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4,615 datasets found

GEOJSON

HDB Public Housing Building Under-Construction

Housing & Development Board GeoJSON layer showing HDB public housing projects in Singapore that were under construction as at February 2018. Site locations are drawn using the site boundaries in each project's layout of site plan. The layer excludes developments such as DBSS flats and Executive Condominiums. Planners, researchers and property analysts use it to map where new public housing supply was being built and to overlay upcoming HDB projects on population, transport or amenity data.

Housing & Development Board
CSV 24 rows

Tax and Penalty Arising from Investigations

Inland Revenue Authority of Singapore CSV of tax and penalty amounts arising from investigations by financial year from 2002 through 2024, with case counts. Tax compliance analysts monitor investigation outcomes and penalty totals over time.

Inland Revenue Authority of Singapore
CSV 65 rows

Tax and Penalty Arising from Audits by Tax Type

Inland Revenue Authority of Singapore record of tax and penalty amounts arising from audits, broken down by tax type, covering financial years 2002 through 2024. Each row gives the financial year, the tax type, the number of cases, and the tax and penalty arising, so users can compare enforcement outcomes across income tax, GST, and other tax streams. Several definitional breaks apply: FY2003/04 income tax audits include a one-time recovery relating to interest-free or subsidised director loans, GST refund review cases have been excluded from GST audit figures since FY2004/05, and the corporate income tax compliance case definition was revised from FY2021/22. Tax practitioners and policy researchers use the series to study compliance and enforcement trends.

Inland Revenue Authority of Singapore
CSV 24 rows

Total Government Operating Revenue and IRAS' Collection

This dataset compares Singapore's total Government operating revenue with collections by the Inland Revenue Authority of Singapore for financial years from 2002 to 2024. The two annual series provide a concise view of how IRAS-administered receipts relate to the broader operating-revenue base. It can support fiscal and tax-revenue trend analysis, with the important qualification that the stated Government total excludes interest income, investment income and capital receipts.

Inland Revenue Authority of Singapore
CSV 188 rows

IRAS' Collection By Tax Type

Inland Revenue Authority of Singapore CSV of tax collections by tax type and financial year from FY2002 through FY2024, covering property tax, betting taxes (including casino tax from March 2010), estate duty (removed for deaths on or after 15 February 2008), and other levies. Fiscal analysts track IRAS revenue composition over time.

Inland Revenue Authority of Singapore
CSV 26 rows

Cost of Tax Collection

This Inland Revenue Authority of Singapore (IRAS) dataset reports the cost of tax collection, expressed as the cost incurred for every dollar of tax collected, for each financial year from 2000 to 2024. The measure is a standard efficiency indicator for revenue authorities: a falling cost per dollar means the agency is collecting the same revenue with proportionally fewer resources. With just a financial year and a ratio in each row, the series is easy to chart and to compare against the collection efficiency of tax administrations elsewhere. Public finance researchers, auditors and policy analysts use it to assess productivity gains from digitalisation and process reform at IRAS.

Inland Revenue Authority of Singapore
CSV 7 rows

Resident Population Aged 65 Years and Over in Resident Households by Main Source of Financial Support and Type of Dwelling (General Household Survey 2015)

General Household Survey 2015 table in thousands on residents aged 65 and over in resident households by main source of financial support and type of dwelling, including HDB flat sizes and private apartments. Ageing-policy analysts study elderly reliance on family, work, or government support across Singapore housing types.

Singapore Department of Statistics
CSV 13 rows

Resident Population Aged 15 Years and Over by Age Group, Highest Qualification Attained, Sex and Ethnic Group (General Household Survey 2015)

General Household Survey 2015 CSV of resident population aged 15 and over by age group, highest qualification, sex, and ethnic group (thousands), covering non-full-time students including part-time upgraders, from the Singapore Department of Statistics. Education and equity researchers profile Singapore’s adult qualification structure by ethnicity. Adapted from CT/8358.

Singapore Department of Statistics
CSV 16 rows

Resident Population Aged 5 Years and Over by Age Group, Ethnic Group and Language Most Frequently Spoken at Home (General Household Survey 2015)

General Household Survey 2015 resident population aged 5 and over by age group, ethnic group, and language most frequently spoken at home (English, Mandarin, Chinese dialects, and others), in thousands, with exclusions noted in the metadata. Language planners study home-language patterns across Chinese, Malay, and Indian communities in Singapore.

Singapore Department of Statistics
CSV 7 rows

Resident Population Aged 65 Years and Over in Resident Households by Main Source of Financial Support, Marital Status and Sex (General Household Survey 2015)

General Household Survey 2015 table on residents aged 65 and over in resident households by main source of financial support, marital status, and sex, in thousands. Singapore Department of Statistics data informs ageing, silver support, and family dependency research in Singapore. Breakdowns cover single and married groups among seniors.

Singapore Department of Statistics
CSV 12 rows

Resident Population Aged 65 Years and Over in Resident Households by Living Arrangements, Age Group and Sex (General Household Survey 2015)

General Household Survey 2015 residents aged 65 and over in households by living arrangements, age group, and sex, in thousands. June 2026 methodological refinements improve identification of children-in-law. Ageing researchers study co-residence, solo living, and family support structures for seniors in Singapore.

Singapore Department of Statistics
CSV 17 rows

Resident Households by Monthly Household Income from Work Per Household Member and Number of Working Persons in Household (General Household Survey 2015)

Source: SINGAPORE DEPARTMENT OF STATISTICS Data Last Updated: 30/06/2026 Update Frequency: 10 years Survey period: General Household Survey 2015 Footnotes: Note: Data on income from work have been updated to include Additional MediSave Contributions from employers with the release of the Key Household Income Trends 2025 report in February 2026. For more information, you may refer to the Technical Note on Household Income (https://go.gov.sg/khit2025-tech-note) which explains the concepts and components of our household income coverage. Adapted from: https://tablebuilder.singstat.gov.sg/table/CT/8276

Singapore Department of Statistics
CSV 7 rows

Resident Population Aged 65 Years and Over in Resident Households by Main Source of Financial Support, Ethnic Group and Sex (General Household Survey 2015)

General Household Survey 2015 table on Singapore residents aged 65 and over in resident households, classified by main source of financial support, ethnic group, and sex. The Singapore Department of Statistics CSV supports ageing and elder-income security research at the decennial household benchmark. Adapted from SingStat TableBuilder CT/8303.

Singapore Department of Statistics
CSV 9 rows

Resident Population Aged 5 Years and Over by Type of Dwelling and Language Most Frequently Spoken at Home (General Household Survey 2015)

General Household Survey 2015 table from the Singapore Department of Statistics cross-tabulating resident population aged five and over by dwelling type and language most frequently spoken at home, in thousands. Sociolinguistics and housing researchers study home-language patterns across HDB and private housing with noted exclusions for non-speaking persons and certain household types.

Singapore Department of Statistics