University of Cincinnati Lindner College of Business

Estimation of Poverty Transition Matrices with Noisy Data
Na Young Lee

Status: Published
Year: 2017
Publication Name: Journal of Applied Econometrics

Abstract

This paper investigates measurement error biases in estimated poverty transition matrices. We compare transition matrices based on survey expenditure data to transition matrices based on measurement-error-free simulated expenditure. The simulation model uses estimates that correct for measurement error in expenditure. We find that time-varying measurement error in expenditure data magnifies economic mobility. Roughly 45% of households initially in poverty at time t − 1 are found to be out of poverty at time t using data from the Korean Labor and Income Panel Study. When measurement error is removed, this drops to between 26 and 31% of households initially in poverty. Copyright © 2016 John Wiley & Sons, Ltd.

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Na Young Lee
Na Young Lee