Skip to content
D

Monthly Household Employment Income (Including Employer CPF Contributions) Among Resident Employed Households at Selected Percentiles (Household Income, Annual 2000-2025)

Description

Annual monthly household employment income including employer CPF contributions among Singapore resident employed households at selected percentiles for 2000–2025, published by the Singapore Department of Statistics in CSV. Footnotes explain lowest-decile composition and year-to-year decile mobility. Supports inequality and wage-distribution research. Adapted from SingStat TableBuilder CT/17886.

Official description

Source: SINGAPORE DEPARTMENT OF STATISTICS Data Last Updated: 09/02/2026 Update Frequency: Annual Survey period: Household Income, Annual 2000-2025 Footnotes: Note: It is notable that some resident employed households in the lowest income decile owned a car (10.7%), employed a domestic worker (8.8%), lived in private property (9.0%) or were with household reference persons aged 65 years and over (45.2%) in 2025. Not all households are consistently in the same decile group from one year to the next. For example, a household may move from a higher to a lower decile in a particular year due to reduced income if a household member is temporarily unemployed, before moving up the deciles when the member resumes employment in the subsequent year. In comparing the performance of any particular decile group over time, it is therefore relevant to note that the comparison may not pertain to the same group of households. Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/17886

Last updated
Rows
9
Columns
27

Chart

Values are summed where multiple rows share the same category.

Data

Dollar 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
10th 1500.000000 1500.000000 1450.000000 1392.000000 1436.000000 1448.000000 1462.000000 1500.000000 1625.000000 1636.000000 1768.000000 1890.000000 1985.000000 2000.000000 2090.000000 2196.000000 2223.000000 2223.000000 2264.000000 2329.000000 2282.000000 2340.000000 2619.000000 2781.000000 2836.000000 3008.000000
20th 2184.000000 2255.000000 2178.000000 2153.000000 2162.000000 2220.000000 2260.000000 2398.000000 2708.000000 2701.000000 2889.000000 3128.000000 3393.000000 3424.000000 3618.000000 3807.000000 3927.000000 3937.000000 4000.000000 4020.000000 3955.000000 4001.000000 4446.000000 4694.000000 4910.000000 5215.000000
30th 2893.000000 3000.000000 2916.000000 2941.000000 2911.000000 3000.000000 3060.000000 3312.000000 3767.000000 3721.000000 3982.000000 4388.000000 4725.000000 4841.000000 5120.000000 5377.000000 5511.000000 5616.000000 5641.000000 5728.000000 5611.000000 5785.000000 6198.000000 6738.000000 6981.000000 7407.000000
40th 3600.000000 3804.000000 3700.000000 3694.000000 3683.000000 3870.000000 3955.000000 4286.000000 4882.000000 4830.000000 5095.000000 5657.000000 6037.000000 6286.000000 6650.000000 6972.000000 7078.000000 7303.000000 7379.000000 7520.000000 7325.000000 7627.000000 8075.000000 8777.000000 9151.000000 9733.000000
50th (Median) 4400.000000 4719.000000 4595.000000 4617.000000 4556.000000 4839.000000 4957.000000 5370.000000 6102.000000 6012.000000 6350.000000 7040.000000 7570.000000 7882.000000 8297.000000 8673.000000 8867.000000 9044.000000 9315.000000 9442.000000 9208.000000 9544.000000 10120.000000 10882.000000 11314.000000 12027.000000
60th 5368.000000 5800.000000 5660.000000 5695.000000 5628.000000 5968.000000 6083.000000 6644.000000 7596.000000 7401.000000 7822.000000 8605.000000 9264.000000 9704.000000 10155.000000 10560.000000 10832.000000 11060.000000 11360.000000 11607.000000 11355.000000 11787.000000 12438.000000 13431.000000 13848.000000 14714.000000
70th 6593.000000 7208.000000 7009.000000 6964.000000 7001.000000 7397.000000 7509.000000 8215.000000 9398.000000 9213.000000 9668.000000 10539.000000 11414.000000 11908.000000 12451.000000 12956.000000 13258.000000 13738.000000 13987.000000 14259.000000 14064.000000 14508.000000 15471.000000 16479.000000 17161.000000 18175.000000
80th 8357.000000 9240.000000 8954.000000 8979.000000 8889.000000 9412.000000 9612.000000 10561.000000 11911.000000 11754.000000 12299.000000 13570.000000 14450.000000 14943.000000 15682.000000 16419.000000 16784.000000 17425.000000 17650.000000 18192.000000 17842.000000 18278.000000 19677.000000 20786.000000 21545.000000 22708.000000
90th 11636.000000 12897.000000 12395.000000 12570.000000 12483.000000 13216.000000 13550.000000 14896.000000 17067.000000 16403.000000 17350.000000 18961.000000 20056.000000 20768.000000 21901.000000 22795.000000 22988.000000 23833.000000 24457.000000 25133.000000 24760.000000 24737.000000 26791.000000 28219.000000 29159.000000 30269.000000

Columns

Column Type Categorical
Dollar Text No
2000 Numeric No
2001 Numeric No
2002 Numeric No
2003 Numeric No
2004 Numeric No
2005 Numeric No
2006 Numeric No
2007 Numeric No
2008 Numeric No
2009 Numeric No
2010 Numeric No
2011 Numeric No
2012 Numeric No
2013 Numeric No
2014 Numeric No
2015 Numeric No
2016 Numeric No
2017 Numeric No
2018 Numeric No
2019 Numeric No
2020 Numeric No
2021 Numeric No
2022 Numeric No
2023 Numeric No
2024 Numeric No
2025 Numeric No