We have carried out high-resolution (∼3′) HI and CO line observations along onedimensional cuts through the Galactic worm GW46.4+5.5. By comparing the HI data with IRAS data, we have derived the distributions of I100 excess and τ100 excess, which are respectively the 100 μm intensity and 100 μm optical depth in excess of what would be expected from HI emission. In two observed regions, we were ...

This paper investigates the impact of stock markets and banks on economic growth using a panel data set for the period 1976-98 and applying recent GMM techniques developed for dynamic panels. On balance, we find that stock markets and banks positively influence economic growth and these findings are not due to potential biases induced by simultaneity, omitted variables or unobserved country-spe...

This paper discusses inference about the pre and post break value of a scalar parameter in GMM time series models with a single break at an unknown point in time. We show that treating the break date estimated by least squares as the true break date leads to substantially oversized tests and confidence intervals unless the break is large. We develop an alternative test that controls size unifor...

In this paper, by employing the Generalized Method of Moment (GMM) techniques and Chinese provincial level data from 1991 to 2003, we empirically investigate the relationship between finance and growth in post-reform China. We find that financial development significantly promotes economic growth in coastal regions but not in inland regions; the weak finance-growth nexus in inland provinces has...

This paper investigates the impact of stock markets and banks on economic growth using a panel data set for the period 1976-98 and applying recent GMM techniques developed for dynamic panels. Econometrically, the paper illustrates the differences that emerge from different panel procedures. On balance, we find that stock markets and banks positively influence economic growth and these findings ...

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...

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 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...