Marriage, motherhood, and women's employment in rural India

Lahoti, Rahul; Abraham, Rosa; Swaminathan, Hema Working Paper Marriage, motherhood, and women's employment in rural India ADB Economics Working Paper Series, No. 757 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Lahoti, Rahul; Abraham, Rosa; Swaminathan, Hema (2024) : Marriage, motherhood, and women's employment in rural India, ADB Economics Working Paper Series, No. 757, Asian Development Bank (ADB), Manila, https://doi.org/10.22617/WPS240568-2 This Version is available at: https://hdl.handle.net/10419/310396 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/3.0/igo/ ASIAN DEVELOPMENT BANK ASIAN DEVELOPMENT BANK 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org MARRIAGE, MOTHERHOOD, AND WOMEN’S EMPLOYMENT IN RURAL INDIA Rahul Lahoti, Rosa Abraham, and Hema Swaminathan ADB ECONOMICS WORKING PAPER SERIES NO. 757 December 2024 Marriage, Motherhood, and Women’s Employment in Rural India Life cycle events—marriage and motherhood—often impact women’s labor force participation. However, these impacts are mediated by the context in which they occur including the type of labor market (formal or informal), economic status, and prevailing social norms governing gender roles. Using unique data from two states in India, the paper finds that contrary to expectations, childbirth does not negatively affect women’s labor supply. On the other hand, marriage leads to a sustained increase in women’s labor market participation. About the Asian Development Bank ADB is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Pacific, while sustaining its efforts to eradicate extreme poverty. Established in 1966, it is owned by 69 members —49 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. ASIAN DEVELOPMENT BANK The ADB Economics Working Paper Series presents research in progress to elicit comments and encourage debate on development issues in Asia and the Pacific. The views expressed are those of the authors and do not necessarily reflect the views and policies of ADB or its Board of Governors or the governments they represent. ADB Economics Working Paper Series Marriage, Motherhood, and Women’s Employment in Rural India Rahul Lahoti, Rosa Abraham, and Hema Swaminathan No. 757 | December 2024 Rahul Lahoti ([email protected]) is a research associate at the United Nations University World Institute for Development Economics Research (UNU-WIDER). Rosa Abraham (rosa.abr[email protected]) is an assistant professor at Azim Premji University. Hema Swaminathan ([email protected]) is a senior economist at the Economic Research and Development Impact Department, Asian Development Bank. Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) © 2024 Asian Development Bank 6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines Tel +63 2 8632 4444; Fax +63 2 8636 2444 www.adb.org Some rights reserved. Published in 2024. 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Corrigenda to ADB publications may be found at http://www.adb.org/publications/corrigenda. Note: ADB recognizes “China” as the People’s Republic of China. ABSTRACT We investigate the impact of marriage and childbirth on women’s labor market participation in rural India. In the absence of panel data, we employ a novel approach using Life History Calendar data to analyze women’s labor market trajectories from age 15 onward. Our event study models reveal that marriage leads to a significant and sustained increase in women’s labor supply, particularly in informal agricultural work. This increase is more pronounced among women from poorer households and those with working mothers. Notably, childbirth does not negatively impact labor supply; this differs from findings in developed countries. We attribute these results to early marriage and motherhood, low levels of economic development, and prevalence of informal employment. Our research highlights the crucial role of socioeconomic context in shaping the impact of life events on women’s labor market outcomes in developing economies. Keywords: marriage, motherhood penalty, women’s labor force participation, event studies, life history calendar (LHC) JEL codes: J13, J16, J18 We are grateful for the support provided for the paper and the broader data collection project by the United Nations University World Institute for Development Economics Research (UNU-WIDER), the Institute for What Works to Advance Women and Girls in the Economy (IWWAGE), the Indian Institute of Management Bangalore (IIMB), and Azim Premji University. We also thank Mridhula Mohan for her invaluable assistance in designing and implementing the Life History Calendar. The authors do not have any conflicts of interest. 1 INTRODUCTION Marriage and childbirth profoundly shape women’s labor market trajectories, particularly in developing countries. In middle- and high-income countries, “marriage and child penalties” explain a large share of gender inequality in labor markets (Juhn and McCue, 2017; Kleven et al., 2023). While extensive research in such countries has documented a “male marriage premium” (Antonovics and Town, 2004)1and substantial “child penalties” for women Kleven et al. (2023); Berniell et al. (2023), the impact of these life events on women’s labor market outcomes in low-income settings remains understudied. Data constraints, such as unavailability of long-term panel or administrative data, mean that research exploring the impact of marriage on women’s work in developing countries is limited. Furthermore, vast differences in family formations and structures, gender norms, and labor markets raise doubts about the wisdom of applying theories and findings from high-income settings to low-income contexts. Even though the literature has explored other issues related to marriage, such as choice (Allendorf and Pandian, 2016), migration, timing, asset transfer (Quisumbing and Hallman, 2005) and decision making (Banerji and Deshpande, 2021), there is little available on the impact of marriage on work in developing countries. On the other hand, there is growing evidence of the impact of childbirth and fertility on women’s work in developing countries. Recent research using instrumental variable and pseudo-event studies in developing countries has shown that levels of economic development and formality in the economy are key determinants of whether and to what extent motherhood impacts women’s labor market outcomes (Aaronson et al., 2021; Agüero et al., 2020; Kleven et al., 2023). Also, these two life events—marriage and childbirth—are closely linked, with childbirth coming closely after marriage in most developing countries. However, they have rarely been studied jointly to ascertain each event’s impact separately. 1The male marriage premium is the improvement in labor market outcomes, including an increase in wages, observed among men after marriage. This paper addresses this knowledge gap by leveraging unique retrospective data to estimate the causal effects of marriage and first childbirth on women’s labor market participation and work characteristics. Given the lack of long-term panel data in our setting, we employ the Life History Calendar (LHC) method to collect retrospective information on women’s labor market participation and key life events from age 15 onward. We use an event study framework to estimate the impact of marriage and childbirth on various labor market outcomes like workforce participation, and type and sector of work (Kleven et al., 2019). Since marriage and childbirth often occur close together, we implement a joint event study approach following Kleven et al. (2023) to address this temporal proximity. Additionally, extensive robustness and heterogeneity analyses are conducted to explore the underlying mechanisms. Our analysis is based on data from rural India and offers a starkly different context compared with developed countries, where these topics have been extensively explored. Within India, the rural workforce constitutes more than three-quarters of the total. Rural India is a mostly informal, agriculture-dependent economy, in contrast with the formal, non-agricultural economies of developed countries. About 87% of the rural workforce in India is in informal employment, which includes self- and casual wage employment in agriculture. Marriage and childbirth occur substantially earlier in life in rural India than in high- and middle-income countries. India is mostly a patrilocal society, whereby women migrate after marriage and gender norms are stricter. We collected retrospective data in two states in India, Karnataka and Rajasthan, located in southern and northwestern India, respectively. The rural population of these two states combined is over 100 million. In rural Karnataka and Rajasthan, 95% and 90% of women, respectively, work in the informal sector.2 Our findings from the joint event study reveal a significant increase in labor market participation following marriage, with no significant impact observed for the first 2These estimates exclude those who are self-employed without any written contract and are based on a 2013–2014 survey as reported in Labour Bureau (2015). 