assumptions and less prone to biases. Second, while most previous studies analyze access to childcare in relation to traditional labor market outcomes, this paper complements that approach with time-use analysis to validate and enrich the labor market impacts, and to provide a more accurate depiction of the double burden of paid work and unpaid work on mothers of young children. In addition, it takes advantage of a unique feature of the dataset to analyze childcare performed as a secondary activity, capturing an important aspect of caregiving for working mothers: that a large part of childcare constitutes secondary supervision as opposed to full and active involvement in children’s activities throughout the day.<sup>5</sup> Finally, this study uses a unique dataset from the low-income neighborhoods of a megacity where FLFP has declined in recent years, with a particular focus on a population group that is constrained in their access to childcare and in their ability to withdraw from the labor force due to their socioeconomic status. Hence, the findings have direct policy relevance as they pertain to the urban context where FLFP trends have reversed and a population group that is most likely to benefit from targeted interventions to ease the double burden on mothers.

# **2. Data and Methodology**

# _2.1. Data_

This paper uses the Dhaka Low-Income Area Gender, Inclusion, and Poverty Survey data collected by the World Bank in low-income neighborhoods of Dhaka in 2018 (see Kotikula, Hill, and Raza 2019). The dataset is representative of slums and low-income areas of the Dhaka City Corporations (North and South) and the low-income areas of the Greater Dhaka Statistical Metropolitan Area. The slums include informal settlements listed in the Bangladesh Bureau of Statistics’ slum census of 2013/14. The low-income areas include non-slum census enumeration areas with a poverty rate of 8 percent or above. The households were sampled using a two-stage stratification process based on neighborhood population size (slums) and poverty rate (low-income neighborhoods).<sup>6</sup> In addition to interviewing the heads of households, an

> 5 Several studies on women's time use and childcare, including secondary childcare, discuss women’s disproportionate burden of childcare and its valuation (Bittman 1999, Ironmonger 2004, Mullan 2010, Floro and Miles, 2003, Floro and Pichetpongsa 2010). App and Rees (2005) assess the gender differences in the time allocation of women and men in Australia, Germany, and the United Kingdom based on access to childcare and the tax treatment of the female partner. However, they only consider situations in which childcare is provided as a primary activity, such as feeding or bathing the child, which likely underestimates the time women spent on childcare.

> 6 The first stage randomly selected the primary sampling units (PSUs) using probability proportional to size, based on the strata for low-income enumeration areas and slums. In the low-income PSUs, the first stratum consisted of enumeration areas with a poverty headcount ratio of 8–10 percent, the second stratum with a poverty headcount ratio 11–14 percent, and the third stratum with a poverty headcount ratio of 15 percent or above. In the slum PSUs, the first, second, and third strata consisted of slums that included 50–75 households, 76–99 households, and more than 100 households, respectively. In the second stage of sampling, 20 households were selected in each PSU for face-to-face interviews from three categories: (a) households with

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