Abstract

On November 26, 2001, the National Bureau of Economic Research announced that the U.S. economy had officially entered into a recession in March 2001. This decision was a surprise and did not end all the conflicting opinions expressed by economists. This matter was finally settled in July 2002 after a revision to the 2001 real gross domestic products showed negative growth rates for its first three quarters. A series of political and economic events in the years 2000-01 has increased the amount of uncertainty in the state of the economy, which, in turn, has resulted in the production of less reliable economic indicators and forecasts. This paper evaluates the performances of two very reliable methodologies for predicting a downturn in the U.S. economy using composite leading economic indicators (CLI) for the years 2000-01. It explores the impact of the monetary policy on CLI and on the overall economy and shows how the gradualness and uncertainty of this impact on the overall economy have affected the forecasts of these methodologies. It suggests that the overexposure of the CLI to the monetary policy tools and a strong, but less effective, expansionary money policy have been the major factors in deteriorating the predictions of these methodologies. To improve these forecasts, it has explored the inclusion of the CLI diffusion index as a prior in the Bayesian methodology.

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