Forecasting Inflation in Argentina

Lorena Garegnani and Maximiliano Gómez Aguirre

No 8940, IDB Publications (Working Papers) from Inter-American Development Bank

Abstract: In 2016 the Central Bank of Argentina began to announce inflation targets. In this context, providing authorities with good estimates of relevant macroeconomic variables is crucial for making pertinent corrections in order to reach the desired policy goals. This paper develops a group of models to forecast inflation for Argentina, which includes autoregressive models and different scale Bayesian VARs (BVAR), and compares their relative accuracy. The results show that the BVAR model can improve the forecast ability of the univariate autoregressive benchmark’s model of inflation. The Giacomini-White test indicates that a BVAR performs better than the benchmark in all forecast horizons. Statistical differences between the two BVAR model specifications (small and large-scale) are not found. However, looking at the RMSEs, one can see that the larger model seems to perform better for longer forecast horizons.

Keywords: Bayesian Vector Autoregressive; Forecasting; Prior specification; Marginal likelihood; Small-scale and large-scale models (search for similar items in EconPapers)
JEL-codes: C32 C53 (search for similar items in EconPapers)
Date: 2018-06
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://publications.iadb.org/publications/english ... ion-in-Argentina.pdf (application/pdf)

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:idb:brikps:8940

DOI: 10.18235/0001160

Access Statistics for this paper

More papers in IDB Publications (Working Papers) from Inter-American Development Bank Contact information at EDIRC.
Bibliographic data for series maintained by Felipe Herrera Library ().