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Determinants of Inflation in Iran Based on Bayesian Model Averaging (BMA)

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Abstract:

Due to the important influence of inflation on macro-economic variables, researchers pay tremendous amount of attention to its determinants. Accordingly, in the following research, the impact of 13 variables on inflation during the period of 1338-1391 by using Bayesian Model Averaging (BMA) method has been investigated for Iran economy. The ranking of the 13 explanatory variables are obtained based on the probability of their inclusion in model. The results show that the energy price and money imbalance (lagged ratio of money to nominal output) have expected and positive effect on inflation rate with a probability of 100 % and they are considered as the key explanatory variables in inflation equation. The energy price, money imbalance, money growth and market exchange rate growth have the first to fourth rank respectively. The influence of the production growth is not significant on the inflation in the short-run but it gradually influences the inflation through money imbalance channel in the long-run. In addition, most of the disinflation effects due to decrease in money supply will appear with delay. These results imply the dominance of monetary variables on inflation with cost push factors not having important impacts on prices. Also, oil revenue and imports influence the inflation through exchange rate channel, production and money velocity.

Info:

Periodical:
International Letters of Social and Humanistic Sciences (Volume 43)
Pages:
10-17
DOI:
https://doi.org/10.18052/www.scipress.com/ILSHS.43.10
Citation:
M. Mehrara et al., "Determinants of Inflation in Iran Based on Bayesian Model Averaging (BMA)", International Letters of Social and Humanistic Sciences, Vol. 43, pp. 10-17, 2015
Online since:
Nov 2014
Authors:
Mohsen Mehrara, Arezoo Ghazanfari, Motahareh Alsadat Majdzadeh
Keywords:
Bayesian Model Averaging (BMA), Inflation, Iran Economy
Export:
RIS, BibTeX, Text
Distribution:
Open Access

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This work is licensed under a
Creative Commons Attribution 4.0 International License

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