Bedroom & Flat Type Analysis

Price comparison by unit size — condos and HDB

How to Read the Bedroom Analysis Insight

Key Takeaways

  • This insight is powered by live URA and HDB transaction data refreshed monthly.
  • Use the district filter above the chart to narrow results to a specific planning area.
  • Hover any data point on the chart for exact values and transaction counts.

What It Does

The Bedroom Analysis insight breaks down median PSF and transaction volume by bedroom count — Studio, 1BR, 2BR, 3BR, 4BR, and 5BR+ — across all private non-landed residential transactions recorded by URA. The primary chart shows how the PSF premium or discount for each bedroom type has evolved over time, so you can see whether the gap between 1BR and 3BR PSF is widening or compressing and how those trends compare to the Singapore-wide baseline. A companion bar chart shows transaction v...

Why It Matters

Bedroom type is one of the most consequential variables in Singapore property investment, yet most investors default to 2-bedroom units without interrogating whether that choice is actually optimal for their target district and tenant pool. In some districts, 1-bedroom units command a higher PSF than 2-bedrooms because the tenant pool is dominated by single expat professionals willing to pay a premium per square foot for a central, compact unit. In others, family tenants mean 3-bedroom uni...

How It Works

  • Select a district from the filter or leave it blank to view Singapore-wide data.
  • Use the time-range buttons (1Y/2Y/3Y/5Y/All) to adjust the chart window.
  • Hover any point on the chart to see exact values and underlying transaction counts.
  • Review the KPI cards above the chart for headline numbers at a glance.

Examples

D9 bedroom PSF premium: why 1BR commands more per sqft than 3BR

Inputs
District
D9 — Orchard / River Valley
Metric
Median PSF by bedroom type
Time range
2022–2025
View
Line chart — all bedroom types overlaid
Results
1BR median PSF (2024)
~$2,950
2BR median PSF (2024)
~$2,680
3BR median PSF (2024)
~$2,420
Pattern
1BR premium over 3BR: ~22% PSF, consistent 2022–2024

How to read this: D9's 1BR PSF premium over 3BR reflects the area's tenant pool: single expat professionals working in the CBD or Orchard fringe pay premium PSF for compact, well-located units and are price-insensitive to the per-sqft cost. An investor buying a 1BR in D9 benefits from this demand dynamic — but only while the expat professional pool remains active in that district. The chart shows this premium has been stable over 2022–2024, confirming it is structural rather than temporary. A narrowing 1BR premium (visible as the 1BR line approaching the 2BR line) would be an early warning signal that tenant demand is shifting toward families and larger units.

D19 volume share: liquidity risk in the 1BR segment

Inputs
District
D19 — Hougang / Punggol / Sengkang
Metric
Transaction volume share by bedroom type
Time range
2020–2025
View
Bar chart — volume share stacked
Results
2BR share of D19 transactions
~46%
3BR share of D19 transactions
~39%
1BR share of D19 transactions
~6%
Implication
Thin 1BR secondary market — limited exit liquidity

How to read this: In D19, 1-bedroom units represent only 6% of total private transaction volume — a very thin secondary market. An investor buying a 1BR in D19 today may need to wait significantly longer to find a buyer at market price, or discount meaningfully to clear the market. This liquidity risk is invisible from a PSF comparison alone. The volume share chart makes it visible: districts where 1BR share is below 10% carry material exit-liquidity risk for that bedroom type. The same investor's capital deployed into a 2BR or 3BR in D19 (46% and 39% share respectively) would face far less liquidity friction at resale.

Tips & Pitfalls

Expert Tips

  • Compare 2–3 districts side-by-side to spot relative outliers rather than reading a single number in isolation.
  • Always check the transaction count alongside any price metric — small sample sizes can produce misleading averages.
  • Pair this insight with the related calculators and maps below for a complete decision framework.

Common Pitfalls

  • Interpreting short-term movements (under 1 year) as trends — Singapore property data is noisy and needs a longer window.
  • Ignoring the difference between median and mean — means are pulled by luxury outliers in prime districts.
  • Forgetting that new-launch prices are often subsidised by developer discounts not visible in headline data.

Frequently Asked Questions

Where does the data come from?
Data is sourced from the Urban Redevelopment Authority (URA) and Housing & Development Board (HDB) official APIs, refreshed monthly.
How often is this insight updated?
The underlying transaction data is synced monthly from URA and HDB. The charts recompute live as new data arrives.
Can I filter by district?
Yes — use the district filter above the chart. You can also share a deep link to a specific district via the URL.

Related Resources

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