Forecasting Inflation in Argentina: Individual Models or Forecast Pooling?
Inflation forecasting plays a central role in monetary policy formulation. At the same time, recent international empirical evidence suggests that with the decline in inflation of recent years, the joint dynamics of this variable and its potential predictors has changed and inflation has become more unpredictable. Using a univariate model as a benchmark, we evaluate the predictive capacity of certain causal models linked to di¤erent inflation theories, such as the Phillips Curve and a monetary VAR. We also analyze the predictive power of models that use factors that combine the overall variability of a large number of business cycle time series as predictors. We compare their relative performance using a set of parametric and non-parametric tests proposed by Diebold and Mariano (1995). Although the univariate model performs best, as the forecast horizon lengthens, multivariate models performance improves. In particular, a monetary VAR performs better than the univariate ARMA model in the case of a one-year horizon. Nevertheless, when tests are calculated to evaluate the statistical significance of di¤erences in the predictive capacity of models, taking a univariate ARMA model as a benchmark, diferences are not statistically significant. Finally, estimated models are pooled to forecast inflation. Some of the forecast combinations outperform the best individual forecast over a one-year horizon. Taking into account that a one year-horizon is relevant for economic policy decisions, the possibility of combining both univariate and multivariate models for forecasting purpose is interesting, because it it can also be helpful to answer specific economic policy questions.
|Date of creation:||Jul 2008|
|Date of revision:|
|Contact details of provider:|| Postal: Reconquista 266 - C1003ABF - Buenos Aires|
Phone: (54-11) 4348-3582
Fax: (54-11) 4348-3794
Web page: http://www.bcra.gov.ar
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- David F. Hendry & Michael P. Clements, 2004.
"Pooling of forecasts,"
Royal Economic Society, vol. 7(1), pages 1-31, 06.
- David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
- David Hendry & Michael P. Clements, 2001. "Pooling of Forecasts," Economics Papers 2002-W9, Economics Group, Nuffield College, University of Oxford.
- Gali, Jordi & Gertler, Mark, 1999.
"Inflation dynamics: A structural econometric analysis,"
Journal of Monetary Economics,
Elsevier, vol. 44(2), pages 195-222, October.
- Jordi Gali & Mark Gertler, 2000. "Inflation Dynamics: A Structural Econometric Analysis," NBER Working Papers 7551, National Bureau of Economic Research, Inc.
- Jordi Galí & Mark Gertler, 1998. "Inflation dynamics: A structural econometric analysis," Economics Working Papers 341, Department of Economics and Business, Universitat Pompeu Fabra.
- Marcellino, Massimiliano, 2002.
"Forecast Pooling for Short Time Series of Macroeconomic Variables,"
CEPR Discussion Papers
3313, C.E.P.R. Discussion Papers.
- Massimiliano Marcellino, . "Forecast pooling for short time series of macroeconomic variables," Working Papers 212, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Francis X. Diebold & Robert S. Mariano, 1994.
"Comparing Predictive Accuracy,"
NBER Technical Working Papers
0169, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
- Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
- Clements, Michael P. & Hendry, David F., 2006. "Forecasting with Breaks," Handbook of Economic Forecasting, Elsevier.
- Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
- Laura D´Amato & Lorena Garegnani & Juan M. Sotes, 2008.
"Inflation Persistence and Changes in the Monetary Regime: The Argentine Case,"
Central Bank of Argentina, Economic Research Department, vol. 1(50), pages 127-167, January -.
- Laura D´Amato & Lorena Garegnani & Juan M. Sotes Paladino, 2007. "Inflation Persistence and Changes in the Monetary Regime: The Argentine Case," BCRA Working Paper Series 200723, Central Bank of Argentina, Economic Research Department.
When requesting a correction, please mention this item's handle: RePEc:bcr:wpaper:200835. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Federico Grillo)
If references are entirely missing, you can add them using this form.