KYA Private Advisory · Internal

Collective Sale Viability Model

A residual land value model that asks one question per development: can a developer pay these owners more than they will accept, and still make its margin?

Methodology

The model works backwards from what a completed project can sell for, subtracts everything that must be paid before owners see a cent, and compares what is left against what owners will accept. Nothing is scored on "feel".

achievable selling PSF from launch pricing within 3km ↓ land budget = maxLandPsf(sell) × redevelopment GFA − Land Betterment Charge on the GFA uplift only − Lease Upgrading Premium leasehold sites, Bala's Table to a fresh 99 years − ABSD 5% non-remissible; the 35% is remitted upfront ↓ MAX PAYABLE TO OWNERS ÷ existing units vs OWNER REQUIREMENT = market value × 1.45 ↓ ECONOMICS = payable ÷ required × CONSENT (age tier, owner count) = SCORE

The cost stack is measured, not assumed

Rather than guessing a construction cost, the land-to-breakeven relationship is regressed from 66 real launches that carry both a land price and a published breakeven:

breakeven PSF = 339 + 1.5228 × land PSF ppr R² = 0.948, n = 66 realised margin over breakeven: median +25.4% (n = 37)

Planning envelope

Site area and zoned plot ratio come from URA Master Plan 2025 parcel geometry, joined by point-in-polygon to 1,771 developments. The dwelling-unit cap follows URA circular DC22-10:

max dwelling units = (MP allowable GPR × Site Area) ÷ 85 sqm ÷ 100 sqm in nine named localities no cap at all in the Central Area

Validated against a known outcome: Chuan Park computes 910 units against the 916 in Kingsford's actual scheme — 0.7% out.

Consent thresholds

Age tiers follow the Land Titles (Strata) (Amendment) Bill introduced 4 August 2026 — 90% under 10 years, 80% for 10–39, 70% for 40–59, 65% for 60+. The Bill simultaneously tightens the requisition bar to 35%, halves the signature window to six months, and extends the post-failure wait to three years, so its net effect is not assumed to be positive.

From ratio to probability

The economics model says whether a deal is possible. It cannot say how likely one is, because likelihood depends on how rare collective sales are in the first place — and they are very rare. That base rate is the anchor, and everything else moves a development around it.

posterior odds = base rate odds x c x ( PRODUCT of likelihood ratios ) ^ lambda base rate completed sales per year / developments old enough to be candidates LR_i P(feature | sold) / P(feature | universe), measured per factor lambda correlation damping — DU headroom and floor-area uplift correlate +0.70, so multiplying them as independent evidence double-counts c intercept, solved so the mean probability across the universe returns to the base rate. Factors REDISTRIBUTE likelihood; they cannot invent deals the register does not show happening.

Why not a logistic regression

A logit needs failures to separate from successes, and this sample has none — the register records completed sales only. Likelihood ratios can be measured against the whole universe as the negative class instead, which is what this does. It is a weaker instrument and the numbers below are stated with that in mind.

The weights, and where each one comes from

There are no chosen weights. Each factor's weight is its measured likelihood ratio: the share of completed sales in a bin over the share of the universe in the same bin. A ratio above 1 raises the odds, below 1 lowers them, and 1.00 means the factor carries no information. Bins are smoothed toward the universe distribution, so a bin with no completed sales in it returns a mild penalty rather than a verdict of impossible.

How wide the uncertainty really is

Every ratio above rests on 14 reconstructed sales. Resampling those 14 with replacement 400 times, rebuilding the ratios and the calibration from scratch on each draw, gives the bands shown beside each probability. At the top of the list the band spans roughly a factor of three. That width is the honest precision of this exercise, and it is the reason these numbers belong in an internal shortlist rather than in front of an owner.

Factors that earn their place

What we tested and rejected

Widely repeated criteria that do not survive contact with the data.

Rejected
MRT proximity. 86% of sold en blocs sit within 800m of a station — and so do 87% of all 30-year-old condos. Lift 0.98×. Tightening to 500m or 300m does not rescue it: at every radius the base rate falls inside the confidence interval. Median distance is 550m for sold sites against 510m for the universe. Location is already priced through the selling-price input; adding it again would double-count.
Rejected
Freehold preference. 12 of 14 sold sites are freehold, but the two largest deals — Chuan Park ($890m) and Loyang Valley ($880m) — are both 99-year leasehold with ~55 years left, precisely what the advice says to avoid. The skew is a size artefact. The only published study finds tenure insignificant (p = 0.18 and 0.95).
Rejected
Acquisition-cost ceiling. Above $1bn: 12% of candidates, 14% of sold — lift 1.19×. Loyang Valley and Chuan Park both exceeded $1bn all-in and both sold. Acquisition cost also correlates +0.90 with unit count, which is already in the model.
Demoted
Plot ratio gap as a gate. Real, but not a requirement. Median measured uplift is 1.38×, five of fourteen are below 1.2×, and Chuan Park sold at 1.05× — already built to 96% of its zoning. Density and land value are substitutes (corr −0.46), so the model treats them as alternative paths rather than a filter.
Adopted
as a floor
Dwelling-unit headroom. URA caps units at GFA ÷ 85 sqm (÷ 100 sqm in nine localities, no cap in the Central Area). Comparing that cap against units standing today: no completed sale had headroom below 1.5×, against 18% of candidates, and 29% of sales sat above 4× against 10% of candidates — lift 2.94×. Real, unlike MRT. Applied as a floor rather than a weight: it correlates +0.70 with GFA uplift, which already drives the economics, and with n=14 the independent 30% cannot be separated from noise.

