Forecasting Inflation in Argentina: Individual Models or Forecast Pooling?

Laura D´Amato (), Maria Garegnani () and Emilio Blanco
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Laura D´Amato: Central Bank of Argentina
Authors registered in the RePEc Author Service: Laura Inés D'Amato ()

No 200835, BCRA Working Paper Series from Central Bank of Argentina, Economic Research Department

Abstract: 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.

Keywords: Argentina; inflation forecast; multivariate models; pooling; univariate models (search for similar items in EconPapers)
JEL-codes: C32 E31 E37 (search for similar items in EconPapers)
Pages: 29 pages
Date: 2008-07
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