” and “capacity development support” (Amr, 2022). Similarly, many countries have begun to collect such gender-disaggregated data. For example, Spain’s Gender Equality Law (Article 20) states that a variable for the individual’s gender must be methodically included by public authorities in their statistics (OECD, n.d.).
Gender-disaggregrated Data in Singapore
Singapore has made significant efforts to promote gender equality, and disaggregated data has played a critical role in informing these policy decisions. For instance, Singapore’s Ministry of Manpower (MOM) publicises quarterly gender-disaggregated data on topics like employment (Xiu, 2020). MOM has also conducted studies that disaggregate data by occupation, age, and education level to identify the factors that contribute to the gender wage gap. Disaggregated data can also help to identify the impact of other factors like caregiving responsibilities on the gender wage gap. By analysing these patterns, researchers can identify sectors with the largest gender disparity and develop policies to address these gaps. Such analysis has helped inform policies aimed at addressing the wage gap, such as encouraging employers to adopt fair and non-discriminatory hiring practices and promoting flexible work arrangements to support working parents.
Recent studies have shown that there are persistent disparities in income, labour force participation, and job opportunities between men and women in Singapore. The unadjusted gender pay gap in Singapore, for instance, stood at around 16.3% in 2018 and narrowed to around 14.4% in 2020 (Ministry of Manpower, 2022). Based on the Global Gender Gap Index 2022 Rankings, Singapore is ranked 49th in gender parity out of 146 countries with a score of +0.007 in 2022 (Pal et al., 2022). Comparatively, the Philippines are ranked 19th in gender parity and the United Arab Emirates is ranked 68th in gender parity.
To tackle this issue, disaggregated data in Singapore is used to support women's participation in the workforce. Policymakers analyse data on women's labour force participation rates and identify the specific factors that are driving women's decisions to leave the workforce or reduce their hours, such as caregiving responsibilities and a lack of affordable childcare. These studies inform policies such as the introduction of flexible work arrangements (Ministry of Manpower, 2022), which aims to provide women with a greater work-life balance and enables them to participate more fully in the labour market. Another measure is the implementation of gender diversity targets on the boards of listed companies (Ng, 2019), which aim to increase the representation of women in leadership positions. This has increased female board membership in Singapore Exchange-listed companies from 13% in 2019 to 24% in 2022 (Council for Board Diversity, 2022).
Disaggregated data has also been used in Singapore to address the different effects of the COVID-19 pandemic on men and women. According to Rao (17 June 2020), the COVID-19 pandemic is likely to reinforce the effects of gender inequality in Singapore. As the pandemic persists, inequities are indeed compounded as women bear most of the burden of housework and unpaid care work (IPSOS, 2021). Men are still viewed as primarily responsible for paid work, while women, even in higher-paying jobs, are expected to handle unpaid work such as monitoring children's homework, preparing meals, and keeping the home clean.
These disparities have caused significant imbalances in labour force participation rates. Labour force participation rates are the percentage of the population that is either working or looking for a job (Ministry of Manpower, 2022). Looking at Figure 1, the proportion of women working in the labour force steadily increased between 1990 to 2015. However, the proportion of women working in the labour force has fallen post-2019 due to the COVID-19 pandemic. Meanwhile, the male participation rate in the labour force has gradually shrunk since 1990. The downward trend in the labour force of men is attributed due to the life expectancy increase resulting in more retirees (Hirschmann, 2022) and more people pursuing higher education, leading to a smaller labour force participation (Ministry of Education, 2023).
Figure 1: Labour force participation rate, by sex (% of population ages 15+), purple: male, yellow: female (Gender Data Portal, 2022)
The Importance of Disaggregated Data
In conclusion, the use of disaggregated data has played a critical role in informing policy decisions to address gender equality issues in Singapore. While the gradual narrowing of the pay gap, increased access to gender-disaggregated data, and higher female board memberships are movements in the right direction, it is important to continue raising awareness and taking concrete steps to eliminate gender-based economic disparities. By analysing data at a more detailed level, policymakers are more able to identify the specific factors that contribute to gender-related issues and develop policies tailored to the specific needs of different groups. Moreover, as the COVID-19 crisis has amplified the effects of traditional gender roles, the importance of accessing complete and useful data is further heightened.
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