We show that the quantile regression estimator is consistent and asymptotically normal when the error terms are correlated within clusters but independent across clusters. A consistent estimator of the covariance matrix of the asymptotic distribution is provided and we propose a specification test capable of detecting the presence of intra-cluster correlation. A small simulation study illustrat...

This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters. We consider cases in which the nuisance parameter is estimated from independent and identical samples. A simulation experiment is conducted for covariance structure models. Empirical likelihood offers much reduced mean and median bia...

Variability in speech due to dialect is a major factor limiting speech system performance for speech recognition, spoken document retrieval, and dialog systems. In this study, we propose a novel discriminative algorithm to improve dialect classification for unsupervised spontaneous speech in Arabic. No transcripts are used for either training or testing, and all data are spontaneous speech. The...

Theil, Basmann, and Sargan are often credited with the development of the two-stage least squares (TSLS) estimator of the coefficients of one structural equation in a simultaneous equations model. However, Anderson and Rubin had earlier derived the asymptotic distribution of the limited information maximum likelihood (LIML) estimator by finding the asymptotic distribution of what is essentially...

This paper develops a new efficient estimator for the average treatment effect, if selection for treatment is on observables. The new estimator is linear in the first-stage nonparametric estimator. This simplifies the derivation of the means squared error (MSE) of the estimator as a function of the number of basis functions that is used in the first stage nonparametric regression. We propose an...

The article investigates the finite sample properties of estimators for spatial autoregressive models where the disturbance terms may follow a spatial autoregressive process. In particular we investigate the finite sample behavior of the feasible generalized spatial two-stage least squares (FGS2SLS) estimator introduced by Kelejian and Prucha (1998), the maximum likelihood (ML) estimator, as we...

This paper presents a novel automatic speaker age and gender identification approach which combines five different methods at the acoustic level to improve the baseline performance. The five subsystems are (1) Gaussian mixture model (GMM) system based on mel-frequency cepstral coefficient (MFCC) features, (2) Support vector machine (SVM) based on GMM mean supervectors, (3) SVM based on GMM maxi...

Empirical researchers frequently use dynamic panel data models and employ Generalized Method of Moments (GMM) estimators (Hansen, 1982) to estimate model parameters. An important practical problem in the estimation of a dynamic panel data model is the choice of moments as it provides a large number of moment conditions. Even though adding moment conditions leads to efficiency gain according to ...

In this paper we consider three questions. Why do only some firms enter export markets? What are the benefits to the firm from export market entry? Why do some of these firms exit the market at a future date? Using data on UK manufacturing firms from 1988 to 2002 we find evidence that information spillovers between firms can raise the probability of entry and for a matched sample of firms there...

We show for CES demands with heterogeneous production costs that profit, revenue, and output distributions lie in the same class as the productivity distribution (e.g., the "Pareto circle"), although the price distribution lies in the inverse class. We relate distribution shapes via the elasticities of their densities. Introducing product quality decouples the CES circle. Then, all distribution...