Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/265681 
Year of Publication: 
2022
Series/Report no.: 
Working Paper No. 11/2022
Publisher: 
Örebro University School of Business, Örebro
Abstract: 
We develop a novel multinomial logistic model to detect and forecast concurrent recessions across multi-countries. The key advantage of our proposed framework is that we can detect recessions across countries using the additional informational content from the cross-country panel feature of the data. Furthermore, in a simulation study, we show that our proposed model accurately captures the true underlying probabilities. Finally, we apply our proposed framework to a US and UK empirical application. In terms of recession forecastability, the multinomial logistic model with both countries' interest rate spread and the weekly US NFCI as the set of exogenous predictors was the best performing model. For the counterfactual analysis, we found that a previous US recession will increase the probability of a recession occurring jointly in the US and the UK. However, a tightening of the US NFCI and a negative interest rate spread in both countries only increases the probability of a recession exclusively in the US and UK, respectively.
Subjects: 
Recession prediction
multinomial logistic
cross-country
mixed frequency
Bayesian estimation
JEL: 
E32
E37
C22
C25
Document Type: 
Working Paper

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