Skip to content
D

Average Monthly Household Employment Income Per Household Member (Including Employer CPF Contributions) Among Resident Employed Households by Deciles (Household Income, Annual 2000-2025)

What this data shows

Published by Singapore Department of Statistics. 11 records. Fields include Dollar, 2000, 2001, 2002 (27 columns in total). Last updated 2026-02-09.

Description

Annual series from 2000 to 2025 of average monthly household employment income per household member, including employer CPF contributions, among resident employed households ranked into deciles, published by the Singapore Department of Statistics in CSV. Footnotes caution that decile membership is not fixed across years and that some lowest-decile households own cars or private property. Widely used for income inequality, real wage growth and household living standards analysis in Singapore.

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 (15.3%), employed a domestic worker (19.3%), lived in private property (10.0%) or were with household reference persons aged 65 years and over (38.2%) 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/17883

Last updated
Rows
11
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
Total 1736.000000 1927.000000 1884.000000 1910.000000 1918.000000 2015.000000 2129.000000 2339.000000 2589.000000 2526.000000 2711.000000
1st (Lowest) 315.000000 317.000000 303.000000 301.000000 300.000000 297.000000 317.000000 335.000000 365.000000 357.000000 381.000000
2nd 537.000000 556.000000 538.000000 542.000000 541.000000 557.000000 585.000000 620.000000 689.000000 683.000000 738.000000
3rd 720.000000 760.000000 745.000000 745.000000 756.000000 776.000000 817.000000 865.000000 973.000000 958.000000 1037.000000
4th 911.000000 974.000000 956.000000 960.000000 968.000000 1004.000000 1047.000000 1116.000000 1266.000000 1243.000000 1343.000000
5th 1120.000000 1217.000000 1192.000000 1203.000000 1199.000000 1254.000000 1303.000000 1396.000000 1582.000000 1565.000000 1670.000000
6th 1366.000000 1504.000000 1470.000000 1487.000000 1478.000000 1551.000000 1610.000000 1728.000000 1956.000000 1931.000000 2054.000000
7th 1670.000000 1861.000000 1819.000000 1844.000000 1830.000000 1923.000000 1993.000000 2165.000000 2449.000000 2396.000000 2543.000000
8th 2094.000000 2355.000000 2306.000000 2346.000000 2318.000000 2440.000000 2551.000000 2777.000000 3125.000000 3045.000000 3236.000000
9th 2822.000000 3209.000000 3147.000000 3185.000000 3181.000000 3337.000000 3506.000000 3811.000000 4274.000000 4134.000000 4434.000000

Preview shows 10 rows and 12 columns. Use the table search or download the CSV for the full data.

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