We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a more accurate asymptotic approximation to the distribution of the estimator; the LM test; and three criterion-bases tests that have recently been proposed. We consider both the AR(1) panel model, and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases.
Authors
Stephen Bond
Research Fellow University of Bristol
Working Paper details
- DOI
- 10.1920/wp.cem.2002.0402
- Publisher
- IFS
Suggested citation
Bond, S and Windmeijer, F. (2002). Finite sample inference for GMM estimators in linear panel data models. London: IFS. Available at: https://ifs.org.uk/publications/finite-sample-inference-gmm-estimators-linear-panel-data-models (accessed: 4 May 2024).
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