Forecasting Inflation in Argentina: A Comparison of Different Models
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 qu...
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| Formato: | Objeto de conferencia |
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/169117 |
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I19-R120-10915-1691172024-09-02T20:02:05Z http://sedici.unlp.edu.ar/handle/10915/169117 Forecasting Inflation in Argentina: A Comparison of Different Models D'Amato, Garegnani Lorena Gómez Aguirre, Maximiliano Krysa, Ariel Libonatti, Luis 2018-11 2018 2024-08-27T13:27:04Z en Ciencias Económicas Inflation rate Forecasting Time series models Phillips curve 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. Facultad de Ciencias Económicas Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf |
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Universidad Nacional de La Plata |
| institution_str |
I-19 |
| repository_str |
R-120 |
| collection |
SEDICI (UNLP) |
| language |
Inglés |
| topic |
Ciencias Económicas Inflation rate Forecasting Time series models Phillips curve |
| spellingShingle |
Ciencias Económicas Inflation rate Forecasting Time series models Phillips curve D'Amato, Garegnani Lorena Gómez Aguirre, Maximiliano Krysa, Ariel Libonatti, Luis Forecasting Inflation in Argentina: A Comparison of Different Models |
| topic_facet |
Ciencias Económicas Inflation rate Forecasting Time series models Phillips curve |
| description |
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. |
| format |
Objeto de conferencia Objeto de conferencia |
| author |
D'Amato, Garegnani Lorena Gómez Aguirre, Maximiliano Krysa, Ariel Libonatti, Luis |
| author_facet |
D'Amato, Garegnani Lorena Gómez Aguirre, Maximiliano Krysa, Ariel Libonatti, Luis |
| author_sort |
D'Amato, Garegnani Lorena |
| title |
Forecasting Inflation in Argentina: A Comparison of Different Models |
| title_short |
Forecasting Inflation in Argentina: A Comparison of Different Models |
| title_full |
Forecasting Inflation in Argentina: A Comparison of Different Models |
| title_fullStr |
Forecasting Inflation in Argentina: A Comparison of Different Models |
| title_full_unstemmed |
Forecasting Inflation in Argentina: A Comparison of Different Models |
| title_sort |
forecasting inflation in argentina: a comparison of different models |
| publishDate |
2018 |
| url |
http://sedici.unlp.edu.ar/handle/10915/169117 |
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AT damatogaregnanilorena forecastinginflationinargentinaacomparisonofdifferentmodels AT gomezaguirremaximiliano forecastinginflationinargentinaacomparisonofdifferentmodels AT krysaariel forecastinginflationinargentinaacomparisonofdifferentmodels AT libonattiluis forecastinginflationinargentinaacomparisonofdifferentmodels |
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