Real-time Recession Probability with Hidden Markov Model and Unemployment Momentum

The R Journal, Forthcoming

8 Pages Posted: 16 Aug 2019 Last revised: 18 Aug 2019

See all articles by Stephen H.T. Lihn

Stephen H.T. Lihn

Atom Investors LP; Novus Partners, Inc.

Date Written: August 10, 2019

Abstract

We show how to construct a composite Hidden Markov Model (HMM) to calculate real-time recession probability, using the jubilee and ldhmm packages in R. The input data is the unemployment rate (UNRATE) which is released monthly by the U.S. government. There are two sub-models: The one-year momentum model and the 6-month acceleration model. The product of the two generates the recession probability. Our model demonstrates that positive momentum in unemployment kicks off a recession. The momentum accelerates during the recession. And eventually the rapid deceleration marks the end of it.

Keywords: Recession, Hidden Markov Model

JEL Classification: C32, E24

Suggested Citation

Lihn, Stephen H.T., Real-time Recession Probability with Hidden Markov Model and Unemployment Momentum (August 10, 2019). The R Journal, Forthcoming. Available at SSRN: https://ssrn.com/abstract=3435667 or http://dx.doi.org/10.2139/ssrn.3435667

Stephen H.T. Lihn (Contact Author)

Atom Investors LP ( email )

3711 S Mopac Expressway
Austin, TX 78746
United States
917-603-4133 (Phone)

Novus Partners, Inc. ( email )

521 5th Ave
29th Floor
New York, NY 10175
United States
917-603-4133 (Phone)

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