This entry describes the basic framework for statistical estimation and inference using Generalized Method of Moments and also illustrates the types of empirical models in finance to which these techniques have been applied. GeneralizedMethod of Moments (GMM) provides a computationally convenientmethod of obtaining consistent and asymptotically normally distributed estimators of the parameters ...

Information opacity leads to information asymmetry. In this situation, in providing their own financial needs, firms face limitations and inevitably provide their financial needs from the debt market by signalling private information to it. In addition, information opacity affects the leverage adjustment speed. This research investigates the effect of information opacity on deviation from targe...

This paper considers models for panel data in which the individual effects vary over time. The temporal pattern of variation is arbitrary, but it is the same for all individuals. The model thus allows one to control for time-varying unobservables that are faced by all individuals (e.g., macroeconomic events) and to which individuals may respond differently. A generalized within estimator is con...

A robust approach to the estimation of time series models is proposed. Taking from a new estimation method called the Generalized Method of Wavelet Moments (GMWM) which is an indirect method based on the Wavelet Variance (WV), we replace the classical estimator of the WV with a recently proposed robust M-estimator to obtain a robust version of the GMWM. The simulation results show that the prop...

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 P.O.T. method (Peaks Over Threshold) consists in using the generalized Pareto distribution (GPD) as an approximation for the distribution of excesses over a high threshold. In this work, we use a refinement of this approximation in order to estimate second order parameters of the model using the method of probability-weighted moments (PWM): in particular, this leads to the introduction of a...