EconPapers    
Economics at your fingertips  
 

Identifying Business Cycle Turning Points with Sequential Monte Carlo Methods

Monica Billio and Roberto Casarin

Working Papers from University of Brescia, Department of Economics

Abstract: We apply sequential Monte Carlo (SMC) to the detection of turning points in the business cycle and to the evaluation of useful statistics employed in business cycle analysis. The proposed nonlinear filtering method is very useful for sequentially estimating the latent variables and the parameters of nonlinear and non-Gaussian time-series models, such as the Markov-switching (MS) models studied in this work. We show how to combine SMC with Monte Carlo Markov Chain for estimating time series models with MS latent factors. We illustrate the effectiveness of the methodology and measure, in a full Bayesian and realtime context, the ability of a pool of MS models to identify turning points in the European economic activity. We also compare our results with the business cycle datation existing in the literature and provide a sequential evaluation of the forecast accuracy of the competing MS models.

Date: 2008
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-mac and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.unibs.it/on-line/dse/Home/Ricerca/Paper ... o/documento9758.html
Our link check indicates that this URL is bad, the error code is: 403 Forbidden

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ubs:wpaper:0815

Access Statistics for this paper

More papers in Working Papers from University of Brescia, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Matteo Galizzi ( this e-mail address is bad, please contact ).

 
Page updated 2025-03-23
Handle: RePEc:ubs:wpaper:0815