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

What this data shows

Published by Ministry of Manpower. 1,920 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 CSV from the Comprehensive Labour Force Survey on employed Singapore residents aged 15 and over by industry, employment status, and sex for June reference months from 2010 through 2025. About 1,920 rows use SSIC 2020 industry codes (earlier years mapped where possible). Labour economists compare employment status across industries and genders.

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
1,920
Columns
6

Chart

Values are summed where multiple rows share the same category.

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Data

Year Sex Industry1 Industry2 Employment Status Employed
2010 male manufacturing manufacturing employers 10800.000000
2010 male manufacturing manufacturing employees 170500.000000
2010 male manufacturing manufacturing own account workers 4400.000000
2010 male manufacturing manufacturing contributing family workers 400.000000
2010 male construction construction employers 11000.000000
2010 male construction construction employees 62000.000000
2010 male construction construction own account workers 7500.000000
2010 male construction construction contributing family workers 200.000000
2010 male services wholesale and retail trade employers 20600.000000
2010 male services wholesale and retail trade employees 104000.000000

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
Employment Status Text Yes
Employed Numeric No