Forecasting inflation in Argentina

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: IDB Working Paper Series ; No. IDB-WP-891

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Bayesian Analysis: General ; Estimation: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Forecasting Models; Simulation Methods
• Thema: Bayesian Vector Autoregressive ; Forecasting ; Prior specification ; Marginal likelihood ; Small-scale and large-scale models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Garegnani, María Lorena ; Gómez Aguirre, Maximiliano
• Ereignis: Veröffentlichung
• (wer): Inter-American Development Bank (IDB)
• (wo): Washington, DC
• (wann): 2018

Weitere Informationen

• DOI: doi:10.18235/0001160
• Handle: http://hdl.handle.net/10419/208111
• Letzte Aktualisierung: 10.03.2025, 11:45 MEZ