Forecasting Malaysia economic growth using Box Jenkins and Solow Growth Method / Amiernursi Adha Mazlan, Muhammad Harith Halid and Nurul ‘Izzah Othman

• Main Authors: Mazlan, Amiernursi Adha, Halid, Muhammad Harith, Othman, Nurul ‘Izzah
• Format: Student Project
• Language: English
• Published: 2022
• Subjects: Mathematical statistics. Probabilities
• Online Access: https://ir.uitm.edu.my/id/eprint/80826/1/80826.pdf; https://ir.uitm.edu.my/id/eprint/80826/

The term "Gross Domestic Product," or GDP, refers to the total monetary worth of all finished products and services produced (and marketed) inside a nation within a certain period (typically 1 year). The most often used indicator of economic activity is the GDP. Predicting Malaysia's economic progress has proven difficult because of the GDP's tendency to change. The exact metrics of a country's economic development are still up for discussion and are influenced by a variety of other economic factors. As a result, studies on the topic of GDP forecasting are increasingly often conducted by scholars. The main aim for this study is to find the best model either Box Jenkins Method or Solow Growth Method and use the best model to forecast next Malaysia’s economic growth. For this study, different data set were used for each method. It is because each method using different set of attributes. The objective is to assess how well the Box Jenkins and Solow Growth models perform at predicting GDP as an indication of economic growth and to recommend the optimal time series model for doing so in Malaysia. At last, for Box Jenkins, we obtain that ARIMA(2,2,0) is the best model among those two model. The forecasting phases for those models are based on the error measurements, Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).