Better understanding of the working hour mismatch in Australia from three perspectives: education,occupation, and industry sectors
PERMANA, ILHAM SOLEH (Adv.: Robert Breunig, Prof. ), Robert Breunig, Prof.
As an effort to provide better understanding about working hour mismatch in Australia, this paper examine working hour mismatch from three perspectives; education; occupation; and industry sectors. This paper provides descriptive statistics and uses probit models and ordinary least squares model in explaining the relationship. This essay finds that for men and women, overemployment and underemployment are correlated with the level of education, type of occupations and some industry sectors. For men, higher level of education will increase probability to be overemployed and reduce probability to be underemployed. For women, overemployment and education have the same relationship with men, but not for the underemployment. Higher education level does not necessarily reduce the probability of underemployment. From the perspective of occupations, the results for men and women workers are similar. The managers which are the most prevalent occupation for overemployment and the least prevalent for the underemployment have the highest probability to be overemployed and the lowest probability to be underemployed. While the labourers, which are the most prevalent occupation for underemployment and the least prevalent occupation for overemployment have the highest probability to be underemployed and the lowest probability to be overemployed. From the perspective of industry sectors, men workers who work in rental, hiring and real estate services industry have the highest probability to be overemployed, while men workers who work in education and training industry have the highest probability to be underemployed. For women, women workers who work in the rental, hiring and real estate services industry have the highest probability to be overemployed, while women workers who work in the accommodation and food services industry have the highest probability to be underemployed.
Kata Kunci : Higher education level, women workers, overemployed, the accommodation, food services industry, prevalent occupation for underemployment, the least prevalent occupation for overemployment
