TIME SERIES MODELING AND FORECASTING OF CONSUMER PRICE INDICES: COMPREHENSIVE ARIMA ANALYSIS AND EXPLORATION OF FUTURE TRENDS IN IRAQI MARKET

This study aimed to look at information on customer price indexes (CPI) in Iraq, from 2000 to 2023, using the auto-regressive coordinates moving average (ARIMA) demonstrated for prescient investigation. The primary focus of this study was the necessity of a dependable method for determining consumer prices in a constantly shifting landscape. The approach involved obtaining CPI data from the Food and Agriculture Organization of the United Nations, applying the ARIMA (0,2,3) (0,0,1) model with R programming, and conducting a comprehensive analysis that incorporated descriptive statistics, parameter estimation, and validation tests. The key finding revealed that the ARIMA model effectively captured and predicted CPI patterns, consistent with previous theories, demonstrating its efficacy in Iraqi market. In essence, the results of this study provide valuable insights for those involved in financial decision-making, enhancing our understanding of potential buyer price trends and highlighting the significance of utilizing the ARIMA model in CPI analysis in Iraqi market.