The Phillips curve in Iran: econometric versus artificial neural networks.

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ID: 37466
2019
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Abstract
In this paper, we develop a function of inflation, unemployment, liquidity and real effective exchange rate by applying Autoregressive Distributed Lag (ARDL) and Artificial Neural Networks (ANN). We employ the aforementioned methods to derive the so-called Phillips curve. For the empirical objective, our primary purpose is explicitly to compare two types of the Phillips curve models obtained by ANN and the econometric methods, ARDL. Then we can check the behavior of the Phillips curve in Iran. We demonstrate that the Phillips curve for the empirical data in Iran differs slightly across ANN than econometric methods. In other words, according to the structure of Iran's economy, the ANN technique outshines the other one in terms of goodness of fit and prognosis capability. Finally, under two scenarios inflation would be forecasted in Iran up to 2025. Our findings point out that the trend of price changes in Iran would have an increasing trend in the considered period.
Reference Key
jalaee2019theheliyon Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jalaee, Sayyed Abdolmajid;Lashkary, Mehrdad;GhasemiNejad, Amin;
Journal Heliyon
Year 2019
DOI
10.1016/j.heliyon.2019.e02344
URL
Keywords Keywords not found

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