Abstract
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.
Keywords
EstimatorInferencePanel dataSample (material)Linear modelMathematicsEconometricsStatisticsApplied mathematicsComputer scienceArtificial intelligenceChromatographyChemistry
Affiliated Institutions
Related Publications
Large sample estimation and hypothesis testing
Asymptotic distribution theory is the primary method used to examine the properties of econometric estimators and tests. We present conditions for obtaining cosistency and asymp...
Dynamic panel estimation and homogeneity testing under cross section dependence *
This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a pane...
Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
We study the properties of the quasi-maximum likelihood estimator (QMLE) and related test statistics in dynamic models that jointly parameterize conditional means and conditiona...
Statistical Inference in Regressions with Integrated Processes: Part 1
This paper develops a multivariate regression theory for integrated processes which simplifies and extends much earlier work. Our framework allows for both stochastic and certai...
Efficient R-Estimation of Principal and Common Principal Components
We propose rank-based estimators of principal components, both in the one-sample and, under the assumption of common principal components, in the m-sample cases. Those estimator...
Publication Info
- Year
- 2002
- Type
- paratext
- Citations
- 76
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
76
OpenAlex
Cite This
Frank Windmeijer,
Stephen Bond
(2002).
Finite sample inference for GMM estimators in linear panel data models.
Cemmap working papers
.
https://doi.org/10.1920/wp.cem.2002.0402
Identifiers
- DOI
- 10.1920/wp.cem.2002.0402