This paper studies the selection of valid and relevant moments for the generalized method of moments (GMM) estimation. For applications with many candidate moments, our asymptotic analysis accommodates a diverging number of moments as the sample size increases. The proposed procedure achieves...

This paper considers the selection of valid and relevant moments for the generalized method of moments (GMM) estimation. For applications with many candidate moments, our asymptotic analysis ccommodates a diverging number of moments as the sample size increases. The proposed procedure achieves...

This paper considers the selection of valid and relevant moments for the generalized method of moments (GMM) estimation. For applications with many candidate moments, our asymptotic analysis accommodates a diverging number of moments as the sample size increases. The proposed procedure achieves...

The Gibbons, Ross, and Shanken (1989) F-test of mean-variance efficiency of asset returns is stated incorrectly for the multi-factor case. We first derive the correct formula for the test statistic for the general case of K factors and N test assets, then highlight the impact of the error in...

We clear up an ambiguity in Gibbons, Ross and Shanken (1989, GRS hereafter) by providing the correct formula of the GRS test statistic for the multiple factor case and proving its exact F distribution, issues unaddressed in GRS (1989). We theoretically and empirically illustrate the consequences...

The method of sieves has been widely used in estimating semiparametric and nonparametric models. In this paper, we first provide a general theory on the asymptotic normality of plug-in sieve M estimators of possibly irregular functionals of semi/nonparametric time series models. Next, we...

This paper proposes a test for the conditional superior predictive ability (CSPA) of a family of forecast methods with respect to a benchmark. The test is functional in nature: Under the null hypothesis, the benchmark's conditional expected loss is no more than those of the competitors,...