In this paper, we suggest a Bayesian panel (longitudinal) data approach to test for the economic growth convergence hypothesis. This approach can control for possible effects of initial income conditions, observed covariates and cross-sectional correlation of unobserved common error terms on...

In this paper, a Bayesian approach is suggested to compare unit root models with stationary models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. The paper utilizes analytic and Monte Carlo integration techniques for calculating...

In this paper, a Bayesian approach is suggested to compare unit root models with stationary models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. The paper utilizes analytic and Monte Carlo integration techniques for calculating...

In this paper a Bayesian approach to unit root testing for panel data models is proposed based on the comparison of stationary autoregressive models with and without individual determinist trends, with their counterpart models with unit autoregressive roots. This is done under cross-sectional...

In this paper, a Bayesian approach is suggested to compare unit root models with stationary autoregressive models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. Ignoring structural breaks in the error variance may be responsible...

In this paper we suggest a Bayesian approach for inferring stationary autoregressive models allowing for possible structural changes (known as breaks) in both the mean and the error variance of economic series occuring at unknown times. Efficient Bayesian inference for the unknown number and...