Tokyo sample: is the 6.7% price movement meaningful?

The first reading of my Tokyo country-home sample is a 6.7% increase, but I’m hesitant to treat that as a real market move. The properties are marketed from ¥118,700,000 to ¥178,100,000 and have a median exposure of about 70 days, yet differences in neighbourhood and condition could easily be driving the result.

There is more stock available, although little of it appeals to me. Energy performance is the unresolved part: I cannot tell whether buyers use a weaker rating to negotiate a reduction or simply skip the home. For example, an inefficient property that disappears after 70 days might have sold cheaply, been withdrawn or returned under a new listing.

What completed-sale evidence or listing history would best distinguish those outcomes, and which energy measure would make the homes reasonably comparable?

To clarify, I’m treating the +6.7% as a snapshot from this sample, not a Tokyo-wide figure. I also haven’t found a satisfactory way to account for withdrawn stock. A home disappearing after 70 days could have sold, been withdrawn or returned later at a different price, and those outcomes imply very different things.

I wouldn’t infer much from marketing time until you separate completed sales, withdrawals and still-active listings. Energy performance may show up less as a negotiated discount and more as fewer buyers viewing or bidding at all. What are you using as the energy measure, and are the homes close enough in age and condition to compare?

Neighbourhood boundaries may be doing more damage to the sample than the small size. Two similarly priced properties can appeal to different buyer pools even if both are labelled Tokyo. I’d group them narrowly, then record initial price, first cut, days until that cut, condition and final known outcome. That should reveal whether 70 days is normal exposure or sellers waiting too long to adjust.

Completed prices would give the sample a firmer base. The obstacle is timing: those deals reflect earlier negotiations and may not represent the homes competing for buyers now.

I’d keep them as one comparison rather than the whole analysis. First remove properties that do not closely match on neighbourhood, age and condition, then see whether the 6.7% remains. Alongside that, record the original asking price, date of the first cut and final known outcome. A seller facing limited buyer financing may reduce quickly, while another may withdraw instead, and both outcomes are useful even when no completed price is available.

That’s fair. A practical compromise is two views: a tightly matched active-listing set for current competition, and completed outcomes for evidence of what buyers accepted. Keep withdrawals visible rather than deleting them. If the 6.7% vanishes after narrowing neighbourhood and condition, it was probably composition; if it remains, then price-cut timing and seller motivation become worth examining.