Showing 1 - 10 of 12
This paper introduces two different non-parametric tests for panel unit root based on the wavelet decomposition of time series which may be used in the presence of cross-sectional dependency and an unknown structural break in the data. These tests are compared with the parametric IPS test...
Persistent link: https://www.econbiz.de/10011019146
A new shrinkage estimator for the Poisson model is introduced in this paper. This method is a generalization of the Liu (1993) estimator originally developed for the linear regression model and will be generalised here to be used instead of the classical maximum likelihood (ML) method in the...
Persistent link: https://www.econbiz.de/10009225860
In this paper, we modify a number of new biased estimators of seemingly unrelated regression (SUR) parameters which are developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine ridge parameters have been modified and compared in terms...
Persistent link: https://www.econbiz.de/10009225861
Despite that interaction terms are standard tools of regression analysis, the side effects of the inclusion of these terms in models estimated by ordinary least squares (OLS) are yet not fully penetrated. The inclusion of interaction effects induces multicollinearity problems since all non-zero...
Persistent link: https://www.econbiz.de/10009645803
In ridge regression the estimation of the ridge parameter is an important issue. This paper generalizes some methods for estimating the ridge parameter for probit ridge regression (PRR) model based on the work of Kibria et al. (2011). The performance of these new estimators are judged by...
Persistent link: https://www.econbiz.de/10009645804
This paper examines the application of the Least Absolute Deviations (LAD) method for ridge-type parameter estimation of Seemingly Unrelated Regression Equations (SURE) models. The methodology is aimed to deal with the SURE models with non-Gaussian error terms and highly collinear predictors in...
Persistent link: https://www.econbiz.de/10010584041
In this the size and power properties of the common factor Im, Pesaran and Shin (CIPS), Wald (W), likelihood ratio (LR) and Lagrange multiplier (LM) tests are investigated when the error term follows a spatial error model. The results from the Monte Carlo simulations used in this study, firstly...
Persistent link: https://www.econbiz.de/10010585719
In this paper, three innovative panel error correction model (PECM) tests are proposed. These tests are based on the multivariate versions of the Wald (W), Likelihood Ratio (LR) and Lagrange Multiplier (LM) tests. By means of Monte Carlo simulations, the size and power properties of the tests...
Persistent link: https://www.econbiz.de/10010818913
Multilevel (ML) models allow for total variation in the outcome to be decomposed as level one and level two or ‘individual and group’ variance components. Multilevel Mixture (MLM) models can be used to explore unobserved heterogeneity that represents different qualitative relationships in...
Persistent link: https://www.econbiz.de/10010818923
This paper analyzes and compares the properties of the most commonly applied versions of the Granger causality (GC) test to a new ridge regression GC test (RRGC), in the presence of multicollinearity. The investigation has been carried out using Monte Carlo simulations. A large number of models...
Persistent link: https://www.econbiz.de/10009150723