Convergence and Long-Run Uncertainty
Keywords:
Convergence hypothesis, economic growth, Bayesian model averaging, cointegration, Chile.
Abstract
In this paper the neoclassical convergence hypothesis is tested for the thirteen regions of Chile using cross-section techniques and the time-series based tests proposed by Bernard, A. and S. Durlauf, 1995, “Convergence in International Output”, Journal of Applied Econometrics 10 (2), pp. 97-108. Cross-section analysis in combination with a Bayesian Modeling Averaging strategy supports the convergence hypothesis, despite of some instability detected in the estimated speed of convergence. When applying time-series based tests, the no convergence null hypothesis cannot be rejected at the usual significance levels. When clustering the Chilean regions into three different groups, however, evidence of cointegration within these groups is found, indicating that the regional growth process in Chile is driven by a lower number of common trends.
Published
2014-04-26
How to Cite
Pincheira, P. M. (2014). Convergence and Long-Run Uncertainty. Economic Analysis Review, 29(1), 17-52. Retrieved from https://www.rae-ear.org/index.php/rae/article/view/399
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