Spending patterns of Malaysian youth during the covid-19 pandemic / Nurazleena Ismail, Azzah Amran and Wan Yusrol Rizal Wan Yusof

• Main Authors: Ismail, Nurazleena, Amran, Azzah, Wan Yusof, Wan Yusrol Rizal
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA Cawangan Pulau Pinang 2022
• Subjects: H Social Sciences (General); HB Economic Theory. Demography; Demographic surveys; Malaysia; Research; Quantitative research
• Online Access: https://ir.uitm.edu.my/id/eprint/69874/1/69874.pdf; https://ir.uitm.edu.my/id/eprint/69874/; http://ejssh.uitm.edu.my
• Institution: Universiti Teknologi Mara

Paying attention to spending patterns is essential, especially for the younger generation during the COVID-19 pandemic. Previously, young people spent more money on entertainment activities to fulfil their life satisfaction than life survival. Young people also contributed to the highest number of bankruptcy as they borrowed money to buy non-essential products. The main objective of this study is to determine the significant relationship between the factors that influence spending patterns among the young generation during the COVID-19 pandemic in Malaysia. The research considered testing the factors of expenditures on food, transportation, and entertainment activities. The data were gathered from the distribution of a questionnaire to the respondents. SPSS version 23.0 was used to analyse the data. The results found that food and transportation expenditures significantly influenced the spending pattern during COVID-19, while entertainment expenditures had no significant relationship with the spending pattern. Results also highlighted that food expenditure was the highest influencing factor in spending patterns. This study will help policymakers outline the importance of financial assistance based on the priority needed by society, especially in an unexpected crisis. Further research on factors such as personality, behaviour, and financial knowledge can be explored. Besides, future research can also analyse the data using Partial Least Square-Structural Equation Model (PLS-SEM) to produce a variety of results.