Monthly Formal Sector Wages by Sex, Ethnicity & Age
Data as of Jun 2026Number of formal employees and median monthly wages of employees who are Malaysian citizens, overall and by sex, ethnicity or age group.
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How is this data produced?
Conceptually, formal employees are persons who work under a contract of service or apprenticeship with an employer and receive remuneration for the work done. Non-standard employment, such as the self-employed, gig workers, own-account workers and unpaid family workers, is not covered.
Consequently, data on formal sector wages is compiled from administrative records, primarily the mandatory retirement savings contributions to the Employees Provident Fund (EPF) and social security contributions to the Social Security Organisation (SOCSO).
What caveats I should bear in mind when using this data?
The most recent 15 months of data are subject to revision if more complete contribution data are received. Employee numbers are rounded to the nearest hundred until December 2025. Each row is broken down by at most one of sex, ethnicity or age group; the others are set to 'both' or 'overall'. Age is computed from year of birth, so every employee moves up a year of age each January. Employee numbers by age group therefore show a level shift every January (e.g. a sharp fall in employees below 20).
Publication(s) using this data
The Employee Wages Statistics (Formal Sector) Report, Second Quarter 2026, the latest edition of the quarterly formal sector wages statistics published by DOSM.
Metadata
Dataset description
Number of formal employees and median monthly wages of employees who are Malaysian citizens, overall and by sex, ethnicity or age group.
Variable definitions
- Date
- Sex
- Ethnicity
- Age Group
- Employees
- Median Wage
Name in Dataset | Variable | Definition |
|---|---|---|
date (Date) | Date | The date in YYYY-MM-DD format, with DD set to 01 since the data is at monthly frequency |
sex (Categorical) | Sex | Either both sexes ('both'), male ('male') or female ('female') |
ethnicity (Categorical) | Ethnicity | All ethnic groups ('overall'), Bumiputera ('bumi'), Chinese ('chinese'), Indian ('indian') or others ('other') |
age (Categorical) | Age Group | All ages ('overall'), below 20 ('below_20'), 5-year groups from '20-24' to '60-64', or 65 and above ('65_above') |
employees (Integer) | Employees | Number of formal employees; an employee with more than one job is counted once |
wages_median (Integer, RM) | Median Wage | Median monthly wage; half of formal employees earn less than this amount. Wages refer to all remuneration in money paid to employees in the reference month, including bonuses, commissions and allowances. They exclude service charges, overtime payments, gratuities, retirement benefits, retrenchment or termination benefits and travelling allowances. Wages are recorded on an accrual basis, i.e. in the month the work was done, regardless of when payment was made. For an employee with more than one job, wages from all jobs are summed. |
Last updated:
27 Oct 2026, 13:00
Next update:
31 Jan 2027, 13:00
Data source(s)
- Department of Statistics Malaysia
URLs to dataset
License
This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A copy of the license is available Here.
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Data
Full Dataset (CSV)
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Full Dataset (Parquet)
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Code
Connect directly to the data with Python.
# If not already installed, do: pip install pandas fastparquet
import pandas as pd
URL_DATA = 'https://storage.dosm.gov.my/labour/formal_wages.parquet'
df = pd.read_parquet(URL_DATA)
if 'date' in df.columns: df['date'] = pd.to_datetime(df['date'])
print(df)Sample OpenAPI query
The following code is an example of how to make an API query to retrieve the data catalogue mentioned above. You can use different programming languages by switching the code accordingly. For a complete guide on possible query parameters and syntax, please refer to the official Open API Documentation.
import requests
import pprint
url = "https://api.data.gov.my/data-catalogue?id=formal_wages&limit=3"
response_json = requests.get(url=url).json()
pprint.pprint(response_json)
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