Measuring business cycle features

Gregory Hess and Shigeru Iwata

No 95-10, Research Working Paper from Federal Reserve Bank of Kansas City

Abstract: Since the extensive work by Burns and Mitchell (1947), many economists have interpreted economic fluctuations in terms of business cycle phases. Given this, we argue that in addition to usual model selection criteria currently used in the profession, the adequacy of a univariate macroeconomic time series model should be based on its ability to replicate two most important business cycle features of the U.S. data--duration and amplitude. We propose a number of checks for whether univariate statistical models generate business cycle features observed in US GDP and find that many popular non-linear models for the log of real GDP are no better at replicating the duration and amplitude features of the data than a simple ARIMA(1,1,0).

Keywords: Business cycles; Random walks (Mathematics) (search for similar items in EconPapers)
Date: 1995
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