Multidimensional poverty with missing attributes

We show how to minimize the probability of misclassifying individuals as being poor or not poor when data on some of their relevant attributes are missing, but an estimate of the population distribution of attributes is available. •We minimize the probability of misclassifying individuals as being p...

Full description

Saved in:
Bibliographic Details
Published in:Economics letters 2015-05, Vol.130, p.51-55
Main Authors: Acharya, Avidit, Roemer, John E.
Format: Article
Language:English
Subjects:
Classification
Classification error
Estimation
Multidimensional poverty
Poverty
Probability
Social policy
Studies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We show how to minimize the probability of misclassifying individuals as being poor or not poor when data on some of their relevant attributes are missing, but an estimate of the population distribution of attributes is available. •We minimize the probability of misclassifying individuals as being poor or not poor.•The method works when data on some attributes are missing.•The method requires an estimate of the population distribution of attributes.•We take the method to data from India.
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2015.02.033