Page 34 - Contributed Paper Session (CPS) - Volume 7

CPS2021 Noor Ismawati et al.
The analysis was done with earning as the only continuous numerical
variable with age, ethnicity, education attainment and marital status as the
socio-demographic variables. The analysis also includes social-economic and
geographical variables namely occupation, industry, state and area of
residency as additional to the analysis.
Earning is represented by total monthly salaries & wages received which
includes basic salaries or wages before deduction of income tax and Employee
Provident Fund contribution, allowances, commissions, overtime and other
payment in kind from primary occupation. Bonus is not included in this
monthly measurement. For educational attainment, no formal education refers
to those who had never attended school in any of the education institution.
Primary refers to those who went to school between age 6 and 12 years,
secondary for those who had been to education institution until age 17 and
tertiary for those who obtained certificate higher than Sijil Pendidikan Malaysia
(SPM). SPM certificate is awarded to those who passed the national
examination (Department of Statistics Malaysia, 2016), normally taken in the
final year of secondary level. The field of study is only applicable to those who
are with tertiary education. Occupation is categorised into nine categories
following Malaysia Standard Classification of Occupations 2008 (MASCO-08).
Industry is coded in 20 categories based on the Malaysia Standard Industrial
Classification (MSIC). The geographical characteristic is represented by the
state and area of residency. Following the administrative boundaries of the
country, state refers to respondent's usual place of stay during the survey. Out
of 16 states, there are three federal territories. Area of residencies refers to the
urban-rural classification of the survey respondent's living quarters (LQ).
The modified Mincer-Typed earning regression is utilised to determine the
impact of socio-demographic variables in estimating earning for each year
separately for both sector by gender. The regression equation applied is as
follows,

2
ln = 0 + 1 + 2 +3 + 4 + 5 +
+6 + 7 + 8 + 9 +
where
= The logarithm of monthly earning;
= Estimated coefficients;
= Age on last birthday;

2
= Age square;
= A series of dichotomous variables indicating the
respondent is Bumiputera, Chinese, Indian, or other
ethnic group;

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