Since 2014
Forecasting Brazilian Inflation with High-Dimensional Models
Brazilian Review of Econometrics
View Archive Info| Field | Value | |
| Title |
Forecasting Brazilian Inflation with High-Dimensional Models
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| Creator |
Medeiros, Marcelo C; PUC-Rio
Vasconcelos, Gabriel Freitas, Eduardo |
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| Subject |
Emerging economies, Monetary policy, Brazilian in ation, Forecasting,LASSO, Shrinkage, Model selection
C22 |
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| Description |
In this paper we use high-dimensional models, estimated by the Least Absolute Shrinkage and Selection Operator (LASSO), to forecast the Brazilian inflation. The models are compared to benchmark specifications such as linear autoregressive (AR) and the factor models based on principal components. Our results showed that the LASSO-based specifications have the smallest errors for short-horizon forecasts. However, for long horizons the AR benchmark is the best model with respect to point forecasts. The factor model also produces some good long horizon forecasts in a few cases. We estimated all the models for the two most important Brazilian inflation measures, the IPCA and the IGP-M indexes. The results also showed that there are differences on the selected variables for both measures. Finally, the most important variables selected by the LASSO based models are, in general, related to government debt and money. On the other hand, variables such as unemployment and production were rarely selected by the LASSO.
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| Publisher |
Brazilian Review of Econometrics
Brazilian Review of Econometrics |
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| Contributor |
CNPq
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| Date |
2015-09-17
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion — — |
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| Format |
application/pdf
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| Identifier |
http://bibliotecadigital.fgv.br/ojs/index.php/bre/article/view/52273
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| Source |
Brazilian Review of Econometrics; Papers accepted for publication
Brazilian Review of Econometrics; Papers accepted for publication 1980-2447 |
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| Language |
eng
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| Relation |
http://bibliotecadigital.fgv.br/ojs/index.php/bre/article/view/52273/54851
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| Rights |
Copyright (c) 2015 Brazilian Review of Econometrics
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