Evans School Policy Analysis & Research Group (EPAR)

Relative to chronic hunger, seasonal hunger in rural and urban areas of Africa is poorly understood. No estimates are compiled, and limited evidence exists on prevalence, causes, and impacts. This paper contributes to the body of evidence by examining the extent and potential drivers of seasonal hunger using panel data from the Malawi Integrated Household Panel Survey (IHPS). Farmers are commonly thought to use various strategies to smooth consumption, including planting “off-season” crops, investing in post-harvest storage technologies, or generally diversifying farm portfolios including livestock products and/or wild crops. Similarly, when markets are available, farmers may diversify through off-farm income sources in order to purchase food in lean seasons. We investigate whether seasonal hunger – distinct from chronic hunger – exists in Malawi, drawing on two waves of panel data from the LSMS-ISA series. We examine the extent of seasonal hunger, factors associated with variation in seasonal hunger, and how recurring and longer-term seasonal hunger might be associated with various household welfare measures. We find that both urban and rural households report experiencing seasonal hunger in the pre-harvest months, with descriptive evidence suggesting male gender, age, and education of household head, livestock ownership, and storage of crops are associated with lower levels of seasonal hunger. In addition, we find that Malawian households with seasonal hunger harvest crops earlier than average – a short-term coping mechanism that can reduce the crop’s yield and nutritional value, possibly perpetuating hunger.

Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.

This brief summarizes the evidence base for various types of commonly-used time use measurements, lists categories of time use as identified by major organizations and reports, and identifies studies finding significant impacts of interventions designed to reduce specific time constraints. The various approaches to time use measurement method each have different limitations (cost, timing, seasonality, susceptibility to recall bias, etc.), which may have implications for data analysis. The choice of how to measure time use may be particularly important for analyzing women’s time use. For example, limiting respondents to one activity per time slot when measuring daily time allocation may underestimate women's productivity or time allocations, as they are more likely than men to conduct simultaneous activities, such as childcare along with other activities.

This poster presentation summarizes research on changes in crop planting decisions on the extensive and intensive margin in Tanzania, with regards to changes in agricultural land that a farmer has available and area planted in the context of smallholders and farming systems. We use household survey data from the Tanzania National Panel Survey (TNPS), part of the World Bank’s Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS – ISA) to test how much the agricultural land available to households changes, how much farmers change the proportion of land decidated to growing priority crops, and how crop area changes vary with changes in landholding. We find that almost half of households had a change of agricultural land area of at least half a hectare from 2008-2010. Smallholder farmers on average decreased the amount of available land between 2008 and 2010, while non-smallholder farmers increased agricultural land area during that time period, but that smallholder households planted a greater proportion of their agricultural land than nonsmallholders. Eighty percent of households changed crop proportions from 2008 to 2010, yet aggregate level indicators mask household level changes.