Estimation of Poverty Transition Matrices with Noisy Data
研究了调查支出数据中的测量误差如何导致贫困转移矩阵估计偏差，发现时间变化误差会夸大经济流动性，以韩国数据为例，去除误差后脱贫比例从45%降至26%-31%。
Summary 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.