Tokyo 3-bed inventory in December 2024: seasonality or selectivity?

S

SimpleLane

First-time buyer
Established
A small update to my December 2024 tracking has raised more questions than it answered. In the records I have, well-presented Tokyo duplexes with three bedrooms appear to find buyers in about 24 days, while properties requiring work tend to sit. The apparent difference between advertised and completed prices is only 0.0%.

My sample is not large, so the result could reflect the particular neighbourhoods and homes included rather than a change in buyer behaviour. I also need to check whether later revisions have slipped into the December figures and whether listing, agreement and completion dates are aligned. Has anyone compared matched transactions locally, including the price history and relevant dates?
 
A 0.0% gap by itself doesn’t establish much. Are you comparing each completed sale with that same property’s final asking price, or comparing averages from separate groups? The second method can show no gap even when individual sellers negotiate, particularly if the sold homes are the better-presented ones.
 
Also, how large is the sample, and are all the records actually from December 2024? Listing, agreement and publication dates may not represent the same point in a transaction. Mixing them could make a short-lived inventory change look more significant than it was.
 
I’d separate duplexes from other 3-bed homes before drawing a conclusion. Then divide each group by condition and neighbourhood. If the 24-day figure disappears after that, the apparent citywide shift was probably caused by the mix of properties rather than a broad change in buyer behaviour.
 
I wouldn’t dismiss seasonality so quickly. One month can reflect which owners chose to list, not just what buyers preferred. Transaction volume matters here: stable pricing on thin activity tells a different story from stable pricing while many comparable homes complete. Without volume and a longer comparison period, “more selective” is plausible but not demonstrated.
 
I’d audit the individual records before either extending the date range or treating December as a market signal. A longer period will not fix mismatched listings, and it may conceal revisions made after the original entry.

Build one row per property with neighbourhood, type, condition, initial ask, final ask, completed price and the date attached to each stage. Mark any figure that was later corrected or published late. That should show whether 0.0% survives genuine ask-to-sale matching or is simply an artefact of rounding and aggregation.
 
Those are fair challenges. My sample is manually collected and small, and I have mixed several Tokyo neighbourhoods, so I may be seeing composition rather than a citywide turn. The 0.0% figure is from visible asking-versus-completed information, but not every record has an equally clear date trail. I’ll rerun it using matched properties, separate condition and neighbourhood, and keep December 2024 apart from later updates.
 
Even after that, condition may be partly standing in for price realism. A renovated home can move quickly because the seller set an attainable price, while a property needing work may sit because the renovation cost is difficult for buyers to estimate. I’d compare initial ask as well as final ask; otherwise later reductions get hidden.
 
One more complication is timing around policy expectations. Don’t assume a policy announcement and a market response belong to the same month; buyers, sellers and completed records can move on different schedules. I’d extend the comparison on both sides of December, note any revisions to the data, and report neighbourhood results separately. If the pattern survives those tests, the selectivity explanation becomes much stronger.
 
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