Measuring Economic Mobility in India Using Noisy Data: A Partial Identification Approach. A new GLO Discussion Paper by GLO Fellow Punarjit Roychowdhury and colleagues.

A new GLO Discussion Paper casts doubt on the conventional wisdom that marginalized households are catching up.

GLO Discussion Paper No. 1227, 2023

1227 Measuring Economic Mobility in India Using Noisy Data: A Partial Identification Approach – Download PDF
by Li, Hao & Millimet, Daniel L. & Roychowdhury, Punarjit

GLO Fellow Punarjit Roychowdhury

Punarjit Roychowdhury

Author Abstract: We examine economic mobility in India while accounting for misclassification to better understand the welfare e§ects of the rise in inequality. To proceed, we extend recently developed methods on the partial identification of transition matrices. Allowing for modest misclassification, we find overall mobility has been remarkably low: at least 65 percent of poor households remained poor or at-risk of being poor between 2005 and 2012. We also find Muslims, lower caste groups, and rural households are in a more disadvantageous position compared to Hindus, upper caste groups, and urban households. These findings cast doubt on the conventional wisdom that marginalized households in India are catching up.

PUBLISHED
Vol. 36, Issue 1, January 2023: Journal of Population Economics (JOPE) 16 articles. https://link.springer.com/journal/148/volumes-and-issues/36-1
Watch the videos of article presentations on December 1, 2022 during the GLO Global Conference 2022.

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