Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard first-differenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in performance of the proposed estimators compared to the usual first-differenced GMM estimator, and compared to non-linear GMM. The importance of these results is illustrated in an application to the estimation of a labour demand model using company panel data.
Authors
![Richard Blundell](/sites/default/files/styles/square_desktop/public/2024-03/Richard%20Blundell%20Head.jpg?itok=ow7e9OkA)
CPP Co-Director
Richard is Co-Director of the Centre for the Microeconomic Analysis of Public Policy (CPP) and Senior Research Fellow at IFS.
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
Stephen Bond
Journal article details
- Publisher
- Elsevier
- JEL
- C23
- Issue
- August 1998
Suggested citation
Blundell, R and Bond, S. (1998). 'Initial conditions and moment restrictions in dynamic panel data models' (1998)
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