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...

Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard firstdifferenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency comparisons and Monte Carlo simulations for the simple AR(1) model demonstrate the dramatic improvement in p...

The paper considers estimation and inference of time series GMM models where a subset of parameters are time varying. The magnitude of the time variation in the unstable parameters is such that efficient tests detect the instability with (possibly high) probability smaller than one, even in the limit. We show that for many forms of parameter instability and for a large class of GMM models, stan...

abstract in this context, this article tries to presents a conceptual model of the factors affecting the government size and empirical test through econometric generalized methods of moments (gmm) by using data from 15 developing countries, review relationship between fiscal decentralization and the government size. the results of dynamic panel data indicate a positive effect of income and expe...

The Gaussian mixture model (GMM) has been widely used in pattern recognition problems for clustering and probability density estimation. For pattern classification, however, the GMM has to consider two issues: model structure in high-dimensional space and discriminative training for optimizing the decision boundary. In this paper, we propose a classification method using subspace GMM density mo...

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...

this study is an attempt to develop a model of the simultaneous structure of the aggregate dynamic supply and demand to be used for estimation of parameters from data related to iran’s economy. the method for developing the model is an application of the dynamic and simultaneous process of aggregate supply and demand. obtained differential equations are used for solve the model. to estimate the...

This study focuses on the classification of pathological voice using GMM (Gaussian Mixture Model) and compares the results to the previous work which was done by ANN (Artificial Neural Network). Speech data from normal people and patients were collected, then diagnosed and classified into two different categories. Six characteristic parameters (Jitter, Shimmer, NHR, SPI, APQ and RAP) were chose...

Missing values are endemic in the data sets available to econometricians. This paper suggests a unified likelihood-based approach to deal with several nonignorable missing data problems for discrete choice models. Our concern is when either the dependent variable is unobserved or situations when both dependent variable and covariates are missing for some sampling units. These cases are also con...