Sauer, Robert and Keane, Michael (2010) A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables. International Economic Review, 51 (4).
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This article develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. Repeated sampling experiments on dynamic probit models with serially correlated errors indicate the estimator has good small sample properties. We apply the estimator to a model of female labor supply and show that the rarely used Polya model fits the data substantially better than the popular Markov model. The Polya model also produces far less state dependence and many fewer race effects and much stronger effects of education, young children, and husband’s income on female labor supply decisions.
This is a Submitted version This version's date is: 11/2010 This item is not peer reviewed
https://repository.royalholloway.ac.uk/items/fb5e2289-69b9-0ab2-ac72-ce526d64f0b9/1/
Deposited by Research Information System (atira) on 11-Oct-2012 in Royal Holloway Research Online.Last modified on 11-Oct-2012