Long-Run Time Series Tests of Constant Steady-State Growth” manuscript, 2011 Perron, Pierre and Zhongjun Qu, “Estimating Restricted Structural Change Models

We propose a new methodology to study the stability of steady-state growth. Long-run GDP per capita can be characterized by: (1) the linear trend hypothesis, where there are no long-run changes in GDP levels or growth rates, (2) the level shift hypothesis, where there are long-run level shifts, but not changes in growth rates, and (3) the growth shift hypothesis, where there are long-run changes in both GDP levels and growth rates. We formally test these hypotheses using time series techniques with over 135 years of data. The results are not favorable to the hypothesis of constant steady-state growth. While we find evidence supporting the linear trend hypothesis for the United States and Canada and the level shift hypothesis for three additional OECD countries, the growth shift hypothesis is supported for seven OECD and four Asian countries. The results are not driven by transition dynamics. 1 “Consider the following simple exercise. An economist living in the year 1929 (who has miraculous access to historical per capita GDP data) fits a simple linear trend to the natural log of per capita GDP for the United States from 1880 to 1929 in an attempt to forecast per capita GDP today, say in 1987. How far off would the prediction be? ” Charles Jones (1995b) 1