Dataset from Urban Redevelopment Authority. For more information, visit https://data.gov.sg/datasets/d_97f8a2e995022d311c6c68cfda6d034c/view

O Índice de Preços de Casas MoM em Singapura diminuiu para 0,50 por cento no segundo trimestre de 2025, em comparação com 0,80 por cento no primeiro trimestre de 2025. Esta página inclui um gráfico com dados históricos para o Índice de Preços de Propriedades Residenciais de Singapura Mês a Mês.

Housing Index in Singapore increased to 210.70 points in the first quarter of 2025 from 209.40 points in the fourth quarter of 2024. This dataset provides the latest reported value for - Singapore Property Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Dataset from Urban Redevelopment Authority. For more information, visit https://data.gov.sg/datasets/d_f333bf427c827efb484cf57a73ff700a/view

Core Central Region :

Core Central Region comprises Postal Districts 9, 10, 11, Downtown Core Planning Area and Sentosa.

_Rest of Central Region : _

Rest of Central Region comprises the area within Central Region that is outside postal districts 9, 10, 11, Downtown Core Planning Area and Sentosa.

A map of Central Region showing the Core Central Region (CCR) and the Rest of Central Region (RCR) is available at: https://spring.ura.gov.sg/lad/ore/login/map_ccr.pdf

Outside Central Region :

Outside Central Region (OCR) refers to the planning areas which are outside the Central Region.

In late 2016, the URA, in conjunction with Reinvestment Fund, completed the 2016 Market Value Analysis (MVA) for the City of Pittsburgh. The Market Value Analysis (MVA) offers an approach for community revitalization; it recommends applying interventions not only to where there is a need for development but also in places where public investment can stimulate private market activity and capitalize on larger public investment activities. The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional neighborhood boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

Pittsburgh’s 2016 MVA utilized data that helps to define the local real estate market between July, 2013 and June, 2016:

• Median Sales Price

• Variance of Sales Price

• Percent Households Owner Occupied

• Density of Residential Housing Units

• Percent Rental with Subsidy

• Foreclosures as a Percent of Sales

• Permits as a Percent of Housing Units

• Percent of Housing Units Built Before 1940

• Percent of Properties with Assessed Condition “Poor” or worse

• Vacant Housing Units as a Percentage of Habitable Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

During the research process, staff from the URA and Reinvestment Fund spent an extensive amount of effort ensuring the data and analysis was accurate. In addition to testing the data, staff physically examined different areas to verify the data sets being used were appropriate indicators and the resulting MVA categories accurately reflect the market.

In 2021, Allegheny County Economic Development (ACED), in partnership with Urban Redevelopment Authority of Pittsburgh(URA), completed the a Market Value Analysis (MVA) for Allegheny County. This analysis services as both an update to previous MVA’s commissioned separately by ACED and the URA and combines the MVA for the whole of Allegheny County (inclusive of the City of Pittsburgh). The MVA is a unique tool for characterizing markets because it creates an internally referenced index of a municipality’s residential real estate market. It identifies areas that are the highest demand markets as well as areas of greatest distress, and the various markets types between. The MVA offers insight into the variation in market strength and weakness within and between traditional community boundaries because it uses Census block groups as the unit of analysis. Where market types abut each other on the map becomes instructive about the potential direction of market change, and ultimately, the appropriateness of types of investment or intervention strategies.

This MVA utilized data that helps to define the local real estate market. The data used covers the 2017-2019 period, and data used in the analysis includes:

• Residential Real Estate Sales
• Mortgage Foreclosures
• Residential Vacancy
• Parcel Year Built
• Parcel Condition
• Building Violations
• Owner Occupancy
• Subsidized Housing Units

The MVA uses a statistical technique known as cluster analysis, forming groups of areas (i.e., block groups) that are similar along the MVA descriptors, noted above. The goal is to form groups within which there is a similarity of characteristics within each group, but each group itself different from the others. Using this technique, the MVA condenses vast amounts of data for the universe of all properties to a manageable, meaningful typology of market types that can inform area-appropriate programs and decisions regarding the allocation of resources.

Please refer to the presentation and executive summary for more information about the data, methodology, and findings.

Dataset from Urban Redevelopment Authority. For more information, visit https://data.gov.sg/datasets/d_862c74b13138382b9f0c50c68d436b95/view