A new method is proposed for estimating linear triangular models, where identification results from the structural … errors following a bivariate and diagonal GARCH(1,1) process. The associated estimator is a GMM estimator shown to have the …

This paper presents a new method for identifying triangular systems of time-series data. Identification is the product … of a bivariate GARCH process. Relative to the literature on GARCH-based identification, this method distinguishes itself …. Estimation follows OLS and standard univariate GARCH and ARMA techniques, or GMM. A Monte Carlo study of the GMM estimator is …

estimation techniques can then be readily applied. Distribution theory for a kernel-weighted GMM estimator under large-n and …

in the SALS framework. In the particular case of the II and the EMM methods and when the instrumental model is of a GMM …

This paper shows how to construct locally robust semiparametric GMM estimators, meaning equivalently moment conditions …

, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or …

, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or …

It is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small … alternatives are considered in this paper. The first includes estimators which are asymptotically first-order equivalent to the GMM … bias-adjusted GMM estimators form the second class of alternatives. Two extensive Monte Carlo simulation studies are …

The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an …