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.