As a quick econometric solution to handle potential endogeneity issues in panel data models, the Arellano-Bond/Blundell-Bond generalized method of moments (GMM) estimator continues gain popularity IS research. Despite this estimator’s sensitivity model specifications and estimation strategies, noticeable number studies that have employed failed report detailed specifications, robustness check r...

As previously argued, the correlation between included and omitted regressors generally causes inconsistency of standard estimators for count data models. Non-linear instrumental variables estimation of an exponential model under conditional moment restrictions is one of the proposed remedies. This approach is extended here by fully exploiting the model assumptions and thereby improving efficie...

We consider two stage estimation with a non-parametric first stage and a generalized method of moments second stage, in a simpler setting than [CCD16]. We give an alternative proof of the theorem given in Chernozhukov et al. [CCD16] that orthogonal second stage moments, sample splitting and n-consistency of the first stage, imply √ n-consistency and asymptotic normality of second stage estimate...

This paper studies the application of generalized method moments (GMM) to multi-reference alignment (MRA): problem estimating a signal from its circularly-translated and noisy copies. We begin by proving that GMM estimator maintains asymptotic optimality for statistical models with group symmetry, including MRA. Then, we conduct comprehensive numerical study show substantially outperforms class...

The maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM) approach is developed...

A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and autocorrelation in the data by using a nonparametric estimator of the optimal weighting matrix. This paper addresses the issue of choosing the corresponding smoothing parameter (or bandwidth) so that the resulting point estimate is optimal in a certain sense. We derive an asymptotically op...

This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects, which suggested in econometric literature, such as least squares (LS) and generalized method of moments (GMM). These methods obtain biased estimators for DPD models. The LS estimator is inconsistent when the time dimension (T) is short regardless of the cross-sectional dimension (N). Although con...