Economic growth and unemployment an empirical evidence from Malaysia / Carol Erita Kichi

• Main Author: Kichi, Carol Erita
• Format: Student Project
• Language: English
• Published: Perpustakaan Tun Abdul Razak UiTM Caw Sabah 2012
• Subjects: ASEAN; Consumers. Consumer demand. Consumption; Income. Income distribution. National income. Including gross national product, gross domestic product, and gross state product
• Online Access: http://ir.uitm.edu.my/id/eprint/26921/1/PP_CAROL%20ERITA%20BINTI%20KICHI%20BM%20S%2012_5.pdf; http://ir.uitm.edu.my/id/eprint/26921/

The economic growth is extremely important for the country to ensure the welfare and security of its people. A country that has shown an increase in the gross domestic product (GDP) proven that the countries is developing and it shows a good indication. Malaysia has an increasing value in GDP which shows a good indication towards its economy since its GDP is increasing year after year. However, severe unemployment would be detrimental to the country and it is very critical cases to be settled from ancient days. Unemployment is capable to causing economic collapse and cause the country to suffer. Besides that, it may also result that the foreign countries might also feel the collapse. Therefore, this study aims to see the causal relationship between unemployment and economic growth. This study is using the annual data from 1982 to 2010 from Malaysia. The relationship between unemployment and economic growth will be tested by using the Unit Root Test models. Co-integration, Vector Error Correction (VECM) and Granger Causality Causes. Besides that, this research identifies the causal relationship between each of the independent variables towards the economic growth in Malaysia. The Unit Root Test results show the stationary of the variables used in the study. The co-integration and Vector Error Correction (VECM) identifies the short-term relationship between the independent variables with the dependent variable and long-term relationship between the independent variables with the dependent variable, respectively. The Granger Causality Causes tests will results whether the dependent variable has been affect by independent variables or have bilateral relationship among the variables. The results show how a significant relationship between them.