I’m trying to judge the market around $1,275,000 in Atlanta. Across a broader $1,020,000–$1,530,000 sample, the properties still online suggest roughly 115 days to find a buyer. The longest cases seem associated with property-tax differences, but the notes also describe some as “coastal homes,” which makes me question the filtering. Should I rely more heavily on recent completed sales, and how should withdrawn listings be treated?
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Is my 115-day Atlanta sample being distorted by stale listings?
- Thread starter kai_cole
- Start date
The active listings will naturally make the market look slower because the quick sellers have already disappeared from that group. Compare properties first listed during the same period, then divide them into completed, active and withdrawn. For completed deals, keep both time to contract and total time to closing separate if your information allows it.
Before trusting 115 days, what exactly counts as Atlanta in the sample? Neighbourhood boundaries can put very different properties and tax burdens into one bucket. The “coastal” wording is another sign that something may be misclassified. I’d also separate by property form and condition rather than using price alone.
I wouldn’t treat every withdrawal as evidence that buyers rejected the property. A seller can pause, relist or change plans. Still, leaving withdrawals out entirely would overstate how easily stock clears. Keep them as a separate outcome and look for the same address returning with a new price.
cedar.fast
Mortgage adviser
Price-cut timing may explain more than the headline days figure. A home that sat at an ambitious price and sold soon after a reduction tells a different story from one that needed no cut. Seller motivation matters too. I’d record original ask, dates of reductions, final price where available, and whether the buyer’s financing extended the process.
I’m less convinced that property tax is the main cause of the outliers. It may simply be travelling with another variable: neighbourhood, size, condition or asking-price strategy. Compare similar properties within tighter boundaries before assigning the delay to tax. Otherwise one unusual cluster could drive the whole conclusion.
Omar’s boundary point is important. I’d rebuild the sheet with one row per property and fields for neighbourhood, condition, original list date, first price cut, contract status, closing date and withdrawal or relisting. Then calculate outcomes for the same listing cohort. That should reveal whether 115 days describes typical demand or only the stale remainder.
One more useful split: new-listing volume versus completed sales during the period. If fresh supply increased, the active pool can grow even without a major change in buyer pace. I’d fix the apparent location-label problem first, narrow the neighbourhoods, and then compare completed, active and withdrawn properties around $1,275,000. Until that is done, 115 days is better treated as a description of this sample than of Atlanta generally.