Abstract
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 inference procedures about the unit root hypothesis based on panel data dynamic models. Ignoring these effects can lead to spurious evidence supporting economic growth divergence. The application of our suggested approach to real gross domestic product panel data of the G7 countries indicates that the economic growth convergence hypothesis is supported by the data. Our empirical analysis shows that evidence of economic growth divergence for the G7 countries can be attributed to not accounting for the presence of exogenous covariates in the model.
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