2 childbirth. This rise in participation after marriage is driven primarily by increased paid work, particularly informal work and unpaid contributions within family farms or enterprises. Notably, the increase in paid work is more pronounced among women from poorer households and those with working mothers. Early marriage also appears to be associated with a larger participation jump. Importantly, no significant changes are observed in any work category (paid, unpaid, formal, informal) following childbirth over the 5-year period. We attribute these results to several factors: early occurrence of marriage and childbirth; low levels of economic development; and prevalence of informal, flexible employment in rural India. The average age of marriage is a decade or more earlier than in most developed countries and, given low levels of income and a lack of social security, contributing to economic activity is important to obtain resources for the household. A simple cohort analysis of women’s labor force participation in rural India corroborates our results, showing a sharp jump between pre- and post-marriage age groups (Chawla and Singh, 2024; Abraham, 2023). Additionally, some correspondence-style studies have shown that women who are working before marriage face a marriage market penalty in terms of less interest from male suitors (Afridi et al., 2023; Dhar, 2021) pointing to low labor force participation before marriage. We also argue that specialization theory (Becker, 1981), commonly used to explain the division of labor upon marriage, holds limited explanatory power in the rural Indian context. Our findings of no impact of childbirth on women’s labor market outcomes align with recent studies suggesting the absence of a motherhood penalty in contexts with low levels of development and largely informal economies (Agüero et al., 2020; Aaronson et al., 2021; Kleven et al., 2023). Informal sector agricultural jobs are conducive to managing childcare responsibilities, providing both temporal and spatial flexibility (Berniell et al., 2023; Schmieder, 2021; Gautham, 2022), unlike fixed-hour, formal sector jobs in offices or factories (Kleven et al., 2023; Aaronson et al., 2021). More than 90% of 3 jobs in rural India are informal and often home-based, with flexible hours, and most are in the agriculture sector, making it possible for women to keep working even after childbirth. The explanations for motherhood penalty—skills depreciation owing to caregiving breaks (Gangl and Ziefle, 2009), selection of care-compatible jobs (Fuller and Hirsh, 2019), reduced work effort (Anderson et al., 2003), and employer discrimination (Correll et al., 2007; Bedi et al., 2022)—are primarily relevant in formal, developed market settings and hold little explanatory power in the context of a mostly informal, agrarian economy such as our study setting. Our paper makes three key contributions to the existing literature. First, we expand the understanding of the impact of marriage on women’s labor market participation in a patrilocal, early marriage, rural developing country setting. Most existing research on marriage and labor market outcomes has focused on high-income countries, and primarily analyzes men’s outcomes (Antonovics and Town, 2004; McConnell and Valladares-Esteban, 2021; Waldfogel, 1998; Killewald and Gough, 2013; Lundberg and Rose, 2002). In South Asia, where patrilocality dictates that a woman must move to her husband’s home after marriage, traditional household panel surveys become unsuitable for tracking women’s labor market changes. Studies have used cross-sectional data to track the participation of married women, but they cannot track work participation over the lifetime of an individual (Afridi et al., 2018). Additionally, since marriage is universal, cross-sectional studies are not able to compare married and unmarried women over the lifecycle.3We overcome these limitations by employing retrospective data collected through the LHC method. This helps us create a panel with information about women’s work status over their working age. We can hence offer unique insights into how marriage influences women’s labor participation in this understudied context. Second, we contribute to the literature on the impact of childbirth on women’s labor market outcomes in low-income, informal economies. Existing event study research on 3Women who marry late, or those who do not marry or are separated/widowed, are substantially different in characteristics to married women to the extent that it is not possible to compare the two and separate the impact of marriage from other aspects. 4 and motherhood, we jointly estimate the impact of marriage and first childbirth following Kleven et al. (2023). We include both the marriage and the childbirth event time dummies to estimate the events jointly. Yg isτmτc=X m6=−1 βg m.I[m=τm]+ X c6=−1 βg c.I[c=τc]+X k αg k.I[k=ageis]+X y γg y.I[y=s]+g isτ (2) where τmrepresents time relative to marriage (τm=0 is year of marriage) and τc represents time relative to childbirth (τc=0 is the year of childbirth). The employment outcome of individual iat marriage event time τmand child event time τcis regressed over event-time dummies for each event, age and year dummies. The coefficients βg m and βg cmeasure the employment effect of marriage and childbirth, respectively, relative to the year before the corresponding event. Similar to the baseline model, we scale the estimated employment effect by a counterfactual employment level. The counterfactual is calculated as an average predicted outcome when omitting the contribution of both marriage and childbirth coefficients. The identifying assumption for the event studies might not hold if the timing of marriage or childbirth is impacted contemporaneously by labor market outcomes. For instance, an income shock like a drought could delay marriage for girls and be associated with their labor market outcomes in places like India, where marriage is accompanied by payment of dowry by the girl’s family. The COVID-19 shock, for example, resulted in an earlier age of marriage in many states in India, according to multiple reports Jejeebhoy (2021). However, a similar shock could encourage married women to have children. But, as Berniell et al. (2021) argue, individuals cannot control the exact timing of childbirth. In addition, in the Indian setting, where there is social pressure to get married by a particular age and to have a child within a few years of marriage, the timing of marriage and childbirth is controlled primarily by social norms and not necessarily by labor market conditions. Identifying short-term effects in an event study model relies on the smoothness assumption, which posits that other relevant characteristics impacting labor market 11 outcomes change gradually over time compared with changes in the event in question. However, identification of the long-term effects requires stronger assumptions. In particular, we need to