A Multiple Linear Regression approach to forecasting Malaysia's GDP using macroeconomic variables / Siti Nurhanani Shamsuddin ... [et al.]
This study examines the impact of macroeconomic variables on Malaysia’s Gross Domestic Product (GDP) using the Multiple Linear Regression (MLR) method and develops a predictive model through multiple linear regression. Due to data availability constraints, this study utilizes secondary data from the...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Unit Penerbitan JSKM
2025
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/114773/1/114773.pdf https://ir.uitm.edu.my/id/eprint/114773/ https://appspenang.uitm.edu.my/sigcs/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This study examines the impact of macroeconomic variables on Malaysia’s Gross Domestic Product (GDP) using the Multiple Linear Regression (MLR) method and develops a predictive model through multiple linear regression. Due to data availability constraints, this study utilizes secondary data from the World Bank and World Development Indicators, covering the period from 2010 to 2019. Based on a review of previous literature, six macroeconomic variables were selected: inflation, exports, imports, Foreign Direct Investment (FDI), population growth, and unemployment rate. Using EViews 12 Student Lite software, the findings reveal that only exports have a statistically significant positive impact on GDP growth, while inflation, imports, FDI, population growth, and unemployment rates are found to be insignificant. These results provide valuable insights for policymakers in formulating strategies to enhance economic growth, identifying key economic trends, and mitigating potential risks. Additionally, the findings contribute to improved decision-making for firms, investors, and government agencies by supporting risk management and strategic economic planning. |
|---|