Survey design and rural labor measurement: Lessons from three studies

Effective policies and programs aiming to reduce poverty require a clear understanding of how people earn their livelihoods. While great gains have been made in the quantity and availability of data, capturing individuals’ labor supply and types of job activities is still challenging. Measuring employment is especially difficult in settings where productive activities are informal, leading to irregular intensity of engagement, and seasonal, where the majority of effort and earning is concentrated in specific periods of the year. These characteristics tend to be especially relevant in rural labor markets in low-income countries where agriculture and agriculture-linked employment are preeminent. In a set of three studies, IFPRI researchers Kate Ambler and Sylvan Herskowitz, in collaboration with Mywish Maredia of Michigan State University, explore the ways in which survey design can affect the quality of resulting labor data in rural populations. The papers examine the effects of household roster order, question type, and recall windows on resulting data. Survey design decisions matter and, if not careful, can induce unintended noise, or more troublingly, bias in resulting data.