Measuring Time Use in Developing Country Agriculture: Evidence from Bangladesh and Uganda

ABSTRACT

This paper discusses the challenges associated with implementing time-use surveys among agricultural households in developing countries and offers advice on best practices for two common measurement methods: stylized questions and time diaries. Using data from Women’s Empowerment in Agriculture Index (WEAI) surveys in Bangladesh and Uganda, it finds that stylized questions do not always produce shorter interviews compared to time diaries, and recall accuracy may depend on the regularity and saliency of the activity and enumerator abilities. The paper suggests that combining promising methodological innovations from other disciplines with mainstream time-use data collection methods would allow capture of both the quantity and quality of time and provide richer insights into gendered time-use patterns. Broadening the scope of time-use research to other aspects of well-being can help identify how time constraints contribute to gender inequality and inform the design of policies and interventions to relieve those constraints.

HIGHLIGHTS

• Time-use surveys are essential for addressing gender disparities, yet little research has compared time-use survey methods in developing countries.

• Developing country agricultural contexts present unique logistical challenges to time-data collection, including low literacy and unfamiliarity with clock-oriented time.

• In Bangladesh and Uganda, there are systematic differences between time-use estimates obtained using stylized questions and time diaries.

• Men and women experience different emotions toward different types of work, and gender gaps exist in the distribution of pleasant and unpleasant activities.

• Learning from non-economics disciplines, including research on quality of time, leads to richer insights into gendered time-use patterns.

KEYWORDS:

• Time use
• recall error
• measurement error

JEL CODES:

• C81
• J22
• Q12

ACKNOWLEDGMENTS

This paper is part of a broader collaboration on methodological experimentation among several researchers from the World Bank, the International Food Policy Research Institute, the International Rescue Committee, and Oxford University to improve the measurement of time use, women’s agency, and ownership and control of assets. Specifically, the collaboration aims to achieve three goals: (1) assess the relative quality of the existing methods of measuring these constructs; (2) design and test new ideas to measure these constructs; (3) generate evidence on which measurement method is most appropriate given the policy and research question at hand. This work was undertaken as part of the Gender, Agriculture, and Assets Project Phase Two (GAAP2), the CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), and the CGIAR Research Program on Policies, Institutions, and Markets (PIM).

Notes

1 The applicability of time-use studies to research questions in either category, of course, depends on a broad range of factors, including the breadth of information collected in the survey and respondent selection within households.

2 See, for example, the labor force component of the US Current Population Survey: http://www2.census.gov/programs-surveys/cps/techdocs/questionnaires/Labor%20Force.pdf.

3 We thank an anonymous referee for raising these important differences between the WEAI surveys and stand-alone national time-use surveys.

4 Although this evidence comes almost entirely from developed countries, many of the insights are likely still relevant in developing countries.

5 These guidelines were developed based on the protocol developed for the WEAI by Data Analysis and Technical Assistance, Limited (DATA) in Bangladesh. A video tutorial for the method is available online: https://www.youtube.com/watch?v=jr8ebiKUkbQ.

6 Similarly, Man Yee Kan and Stephen Pudney (2008) compare SQ and TD estimates for the same individual in a British survey and find evidence of greater measurement error in SQs versus TDs, though they attribute this mostly to randomness rather than systematic bias.

7 Seasonality bias is not limited to farming. Time spent on other activities that also follow a seasonal schedule (for example, small businesses, construction work, migrant labor) may also exhibit seasonality bias.

8 Question 3 only asked if the time spent on [ACTIVITY] in the last 7 days was unusual according to the respondent.

9 Also called “event sampling methodology,” this method was initially developed by Reed Larson and Mihaly Csikszentmihalyi (1983). Antecedents of this method include random spot observation. In random spot observation, external observers collect the data, whereas in experience sampling, the respondent responds about his or her conditions at a given time.

10 For example, if a respondent reported experiencing happiness (10) more often than sadness (2), tiredness (4), pain (1), and stress (3) during a particular episode of activity, then the episode was classified as pleasant.

11 This draws from notes prepared by Gina Kennedy on measuring energy expenditure and physical activity, see http://www.a4nh.cgiar.org/files/2015/01/Energy-Expenditure-and-Physical-Activity-Reference-Notes1.pdf.

12 A recent example of this approach in a developing country context is the study by Herman Pontzer et al. (2012) in Tanzania.

13 There are several questionnaires, mainly from the US and Europe, that include links to physical activity questionnaires, for example: http://appliedresearch.cancer.gov/resource/collection.html.

Additional information

Funding

Funding support was provided by the Bill & Melinda Gates Foundation (BMGF) [Grant number: OPP1125297], the United States Agency for International Development (USAID) [Grant number: EEM-G-00-04-00013-00], A4NH, and PIM.

Notes on contributors

Greg Seymour

Greg Seymour is Research Fellow at the Environment and Production Technology Division at the International Food Policy Research Institute (IFPRI). His current research focuses on the refinement and validation of the Women’s Empowerment in Agriculture Index (WEAI) and, in broader research efforts, to understand the impacts of women’s empowerment on agricultural outcomes. He received his PhD and MA in economics from American University.

Hazel Malapit

Hazel Malapit is Senior Research Coordinator at the Poverty, Health, and Nutrition Division at IFPRI. She coordinates research, training, and technical assistance on the implementation of the Women’s Empowerment in Agriculture Index (WEAI), manages and coordinates the integration of gender into the research of the CGIAR Research Program on Agriculture for Nutrition and Health (A4NH), and conducts research on gender, women’s empowerment, agriculture, health, and nutrition issues. She received her MA in economics from the University of the Philippines and her PhD in economics from American University.

Agnes Quisumbing

Agnes Quisumbing is Senior Research Fellow at the Poverty, Health, and Nutrition Division at IFPRI. She has published widely on gender, intrahousehold allocation, property rights, poverty, and economic mobility. She is currently engaged in impact evaluations of nutrition-sensitive agricultural development programs in South Asia and Sub–Saharan Africa, focusing on their impacts on women’s empowerment and gender asset inequality. She received her PhD and MA in economics from the University of the Philippines, Quezon City, was a Fulbright-Hays Fellow at the Massachusetts Institute of Technology, and a Visiting Fellow at the Economic Growth Center, Yale University.