In recent years, investigating synchronization of business cycles among countries, after increasing integration of global economies, has been attracted more attention of policy makers and researchers. Perhaps an unknown origin of such similarities, as an open question, is the main reason of these interests. So, with regard to the mentioned question, the aim of this paper is to investigate some ...

In order to sample marginalized and/or hard-to-reach populations, respondent-driven sampling (RDS) and similar techniques reach their participants via peer referral. Under a Markov model for RDS, previous research has shown that if the typical participant refers too many contacts, then the variance of common estimators does not decay like O(n−1), where n is the sample size. This implies that co...

Generalized least squares (GLS) for model parameter estimation has a long and successful history dating to its development by Gauss in 1795. Alternatives can outperform GLS in some settings, and alternatives to GLS are sometimes sought when GLS exhibits curious behavior, such as in Peelle’s Pertinent Puzzle (PPP). PPP was described in 1987 in the context of estimating fundamental parameters tha...

This paper considers estimation of the regression vector of the multiple regression model with elliptically symmetric contoured errors. The generalized least square (GLS), restricted GLS and preliminary test (PT) estimators for regression parameter vector are obtained. The performances of the estimators are studied under multiparameter linear exponential loss function (MLINEX), and the dominanc...

Consider a regression model with infinitely many parameters and time series errors. We are interested in choosing weights for averaging across generalized least squares (GLS) estimators obtained from a set of approximating models. However, GLS estimators, depending on the unknown inverse covariance matrix of the errors, are usually infeasible. We therefore construct feasible generalized least s...

Generalized least squares (GLS) regional regression procedures have been developed for estimating river flow quantiles. A widely used GLS procedure employs a simplified model error structure and average covariances when constructing an approximate residual error covariance matrix. This paper compares that GLS estimator (b̂GLS MC ), an idealized GLS estimator (b̂GLS E ) based on the simplifying as...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of non-spatial estimates of seemingly unrelated regression (SUR) systems. We apply a local sensitivity ap...