FORECASTING IRANIAN INFLATION RATES USING ,STRUCTURAL, TIME
SERIES, AND ARTIFICIAL NEURAL NETWORKS MODELS

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MOSHIRI S.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Journal: Journal of Economic Research Year:2001 | Volume:- | Issue:58 Page(s): 147-184

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Title

FORECASTING IRANIAN INFLATION RATES USING ,STRUCTURAL, TIME SERIES, AND ARTIFICIAL NEURAL NETWORKS MODELS

Author(s)

MOSHIRI S. | Issue Writer Certificate

Keywords

FORECASTING / INFLATIONQ2

STRUCTURAL/TIME SERIES / ARTIFICIAL NEURAL NETWORKSQ2

Abstract

In this paper, I develop three forecasting models: namely structural,
times series, and artificial neural networks; to forecast Iranian inflation
rates. The structural model uses aggregate demand and aggregate supply
approach, the time series model is based on the standard ARIMA
technique, and the artificial neural network applies multi-layer back -
propagation model. The latter, which is rooted in physic, cognitive, and
computer sciences, mimics human brain to learn any complex pattern and
to forecast their future behavior. the results of the forecasting competition
show that the back propagation model is able to generate inflation
forecasts much better than the traditional competitors.

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APA: Copy

MOSHIRI, S.. (2001). FORECASTING IRANIAN INFLATION RATES USING ,STRUCTURAL, TIME SERIES, AND ARTIFICIAL NEURAL NETWORKS MODELS . TAHGHIGHAT-E-EGHTESADI, -(58), 147-184. SID. https://sid.ir/paper/12112/en

Vancouver: Copy

MOSHIRI S.. FORECASTING IRANIAN INFLATION RATES USING ,STRUCTURAL, TIME SERIES, AND ARTIFICIAL NEURAL NETWORKS MODELS . TAHGHIGHAT-E-EGHTESADI[Internet]. 2001;-(58):147-184. Available from: https://sid.ir/paper/12112/en

IEEE: Copy

S. MOSHIRI, “FORECASTING IRANIAN INFLATION RATES USING ,STRUCTURAL, TIME SERIES, AND ARTIFICIAL NEURAL NETWORKS MODELS ,” TAHGHIGHAT-E-EGHTESADI, vol. -, no. 58, pp. 147–184, 2001, [Online]. Available: https://sid.ir/paper/12112/en

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