Singapore Corporate Tax Rate

Singapore · Annual series · EC-SG-CTR

Latest, 2026

17.0%

+0.00pp from 2025

Open interactive chartSingapore Corporate Tax Rate in the app

History through 2026, the forecast path to 2029 (dashed) and its 80% interval (shaded).

Forecast

Forecast for 2029: 17.0%, with an 80% interval of 15.6% to 18.4%.

Forecast path. Intervals are shown where available.
Period	Forecast	80% low	80% high
2027	17.0%	16.2%	17.8%
2028	17.0%	15.9%	18.1%
2029	17.0%	15.6%	18.4%

Model: Exponential smoothing (statistical). Forecast generated 2026-11-14.

AI confidence

Needs refresh

The data refresh is due. Confidence will be reassessed against the refreshed history.

Model: Exponential smoothing (statistical)

Accuracy vs naive: n/aNot evaluated
Direction: n/aNot evaluated
Turning points: n/aNot evaluated

How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Model comparison

Previous comparisonThe stored comparison uses earlier data or a previous model roster. An eligible nightly batch can compare both candidates, subject to call budgets and retry limits.

Models tested

Exponential smoothing scored lowest on the 2 older tests (0.00) and was chosen. The 1 recent tests played no part in the choice and give its grade (0.00). The search for a model that beats the naive forecast on both sets of tests goes on. Scores are MASE: a model's errors divided by the naive forecast's, so 1 is a tie.

2 model classes completed the tests: Statistical, Foundation model. Previous model roster.

Every model tested on this series.
Model	Class and compute	Older tests	Recent tests	Role
Exponential smoothing (statistical)	Statistical · CPU	0.00	0.00	Serving
Agentic Investor TSFM (foundation model)	Foundation model · CPU	0.12	0.06	Tested
State-space model, 167M (foundation model)	Foundation model · CPU	0.13	0.05	Tested
Naive forecast (last value held)	Benchmark · CPU	1.00	1.00	Benchmark
Gradient-boosted trees (machine learning)	Machine learning · CPU	n/a	n/a	Did not run
Hierarchical neural network (neural network)	Neural network · CPU	n/a	n/a	Did not run

Uses ci-proto, released by Continuous Intelligence. Continuous Intelligence does not endorse or approve this product or service. (ci-proto is shown as State-space model, 167M.)

Reading

It is above 0% of the 9 earlier readings since 2017.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)

The 24 most recent observations, newest first.
Period	Value
2026	17.0%
2025	17.0%
2024	17.0%
2023	17.0%
2022	17.0%
2021	17.0%
2020	17.0%
2019	17.0%
2018	17.0%
2017	17.0%
2016	17.0%
2015	17.0%
2014	17.0%
2013	17.0%
2012	17.0%
2011	17.0%
2010	17.0%
2009	18.0%
2008	18.0%
2007	20.0%
2006	20.0%
2005	20.0%
2004	22.0%
2003	22.0%

Source

Data: public market data feeds.