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Event description
Representative surveys on individuals¡¯ daily time use¡ªacross unpaid domestic and care work, employment and other productive activities¡ªare essential to understand economic decision-making among men and women.
However, standard recall-based time use surveys can be costly to conduct, and often face challenges in accurately capturing people¡¯s multiple daily activities. Addressing these difficulties is important to design data-driven labor policies and to improve the monitoring of global targets that recognize and value unpaid work across countries.
Our study is one of the first to compare real-time against recall-based time use data collection from a low-income context, and in this talk, we present findings from a randomized experiment in Malawi. We compare how real-time data collection, through a low-cost pictorial smartphone-based app, can address potential recall bias in traditional 24-hours and 7-days time use diaries.
The findings reveal several benefits of the smartphone diary approach, such as the possibility of capturing a greater range of multitasked activities and the avoidance of potential fatigue in recalling time allocation within the day¡ªparticularly among women.
We will discuss how the insights of our paper can advance the validation of scalable best practices to individual-level data collection on time use, which could, in turn, be considered for implementation as part of large-scale surveys conducted by national statistical offices.
Speakers
Talip Kilic&²Ô²ú²õ±è;¡ª Senior Program Manager for the Living Standards Measurement Study (LSMS), the World Bank¡¯s flagship household survey program housed at the Development Data Group.
He was also a core team member for the World Development Report 2021: Data for Better Lives. In his managerial role, Talip oversees the extensive LSMS portfolio of face-to-face and phone survey data production; methodological and policy research; and capacity development activities. As a researcher, he focuses on poverty, agriculture, labor, and gender in low- and middle-income countries, as well as survey methodology and data integration to improve the quality, timeliness, and policy-relevance of household and farm surveys.
Gayatri Koolwal ¡ª Development Economist and consultant for international development institutions, along with the World Bank.
Her research has focused on topics related to individuals¡¯ economic mobility, including employment, resilience, taxation and wealth in low and middle-income contexts. With the World Bank Living Standards Measurement Study (LSMS) program, she has conducted research on survey methodological approaches to better capture economic roles and opportunities for men and women. This includes improving the measurement of individuals¡¯ time use, and within the LSMS+ initiative, she has worked on assessing the benefits of self-reported data on individuals¡¯ labor and wealth.
Discussant
Nancy Folbre&²Ô²ú²õ±è;¡ª Professor Emerita of Economics and Director of the Program on Gender and Care Work at the Political Economy Research Institute at the University of Massachusetts Amherst and a Senior Fellow of the Levy Economics Institute at Bard College in the United States.
Her research explores the interface between political economy and feminist theory, with a particular emphasis on the value of unpaid care work. In addition to numerous articles published in academic journals, she is the author of The Rise and Decline of Patriarchal Systems (Verso, 2021), the editor of For Love and Money: Care Work in the U.S. (Russell Sage, 2012), the author of Greed, Lust, and Gender: A History of Economic Ideas (Oxford, 2009), Valuing Children: Rethinking the Economics of the Family (Harvard, 2008), and The Invisible Heart: Economics and Family Values (New Press, 2001). She has also written widely for a popular audience, including contributions to the New York Times Economix blog, The Nation, and the American Prospect. She is a co-curator of, and regular contributor to the Care Talk blog at revaluingcare.org.
This event is supported by The Living Standards Measurement Study (LSMS) and the World Bank Gender Group.