Abstract

Attempts have been made to estimate poverty in India using a biased dataset, by adjusting household weights to remove or reduce the bias. The effectiveness of this method, however, is uncertain. Simulation exercises suggest that its ability to correct poverty estimates varies wildly depending on the nature of the underlying bias, which may be hard to guess—there lies the rub. When the bias changes over time, estimating poverty trends becomes truly problematic. There are wider lessons for poverty estimation with biased or missing data. JEL Classifications: C83, I32

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.