Bayesian forecasting and inference in latent structure for the Brazilian Industrial Production Index

Gabriel Huerta and Hedibert Freitas Lopes

Brazilian Review of Econometrics, 2000, vol. 20, issue 1

Abstract: We consider the analysis of the Brazilian industrial production index (IPI) using statistical tools recently developed for time series. The main purpose is short-term forecasting and structural decomposition of the data through an autoregressive model that allows, but not imposes, nonstationary behavior. A very strong point of this model is that it incorporates all kinds of uncertainties by averaging forecasts across competing models, weighted by their posterior probabilities, in contrast with traditional analyses which assign probability one to a particular model. Additionally, the model considers innovation errors with heavy-tailed distributions and consequently accomodates for outlying observations. We interpret the results of the analysis in terms of its relation to the Brazilian economy.

Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://periodicos.fgv.br/bre/article/view/2772 (text/html)

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:sbe:breart:v:20:y:2000:i:1:a:2772

Access Statistics for this article

Brazilian Review of Econometrics is currently edited by Daniel Monte

More articles in Brazilian Review of Econometrics from Sociedade Brasileira de Econometria - SBE Contact information at EDIRC.
Bibliographic data for series maintained by Núcleo de Computação da FGV EPGE ().