assume that, after controlling for other aspects, the outcomes in the counterfactual situation of no marriage or no childbirth do not follow any trend before the event. As we shall see, in the event studies in this paper, we find that the pre-event trends are parallel: there are no significant differences between the men’s and women’s trajectory of workforce participation before the event. Also, the post-event effects are persistent following a sharp effect at the time of the event, indicating a lack of dynamics in the data later on. Motherhood penalty event study estimates have been validated using instruments for fertility: sibling sex mix (Kleven et al., 2019), intrauterine device failure (Gallen et al., 2023) and in vitro fertilization treatment success (Lundborg et al., 2017) in other contexts. To assess robustness, we estimate models with additional controls for individual and household characteristics (e.g., number of children, household structure—co-residence with parents, in-laws, spouse, and other household members in the household for each year), time-invariant characteristics (e.g., education, caste/religion), and Primary Sampling Unit (PSU) fixed effects. The absence of heterogeneous treatment across time/cohorts is vital to the credibility of staggered event study designs (Goodman-Bacon, 2021; De Chaisemartin and d’Haultfoeuille, 2020; Callaway and Sant’Anna, 2021; Borusyak et al., 2021). Heterogeneity in the timing of childbirth has been used by Melentyeva and Riedel (2023) to show biases in the conventional child penalty studies; they suggest estimating the effects separately by cohorts to overcome these biases. We implement this additional check of robustness in our analysis. 12 4 RESULTS 4.1 Descriptive Results We begin our analysis by presenting key descriptive results. Our analytical sample is restricted to only rural areas. In our sample, overall education levels are low, with women on average less educated than men (Table 1). A little less than half the women (46%) and over a quarter of the men (28%) are illiterate; 75% of women have not completed secondary education, whereas the corresponding number for men is 61%. About a quarter of the respondents are lower caste (Scheduled Caste (SC)), about 16% are Scheduled Tribe (ST), nearly half are classified officially as Other Backward Class (OBC), and about 9% are from the higher castes. At 87%, rural areas are overrepresented in our sample. Women typically marry and have children at a younger age than men but enter the workforce later (Table 2). Around half the women in our sample had married by 18, whereas the median male marriage age is 22. On average, women have their first childbirth at 20 years, compared with 25 for men.7The average gap between marriage and first childbirth is 2 years for both sexes. Among those who ever participate in the workforce, men typically join just before turning 18, whereas women enter on average after 19. This delayed women’s labor force entry applies to both paid employment and contributing family work. The context of marriage and childbirth differs significantly between Indian and developed countries, where most motherhood penalty studies have been conducted. Marriage and childbirth are substantially earlier in India and several developing countries as compared with developed countries (Appendix Table A1).8The median marriage age in India and several South Asian and African countries falls between 16 and 21 years, whereas first marriages in richer countries occur much later, at between 28 and 33 7Age at these events for women in our sample aligns with national statistics from the National Family and Health Survey (2015–2016), indicating an average marriage age of 18.1 years and first childbirth at 20.6 years in rural India. 8The Appendix is available at http://dx.doi.org/10.22617/WPS240568-2. 13 years. Marriage and childbirth are universal in India, whereas many choose not to marry or not to have children in developed countries (Singh et al., 2023; Bloome and Ang, 2020; Rindfuss et al., 2022).9Nearly all families in lower- and middle-income countries have children after marriage, unlike in several developed countries (Kleven et al., 2023). The gap between marriage and first childbirth is shorter, and women experience first childbirth early in their lifetime. The median age at first birth in developing countries is in the early 20s, compared with nearly a decade later (around 30 years old) in wealthier nations.10 India is substantially different from developed countries and even some other developing countries in terms of women’s labor force participation, level of informality, and dependence on agriculture for livelihood. Women’s labor force participation is notably low in India—25% in 2020 MSPI (2013)—and also has a significantly higher informal employment share than most developed countries. In South Asia and some African nations, 90% or more women work informally (lacking social security or contracts); this proportion is less than 5% in wealthier countries. Generally, informality decreases with increasing per capita gross domestic product. Similarly, the share of working women in agriculture is substantially higher in developing countries. Over half of working women in South Asian nations are engaged in agriculture; this share falls below 1% in developed countries. Given this starkly different context, we find a different impact of marriage and childbirth on women’s employment to those obtained in developed country settings. In our sample of rural individuals, women experience a sharp jump in workforce participation in the years after marriage, from 27% in the year preceding marriage to an average of 49% in the first 5 years of marriage. This employment is primarily as contributing family workers or in informal agricultural work (Table 3). The corresponding change is smaller for men, going from 88% to 94%. Among men, the share engaged in paid work increases while those in 9In the sample, almost everyone was married by the age of 25. 10These differences are starker when we examine rural India, from where our sample is, compared with the overall country. 14 contributing family work decreases after marriage. For women, the reverse is seen, with contributing work increasing from 36% pre-marriage to 41% after marriage. Formal work among working women is already low pre-marriage, at 9%, and drops to 6% post-marriage. There is an increase in self-employment and agricultural paid work among women who do paid work. Women also experience a jump in workforce participation after first childbirth, but it is far smaller in magnitude (Table 4) than the increase seen after marriage. Women’s workforce participation increases from 45% 1 year before childbirth to an average of 51% in the first 5 years after childbirth. Men’s involvement, which is already high at 94%, increases by 3 percentage points to 97%. There is an increase in paid work participation for both men and women and a slight decline in contributing family work. The extent of formal work sees a minor increase for both men and women; within informal work, selfemployment sees a small increase. 4.2 Impact of Life Events on Participation in Employment In this section, we present the estimates of the impact of marriage and childbirth on labor market outcomes for men and women. We start by showing the impact of each event separately, estimates of equation 1, for the full sample and by excluding families that have their first child within 2 years of marriage, to help disentangle the impact of the two events, as carried out by Berniell et al. (2022); Kleven et al. (2023). We next consider the joint estimate of the two events (estimating equation 3). We estimate equations 1 and 3 separately for men and women. We present all results using figures for simplicity. The y-axis in the figures in this section shows the estimates of Pτ—that is, the scaled event time coefficients at each point of time relative to the event. These can be interpreted as the proportionate change in participation compared with the year before the event (τ= -1), having controlled non-parametrically for age and time trends. The figures include 95% confidence interval bands around the event year coefficients. 