Time use data facilitate deeper understanding of individual labor supply choices, especially for women, who are more likely to engage in unpaid care and home production. However, traditional time use data collection methods are time consuming, expensive and susceptible to significant attrition.
Researchers have developed a novel, low-cost and effective way to collect time use data in developing economies, including both single and multi-tasking.
To address these concerns, the research team based at Inclusion Economics at Yale University, Duke University, Harvard University, the University of Southern California, and the University of California at Berkeley developed an abbreviated, low-cost time use survey module designed for low-literacy populations. It captures contextually-determined broad time use categories of interest to researchers – in this case, time allocations across market work, household labor, and leisure. Using survey experiments in the field, researchers show that, relative to the widely-used assisted diary approach, the new module is lower cost and relatively more accurate in capturing individuals’ average time use. Its primary shortcoming is limited ability to capture short duration activities. Using the example of passive childcare, the research team shows how module design can address this shortcoming for an identified category of interest.