Forecasting U.S. recessions with probit stepwise regression models

John Silvia, Sam Bullard, Huiwen Lai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


Yield spreads have been repeatedly used in the literature as the top candidates in predicting future recessions. In this paper, we show that existing model specifications are good but fall short of the performance of more complete models. Applying a probit stepwise regression procedure to a large number of economic indicators, we find models that dramatically outperform those used in the literature. Due to a time series that only began in 1964Q1 and very few historical recessions, any model specification may capture only a few of the economy's many aspects and thus can potentially be biased. Nevertheless, models with better statistical properties should have a better chance to capture the occurrence of recession. Our chosen models are not immune to statistical limitations but should forecast better than the existing models in the literature.
Original languageEnglish
Pages (from-to)7-18
Number of pages12
JournalBusiness Economics
Issue number1
Publication statusPublished - 1 Jan 2008
Externally publishedYes

ASJC Scopus subject areas

  • Business and International Management
  • Economics and Econometrics


Dive into the research topics of 'Forecasting U.S. recessions with probit stepwise regression models'. Together they form a unique fingerprint.

Cite this