15 At the time of marriage, women experience a sharp increase in participation in work by more than 50%, while men experience no significant change in participation rate after marriage (Figure 1). This holds true even after excluding families that had children within 2 years of marriage, indicating that the impact of marriage might not necessarily be confounded with motherhood. In the years following the initial increase, the levels do not fall back; instead, there is a gradual increase from this initial jump. In the fifth year of marriage, the participation rates for women are double what they were a year before marriage, while the corresponding rate for men has barely changed compared with the year before marriage. The parallel trends assumption holds: the labor force participation of men and women evolves almost in parallel until marriage. A year after first childbirth, women experience a significant increase in participation in work, by about 10% in the first year and increasing in later years, whereas men experience no significant change in participation rate after marriage (Figure 2). This impact loses significance, and the magnitude reduces for the sample excluding families with children within 2 years of marriage. In addition, the parallel trends assumption pre-childbirth does not hold in both samples. Women’s labor force participation differs significantly from men’s before childbirth before first childbirth. Women experience a substantial increase pre-childbirth, potentially driven by the impact of marriage, whereas men see no significant pre-trend. This indicates that the impact of childbirth might be confounded with marriage. The joint event study will help disentangle the impacts of marriage and childbirth. It shows no significant impact of first childbirth on women’s participation in the 5 years after childbirth compared with the year before childbirth. Marriage leads to a sharp increase in the participation rate of women in the year of marriage and this continues over the next 5 years compared with the year before marriage (Figure 3). Women’s labor force participation increases by 74% in the year of marriage compared with 1 year before marriage, and by 5 years after marriage it is more than double that of before marriage. In the year of childbirth, there is a small decline of 5% in the participation rate of women, but this is not statistically significant. Women’s 16 participation increases in the fourth and fifth years after childbirth, but this is not statistically significant. Men’s participation does not change as a result of either of the events. There are no pretrends before both events: women’s and men’s participation in the labor market evolves in parallel, and there are no significant differences between them. Paid work and contributing family work (unpaid work) both increase after marriage but there are no statistically significant changes in the participation of women after childbirth (Figure 4). Both paid and unpaid work participation experience sharp jumps upon marriage. The next few years after marriage see a further increase in paid work, whereas unpaid work stagnates after the initial jump. Paid work witnesses a statistically insignificant increase 2 years after childbirth, whereas contributing family work witnesses a statistically insignificant decline. Figure 5 shows the evolution of informal and formal employment rates among men and women. In the year of marriage, women’s participation in informal work increases significantly, but formal work participation experiences no significant change. Men’s participation in both types of work witnesses no significant change in any year post-marriage. Women experience an immediate increase in participation in informal work by 82% in the year of marriage compared with the year before marriage. Within informal work, participation in self-employment and casual work witnesses a sharp increase in the year of marriage and this continues in the 5 years after marriage (panels C and D in Figure 5). Most of this increase in women’s participation after marriage is seen only in the agriculture sector and not in the non-agriculture sector. There is no significant difference in the pre-marriage trends in informal and formal work for men and women. Informal employment rates experience a statistically insignificant increase after childbirth. Formal work, self-employment, and casual work do not experience significant changes after childbirth (Appendix Figure A1). 17 4.3 Robustness We perform several robustness tests on these results. 4.3.1 Balanced Sample One concern for our identification strategy is that the sample is not balanced—that is, we do not observe the same individuals every year. This is because we have different numbers of years of data pre- and post-events depending on the age at which events occurred in the respondent’s life and the respondent’s current age. For example, for a respondent who married at 18, we have only 3 years of information prior to marriage as we collect information starting from the age of 15. For someone 22 years of age at the time of the survey and married at 20, we have information for 7 years before marriage and only 2 years after marriage. To account for this, we could use a balanced sample. Such a sample would have individuals on whom we have information for at least 5 years before and after the event. This would restrict our sample to individuals who got married or had children at 20 or older. This would change the sample’s size and composition substantially since most women in our sample married before 20, and a large proportion gave birth to their first child before 20. So, we instead first check on predetermined variables and then limit the sample to only respondents for whom we have information for all 5 years post-events. Following Berniell et al. (2021), we show that predetermined characteristics of women and men—for instance, parents’ education and childhood socioeconomic status—do not change across the event time periods. The predetermined characteristics are smooth around the event time and are stable across event time (Appendix Figure A2). Further, we find that, if we restrict our sample to only respondents for whom we have information for all 5 years after the event, our results do not change (Appendix Figure A3). 18 4.3.2 Additional Controls Following Kleven et al. (2019), the baseline model includes only age and year fixed effects in addition to the event dummies as independent variables. To test the robustness of our estimates to inclusion of other variables, we estimate models with additional controls (Appendix Figure A4). These include controls for individual and household characteristics (e.g., number of children, household structure—co-residence with parents, in-laws, spouse, and other household members in the household for each year), time-invariant characteristics (e.g., education, caste/religion), and Primary Sampling Unit fixed effects. Results from this analysis are similar to those of our baseline model: marriage leads to an increase in women’s participation whereas childbirth has no significant impact. 5 HETEROGENEITY IN IMPACT In order to understand the mechanisms through which the change in labor participation happens, we explore whether the impact varies across different individual and household characteristics. To do this we estimate the results of the following interaction model: Yg isτmτc=X m6=−1 βg m.I[m=τm]+ X c6=−1 βg c.I[c=τc]+X k αg k.I[k=ageis] +X y γg y.I[y=s]+δ.Zi+µm.Zi.I[m=τm]+µc.Zi.I[c=τc]+g isτ (3) where Ziis the vector of individual and household controls and we include interaction terms between event time dummies (τmand τc) and select individual and household attributes in Z.Zincludes age at the time of event, women’s education, current age of the respondent, social group of the respondent, wealth status of the household (below or above median), employment status of the women’s mother during her childhood, household structure at the time of the event and spouse’s education. The coefficients on these interaction terms 19 µmand µccan be interpreted as the heterogeneous impact in the particular event time of the individual/household attribute Zion employment outcome. We present the results in the form of margin plots of these coefficients. 