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CSV Singapore Department of Statistics

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

Description

This Singapore Department of Statistics table reports monthly household employment income per household member, including employer CPF contributions, at selected percentiles among resident employed households. Values are in dollars, with each row a percentile point and each column a year from 2000 to 2025, so users can compare income growth at the bottom, middle and top of the distribution rather than relying on averages alone. Including employer CPF contributions gives a fuller measure of labour compensation than the excluding-CPF series. The Department cautions that households do not stay in the same decile from year to year, so comparisons over time track income groups rather than the same households, an important caveat for inequality analysis.

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/17889

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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 441.000000 456.000000 435.000000 438.000000 436.000000 448.000000 466.000000 500.000000 541.000000 532.000000 580.000000 630.000000 669.000000 698.000000 755.000000 819.000000 833.000000 858.000000 875.000000 923.000000 878.000000 955.000000 1053.000000 1094.000000 1151.000000 1267.000000
20th 628.000000 660.000000 638.000000 641.000000 653.000000 667.000000 702.000000 747.000000 832.000000 824.000000 890.000000 972.000000 1021.000000 1084.000000 1167.000000 1246.000000 1282.000000 1313.000000 1360.000000 1416.000000 1398.000000 1499.000000 1625.000000 1709.000000 1774.000000 1928.000000
30th 811.000000 868.000000 846.000000 848.000000 860.000000 887.000000 929.000000 993.000000 1117.000000 1098.000000 1188.000000 1283.000000 1377.000000 1451.000000 1546.000000 1653.000000 1690.000000 1743.000000 1812.000000 1888.000000 1840.000000 1961.000000 2120.000000 2283.000000 2340.000000 2522.000000
40th 1006.000000 1089.000000 1068.000000 1074.000000 1080.000000 1125.000000 1167.000000 1250.000000 1420.000000 1400.000000 1500.000000 1613.000000 1720.000000 1823.000000 1944.000000 2066.000000 2107.000000 2187.000000 2269.000000 2384.000000 2340.000000 2480.000000 2689.000000 2867.000000 2967.000000 3173.000000
50th (Median) 1237.000000 1353.000000 1321.000000 1337.000000 1333.000000 1394.000000 1448.000000 1549.000000 1756.000000 1736.000000 1850.000000 1997.000000 2129.000000 2250.000000 2383.000000 2503.000000 2591.000000 2706.000000 2799.000000 2930.000000 2891.000000 3033.000000 3291.000000 3507.000000 3621.000000 3909.000000
60th 1503.000000 1667.000000 1633.000000 1641.000000 1636.000000 1722.000000 1789.000000 1932.000000 2176.000000 2144.000000 2277.000000 2438.000000 2601.000000 2737.000000 2898.000000 3073.000000 3162.000000 3310.000000 3408.000000 3620.000000 3548.000000 3702.000000 4000.000000 4255.000000 4417.000000 4715.000000
70th 1855.000000 2069.000000 2027.000000 2063.000000 2041.000000 2144.000000 2232.000000 2432.000000 2742.000000 2677.000000 2847.000000 3052.000000 3212.000000 3390.000000 3578.000000 3788.000000 3935.000000 4088.000000 4264.000000 4500.000000 4400.000000 4576.000000 4976.000000 5262.000000 5446.000000 5805.000000
80th 2383.000000 2675.000000 2629.000000 2673.000000 2653.000000 2797.000000 2930.000000 3194.000000 3586.000000 3473.000000 3704.000000 3960.000000 4167.000000 4377.000000 4648.000000 4892.000000 5059.000000 5260.000000 5514.000000 5816.000000 5664.000000 5854.000000 6337.000000 6685.000000 6905.000000 7290.000000
90th 3418.000000 3916.000000 3837.000000 3862.000000 3872.000000 4056.000000 4312.000000 4690.000000 5211.000000 5027.000000 5417.000000 5787.000000 6118.000000 6276.000000 6734.000000 7099.000000 7234.000000 7684.000000 8018.000000 8268.000000 8153.000000 8461.000000 9015.000000 9446.000000 9840.000000 10380.000000

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