Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/202490
Authors: 
D'Amato, Laura
Aguirre, Maximiliano Gómez
Garegnani, María Lorena
Krysa, Ariel
Libonatti, Luis
Year of Publication: 
2018
Series/Report no.: 
Economic Research Working Papers 81
Abstract: 
In general, central banks are concerned with keeping the inflation rate stable while also sustaining output close to an efficient level. Under "inflation targeting", forecasts of the evolution of the general price level are an essential input for policy decisions and these are usually released in quarterly "Inflation Reports". The costs and benefits of transparency in monetary policy are widely debated, but the need for a central bank to incorporate forecasts of future inflation is broadly agreed. In short, forecasting inflation is of foremost importance to households, businesses, and policymakers. In 2016, the Central Bank of Argentina began announcing and inflation targeting scheme. In this context, providing the authorities with good estimates of relevant macroeconomic variables turns out to be crucial to make the pertinent corrections to reach the desired policy goals. This paper develops a group of models to forecast inflation in Argentina and conducts a comparison of their predictive ability at different horizons. Our variety of models includes: (i) univariate time series models, (ii) VARs, Bayesian VARs and Time-Varying Parameter VARs, and (iii) conventional New Keynesian Phillips Curves including one that incorporates money to evaluate its information content as a predictor of inflation. We compare the predictive performance of the different methods using the Giacomini-White test over the relevant horizons for monetary policy decisions.
Subjects: 
Inflation rate
Forecasting
Time series models
Phillips curve
JEL: 
C22
C32
E31
E37
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.