5.1 Impact of Marriage by Work Status of Women’s Mother Women whose mothers were reported as working in their lifetime were far more likely to experience an increase in work participation than women whose mothers were not working, even after controlling for a range of other factors (Figure 6). Before marriage, the participation rates of the two groups are not statistically different, but 1 year after marriage they differ. Women whose mothers have worked experience a sharp jump the year after marriage and have significantly higher participation rates than do women whose mothers did not work. Both samples of women (whose mothers worked and did not work) experienced no significant change in participation upon childbirth and a small increase a few years after childbirth. 5.2 Impact of Life Events by Household Wealth Levels We categorize households below the median and at or above the median asset index.11 Figure 7 shows the differential impact of life events among these two groups. Before the events, there was no statistically significant difference in the participation rates of women between the two groups. Both groups experience an increase after marriage and a lower and insignificant increase after childbirth. However, upon marriage, the magnitude of the increase is significantly higher for the poorer group. From the second year after marriage, participation rates among poorer households are significantly higher than among women from richer households. After childbirth, differences in participation in the two groups are statistically insignificant. 11The survey collected information on amenities available in each household (fridge, washing machine, television, car, mixer, tractor, etc.) as well as details of the household structure (number of rooms, type of material used for walls, flooring and roof). We used a principal component analysis to combine these indicators and constructed an asset index for each household. 20 participation in the labor market with structural changes in the economy but does not directly take childcare responsibilities into account. Recent literature in developing countries shows there is no significant impact of motherhood on labor supply at low levels of development (Agüero et al., 2020; Agüero and Marks, 2011; Aaronson et al., 2021; Godefroy, 2019; Kleven et al., 2023). This holds true even when examining historical data for developed countries (Kleven et al., 2023; Aaronson et al., 2021). Agüero et al. (2020) find that self-employment, working from home, occupational segregation, and seasonal work account for very little of the family penalty in low-income countries. Heath (2017) also provides suggestive evidence that demand for greater flexibility drives women’s switch to self-employment. Kleven et al. (2023) analyze child penalties in 134 countries using pseudo-event studies and find that child penalties are negatively associated with agriculture while share of industry, services, formalization, salaried work, and urbanization are positively associated with child penalties. In Nicaragua, Behrman and Wolfe (1984) find that women’s participation in employment is less affected by the presence of young children than it is in developed countries, with the presence of informal employment arrangements and family-based childcare explaining the mitigated impact. (Berniell et al., 2023) show that, in Chile, mothers in informal jobs find the flexibility needed for family–work balance and the fall in women’s employment is mainly explained by declining salaried employment. Using Mexican census data, Schmieder (2021) finds no negative employment effects of an instrument-induced increase in fertility; instead, mothers move to the informal sector. In the rural Indian context, women on average have low levels of education and are mainly engaged in physical tasks in agriculture that provide flexibility in work hours. Employment is seasonal and requires little training, and absence from work has a relatively low impact on skills or productivity. Agricultural employment is also conducive to care responsibilities. These employment characteristics could explain our results of the null impact of childbirth on women’s economic activities. 27 Our paper has a few limitations. In retrospective data, there are concerns of inaccurate recall affecting the results. We address this by using carefully trained enumerators to pictorially depict the timeline of key life events and paying extra attention to data close to the life events to minimize errors. Our estimations using younger women in our sample with shorter recall periods also show similar patterns to the overall sample. This points to a lesser likelihood of recall error. The descriptive cohort analysis discussed in Section VI. A using national data also points toward a jump in participation after the marriage age, validating our results. However, without access to long-term panel data, we cannot fully rule out the possibility of recall error. Another explanation for the jump in labor participation post-marriage is that women drop out of the labor market the year before marriage in anticipation of the event. This could be because of the stigma of working outside or to prevent association with strangers. However, our event study graphs show there is no statistically significant change in women’s participation in the years before marriage. We lack wages or hours of work data to investigate the change in the intensive margin of work. It is possible that, after marriage, the participation rate increases, and it stays the same post-childbirth but with a reduced number of hours. Most of the literature on the motherhood penalty in developed countries investigates changes in wages. Given the nature of our recall-based data, we did not ask for wage or hours information as it would not have been reliable. 7 CONCLUSION Using a unique dataset on the lifetime histories of women, this paper contributes to the nascent literature on life events and women’s employment in developing countries. Our study evaluates the impact of major life events—marriage and childbirth—on women’s labor market participation in rural India. We find that labor market participation increases drastically upon marriage, and women do not face a “motherhood penalty” in terms of participation in employment. 28 The rural Indian context is similar to that in low-income countries with high levels of informal employment dominated by the agriculture sector. Literature in these settings has found non-existence of a child penalty (Agüero et al., 2020). At the same time, there are important differences along several dimensions, including an early age of marriage and childbirth, as well as conservative social norms. Further, norms of mobility and labor market participation among unmarried women and married women differ, with relatively higher constraints on participation among the former group. Although we do not find a motherhood penalty, and there is no apparent conflict between employment and childbirth, the continuation of women in employment immediately after childbirth could reflect distress. Several aspects of our study confirm this. First, the increase in employment after marriage, which continues even after childbirth, is largely in informal employment—that is, self-employment or casual wage work. Formal employment—that is, regular salaried employment—is unchanged. Second, the increase is larger among poorer households. These suggest that, for most women, paid work is imperative, not an option. The organization of the rural labor market and the types of employment—informal and agricultural—allow for joint reproductive and productive work. However, the