Evaluating The Prioritization of The Effect of Monetary Base Resources on Inflation in Iran Using The New Random Forest Algorithm

Inflation is one of the basic problems in any economy that has adverse and unavoidable effects. Economists and policymakers have always paid attention to the issue of inflation and investigated ways to reduce it. One of the crucial economic issues in Iran is identifying the factors that affect the inflation rate. Among these, the monetary base and its various components play an important role in this field. Therefore, this study attempts to compare the impact of the components of monetary base resources on inflation in Iran. In this research, the influence of the components of monetary base resources on inflation in Iran in the period 1975–2020 has been compared using the random forest model. The results of parameter estimation using random forest regression for the main influential variables are currency growth rate, GDP growth rate, expected inflation, growth rate of public sector debt to the central bank, and growth rate of net foreign assets of the central bank. The growth rate of bank debt to the central bank does not affect inflation, so the relationship between the government and the central bank should be such that it removes the burden of the money volume caused by the budget deficit of the government and can relate the money volume to changes in production. Some of these results confirm the results of some previous research. In previous research, the growth rate of the exchange rate and the growth rate of the public sector debt to the central bank have been listed as the most important factors affecting the monetary base, and the variables that did not have an effect on inflation in this research were mostly unaffected in the previous researches as well.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
DOI
https://doi.org/10.22111/sedj.2024.47334.1418
Primary Topic
Stock Market Forecasting Methods
Type
article
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article

Evaluating The Prioritization of The Effect of Monetary Base Resources on Inflation in Iran Using The New Random Forest Algorithm

SHILAP Revista de lepidopterología
Stock Market Forecasting Methods
article

Evaluating The Prioritization of The Effect of Monetary Base Resources on Inflation in Iran Using The New Random Forest Algorithm

article en

Abstract

Inflation is one of the basic problems in any economy that has adverse and unavoidable effects. Economists and policymakers have always paid attention to the issue of inflation and investigated ways to reduce it. One of the crucial economic issues in Iran is identifying the factors that affect the inflation rate. Among these, the monetary base and its various components play an important role in this field. Therefore, this study attempts to compare the impact of the components of monetary base resources on inflation in Iran. In this research, the influence of the components of monetary base resources on inflation in Iran in the period 1975–2020 has been compared using the random forest model. The results of parameter estimation using random forest regression for the main influential variables are currency growth rate, GDP growth rate, expected inflation, growth rate of public sector debt to the central bank, and growth rate of net foreign assets of the central bank. The growth rate of bank debt to the central bank does not affect inflation, so the relationship between the government and the central bank should be such that it removes the burden of the money volume caused by the budget deficit of the government and can relate the money volume to changes in production. Some of these results confirm the results of some previous research. In previous research, the growth rate of the exchange rate and the growth rate of the public sector debt to the central bank have been listed as the most important factors affecting the monetary base, and the variables that did not have an effect on inflation in this research were mostly unaffected in the previous researches as well.

SHILAP Revista de lepidopterología
Razi University (IR)
Decent work and economic growth
Openalex Percentile: Top 57%
Stock Market Forecasting Methods
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