RELIABLE INFERENCE FOR GMM ESTIMATORS? FINITE SAMPLE PROPERTIES OF ALTERNATIVE TEST PROCEDURES IN LINEAR PANEL DATA MODELS
比较了线性面板数据模型GMM估计中多种检验方法的有限样本表现，发现校正的两步Wald检验与标准一步Wald检验表现相似，而自助法一步Wald检验、LM检验和简单准则差异检验在某些情况下能提供更可靠的推断。
ABSTRACT We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using the generalized 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 finite sample corrected estimate of the variance of the two-step GMM estimator; the LM test; and three criterion-based 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.