demand for women’s reproductive work entails a compromise on the quality of the paid work they engage in. Not surprisingly, joint production also entails a compromise on childcare. Chowdhury et al. (2021) find early weaning among 59% of working mothers, with exclusive breastfeeding more likely among those in home-based work—the least-paying among occupations. Chari et al. (2019) find that India’s workfare scheme, the National Rural Employment Guarantee Act (NREGA), is associated with increased newborn mortality among the sample of women eligible to participate. Employment during pregnancy and early childbirth compromise maternal and fetal health. Qualitative studies among NREGA workers describe the costs of this employment in terms of compromised childcare as outweighing the benefits, even describing employment as “disempowering.” Thus, a lack of motherhood penalty, traditionally understood as reduced employment, is 29 not always cause for celebration. Providing accessible and quality childcare in creches close to the workplace and with adequate feeding breaks is an option suggested in the context of NREGA programs (Nair et al., 2014). A recent study by Chigateri (2017) highlights two successful, albeit different models of quality childcare provision that cater to children under 6 from marginalized groups. The two schemes are the state funded Tamil Nadu Integrated Child Development Scheme and Mobile Creches, a non-government organization that works with grassroots women. Further research would be useful in informing the design of programs aimed at providing high quality and affordable childcare that would enable women to optimize their employment options. 30 TABLES AND FIGURES Table 1 Summary Descriptives at τ=-1 Gender of Respondent Men Women Total % % % Education Not literate 27.9 45.8 38.9 Primary or below 15.4 15.4 15.4 Middle 18.0 14.0 15.6 Secondary 16.1 14.2 14.9 Higher secondary 10.6 6.6 8.2 Above higher secondary 12.1 4.0 7.1 Caste SC 24.4 25.9 25.3 ST 15.5 15.8 15.7 OBC 51.6 50.5 50.9 Others 8.4 7.8 8.1 State Karnataka 54.5 61.8 59.0 Rajasthan 45.5 38.2 41.0 Total 1312 1766 3075 OBC = other backward classes, SC = scheduled castes, ST = scheduled tribes. Source: India Working Survey. 31 Table 2 Age of Respondent at Various Life Events Men Women Mean Median SD Mean Median SD Respondents age 35.09 35 6.47 32.59 32 7.18 Age at marriage 22.65 22 4.79 18.1 17 3.27 Age at first childbirth 25.23 25 4.52 20.01 20 3.25 Gap between marriage and childbirth 2.64 2 2.39 2.13 2 2.3 Age at entry in workforce 17.82 15 4.55 19.27 17 5.43 Age at entry in paid work 19.11 17 5.35 20.22 18 6.27 Age at entry as contributing worker 17.12 15 4.01 19.32 18 5.23 SD = standard deviation. Note: The table presents age of respondent at various key life events in the rural sample. Average age for events is conditional on that respondent experiencing the event. For example, average age of entry into this workforce is calculated only among those individuals who ever enter the workforce. Source: India Working Survey. 32 Table 3 Labor Market Participation Before and After Marriage Men Women One year before marriage (τ=-1) Average from marriage to five years after childbirth (τ=0 to τ=5) One year before marriage (τ=-1) Average from marriage to five years after marriage (τ=0 to τ=5) Mean SD Mean SD Mean SD Mean SD Work force 0.88 0.32 0.94 0.25 0.27 0.45 0.49 0.5 Distribution of workers Paid work 0.86 0.34 0.91 0.29 0.64 0.48 0.59 0.49 Contributing family work 0.14 0.34 0.09 0.29 0.36 0.48 0.41 0.49 Distribution of paid workers Formal paid work 0.13 0.34 0.14 0.34 0.09 0.29 0.06 0.23 Informal paid work 0.87 0.34 0.86 0.34 0.91 0.29 0.94 0.23 Distribution of paid workers in informal sector Casual paid work 0.5 0.5 0.46 0.5 0.71 0.46 0.69 0.46 Self employed 0.5 0.5 0.54 0.5 0.29 0.46 0.31 0.46 Distribution of paid workers across sectors Agricultural paid work 0.53 0.5 0.54 0.5 0.67 0.47 0.74 0.44 Non-agricultural paid work 0.47 0.5 0.46 0.5 0.33 0.47 0.26 0.44 SD = standard deviation. Note: The table presents proportion of individuals who participate in workforce and various forms of work 1 year prior to marriage and average participation from year of marriage to 5 years after marriage for men and women. Source: India Working Survey. 33 Table 4 Labor Market Participation and Household Structure Before and After First Childbirth Fathers Mothers One year before first childbirth (τ=-1) Average from childbirth to five years after childbirth (τ=0 to τ=5) One year before childbirth (τ=-1) Average from childbirth to five years after childbirth (τ=0 to τ=5) Mean SD Mean SD Mean SD Mean SD Work force 0.94 0.23 0.97 0.18 0.45 0.5 0.51 0.5 Distribution of workers Paid work 0.91 0.29 0.93 0.25 0.57 0.5 0.59 0.49 Contributing family work 0.09 0.29 0.07 0.25 0.43 0.5 0.41 0.49 Distribution of paid workers Formal paid work 0.12 0.32 0.13 0.34 0.05 0.22 0.07 0.25 Informal paid work 0.88 0.32 0.87 0.34 0.95 0.22 0.93 0.25 Distribution of paid workers in informal sector Casual paid work 0.48 0.5 0.45 0.5 0.7 0.46 0.68 0.47 Self employed 0.52 0.5 0.55 0.5 0.3 0.46 0.32 0.47 Distribution of paid workers across sectors Agricultural paid work 0.54 0.5 0.55 0.5 0.76 0.43 0.71 0.45 Non-agricultural paid work 0.46 0.5 0.45 0.5 0.24 0.43 0.29 0.45 SD = standard deviation. Note: The table presents proportion of individuals who participate in workforce and various forms of work 1 year prior to first childbirth and average participation from year of childbirth to 5 years after childbirth for men and women. Source: India Working Survey. 34 Figure 1: Impact of Marriage on Overall Work Force Participation Marriage -.5 0 .5 1 1.5 Participation relative to t = -1 (a) Full sample Marriage -.5 0 .5 1 1.5 (b) Exclude individuals who have child within 2 years of marriage Men Women Participation relative to t = -1 --5 -4 -3 -2 -1 0 1 2 3 4 5 Event time (years) --5 -4 -3 -2 -1 0 1 2 3 4 5 Event time (years) Note: The figure shows, for men and women separately, the estimated impacts of marriage on overall work participation rates. The y-axis shows the scaled coefficients Pτthat measure the impact of marriage as a percentage of the counterfactual outcome relative to the year before marriage. Calendar-year and age-in-year fixed effects are controlled in the regression. Standard errors are clustered at the individual level. Source: Authors’ calculations. 35 Figure 2: Impact of First Childbirth on Overall Work Force Participation First childbirth -.4 -.2 0 .2 .4 First childbirth -.4 -.2 0 .2 Men Women .4 (a) Full sample (b) Exclude individuals who have child within 2 years of marriage --5 -4 -3 -2 -1 0 1 2 3 4 5 Event time (years) --5 -4 -3 -2 -1 0 1 2 3 4 5 Event time (years) Participation relative to t = -1 Participation relative to t = -1 Note: The figure shows, for men and women separately, the estimated impacts of first childbirth on overall work participation rates. The y-axis shows the scaled coefficients Pτthat measure the impact of childbirth as a percentage of the counterfactual outcome relative to the year before childbirth. Calendar-year and age-in-year fixed effects are controlled in the regression. Standard errors are clustered at the individual level. Source: Authors’ calculations. 