I’m trying to understand what changed in Rio de Janeiro this month. In the R$4,682,000–R$7,022,000 range, my property sample suggests roughly 78 days to find a buyer. The longest-lived listings mostly seem connected to property-tax burden, while I’m treating flood risk as a separate concern. Do recent completed sales support that timing, or are the listings still online creating a distorted picture?
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Rio properties at R$4,682,000–R$7,022,000: what does 78 days really show?
- Thread starter mara_dove
- Start date
Listings still online will naturally overrepresent properties that have not sold, so 78 days may describe the difficult stock rather than the whole market. Completed sales would help, but withdrawn listings matter too: otherwise an unsuccessful listing simply disappears from the calculation.
saveTheInk
First-time buyer
Is 78 days the median or the average? One unusually old property could move the average substantially. I’d also look for listings removed and then reposted, because their displayed age may have restarted even though the seller has been trying for much longer.
There is another timing problem: “found a buyer” is not necessarily the same date as a completed transaction becoming visible. Financing and completion delays could make recent sales describe buyer decisions made earlier, depending on how the information was recorded.
Using a broad Rio area gives you more observations, while using narrow neighbourhoods makes the properties more comparable. I would favour the second approach here. In the R$4,682,000–R$7,022,000 bracket, different property profiles can easily be blended into a 78-day result that is not representative of any one segment.
As a compromise, rerun the same completed, withdrawn and active groups using smaller boundaries. If the timing changes sharply, the broad sample was hiding local differences; if it remains similar, the 78-day figure has more support.
As a compromise, rerun the same completed, withdrawn and active groups using smaller boundaries. If the timing changes sharply, the broad sample was hiding local differences; if it remains similar, the 78-day figure has more support.
I’m not convinced property tax is the main reason for the outliers. It may be correlated with larger or more valuable properties, while condition, layout or an ambitious asking price is what actually keeps them online.
Flood risk also needs careful handling. A broad location flag may not distinguish between two properties in the same area, and condition could change how buyers perceive the issue. I would not combine that flag with property tax into one explanation.
Do you know whether the sample includes properties marketed mainly to financed buyers, cash buyers, or both? At these prices, the financing path could affect the gap between an accepted offer and a recorded completion without saying much about demand itself.
One more distinction: a property can attract a buyer quickly and then remain marked online. If status updates are inconsistent, counting the final removal date as the sale date will stretch the apparent marketing period.
Seller motivation may explain part of the tail. A seller who can wait is less likely to reduce the price after a quiet month, whereas someone with a firm deadline may accept an offer sooner. Both can begin with similar properties.
leo_questions
Mortgage adviser
Price-cut timing would tell us more than the final asking price. If the outliers waited most of those 78 days before reducing, the issue may have been the initial price rather than tax or flood risk.
That also affects any month-to-month conclusion. A rise in new-listing volume can make the active sample look younger even if nothing improved, while a quiet month leaves a larger share of old stock. The entry dates need to be separated.
Withdrawals are the awkward category. Some may represent failed attempts, but others could reflect a seller changing plans or moving the property elsewhere. I would show them separately rather than automatically treating every withdrawal as an unsold failure.
leo_questions
Mortgage adviser
Reposted properties are worth matching by more than wording. Photos and descriptions can change, and a price change may accompany the new listing. Without identifying likely repeats, the shortest-looking marketing periods may be the least reliable.
For condition, even broad categories would help: ready to occupy, cosmetically dated, or requiring substantial work. No need to assign an exact renovation cost. The point is to stop a major condition difference from being misread as a tax effect.
Completed transactions will answer a different question, and with a lag. I’d compare them with the earlier listing cohort rather than with whatever happens to be active on the day the completed sale appears.
A simple working table could include first observed date, current status, last observed date, original and latest asking price, first price-cut date, neighbourhood, condition, financing indication, tax concern and flood-risk flag. Unknowns should stay unknown rather than being guessed.