| SMART JOURNAL OF BUSINESS MANAGEMENT STUDIES |
VOL. 21 |
NO. 2 |
PAPER 4 |
DOI: 10.34293/2321-2012.2025.0002.4 |
CONSTRUCTING AN ENHANCED UNEMPLOYMENT MODEL IN CANADA, USING ARDL |
| |
| Halimahton Borhan*, Azhana Othman*, Geetha Subramaniam**, Rozita Naina Mohamed*** and Abdul Rahim Ridzuan**** |
| *Faculty of Business and Management Universiti Teknologi MARA, Melaka, Malaysia |
| **Faculty of Education, Languages, Psychology and Music, SEGi University, Petaling Jaya, Malaysia |
| ***Faculty of Business & Management, Universiti Teknologi MARA, Puncak Alam Campus, 42300 Selangor Darul Ehsan, Malaysia |
| ****Faculty of Business and Management Universiti Teknologi MARA, Cawangan SelaFaculty of Business and Management, Universiti Teknologi MARA Shah Alam, Malaysia |
| |
| The unemployment rate in Canada has been increasing from 2019 to 2023 and this high volatility of Canada’s unemployment rate has drawn researchers’ attention in recent times. Quarterly data from OECD Data, World Bank, IMF Data and DataStream, were collected from 1993 to 2023, to examine the factors affecting unemployment rate in Canada, using the Unit Root Test and the Autoregressive Distributed Lag (ARDL) approach. ARDL was used to study the long run effect between unemployment rate and related factors. This approach can be used only when Unit Root Test had been applied. The results of the study revealed that only Gross Domestic Product (GDP) reported a short run causality with the unemployment rate in Canada while other independent variables did not. The study indicated no long run causality relationship between all independent variables, namely population, GDP, inflation, foreign direct investment and average wages, as the F-statistics was below the threshold value. This study added a new independent variable, that is average wages, in the study of unemployment rate in Canada. This study covered the period from 1993 until 2023. |
| |