⚠ The false signal: high unit headroom with shrinking floor area. Honolulu Tower shows 5.27× DU headroom on 0.65× GFA uplift — a developer could slice thirty huge flats into many normal ones, but has 35% less area to sell, and smaller units earn no PSF premium (measured 1.000 across 804 within-project matched pairs). 41 candidates carry this pattern and are flagged.
Adopted
Unit count. The strongest survivor. Median completed deal 2021–26 is 22 units; 21 of 24 are under 150. Significant at p = 0.00 in both published logit specifications.

Validation against completed sales

For each completed collective sale, the model's maximum payable to owners against the price actually paid. Inputs are the site's real parcel geometry and the caveat record.

0.92
Median predicted ÷ actual
13 / 14
Within ±40%
+83%
Median realised premium to owners

The economics of one deal, line by line

Pick a completed sale to see the whole arithmetic: what the developer paid, what came off the top before owners saw anything, what each owner received against what their home was worth, and what a new unit on the site has to fetch for the numbers to work.


What every one of these deals needed a new unit to fetch

The five sales with enough pre-deal caveats to price them share one finding, and it is the model's binding defect. Each site had to command roughly three times its own resale PSF as a new launch. The scorer's fallback rule for a site with no launch comparable assumes 1.35×.

This is a test of the fallback, not of the live model: all scored candidates price off launch comparables within 3km, so the fallback is currently dead code. It is shown because the multiple is the number that matters — live candidates are priced at a median 1.74× (freehold) and 2.27× (leasehold) of their own resale PSF, against the 2.92× these deals actually required. The model is reading the selling price low across the board, not only at Loyang Valley.

These sites cannot be rescored as of their sale dates: per the survivorship correction, only two of them still geocode, because the buildings are gone. Not out-of-sample either — the Land Betterment Charge rate was calibrated on Loyang Valley, which appears here.

The probability the model would have assigned

The fairer test of a shortlist is where a development that really sold sat in the distribution. 50% is a coin.

Top 20 by score

Ranked from developments aged 30+ with a readable parcel, after excluding commercial and mixed strata and developments under 10 units. Ranking is driven by economics — payable ÷ required — not by either uplift ratio.

exPR existing plot ratio · GPR zoned · GFA uplift = GPR ÷ exPR, the ratio that drives revenue · Unit uplift new units ÷ existing units, a consequence of the URA dwelling-unit cap rather than a source of value (at Chuan Park these are 1.05× and 2.05×) · Econ payable ÷ required, ≥1 means a deal can clear · Acq total acquisition cost including ABSD, BSD, LBC and lease premium · p(5y) probability of a completed collective sale within five years, with its bootstrap band.

Ordering is now by probability rather than by score, which moves rows: a site can carry excellent economics and still rank below a weaker one that sits in better-evidenced bins on owner count and floor-area uplift. Click a row to see which factor contributed what.

Where the leasehold candidates went

The top of the list is entirely freehold. That is a real property of the output and it is worth being precise about the cause, because the obvious explanation is the wrong one.

Not this
A freehold preference in the model. There is none. The tenure multiplier was removed after EdgeProp's logit found tenure insignificant (p = 0.18 and 0.95), and the likelihood ratio measured here is — statistically indistinguishable from no effect. Median economics are freehold against leasehold. On the economics itself, tenure does nothing.
Cause 1
Owner count, which travels with tenure. Median freehold candidate: units. Median leasehold candidate: . Singapore's old freehold stock is boutique walk-up blocks; its old leasehold stock is large HUDC-era estates. The consent curve is calibrated to a register whose median deal is 22 units, so it penalises size hard — median consent factor freehold against leasehold. The freehold skew is an owner-count skew wearing a tenure label.
Cause 2
The Lease Upgrading Premium. Topping a site back up to a fresh 99 years costs a median of the entire land budget, and it comes off the top before owners see a cent. Freehold sites pay nothing. This is a real cost, not a modelling choice — Loyang Valley's was $246m — but it means a leasehold site must clear a bar its freehold neighbour never sees.
Cause 3
Seven "leasehold" developments are 999-year leases and are freehold in every way that matters — Roxy Square, Le Loyang, Kensington Park, Grande Vista, Ridgewood, Allsworth Park, Azalea Park. They were inflating the leasehold count while behaving as freehold. They are now classified as freehold, which is why the true 99-year leasehold pool is developments and not 48.

The counterfactual: leasehold with the lease premium removed

Setting the Lease Upgrading Premium to zero — not a proposal, a diagnostic — shows how much of the leasehold gap it accounts for on its own.

Several perennial candidates cross 1.00 the moment the lease premium comes out, which locates the constraint precisely. It does not make them viable: the premium is genuinely payable. What it shows is that leasehold sites are not failing on developer appetite or on location — they are failing on a statutory cost plus an owner count the consent curve punishes.

The best true-leasehold candidates

The strongest leasehold development ranks overall, and only appears in the top 50. Against the two largest completed deals in the register both being 99-year leasehold — Chuan Park and Loyang Valley — that ordering should be treated as a caution about the consent curve's steepness, not as a finding that leasehold estates do not sell.

Live attempts

Developments currently launched for collective sale. These are the prospective test set — a failure is worth as much as a sale, because it is the only way to measure false positives.

Worked example — Lakeside Towers, asking $350m

144 units on 153,237 sqft, GPR 2.1, 99-year lease from ~1979, third attempt. Existing plot ratio ~1.81 gives just 1.16× uplift, and the lease top-up premium takes $59–91m off the top before owners see anything.

The ask implies $968 psf ppr, close to the $1,077 psf ppr its neighbour Lakeside Apartments achieved in May 2022 — which is presumably how it was set. But that neighbour was less built-out with a longer lease. On residual value the ask needs about $3,112 psf to work, against roughly $2,500 for the nearest launch. Every completed deal cleared at 70–143% of model max payable; this ask is around 135–210% of it.

Known limitations

Register coverage by year