Per Capita Output Convergence : The Dickey-Fuller Test Under the Simultaneous Presence of Stochastic and Deterministic Trends
We reconsider previous studies that analyze the convergence hypothesis in a time series framework. In doing so, we first describe two possible outcomes overlooked in this literature, namely loose catching-up and loose lagging-behind, these cases are in-between divergence and catching-up; then, we provide evidence of the proficiency of the Dickey-Fuller (DF) test to identify the new out-comes by means of asymptotic theory as well as Monte Carlo experiments. Finally, in the empirical section we illustrate that the excessive evidence in favor of divergence may be due to lack of attention to the cases loose catching-up and loose lagging-behind.
Volume (Year): (2010)
Issue (Month): 99-100 ()
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