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Estimation of Poverty Transition Matrices with Noisy Data

  • Nayoung Lee

    ()

    (Department of Economics, Chinese University of Hong Kong)

  • Geert Ridder

    ()

    (Department of Economics, USC)

  • John Strauss

    ()

    (Department of Economics, University of Southern California;)

This paper investigates potential 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. This dynamic model needs error-free initial conditions that can not be derived from these estimates. We provide bounds on the initial-conditions parameters, when these initial conditions are obtained by projection, and we also obtain initial conditions on the assumption that there is no time-constant measurement error. We ?nd that for both estimates of the initial conditions measurement error in expenditure data magni?es economic mobility in and out of poverty. Roughly 44% of households initially in poverty at time t??1 are found to be out of poverty at time t using expenditure data from the Korean Labor and Income Panel Study (KLIPS). However, when we remove measurement error through a model-based simulation, only between 32 and 40% of households initially in poverty are found to be out of poverty.

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Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 576.

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Length: 60p
Date of creation: Sep 2010
Date of revision:
Handle: RePEc:rio:texdis:576
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