We propose a class of new robust Generalized Method of Moments (GMM) tests for endogenous structural breaks. The tests are based on supremum, average and exponential functionals derived from robust GMM estimators with bounded influence function. We study the theoretical local robustness properties of the new tests and show that they imply a uniformly bounded asymptotic sensitivity of size and p...

The ability to monitor cognitive load level in real time is extremely useful for preventing fatal operating errors or improving the efficiency of task execution. In top of the success of our previously proposed speech based cognitive load monitoring system, we explored alternative classification techniques in this paper, including simple linear kernel Support Vector Machine (SVM), hybrid SVM-GM...

This paper indicates that the consequences of regional trade agreements for the world trade system may be deceiving—an arrangement’s apparent virtue may constitute the source of its drawback. In a model where governments have political, as well as economic, motivations, I show that a free trade area induces its members to reduce protection against the non-members, and to do so sufficiently deep...

Gaussian mixture modeling with universal background model (GMM-UBM) is a widely used method for speaker identification, where the GMM model is used to characterize a specific speaker’s voice. The estimation of model parameters is generally performed based on the maximum likelihood (ML) or maximum a posteriori (MAP) criteria. In this way, interspeaker information that discriminates between diffe...

This paper demonstrates that modelling session variability during GMM training can improve the performance of a GMM supervector SVM speaker verification system. Recently, a method of modelling session variability in GMM-UBM systems has led to significant improvements when the training and testing conditions are subject to session effects. In this work, session variability modelling is applied d...

This paper proposes a simple test for global identi…cation of Generalized Method of Moments (GMM) estimators in models de…ned by conditional moment restrictions. The test is based on comparing two estimators, one which is always consistent, even under global identi…cation failure of the unconditional model, and the GMM estimator. It is shown that the test is able to detect Pitman alternatives, ...

This paper examines the association between government ownership and bank stability over 1997-2010 across a sample of 103 countries. With a continuous variable to proxy for government ownership, our system GMM estimates indicate that the association between government ownership and bank stability depends on a country’s economic development and regulatory quality. In developed, high income count...

We propose a new finite sample corrected variance estimator for the linear generalized method of moments (GMM) including one-step, two-step, and iterated estimators. Our formula also corrects over-identification bias in estimation on top commonly used correction Windmeijer (2005), which from estimating efficient weight matrix, so is doubly corrected. An important feature proposed double that it...

Emotion classification is essential for understanding human interactions and hence is an important module in HumanComputer Interaction (HCI) systems. Well-performed emotion classification systems have potential to integrate into the HCI systems to provide additional user state details. This paper presents an emotion classification system that employs Emotional Dissimilarity (ED) measure. Instea...

In this paper, we adopt the boosting framework to improve the performance of acoustic-based Gaussian mixture model (GMM) Language Identification (LID) systems. We introduce a set of low-complexity, boosted target and anti-models that are estimated from training data to improve class separation, and these models are integrated during the LID backend process. This results in a fast estimation pro...