Perfect Recession Predictors

55 Pages Posted: Last revised: 16 Nov 2024

See all articles by Anthony M. Diercks

Anthony M. Diercks

Board of Governors of the Federal Reserve System

Daniel Soques

University of North Carolina (UNC) at Wilmington

Jing Cynthia Wu

The University of Illinois at Urbana-Champaign; National Bureau of Economic Research (NBER)

Date Written: November 15, 2024

Abstract

Define a perfect recession predictor as one that correctly predicts every recession and does not falsely signal a recession when one does not occur. The benchmark spreads (10-year minus 2-year and 10-year minus 3-month term spreads, and the nearterm forward spread) are far from perfect, and generate up to 59 mispredictions from 1962 to now. Using a supercomputer to search over 645 million series of forward and term spreads that are averaged over different horizons, we discover 83 perfect spreads. In contrast to the benchmark spreads, the perfects tend to be forward spreads starting 4 years out with a moving average of about a year. We use a New Keynesian model to rationalize these features of the perfects and highlight the underlying economic mechanisms. Finally, we expand on the concept of perfect spreads to construct recession-predicting indices and show their superior statistical performances compared to the benchmarks.

Suggested Citation

Diercks, Anthony M. and Soques, Daniel and Wu, Jing Cynthia, Perfect Recession Predictors (November 15, 2024). Available at SSRN: https://ssrn.com/abstract=

Anthony M. Diercks

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

Daniel Soques

University of North Carolina (UNC) at Wilmington ( email )

601 South College Road
Wilmington, NC 28403
United States

HOME PAGE: http://people.uncw.edu/soquesd/index.html

Jing Cynthia Wu (Contact Author)

The University of Illinois at Urbana-Champaign ( email )

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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