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
Volume: 32, Issue: 1, Page Number(s): 37-55


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