share of care work among rural women. On the other hand, we observe higher participation in leisure and self-care activities in the recall arm, including personal care, sleep and food consumption. Importantly, the smartphone arm also reflects greater participation among men in different areas of unpaid work — so that gender gaps in unpaid work in the smartphone sample, while remaining large, are narrowed when compared to the recall arm. Further, we show that the total reported time across most activities is, on average, higher in the recall arm, for both men and men and across urban and rural areas. The main driver of this finding is the set-up of the 24-hour time use diary to record activities in 15-minute intervals, while around a third of activities reported in the smartphone arm in fact last less than 15 minutes, with non-farm employment, unpaid domestic and care work, and self-care activities making up the greatest shares of these tasks. Given the common use of the 15-minute structure of time use diaries (UN Women, 2021; Seymour et al., 2020), our findings highlight how this structure can lead to “rounding” and overestimation of reported time.

Second, the smartphone data collection provides greater insights regarding the diversity and frequency of activities conducted throughout the day and a <mark>significantly greater incidence of activities (in particular nonleisure activities) conducted simultaneously with each other vis-à-vis the recall treatment arm.</mark> These nuances on time allocation can also help explain some of the drops in participation across activities that we observe in the recall arm. Recall, for example, leads to a substantial drop-off in reporting <mark>of active time in the early evening hours (after 6 pm), particularly among women. These hours account for a large share of daily time — about 26 percent of daily time for women and 29 percent of daily time for men in the smartphone arm. We discuss how underreporting of activities in the evening in the recall arm may be due to respondent fatigue - since each recall interview could last up to 30 to 40 minutes – as well as other interview-related factors. We also discuss how activity-linked pop-ups in the smartphone data collection to record the presence of other children, may highlight an important but understudied dimension of passive childcare (Folbre, 2005), over and above respondents’ own estimates of childcare.</mark> Third, we show that the stylized recall module with a 7-day reference period leads to even higher estimates of reported daily time compared to the 24-hour recall diary. Moving from real-time data collection to 24hour recall, and to 7-day recall therefore leads to increasing estimates of time allocation to both employment and unpaid domestic and care work. <mark>Recent studies on farm labor (Arthi et al., 2018; Gaddis et al., 2021) have also found that longer recall periods (e.g., over the last 30 days or the past season vis-àvis the last 7 days) overestimate labor time.</mark> Our findings are consistent over different reporting days, and treatment effects are robust to controlling for a range of individual, household, and community characteristics. We also discuss the successful experience with smartphone-based data collection, including the fact that the drop-offs among the selected participants were limited; that there was high, sustained participation in terms of logged activities and time; and that there was increasing proficiency in the use of the app throughout the study period. These findings can help accelerate the validation of scalable, improved approaches to individual-level data 4