Mnemonic | HPI.ISGP | |
---|---|---|
Unit | Index 2009Q1=100, NSA | |
Adjustments | Not Seasonally Adjusted | |
Quarterly | 2.81 % | |
Data | 2023 Q4 | 201.5 |
2023 Q3 | 196 |
Source | Singapore Department of Statistics (DOS) |
Release | Private Residential Property Price Index By Type Of Property (PPI) [HPI] |
Frequency | Quarterly |
Start Date | 3/31/1975 |
End Date | 12/31/2023 |
Reference | Last | Previous | Units | Frequency | |
---|---|---|---|---|---|
House Price Index | 2023 Q4 | 201.5 | 196 | Index 2009Q1=100, NSA | Quarterly |
Vacancy | 2023 Q4 | 33,340 | 34,341 | # EOP, NSA | Quarterly |
Building Permits | 2020 Q1 | 1,997 | 2,767 | # of units, NSA | Quarterly |
Residential Building Completions | 2020 Q1 | 1,528 | 2,298 | # of units, NSA | Quarterly |
Residential Building Permits | 2020 Q1 | 1,827 | 2,151 | # of units, NSA | Quarterly |
Residential Housing Starts | 2020 Q1 | 2,113 | 4,317 | # of units, NSA | Quarterly |
For Singapore, the private residential property price index is quarterly and divided between landed and non-landed. (The local abbreviation is "PPI" but it is not a producer price index; for international uniformity, Data Buffet calls it an HPI.)
Typologies classified as "landed" include bungalow, semi-detached, shophouse, terrace, villa, freehold and strata landed; "non-landed" include HDB flat, apartment and condominum.
Active:
Predecessor:
The source writes:
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
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.
We construct a seasonally adjusted counterpart using X-13ARIMA-SEATS.
Yes. Data are revised each quarter when new data becomes available.
The ultimate source is the Urban Redevelopment Authority (URA), but Data Buffet's proximate source is Statistics Singapore, viz., table M202261 at SingStat Table Builder.
At the ultimate source:
At third parties: