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Employed Residents Aged 15 Years & Over by Industry, Age And Sex

What this data shows

Published by Ministry of Manpower. 5,760 records. Fields include Year, Sex, Industry1, Industry2 (6 columns in total). Covers 2010-01-01 to 2025-01-01. Last updated 2026-03-27.

Description

Ministry of Manpower Comprehensive Labour Force Survey CSV of employed Singapore residents aged 15 and over, broken down by industry, age, and sex, from 2010 through 2025 (June reference month). Industries are classified under SSIC 2020, with earlier years mapped for comparability; residents refer to citizens and permanent residents. Labour economists analyse employment structure across sectors, age groups, and gender over time. Columns cover year, sex, industry, age, and number employed.

Official description

1. Reference month of June 2. Residents refer to Singapore Citizens and Permanent Residents. 3. Data are classified based on Singapore Standard Industrial Classification (SSIC) 2020. Data before year 2020 which were coded based on earlier versions of the SSIC were mapped to SSIC 2020 as far as possible to facilitate data comparability. Source: Comprehensive Labour Force Survey, Manpower Research & Statistics Department, MOM

Last updated
Coverage
2010-01-01 – 2025-01-01
Rows
5,760
Columns
6

Chart

Values are summed where multiple rows share the same category.

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Data

Year Sex Industry1 Industry2 Age Employed
2010 male manufacturing manufacturing 15-19 400.000000
2010 male manufacturing manufacturing 20-24 3800.000000
2010 male manufacturing manufacturing 25-29 15000.000000
2010 male manufacturing manufacturing 30-34 24900.000000
2010 male manufacturing manufacturing 35-39 30200.000000
2010 male manufacturing manufacturing 40-44 31200.000000
2010 male manufacturing manufacturing 45-49 29300.000000
2010 male manufacturing manufacturing 50-54 23600.000000
2010 male manufacturing manufacturing 55-59 15100.000000
2010 male manufacturing manufacturing 60-64 8500.000000

Preview shows 10 rows and 6 columns. Use the table search or download the CSV for the full data.

Columns

Column Type Categorical
Year Year (YYYY) Yes
Sex Text Yes
Industry1 Text Yes
Industry2 Text Yes
Age Text Yes
Employed Numeric Yes