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...

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...

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...

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...

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...

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...

Agencies that regulate providers of electricity often apply nonparametric data envelopment analysis (DEA) to assess the relative efficiency of each firm. The reliability and validity of DEA are contingent upon selecting relevant input variables. In the era of big (wide) data, the assumptions of...

In this paper we generalize four tests of multivariate linear hypothesis to panel data unit root testing. The test statistics are invariant to certain linear transformations of data and therefore simulated critical values may conveniently be used. It is demonstrated that all four tests remains...