Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/91674 
Year of Publication: 
2013
Series/Report no.: 
ISER Working Paper Series No. 2013-22
Publisher: 
University of Essex, Institute for Social and Economic Research (ISER), Colchester
Abstract: 
We consider the estimation of measures of persistent poverty in panel surveys with missing data, focusing on the persistent poverty headcount, its duration-adjusted variant, and a related measure used by the European Union as an indicator of the risk of persistent poverty. We develop a partial identification approach to allow for data missing-not-at-random, and apply it to panel data from Peru for 2007-11. The worst case bounds are very wide, but we achieve much more precise identification by adding a set of weak a priori restrictions. Standard non-response weighting adjustments cannot be relied upon to remove missing-data bias.
Subjects: 
Missing data
Poverty persistence
Partial identification
JEL: 
D31
I32
Document Type: 
Working Paper

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