Predictive Analysis & Visualization of GDP of the Top Economies

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Authors
Arun Sathe, Niket
Issue Date
2024
Degree
MSc in Business Analytics
Publisher
Dublin Business School
Rights
Abstract
This study investigates the use of the autoregressive integrated moving average (ARIMA) model to predict the gross domestic product (GDP) of the three leading global economies, which are considered possible contenders for becoming the next superpower. The data utilized in this study were gathered from the official website of the World Bank for the time frame spanning from 1990 to 2022. The study utilizes a response variable, GDP, and a time variable, Year. The ARIMA model is exclusively fitted to the response variable. The Akaike Information Criterion Corrected (AICc) and Bayesian Information Criterion (BIC) were employed to determine the optimal model from the chosen ARIMA models. The auto_arima() function from the pmdarima package was utilised to accomplish this task. Residual plots were generated to visually represent the performance of the models, and the Mean Absolute Percentage Error (MAPE) was computed. The MAPE values for the countries USA, China, and India were 3.6, 4.1, and 4.7, respectively.