University of Michigan (Measuring livelihoods)

University of Michigan

Developing an innovative approach to measuring the livelihoods of smallholder farmers and testing critical linkages from farmer livelihoods to nutrition

PI: Andrew Jones
Partners: Jennifer Blesh (University of Michigan), Andrew Dillon (Michigan State University), Innovations for Poverty Action
Start date: 1 September 2015
Duration: 28 months
Value: £225,104
Countries of research: Burkina Faso

Summary of project:

Much of the current empirical literature examining the impacts of agriculture on nutrition outcomes has not assessed the most salient mechanisms by which agriculture will likely impact nutrition outcomes in the next 30 years. There is a critical need to adequately conceptualise and measure the diverse and rapidly evolving livelihood strategies of smallholder farmers in low- and middle-income countries, and understand the extent to which these livelihood strategies influence the diets and nutrition outcomes of the most vulnerable members of farming households. One of the main challenges to rigorously assessing the dynamic linkages between agriculture and nutrition is the difficulty in obtaining sufficiently comprehensive data to examine the multiple dimensions of farmer livelihoods that may influence diet and nutrition outcomes. Cross-country analyses of agriculture and nutrition relationships, and even comparisons of studies within countries, often rely on data collected using different survey design methods, which may bias estimates of agricultural production and livelihood characteristics, and the associations between these characteristics and nutrition outcomes.

Our proposed research leverages the expertise of an interdisciplinary team of investigators from the fields of nutritional science, agricultural economics, agroecology, and rural development, to develop a nutrition-sensitive metric for assessing the rapidly evolving livelihoods of farmers, and examining the dynamic linkages between agriculture and nutrition. Our team will also assess the effect of agricultural survey design on estimates of farmer livelihood characteristics, and the associations of these characteristics with nutrition outcomes. 

We will combine analysis of new, nationally representative data from Burkina Faso on the agricultural production, livelihoods, consumption, and nutritional status of farming households, with primary data collection as part of a methodological cluster-randomised trial from a unique sample of households engaged in agriculture across diverse regions of Burkina Faso. We propose to develop an integrated, nutrition-sensitive metric of smallholder farmer livelihoods, and apply a rigorous, randomised trial methodology to assess the effect of agricultural survey design on the measurement of farmer livelihood characteristics relevant to the assessment of agriculture and nutrition linkages. Little empirical research overall has examined the linkages between smallholder agriculture and nutrition, let alone attempted to identify and measure in an integrated fashion the importance of specific production and livelihood factors. Furthermore, this study is also innovative for its examination of bias in survey design with the aim of explicitly measuring and reducing bias in the estimation of cross-cutting agriculture-nutrition relationships.

We expect that the successful completion of this research will not only address the critical scientific need to understand how to conceptualise and measure the livelihood strategies of smallholder farmers, and assess their impact on nutrition, but will also have significant development relevance by informing nutrition-sensitive programmes and policies with rigorous empirical evidence on those agricultural livelihood factors most important for leveraging nutrition improvements. We expect that our testing of alternative survey design approaches will contribute to improvements in survey instruments that are comparable across contexts, that reduce implementation costs, and that allow for more widespread collection of integrated data sets to answer policy-relevant questions on the agriculture-nutrition nexus.