Characterizing growth instability: new evidence on unit roots and structural breaks in long run time series
Emanuele Russo, Neil Foster-McGregor & Bart Verspagen
#2019-026
In this paper we investigate whether long run time series of income per
capita are better described by a trend-stationary model with few
structural changes or by unit root processes in which permanent
stochastic shocks are responsible for the observed growth
discontinuities. To this purpose, we develop a methodology to test the
null of a generic I(1) process versus a set of stationary alternatives
with structural breaks. Differently from other tests in the literature,
the number of structural breaks under the alternative hypothesis is
treated as an unknown (up to some ex ante determined maximum). Critical
values are obtained via Monte Carlo simulations and finite sample size
and power properties of the test are reported. An application is
provided for a group of advanced and developing countries in the
Maddison dataset, also using bootstrapped critical values. As compared
to previous findings in the literature, less evidence is found against
the unit root hypothesis. Failures to reject the I(1) null are
particularly strong for a set of developing countries considered.
Finally, even less rejections are found when relaxing the assumption of
Gaussian shocks.
Keywords Long-run growth, structural breaks, unit roots
JEL Classification: O47, C22