A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables
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 practiceDownload Info
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Bibliographic Info
Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 136.Length:
Date of creation: 11 Aug 2004
Date of revision:
Handle: RePEc:ecm:nasm04:136
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Related research
Keywords: Initial Conditions; Missing Data; Simulation Estimation;Other versions of this item:
- Michael P. Keane & Robert M. Sauer, 2010. "A Computationally Practical Simulation Estimation Algorithm For Dynamic Panel Data Models With Unobserved Endogenous State Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 51(4), pages 925-958, November.
- Keane, Michael P. & Sauer, Robert M., 2009. "A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables," IZA Discussion Papers 4054, Institute for the Study of Labor (IZA).
- Sauer, Robert & Keane, Michael P., 2007. "A computationally practical simulation estimation algorithm for dynamic panel data models with unobserved endogenous state variables," Discussion Paper Series In Economics And Econometrics 0705, Economics Division, School of Social Sciences, University of Southampton.
- Michael P. Keane & Robert M. Sauer, 2010. "A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables," Working Papers 1008, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 05 Jul 2010.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
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