Singapore - House Price Index





Singapore: House Price Index

Mnemonic HPI.ISGP
Unit Index 2009Q1=100, NSA
Adjustments Not Seasonally Adjusted
Quarterly 1.33 %
Data 2019 Q3 152.8
2019 Q2 150.8

Series Information

Source Urban Redevelopment Association (URA)
Release House Price Index
Frequency Quarterly
Start Date 3/31/1975
End Date 9/30/2019

Singapore: Real Estate

Reference Last Previous Units Frequency
Building Permits 2019 Q3 2,770 8,534 # of units, NSA Quarterly
House Price Index 2019 Q3 152.8 150.8 Index 2009Q1=100, NSA Quarterly
Residential Building Completions 2019 Q3 1,093 1,874 # of units, NSA Quarterly
Residential Building Permits 2019 Q3 4,435 5,953 # of units, NSA Quarterly
Residential Housing Starts 2019 Q3 1,860 4,141 # of units, NSA Quarterly
Vacancy 2019 Q3 22,819 23,636 # EOP, NSA Quarterly

Release Information

The collection and compilation of data for the Property Price Index and Commercial Property Rental Index are undertaken by the Urban Redevelopment Authority (URA).

URA’s private residential PPI reflects the broad price trends in Singapore's private residential market. Since the last revision to the PPI methodology in 2000, the private housing market has become more diverse. For instance, there is greater variation in the unit size and age of private housing developments. To ensure that the PPI remains robust, the source has reviewed and improved the computation methodology.

Previously, the property price index was calculated using transactions which are grouped according to property type, tenure, completion status and region. The median prices for each category were then computed, using 12-quarter moving average weights, to derive the price index. The older base year was 1998Q4=100. 

However, the method did not fully differentiate between a large apartment and a shoebox unit, or between new and old houses. So when more lower-priced shoebox units were sold in a particular quarter, for example, overall prices may appear to have fallen.

With the revised index, more property attributes, such as proximity to the MRT, size and age of the property, will be considered. And when these attributes are removed, the index will show only how prices of properties move over time.

The key changes to the PPI are as follows:

a.   Improved methodology

    1. Adopting the stratified hedonic regression method which can better control for variations in the attributes of transacted private properties such as age and unit size;
    2. Switching from 12-quarter moving average weights to 5-quarter fixed weights;
    3. Adopting a new base period of 1Q2009

b.    More comprehensive coverage of transactions:

 The source has supplemented the existing data sources used to compute the PPI with stamp duty data from the Inland Revenue Authority of Singapore. With this, the improved PPI will capture all private housing transactions.   

Data is revised each quarter when new data becomes available.

Singapore's property price dataset also includes data from other base years. It is recommened to check the catalog for more information.