ABSTRACT
This paper aims to give an overall view of the Gross Domestic Product (GDP) in the United States and determine the optimal model to predict the growth of GDP by using the Autoregressive Integrated Moving Average Model (ARIMA). The ARIMA model was performed for 93 years from 1929 to 2022 of Gross Domestic Product, Billions of Dollars, Annually from Federal Reserve Economic Data (https://fred. stlouisfed.org). The researcher conclude that the estimated model of the first-order difference for the logarithm of GDP (DLGDP) series is ARIMA (1,1,1) with coefficients: C = 0.057064, AR (1) = 0.489046 & MA (1) = 0.265583 where S.E. of regression equals 0.051529, R-squared value is about 0.412974, Durbin-Waston statistic (1.961008) and the probability of F-statistic equals (0.000000), which gives the forecast value 0.10436 of LGDP in 2022, while the actual value equals 0.8818 with very low relative error 1.617%, therefore, the forecast value is close to the actual value and indicates that the ARIMA (1,1,1) model has a good fitting effect.
Keywords: Forecasting, GDP, Autoregressive integrated moving average (ARIMA), and Model.
Citation: Sultan MA. (2023). Forecasting the GDP in the United States by Using ARIMA Model, Can. J. Bus. Inf. Stud., 5(3), 63-69. https://doi.org/10.34104/cjbis.023.063069