36 REFERENCES Aaronson, D., R. Dehejia, A. Jordan, C. Pop-Eleches, C. Samii, and K. Schulze (2021). The effect of fertility on mothers’ labor supply over the last two centuries. The Economic Journal 131(633), 1–32. Abraham, R. (2023). Tracking workers across generations–a cohort-based analysis. Abraham, R., N. Anjum, R. Lahoti, and H. Swaminathan (2023). What did they say? respondent identity, question framing and the measurement of employment. Technical report, CSE Working Paper# 55. Afridi, F., A. Arora, D. Dhar, and K. Mahajan (2023). Women’s work, social norms and the marriage market. Technical report, IZA Discussion Papers. Afridi, F., M. Bishnu, and K. Mahajan (2022). Gender and mechanization: Evidence from indian agriculture. American Journal of Agricultural Economics. Afridi, F., T. Dinkelman, and K. Mahajan (2018). Why are fewer married women joining the work force in rural india? a decomposition analysis over two decades. Journal of Population Economics 31(3), 783–818. Agüero, J. M., M. Marks, N. Raykar, et al. (2020). Economic development and the motherhood wage penalty. Technical report, University of Connecticut, Department of Economics. Agüero, J. M. and M. S. Marks (2011). Motherhood and female labor supply in the developing world: Evidence from infertility shocks. Journal of Human Resources 46(4), 800–826. Aisenbrey, S., M. Evertsson, and D. Grunow (2009). Is there a career penalty for mothers’ time out? a comparison of germany, sweden and the united states. Social forces 88(2), 573–605. Allendorf, K. and R. K. Pandian (2016). The decline of arranged marriage? marital change and continuity in india. Population and development review 42(3), 435. Anderson, D. J., M. Binder, and K. Krause (2003). The motherhood wage penalty revisited: Experience, heterogeneity, work effort, and work-schedule flexibility. ILR Review 56(2), 273–294. Angelov, N., P. Johansson, and E. Lindahl (2016). Parenthood and the gender gap in pay. Journal of labor economics 34(3), 545–579. Angrist, J. and W. N. Evans (1996). Children and their parents’ labor supply: Evidence from exogenous variation in family size. Antonovics, K. and R. Town (2004). Are all the good men married? uncovering the sources of the marital wage premium. American Economic Review 94(2), 317–321. 43 Anukriti, S., C. Herrera-Almanza, P. Pathak, and M. Karra (2020). Curse of the mummy-ji: The influence of mothers-in-law on women in india. American Journal of Agricultural Economics 102, 1328–1351. Banerji, M. and A. S. Deshpande (2021). Does ‘love’make a difference? marriage choice and post-marriage decision-making power in india. Asian Population Studies 17(2), 201–220. Becker, G. (1981). A Treatise on the Family. Harvard University Press. Becker, G. S. (1985). Human capital, effort, and the sexual division of labor. Journal of labor economics 3(1, Part 2), S33–S58. Bedi, A., T. Majilla, and M. Rieger (2022). Does signaling childcare support on job applications reduce the motherhood penalty? Review of Economics of the Household, 1–15. Behrman, Jere, R. and B. L. Wolfe (1984). Labor force participation and earnings determinants for women in the special conditions of developing countries. 15, 259–288. Berniell, I., L. Berniell, D. De la Mata, M. Edo, Y. Fawaz, M. P. Machado, and M. Marchionni (2022). Motherhood, pregnancy or marriage effects? Economics Letters 214, 110462. Berniell, I., L. Berniell, D. De la Mata, M. Edo, and M. Marchionni (2021). Gender gaps in labor informality: The motherhood effect. Journal of Development Economics 150, 102599. Berniell, I., L. Berniell, D. de la Mata, M. Edo, and M. Marchionni (2023). Motherhood and flexible jobs: Evidence from latin american countries. World Development 167, 106225. Bloome, D. and S. Ang (2020). Marriage and union formation in the united states: Recent trends across racial groups and economic backgrounds. Demography 57(5), 1753–1786. Borusyak, K., X. Jaravel, and J. Spiess (2021). Revisiting event study designs: Robust and efficient estimation. arXiv preprint arXiv:2108.12419. Bronars, S. G. and J. Grogger (1994). The economic consequences of unwed motherhood: Using twin births as a natural experiment. The American Economic Review, 1141–1156. Budig, M. J. and P. England (2001). The wage penalty for motherhood. American sociological review 66(2), 204–225. Budig, M. J., J. Misra, and I. Boeckmann (2012). The motherhood penalty in crossnational perspective: The importance of work–family policies and cultural attitudes. Social Politics 19(2), 163–193. 44 Budig, M. J., J. Misra, and I. Boeckmann (2016). Work–family policy trade-offs for mothers? unpacking the cross-national variation in motherhood earnings penalties. Work and occupations 43(2), 119–177. Callaway, B. and P. H. Sant’Anna (2021). Difference-in-differences with multiple time periods. Journal of econometrics 225(2), 200–230. Casale, D. and D. Posel (2010). The male marital earnings premium in the context of bride wealth payments: Evidence from south africa. Economic Development and Cultural Change 58(2), 211–230. Chari, A. V., P. Glick, E. Okeke, and S. V. Srinivasan (2019). Workfare and infant health: Evidence from india’s public works program. Journal of Development Economics. Chatterjee, U., R. Murgai, and M. Rama (2015). Job opportunities along the rural-urban gradation and female labor force participation in india. World Bank Policy Research Working Paper (7412). Chawla, A. and K. Singh (2024). How labour force participation rates in india vary across age groups. https://ceda.ashoka.edu.in/ how-labour-force-participation-rates-in-india-vary-across-age-groups/. Accessed: 10th May 2024. Chigateri, S. (2017). Pathways to accessible, affordable and gender-responsive childcare provision for children under six—india case studies. Background paper for the research and data section, UN Women, New York. Chowdhury, A. R., A. Suri, and G. Bhan (2021). Breastfeeding knowledge and practices of working mothers in the informal economy in new delhi: A formative study to explore new intervention pathways towards improved maternal and child health outcomes. Social Science and Medicine. Coavas Blanquicetta, S. G. and L. Gómez Duarteb (2016). For love or for money? a study of the marriage wage premium in colombia. Ecos de Economía 20(42), 70–89. Correll, S. J., S. Benard, and I. Paik (2007). Getting a job: Is there a motherhood penalty? American journal of sociology 112(5), 1297–1338. Das, M. B. and I. Zumbyte (2017). The motherhood penalty and female employment in urban india. Das, S., S. Jain-Chandra, K. Kochhar, and N. Kumar (2015). Women workers in India: why so few among so many? International Monetary Fund. De Chaisemartin, C. and X. d’Haultfoeuille (2020). Two-way fixed effects estimators with heterogeneous treatment effects. American economic review 110(9), 2964–2996. De Hoon, S., R. Keizer, and P. Dykstra (2015). The male marriage wage premium in cross-national perspective. Technical report, LIS Working Paper Series. 45 Deshpande, A. and N. Kabeer (2024). Norms that matter: Exploring the distribution of women’s work between income generation, expenditure-saving and unpaid domestic responsibilities in india. World Development 174, 106435. Deshpande, A. and J. Singh (2021). Dropping out, being pushed out or can’t get in? decoding declining labour force participation of indian women. Technical report, IZA Discussion Papers. Dhar, D. (2021). Indian matchmaking: Are working women penalized in the marriage market in india. Technical report, Tech. rep. Ensel, W. M., M. K. Peek, N. Lin, and G. Lai (1996). Stress in the life course: A life history approach. Journal of Aging and Health 8(3), 389–416. Freedman, D., A. Thornton, D. Camburn, D. Alwin, and L. Young-DeMarco (1988). The life history calendar: A technique for collecting retrospective data. Sociological methodology, 37–68. Fuller, S. and C. E. Hirsh (2019). “family-friendly” jobs and motherhood pay penalties: The impact of flexible work arrangements across the educational spectrum. Work and Occupations 46(1), 3–44. Gallen, Y., J. S. Joensen, E. R. Johansen, and G. F. Veramendi (2023). The labor market returns to delaying pregnancy. Available at SSRN 4554407. Gangl, M. and A. Ziefle (2009). Motherhood, labor force behavior, and women’s careers: An empirical assessment of the wage penalty for motherhood in britain, germany, and the united states. Demography 46, 341–369. Gautham, L. (2022). It takes a village: Childcare and women’s paid employment in india. Population and Development Review 48, 798–828. Glasner, T. and W. Van der Vaart (2009). Applications of calendar instruments in social surveys: a review. Quality and Quantity 43(3), 333–349. Godefroy, R. (2019). How women’s rights affect fertility: evidence from nigeria. The Economic Journal 129(619), 1247–1280. Goldin, C. (1994). The u-shaped female labor force function in economic development and economic history. Goldin, C. (2014). A grand gender convergence: Its last chapter. American Economic Review, 1091–1119. Goodman-Bacon, A. (2021). Difference-in-differences with variation in treatment timing. Journal of econometrics 225(2), 254–277. Gorman, E. H. (2000). Marriage and money: The effect of marital status on attitudes toward pay and finances. Work and Occupations 27(1), 64–88. 