FORECASTING MEASURES OF INFLATION FOR THE ESTONIAN ECONOMY
Agostino Consolo*
Working Papers of Eesti Pank
No 3, 2006
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The aim of this paper is to forecast some of the most important measures
of inflation of the Estonian economy by making use of linear and
non-linear models. Results from comparing classes of optimal models
are similar to those in the forecasting literature. In particular, there are
gains from using more sophisticated methods such as factor analysis and
time-varying parameters methods.
Model discrimination is based on evaluation criteria which are computed
by a real-time dynamic estimation procedure. Moreover, forecasts
uncertainty is appropriately taken into account: Fan Charts can exhaustively
describe the final output for what concerns out-of-sample forecasting.
JEL Code: C22, C32, C53, E31
Key words: Estonian Economy, forecasting, inflation modelling
* I am grateful to Marco Aiolfi, Andrea Carriero, Martin Lindpere and Massimiliano Marcellino for several conversations on some of the issues discussed in this paper. I acknowledge
the financial support of Eesti Pank. Any remaining errors are my own responsibility.
Author's e-mail address: email@agostino.it
The views expressed are those of the author and do not necessarily represent the official views of Eesti Pank.
Contents
- 1. Introduction
- 2. Forecasting Methodology
- 2.1. Forecasting by Dynamic Estimation
- 2.2. Forecasts Evaluation
- 2.3. Forecasting with Uncertainty
- 3. Methods Specification
- 3.1. Linear Methods
- 3.2. Autoregressive Time-Varying Parameters
- 3.3. Smooth Transition Regression
- 3.4. Phillips' Curve
- 4. Data Source and Description
- 5. Forecasting Inflation Measures
- 5.1. Model Selection
- 5.2. Model Specification
- 5.2.1. AR Models
- 5.2.2. VAR Models
- 5.2.3. Logistic Smooth Transition
- 5.2.4. Time-Varying Parameters
- 5.2.4. Phillips' Curve: A Factor Analysis
- 5.3. Forecasts Evaluation
- 5.4. Out-of-Sample Forecasting
- 6. Conclusions
- References
- Appendices
- Appendix 1. Absolute MAFE and MSFE
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