Analyzing the ambiguity of the relationship between exchange rate and inflation in Iraq using a fuzzy regression model
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Abstract
This study aims to examine the relationship between exchange rate and inflation in Iraq over the period 2015–2024, using the Fuzzy Regression Model as an analytical tool to address the uncertainty and imprecision often present in economic data. Due to the country’s heavy reliance on oil exports and frequent political instability, traditional econometric models such as linear regression may fall short in capturing the true dynamics between variables.
Fuzzy regression provides a flexible alternative by allowing imprecise relationships to be modeled using fuzzy numbers, estimated through linear programming techniques. The research utilizes annual data from the Central Bank of Iraq and the World Bank, employing a linear fuzzy regression model where the exchange rate is the independent variable and inflation is the dependent variable. The results indicate a positive relationship between the exchange rate and inflation, suggesting that a depreciation of the Iraqi dinar contributes to rising domestic prices. This finding aligns with conventional economic theory regarding imported inflation in developing economies.
The study concludes that fuzzy regression is a valuable approach for analyzing economic phenomena in uncertain environments and recommends its application in designing monetary policies, especially in fragile economies like Iraq.
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