Forecasting Inflation in Tunisia Using Dynamic Factors Model
Bilel Ammouri (),
Hassen Toumi and
Habib Zitouna ()
MPRA Paper from University Library of Munich, Germany
This work presents a forecasting inflation model using a monthly database. Conventional models for forecasting inflation use a small number of macroeconomic variables. In the context of globalization and dependent economic world, models have to account a large number of information. This model is the goal of recent research in the various industrialized countries as well as developing countries. With Dynamic Factors Model the forecast values are closer to actual inflation than those obtained from conventional models in the short term. In our research we devise the inflation in to “free inflation and administered inflation” and we test the performance of the DFM in different types of inflation namely administered and free inflation. We found that dynamic factors model leads to substantial forecasting improvements over simple benchmark regressions.
Keywords: Inflation; PCA; VAR; Dynamic Factors Model; Kalman Filter; algorithmic EM; Space-state; forecast. (search for similar items in EconPapers)
JEL-codes: C13 C22 C53 E31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ara, nep-for, nep-mac and nep-mon
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