Household-Level Inequality in Sub-Saharan Africa: An Empirical Analysis Using Cross-Sectional and Panel Data

Type Working Paper
Title Household-Level Inequality in Sub-Saharan Africa: An Empirical Analysis Using Cross-Sectional and Panel Data
Author(s)
Publication (Day/Month/Year) 2012
URL http://www.artsci.wustl.edu/~rllopis/pdfs/CrossSecandMobFactsSSA_Updated.pdf
Abstract
Facts on household-level economic inequality on consumption, income, wealth, and la- bor supply are readily available for a large set of industrialized economies—see a comprehen- sive and updated review in Krueger et al. (2010). However, little is known about the same distributional facts in developing countries, in particular, in Sub-Saharan Africa (SSA). This paper works toward closing this gap. First, using new and unique cross-sectional nationally representative data from the Living Standards Measurement Study: Integrated Surveys on Agriculture (LSMS-ISA), we empirically investigate dimensions of economic inequality for Malawi (2010), a typical SSA country. We study the cross-sectional facts of household con- sumption, income—including its main sources, labor income and agricultural production—, land, and wealth separately. Further, we analyze the behavior of the extensive and intensive margins of labor supply. The distribution of market wages, agricultural labor productivity, and land productivity is also empirically investigated. Throughout our analysis, alternative sources of inequality such as education, gender, marital status, household composition, and societal systems are explored. Our exercise is then extended to the SSA countries for which cross-sectional LSMS-ISA data are currently available: Nigeria (2011), Tanzania (2008), and Uganda (2011). Second, using a unique panel of individual data representative of rural Malawi, the Malawi Longitudinal Survey of Families and Health (MLSFH), we study income dynamics. We estimate the income process of labor income and agricultural production, and quantify the respective permanent and transitory components of residual inequality over the life cycle. Further, motivated by the HIV epidemic that severely affects SSA, we provide empirical evidence on the effects of individual HIV status on income dynamics.

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