Forecasting Economic Growth and Movements with Wavelet Transform and ARIMA Model

Authors

Omar Alsinglawi, Accounting Department, Business School, The University of Jordan, Amman, JordanFollow
Omar Alsinglawi, Accounting Department, Business School, The University of Jordan, Amman, JordanFollow
Mohammad Aladwan, Accounting Department, Business School, The University of Jordan, Amman, JordanFollow
Mohammad Aladwan, Accounting Department, Business School, The University of Jordan, Amman, JordanFollow
Saddam Alwadi, Finance Department, Business School, The University of Jordan, Amman, JordanFollow
Saddam Alwadi, Finance Department, Business School, The University of Jordan, Amman, JordanFollow

Author Country (or Countries)

Jordan

Abstract

This study uses historical data and modern statistical models to forecast future Gross Domestic Product (GDP) in Jordan. The Wavelet Transformation model (WT) and Autoregressive Integrated Moving Average (ARIMA) model were applied to the time series data and yielded a best-fitting result of (2,1,1) for estimating GDP between 2022-2031. The study concludes that GDP is expected to increase with a positive growth rate of around 3.22%, and recommends government agencies to monitor GDP, strengthen existing policies, and adopt necessary economic reforms to support growth. Additionally, the private sector is encouraged to enhance production tools to achieve economic growth that benefits all sectors of society.

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/170508

Recommended Citation

Alsinglawi, Omar; Alsinglawi, Omar; Aladwan, Mohammad; Aladwan, Mohammad; Alwadi, Saddam; and Alwadi, Saddam (2023) "Forecasting Economic Growth and Movements with Wavelet Transform and ARIMA Model," Applied Mathematics & Information Sciences: Vol. 17: Iss. 5, Article 8.
DOI: http://dx.doi.org/10.18576/amis/170508
Available at: https://digitalcommons.aaru.edu.jo/amis/vol17/iss5/8