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A BIVARIATE AUTOREGRESSIVE PROBIT MODEL: BUSINESS CYCLE LINKAGES AND TRANSMISSION OF RECESSION PROBABILITIES

Published online by Cambridge University Press:  18 March 2013

Henri Nyberg
Henri Nyberg*
Affiliation:
University of Helsinki and HECER
*
Address correspondence to: Henri Nyberg, Department of Political and Economic Studies, P.O. Box 17 (Arkadiankatu 7), 00014University of Helsinki, Finland; e-mail: henri.nyberg@helsinki.fi.
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Abstract

I propose a new binary bivariate autoregressive probit model of the state of the business cycle. This model nests various special cases, such as two separate univariate probit models used extensively in the previous literature. The parameters are estimated by the method of maximum likelihood and forecasts can be computed by explicit formulae. The model is applied to predict the U.S. and German business cycle recession and expansion periods. Evidence of in-sample and out-of-sample predictability of recession periods by financial variables is obtained. The proposed bivariate autoregressive probit model allowing links between the recession probabilities in the United States and Germany turns out to outperform two univariate models.

Keywords

Bivariate Probit ModelAutoregressive ModelRecessionFinancial Variables
Type
Articles
Information
Macroeconomic Dynamics , Volume 18 , Issue 4 , June 2014 , pp. 838 - 862
Copyright
Copyright © Cambridge University Press 2013 

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