The generalised method of moments (GMM) is combined with the nonparametric estimation of the instrument matrix to obtain an easily computable estimator for the panel probit model. It is based on the speciication of the conditional mean of the binary dependent variable in each period, and therefore high-dimensional numerical integrations are avoided. An extensive Monte Carlo study compares this ...

Language recognition with support vector machines and shifteddelta cepstral features has been an excellent performer in NISTsponsored language evaluation for many years. A novel improvement of this method has been the introduction of hybrid SVM/GMM systems. These systems use GMM supervectors as an SVM expansion for classification. In prior work, methods for scoring SVM/GMM systems have been int...

This paper explores the time series properties of commonly used variables in ̄rm-level panels: sales (turnover), employment, R&D, investment, and cash °ow. We focus on two questions: 1) whether the behavior of these series is consistent with stationarity, and if so, 2) what order of autoregressive process best describes them. The answer to these two questions is of substantive interest for those...

This study empirically examines the impact of international monetary policy on bank risk in Indian context. Using annual data from 64 banks and employing panel OLS GMM techniques, this finds that: (1) a contractionary increases risk; (2) an appreciation domestic exchange rate induces riskiness; (3) affects through “search for yield” channel; (4) is relatively significant explaining riskiness po...

This paper develops consistent model and moment selection criteria for GMM estimation. The criteria select the correct model speci"cation and all correct moment conditions asymptotically. The selection criteria resemble the widely used likelihoodbased selection criteria BIC, HQIC, and AIC. (The latter is not consistent.) The GMM selection criteria are based on the J statistic for testing over-i...

Gaussian mixture models (GMMs) have proven extremely successful for textindependent speaker verification. The standard training method for GMM models is to use MAP adaptation of the means of the mixture components based on speech from a target speaker. In this work we look into the various models (GMM-UBM and GMM-SVM) and their application to speaker verification. In this paper, features vector...

The paper considers text independent speaker identification over the telephone using short training and testing data. Gaussian Mixture Modeling (GMM) is used in the testing phase, but the parameters of the model are taken from clusters obtained for the training data by an adequate choice of feature vectors and a distance measure without optimization in the maximum likelihood (ML) sense. This di...

in present study, role of agricultural on eco countries regional convergence was assessed in dynamic panel data model. at first, eco countries convergence and agricultural sector effect in convergence acceleration was surveyed by generalized method of moments (gmm) over the period 1996-2005. results showed that, this is convergence between eco countries. in spite of increasing regional growth, ...