STATISTICAL ANALYSIS ON UNEMPLOYMENT RATE IN MALAYSIA
DOI:
https://doi.org/10.46754/jmsi.2026.06.005Keywords:
Unemployment, correlation, multiple linear regression, Gross Domestic Product (GDP), Consumer Price Index (CPI)Abstract
Unemployment is a critical socio-economic issue affecting individual livelihoods and national economic performance. In Malaysia, the unemployment rate has fluctuated over the past decade, influenced by various social, economic, macroeconomic, demographic factors, and any other factors. The objectives of this research are to investigate the patterns and trends of the unemployment rate and to identify the significant factors that contribute to the joblessness in Malaysia. Several factors were considered such as the Gross Domestic Product (GDP), inflation, population growth, the COVID-19 pandemic, and Consumer Price Index (CPI). A correlation coefficient and multiple regression model were used to achieve the objective. Monthly data comprising 168 observations is collected from various sources such as the Department of Statistics Malaysia (DOSM) and the Central Bank of Malaysia. The dataset is categorised into two distinct periods, 2010-2019, representing the pre-pandemic era, and 2020-2023, which represents the COVID-19 pandemic era. The findings show that the CPI for food was both a consistent and significant predictor of unemployment across both periods under review, while the GDP was only significant before the pandemic, while the CPI for housing became a significant factor over the pandemic period. The remaining variables, such as inflation, the COVID-19 rate of infection, and population growth were not significant. In conclusion, the study showed that, while the GDP and CPI for food and housing have a significant effect on Malaysia’s unemployment rate, their impact changes between periods, which illustrates the shifting nature of economic determinants both before and after the COVID-19 pandemic.
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