This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters. We consider cases in which the nuisance parameter is estimated from independent and identical samples. A simulation experiment is conducted for covariance structure models. Empirical likelihood offers much reduced mean and median bia...

tourism industry has been the fastest and the most income-generating industry in the first decade of the third millennium. it has been for many countries including some of oic member countries a source of foreign exchange and contributed into their development. in this paper, we try to test empirically whether tourism expansion has had any significant effect on economic growth of oic member cou...

â â â  â â â â â â â â â â â  financial sector is one of the most influential sectors in economic activities. empirical and theoretical studies conducted in recent years have also confirmed the significant role of financial institutions in economic growth. additionally, trade and financial liberalization policies have been particular concerned with strategic policies in developed and developing...

Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. Two step GMM is biased. Generalized empirical likelihood (GEL) has smaller bias but the usual standard errors are too small in instrumental variable settings. In this paper we give a new variance estimator for GEL that addresses this problem. It is consistent under the usual asymptotics and under ...

during recent years, a debate has been taking place on the relationship between economic growth and trade policies. the present article explores the impact of trade liberalization on economic growth in islamic countries. we chose a sample of 26 islamic countries and using the gmm method, estimated the correlation between trade liberalization and economic growth for the period 1990-2003. the emp...

The problem of unsupervised audio classification continuous to be a challenging research problem which significantly impacts ASR and Spoken Document Retrieval (SDR) performance. This paper addresses novel advances in audio classification for speech recognition. A new algorithm is proposed for audio classification, which is based on Weighted GMM Network (WGN). Two new high-level features: VSF (V...

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...

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 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...

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 ...