reallocation; instead, they used the saved travel time for work.

Our analysis thus suggests that the disproportionately large burden of household work on married women precludes them from benefiting in the labor market to either search for jobs or work more. These women instead use the time saved from commuting to help their spouses and men residing in the household increase their labor supply. Gender roles within households and bargaining power undermine the effects of the policy. In the next subsection, we provide a simple model of optimal time allocation within the household to formalize these mechanisms and to explicitly state the assumptions needed for it to be consistent with the empirical results obtained above.

# **H.2 A Model of Intra-Household Time Allocation**

The reallocation of household chores from men to women, along with the reduction in labor supply among married women–specifically those with low and medium skills– could be driven by two mechanisms related to household-level decision-making aimed at maximizing joint utility. First, there may be a discrete shift from men to women in household chores that require a discrete amount of time. For example, a long commute by mothers may have previously made it optimal for the father to take their kids to school, perhaps on a bus. After the roll-out of free bus rides for women, this responsibility may be reallocated to the mother. The gender wage gap in India increases the likelihood of such re-optimization at the household level, as men typically earn more than women within the same household.<sup>38</sup> A second mechanism could be the nature of work typically performed by women, which, compared to men, is less likely to be full-time with a fixed wage.<sup>39</sup> Let’s consider the following example of part-time work: a low-skilled woman employed as a house cleaner, who must commute to a neighborhood with high socioeconomic status. Before the free rides program, she has a time-consuming commute on foot. This leads to an

> 38We use the PoI section data to identify husbands and wives, and the InP section data to determine individuals’ average monthly wages between January and March 2021, the three months prior to the scheme’s implementation. After matching data from these two sections, 21% of the observations did not respond to the income survey, raising concerns about potential selection bias. However, over 70% of those who failed to report income did so because interviewers were unable to reach the households during the designated time span. Among the matched sample with income observations, about 99% of the households reported the husband’s wage as being higher than or equal to the wife’s. In these households, husbands’ wages are, on average, twice as high as those of their wives.

> 39Fletcher, Pande and Moore (2017) show that the types of jobs Indian women report wanting vary by age, but are primarily of a part-time nature, reflecting the demands of other household responsibilities, particularly in the context of marriage and childbearing. 73% of women willing to take a job prefer regular, part-time work while only 22% report wanting regular, full-time work; the remaining 5% want a mixture of only occasional full or part-time work.

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