46 Gupta, N. D. and N. Smith (2002). Children and career interruptions: the family gap in denmark. Economica 69(276), 609–629. Halldén, K., A. Levanon, and T. Kricheli-Katz (2016). Does the motherhood wage penalty differ by individual skill and country family policy? a longitudinal study of ten european countries. Social Politics: International Studies in Gender, State & Society 23(3), 363–388. He, D., X. Zhang, Y. Zhuang, Z. Wang, and Y. Jiang (2019). China fertility report, 2006–2016. China population and development studies 2(4), 430–439. Heath, R. (2017). Fertility at work: Children and women’s labor market outcomes in urban ghana. Journal of Development Economics 126, 190–214. Herrendorf, B., R. Rogerson, and A. Valentinyi (2014). Growth and structural transformation. Handbook of economic growth 2, 855–941. Hirway, I. and S. Jose (2011). Understanding women’s work using time-use statistics: The case of india. Feminist Economics 17(4), 67–92. Jayachandran, S. (2021). Social norms as a barrier to women’s employment in developing countries. IMF Economic Review 69(3), 576–595. Jejeebhoy, S. (2021). Child marriages during the pandemic. https://www.theindiaforum. in/article/child-marriages-during-pandemic. Accessed: 10th May 2024. Jones, L., R. Cook, and S. Connolly (2023). Parenthood and job quality: Is there a motherhood penalty in the uk? Social Indicators Research 170(2), 765–792. Juhn, C. and K. McCue (2017). Specialization then and now: Marriage, children, and the gender earnings gap across cohorts. Journal of Economic Perspectives 31(1), 183–204. Kapur, D., M. Vaishnav, and D. Verley (2021). What is women’s work? reflections from four north indian urban clusters. Urbanisation 6(1_suppl), S20–S39. Killewald, A. and M. Gough (2013). Does specialization explain marriage penalties and premiums? American sociological review 78(3), 477–502. Klasen, S. and J. Pieters (2015). What explains the stagnation of female labor force participation in urban india? The World Bank Economic Review 29(3), 449–478. Kleven, H., C. Landais, and G. Leite-Mariante (2023). The child penalty atlas. Technical report, National Bureau of Economic Research. Kleven, H., C. Landais, J. Posch, A. Steinhauer, and J. Zweimüller (2019). Child penalties across countries: Evidence and explanations. In AEA Papers and Proceedings, Volume 109, pp. 122–26. 47 Kleven, H., C. Landais, and J. E. Søgaard (2019). Children and gender inequality: Evidence from denmark. American Economic Journal: Applied Economics 11(4), 181–209. Labour Bureau (2015). Report on Employment in Informal Sector and Conditions of Informal Employment 2013-142015. Lahoti, R. and H. Swaminathan (2016). Economic development and women’s labor force participation in india. Feminist Economics 22(2), 168–195. Liang, Z., S. Appleton, and L. Song (2016). Informal employment in china: Trends, patterns and determinants of entry. Technical report. Lundberg, S. and E. Rose (2002). The effects of sons and daughters on men’s labor supply and wages. Review of Economics and Statistics 84(2), 251–268. Lundborg, P., E. Plug, and A. W. Rasmussen (2017). Can women have children and a career? iv evidence from ivf treatments. American Economic Review 107(6), 1611–1637. Manzoni, A. (2012). In and out of employment: Effects in panel and life-history data. Advances in Life Course Research 17(1), 11–24. McConnell, B. and A. Valladares-Esteban (2021). On the marriage wage premium. Melentyeva, V. and L. Riedel (2023). Child penalty estimation and mothers’ age at first birth. Technical report, ECONtribute Discussion Paper. Mincer, J. (1962). Labor force participation of married women: A study of labor supply. pp. 63–105. Moriconi, S. and N. Rodríguez-Planas (2021). Gender norms and the motherhood employment gap. Morselli, D., N. Dasoki, R. Gabriel, J.-A. Gauthier, J. Henke, and J.-M. Le Goff (2016). Using life history calendars to survey vulnerability. In Surveying human vulnerabilities across the life course, pp. 179–201. Springer, Cham. Morselli, D., J.-M. Le Goff, and J.-A. Gauthier (2019). Self-administered event history calendars: a possibility for surveys? Contemporary Social Science 14(3-4), 423–446. MSPI (2013). Periodic labour force survey annual report, july 2020-june 2021. Technical report, The Ministry of Statistics and Programme Implementation, Government of India. Nair, M., A. P., and W. P. (2014). Impact of mothers’ employment on infant feeding and care: a qualitative study of the experiences of mothers employed through the mahatma gandhi national rural employment guarantee act. BMJ Open. Neff, D. F., K. Sen, and V. Kling (2012). The puzzling decline in rural women’s labor force participation in india: A reexamination. 48 Quisumbing, A. R. and K. Hallman (2005). Marriage in transition: Evidence on age, education, and assets from six developing countries. The changing transitions to adulthood in developing countries: Selected studies, 200–269. Rindfuss, R. R., S. P. Morgan, and C. G. Swicegood (2022). First births in America: Changes in the timing of parenthood, Volume 2. Univ of California Press. Rosenzweig, M. R. and K. I. Wolpin (1980). Life-cycle labor supply and fertility: Causal inferences from household models. Journal of Political economy 88(2), 328–348. Sarkar, S., S. Sahoo, and S. Klasen (2019). Employment transitions of women in india: A panel analysis. World Development 115, 291–309. Schmieder, J. (2021). Fertility as a driver of maternal employment. Labour Economics 72, 102048. Siddique, Z. (2022). Media-reported violence and female labor supply. Economic Development and Cultural Change 70(4), 1337–1365. Singh, M., C. Shekhar, and N. Shri (2023). Patterns in age at first marriage and its determinants in india: A historical perspective of last 30 years (1992–2021). SSM- Population Health 22, 101363. Solga, H. (2001). Longitudinal surveys and the study of occupational mobility: Panel and retrospective design in comparison. Quality and quantity 35(3), 291–309. Waldfogel, J. (1998). Understanding the ‘family gap’in pay for women with children. Journal of economic Perspectives 12(1), 137–156. Wuestenenk, N. and K. Begall (2022). The motherhood wage gap and trade-offs between family and work: A test of compensating wage differentials. Social science research 106, 102726. Yoshihama, M., B. Gillespie, A. C. Hammock, R. F. Belli, and R. M. Tolman (2005). Does the life history calendar method facilitate the recall of intimate partner violence? comparison of two methods of data collection. Social Work Research 29(3), 151–163. 49 ASIAN DEVELOPMENT BANK ASIAN DEVELOPMENT BANK 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org MARRIAGE, MOTHERHOOD, AND WOMEN’S EMPLOYMENT IN RURAL INDIA ASIA Rahul Lahoti, Rosa Abraham, and Hema Swaminathan ADB ECONOMICS WORKING PAPER SERIES NO. 757 December 2024 Marriage, Motherhood, and Women’s Employment in Rural India Life cycle events—marriage and motherhood—often impact women’s labor force participation. However, these impacts are mediated by the context in which they occur including the type of labor market (formal or informal), economic status, and prevailing social norms governing gender roles. Using unique data from two states in India, the paper finds that contrary to expectations, childbirth does not negatively affect women’s labor supply. On the other hand, marriage leads to a sustained increase in women’s labor market participation. About the Asian Development Bank ADB is committed to achieving a prosperous, inclusive, resilient, and sustainable Asia and the Pacific, while sustaining its efforts to eradicate extreme poverty. Established in 1966, it is owned by 69 members —49 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance.