Is it One Break or Ongoing Permanent Shocks That Explains U.S. Real GDP?

Abstract

The relative importance of permanent (trend) versus cyclical shocks to GDP has been a central issue in macroeconomics, since the work of Nelson and Plosser (1982) and Morley et al. (2003) found large trend shocks. In contrast, Perron and Wada (2009) argued for a one time change in the mean growth rate in 1973 to be the only trend shock to the postwar U.S. real output. We re-estimate the Perron and Wada (2009) model conditional on a trend break having occurred at any one quarter. We then average the conditional estimates of the trend variance over the probability that the break occurred in a specified quarter. We do this both by an approximate Bayesian model average, in which the conditional estimates are done by maximum likelihood, and the date probabilities are found using the Schwarz (1978) approximation to the Bayesian marginal likelihood, and an exact Bayesian analysis which incorporates break date uncertainty into a trend-cycle decomposition of U.S. real GDP. The weight of the evidence supports the Perron and Wada (2009)’s finding of a fairly small trend variance, but the data does not provide very strong evidence against the alternative.