Arbeitspapier

Forecasting inflation in Argentina

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.

Language
Englisch

Bibliographic citation
Series: IDB Working Paper Series ; No. IDB-WP-891

Classification
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
Subject
Bayesian Vector Autoregressive
Forecasting
Prior specification
Marginal likelihood
Small-scale and large-scale models

Event
Geistige Schöpfung
(who)
Garegnani, María Lorena
Gómez Aguirre, Maximiliano
Event
Veröffentlichung
(who)
Inter-American Development Bank (IDB)
(where)
Washington, DC
(when)
2018

DOI
doi:10.18235/0001160
Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Garegnani, María Lorena
  • Gómez Aguirre, Maximiliano
  • Inter-American Development Bank (IDB)

Time of origin

  • 2018

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