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Open Access Publications from the University of California

Fixed-smoothing Asymptotics in a Two-step GMM Framework

Creative Commons 'BY-NC-SA' version 3.0 license

The paper develops the Öxed-smoothing asymptotics in a two-step GMM framework. Under this type of asymptotics, the weighting matrix in the second-step GMM criterion function converges weakly to a random matrix and the two-step GMM estimator is asymptotically mixed normal. Nevertheless, the Wald statistic, the GMM criterion function statistic and the LM statistic remain asymptotically pivotal. It is shown that critical values from the fixedsmoothing asymptotic distribution are high order correct under the conventional increasingsmoothing asymptotics. When an orthonormal series covariance estimator is used, the critical values can be approximated very well by the quantiles of a noncentral F distribution. A simulation study shows that the new statistical tests based on the fixed-smoothing critical values are much more accurate in size than the conventional chi-square test.

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