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D

Retail Sales Index, (2017 = 100), In Chained Volume Terms, Monthly

What this data shows

Published by Singapore Department of Statistics. 16 records. Fields include Data Series, 2025 Dec, 2025 Nov, 2025 Oct (493 columns in total). Covers 1985-01-01 to 2025-12-01. Last updated 2026-02-05.

Description

Non-seasonally adjusted monthly Retail Sales Index in chained volume terms (2017 = 100) from 1985, published by the Singapore Department of Statistics. Analysts compare this series with the seasonally adjusted release to study raw retail trends and calendar effects in Singapore consumer spending.

Official description

Source: SINGAPORE DEPARTMENT OF STATISTICS Data Last Updated: 05/02/2026 Update Frequency: Monthly Footnotes: Link to latest RSI/FSI release is available via www.singstat.gov.sg/find-data/search-by-theme/industry/services/latest-data. Relevant methodology paper is available via www.singstat.gov.sg/find-data/search-by-theme/industry/services/publications-and-methodology. Adapted from: https://tablebuilder.singstat.gov.sg/table/TS/M601871

Last updated
Coverage
1985-01-01 – 2025-12-01
Rows
16
Columns
493

Chart

Values are summed where multiple rows share the same category.

Data

Data Series 2025 Dec 2025 Nov 2025 Oct 2025 Sep 2025 Aug 2025 Jul 2025 Jun 2025 May 2025 Apr 2025 Mar 2025 Feb
Total 109.461000 101.952000 98.992000 94.853000 99.959000 98.002000 91.877000 97.578000 90.159000 99.862000 87.348000
Department Stores 102.849000 93.859000 79.018000 76.426000 75.327000 72.879000 74.307000 82.464000 67.760000 79.328000 63.084000
Supermarkets & Hypermarkets 116.284000 111.869000 113.654000 112.606000 125.157000 120.208000 105.393000 115.914000 105.511000 112.041000 98.298000
Mini-Marts & Convenience Stores 73.519000 76.929000 78.379000 77.301000 82.399000 82.573000 73.494000 80.229000 76.381000 77.869000 73.021000
Food & Alcohol 111.100000 97.895000 98.716000 90.337000 100.940000 96.162000 89.977000 99.543000 93.161000 96.210000 92.757000
Motor Vehicles 70.422000 60.643000 67.247000 71.435000 69.739000 74.606000 70.853000 72.075000 64.462000 76.844000 64.846000
Petrol Service Stations 69.514000 74.199000 72.359000 76.705000 83.820000 83.274000 74.272000 81.120000 79.177000 83.194000 73.876000
Cosmetics, Toiletries & Medical Goods 121.361000 120.623000 107.384000 104.154000 108.103000 102.667000 104.494000 105.059000 94.187000 106.774000 93.845000
Wearing Apparel & Footwear 154.902000 151.165000 124.355000 111.823000 127.231000 123.702000 119.007000 123.521000 106.806000 121.938000 111.085000
Furniture & Household Equipment 135.711000 132.788000 111.686000 103.404000 114.122000 106.847000 105.795000 105.921000 98.972000 110.710000 86.471000

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

Columns

Column Type Categorical
Data Series Text No
2025 Dec Numeric No
2025 Nov Numeric No
2025 Oct Numeric No
2025 Sep Numeric No
2025 Aug Numeric No
2025 Jul Numeric No
2025 Jun Numeric No
2025 May Numeric No
2025 Apr Numeric No
2025 Mar Numeric No
2025 Feb Numeric No
2025 Jan Numeric No
2024 Dec Numeric No
2024 Nov Numeric No
2024 Oct Numeric No
2024 Sep Numeric No
2024 Aug Numeric No
2024 Jul Numeric No
2024 Jun Numeric No
2024 May Numeric No
2024 Apr Numeric No
2024 Mar Numeric No
2024 Feb Numeric No
2024 Jan Numeric No
2023 Dec Numeric No
2023 Nov Numeric No
2023 Oct Numeric No
2023 Sep Numeric No
2023 Aug Numeric No
2023 Jul Numeric No
2023 Jun Numeric No
2023 May Numeric No
2023 Apr Numeric No
2023 Mar Numeric No
2023 Feb Numeric No
2023 Jan Numeric No
2022 Dec Numeric No
2022 Nov Numeric No
2022 Oct Numeric No
2022 Sep Numeric No
2022 Aug Numeric No
2022 Jul Numeric No
2022 Jun Numeric No
2022 May Numeric No
2022 Apr Numeric No
2022 Mar Numeric No
2022 Feb Numeric No
2022 Jan Numeric No
2021 Dec Numeric No
2021 Nov Numeric No
2021 Oct Numeric No
2021 Sep Numeric No
2021 Aug Numeric No
2021 Jul Numeric No
2021 Jun Numeric No
2021 May Numeric No
2021 Apr Numeric No
2021 Mar Numeric No
2021 Feb Numeric No

Showing the first 60 of 493 columns. Download the CSV for the full schema.