Studying And Analyzing Of Inflation Level For Standard Numbers Depending On Time Series (ARIMA) Compared With Artificial Neural Network Models (ANNM)
DOI:
https://doi.org/10.55562/jrucs.v31i1.351Keywords:
Time SeriesAbstract
Inflation is one of the most economic terminology common is that despite the widespread use of this term is no agreement among economists regarding the definition, due to the division of opinion on defining the concept of inflation where this term is used to describe a number of different situations:1.Height wasteful in the general price level (inflation in prices).2.Rising incomes in cash or a cash income such as wages and profits (income inflation).3.(High cost or cost inflation).Excessive create cash balances / inflation.All these economic phenomena different that can be called on each of them (inflation) are phenomena independent from each other and this independence is raising confusion in defining the concept of inflation, but it is not necessary to move these different phenomena in one direction at a time and one in the sense that it could happen a rise in prices without corresponding increase in cash income as it is possible that the rise in costs occurs without accompanying rise in profits. Hence the view of some economists when using the term inflation without discrimination case means inflation in prices, which goes out to mind immediately when he mentions the term inflationIn order to ensure that the Iraqi economy suffers from the problem of inflation has to be the use of some of the indicators by which to rule that the Iraqi economy is witnessing fluctuating between high or low in price, no need to be using some of the indicators by which to measure the degree of inflation, and the figures standard indicators used to measure inflation.Downloads
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Published
2021-10-18
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How to Cite
Studying And Analyzing Of Inflation Level For Standard Numbers Depending On Time Series (ARIMA) Compared With Artificial Neural Network Models (ANNM). (2021). Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), 31(1), 75-97. https://doi.org/10.55562/jrucs.v31i1.351