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A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables

Robert Sauer () and Michael Keane ()

No 136, Econometric Society 2004 North American Summer Meetings from Econometric Society

Abstract: This paper develops a new simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can deal with the commonly encountered and widely discussed ``initial conditions problem,'' as well as the more general problem of missing state variables at any point during the sample period. Repeated sampling experiments on a dynamic panel data probit model with serially correlated errors indicate that the estimator has good small sample properties and is computationally practical for use with panels of the size that are likely to be encountered in practice

Keywords: Initial Conditions; Missing Data; Simulation Estimation (search for similar items in EconPapers)
JEL-codes: C15 C23 C25 (search for similar items in EconPapers)
Date: 2004-08-11
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Related works:
Journal Article: A COMPUTATIONALLY PRACTICAL SIMULATION ESTIMATION ALGORITHM FOR DYNAMIC PANEL DATA MODELS WITH UNOBSERVED ENDOGENOUS STATE VARIABLES (2010) Downloads
Working Paper: A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables (2010) Downloads
Working Paper: A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables (2009) Downloads
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