Xinshen Diao, Mia Ellis, Margaret McMillan, Dani Rodrik, 01 March 2021

Before Covid-19 struck, many economies in sub-Saharan Africa were expanding rapidly – faster than at any time since independence. Yet African growth accelerations were anomalous when viewed from the perspective of comparative development patterns; structural changes were accompanied by declining within-sector productivity growth in modern sectors. This column explores this anomaly in the context of African manufacturing using newly created firm-level panel data for Tanzania and Ethiopia. In both countries, there is a sharp dichotomy between larger firms that exhibit superior productivity performance but do not expand employment much, and small firms that absorb employment but do not experience any productivity growth. These patterns appear to be related to technological advances in global manufacturing which are making it more capital intensive.

Margherita Comola, Marcel Fafchamps, 08 December 2015

Dyadic social network data – describing relations between two actors – are frequently derived from self-reporting surveys. This column explores how the misreporting problems that are typical of such data can bias estimations. Data on transfers between households in a Tanzanian village are shown to display a high rate of discrepancies within dyads. Failure to account for such misreporting results in a sizeable underestimation of inter-household transfers. 

Joachim De Weerdt, Kathleen Beegle, Jed Friedman, John Gibson, 18 February 2014

Whereas the Millennium Development Goal of reducing extreme poverty by half was achieved by 2010, the global hunger rate has only fallen by a third since 1990. Differences in survey design may account for part of this discrepancy. This column presents the results of a recent experiment in which households were randomly assigned to different survey designs. These different designs yield vastly different hunger estimates, ranging from 19% to 68% of the population being hungry.

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