In this paper, in order to cope with the problem of endogenous regressors in cases that the linear regression model is non-identifiable, we suggest estimators handling the problem of multicollinearity to improve the performance of the Gaussian copula approach. This problem occurs when the...

We contribute a new method for dealing with the problem of endogeneity of the threshold variable in threshold vector auto-regression (TVAR) models. Drawing on copula theory, enables us to capture the dependence structure between the threshold variable and the vector of TVAR innovations,...

This paper provides evidence that, since the sign of Maastricht Treaty, euro-area monetary authorities mainly follow a strong anti-inflationary policy. This policy can be described by a threshold monetary policy rule model which allows for distinct inflation policy regimes: a low and high. The...

Missing data or missing values are a common phenomenon in applied panel data research and of great interest for panel data unit root testing. The standard approach in the literature is to balance the panel by removing units and/or trimming a common time period for all units. However, this...

We investigate the relationship between non-performing loans (NPLs) and their fundamentals, mainly bank and macroeconomic variables. This is done based on aggregate portfolio loans in the Greek economy. Greece constitutes an interesting case to study the factors determining NPLs, given the...

We investigate for human capital threshold effects on economic growth dealing with the issue of endogeneity of the threshold variable. We consider two measures of human capital: (i) the education level and (ii) an extended measure of it accounting for the health level. We provide clear-cut...

This paper suggests a multilayer artificial neural network (ANN) method to predict the probability of default (PD) within the survival analysis framework. ANN structures consider hidden interconnections among covariates determining the PD which can lead to prediction improvements, compared to...