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.
Margherita Comola, Marcel Fafchamps, 08 December 2015
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.