Forecasting Inflation in Tunisia Using Dynamic Factors Model
Bilel Ammouri, Hassen Toumi, Habib Zitouna
Abstract
Open-access reader
Bilel Ammouri, Hassen Toumi, Habib Zitouna
Abstract
Open-access reader
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.
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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.
Key concepts: Inflation (cosmology), Economics, Dynamic factor, Econometrics, Context (archaeology), Benchmark (surveying), Macroeconomics, Geography