Singapore - House Price Index





Singapore: House Price Index

Mnemonic HPI.ISGP
Unit Index 2009Q1=100, NSA
Adjustments Not Seasonally Adjusted
Quarterly 2.81 %
Data 2023 Q4 201.5
2023 Q3 196

Series Information

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

Singapore: Real Estate

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

Release Information

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:

  • Measurement: Fixed-base index relative to 2009Q1 (Index 2009Q1=100)
  • Adjustment: Not seasonally adjusted (NSA)
  • Native frequency: Quarterly
  • Start date: Uniformly 1975Q1

Predecessor:

  • 1998Q4=100 - 1975Q1 to 2014Q4 ("_98")

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

  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.

Moody's Analytics supplements

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.

Further reading

At the ultimate source:

At third parties:

  • Nov 2006 - Initial version.
  • Apr 2015 - Rebased from 1998 to 2009.
  • 31 Jul 2023, Phillip Thorne - Properties, Moody's Analytics supplements, Further reading, Notes.