Forecasting Inflation in a Macroeconomic Framework: An Application to Tunisia
Souhaïb Chamseddine Zardi
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Souhaïb Chamseddine Zardi: Central Bank of Tunisia
No 07-2017, IHEID Working Papers from Economics Section, The Graduate Institute of International Studies
The aim of this paper is to evaluate the relative performance of different forecasts of inflation methods for the case of Tunisia. For that, we use a large number of econometric models to forecast short-run inflation. Specifically, we use univariate models as Random Walk, SARIMA, a Time Varying Parameter model and a suite of multivariate autoregressive models as Bayesian VAR and Dynamic Factor models. The forecasting results suggest that models which incorporate more economic information outperform the benchmark random walk for the first two quarters ahead. Furthermore, we combine our forecasts by means and the results reveal that the combination of forecasts leads to a reduction in forecast errors compared to individual models.
Keywords: Short-run forecasting; Dynamic Factor Models; Forecast combination (search for similar items in EconPapers)
Pages: 24 pages
New Economics Papers: this item is included in nep-ara, nep-for, nep-mac and nep-mon
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Persistent link: https://EconPapers.repec.org/RePEc:gii:giihei:heidwp07-2017
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