Bogotá’s November 2025 price gap: selectivity or seasonal noise?

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I have looked through the visible Bogotá listings for November 2025, but I cannot tell whether they show a market shift or simply an unusual month. Renovated duplexes seem to reach a deal in about 33 days, whereas stock needing work appears slower, and the reported gap between advertised and completed prices is around 10.4%.

Those figures may be misleading. A small set of well-priced sales, refreshed listing dates or a mix of neighbourhoods could produce the same pattern without buyers becoming broadly more selective. Monthly service charges may also affect otherwise similar properties.

Does anyone have the transaction counts and the basis of the price comparison—original ask, latest ask or another measure? It would help to separate completed sales from active listings, include revision history and sample size, and identify the Bogotá areas actually being tracked.
 
One month is too thin to separate seasonality from a real change in buyer behaviour. The 33-day figure could also be skewed toward a small group of renovated duplexes priced realistically from the start. I would compare like with like: same property type, similar condition and location, and similar service-charge burden.
 
What is behind the 10.4% figure? In particular, are you comparing final asking prices with recorded sale prices, or original asking prices with sales? Also, were the completed deals agreed in November 2025 or merely recorded then? Those timing differences could materially change the apparent gap, especially if the sample is small.
 
Marco’s timing point is important. Live November listings and transactions completed or recorded in November are not necessarily from the same market cohort. A cleaner test would follow properties from their first advertised price through revisions and then match that history to the completed price where available.
 
Service charges deserve their own column rather than being treated as background detail. Two similar duplexes can present different overall costs to a buyer even if their asking prices look comparable. That may help explain why one moves quickly and another needs a reduction, but it still would not prove that service charges caused the whole 10.4% gap.
 
I’d be cautious about leaning too heavily on the service-charge explanation. Transaction volume matters first: a percentage based on a handful of completed deals can move sharply because of the particular properties sold. We need the counts behind both the 33 days and the 10.4%, plus some indication of how widely the results are distributed.
 
Adding the service-charge field raises another question: are we following the same property through its full history, or treating every refreshed advertisement as a new observation? A duplex listed at one price, withdrawn and returned lower could otherwise look like a quick sale with a modest discount.

I would build one row per property and retain the first listing date, every price change, final advertised price, completed price, condition, type, neighbourhood and monthly charge. Withdrawn and unsold stock should remain in the table. Otherwise a completed-sales-only sample will make both liquidity and speed look stronger than they were.
 
Yes, and days on market should run from the first listing, not from a refreshed advertisement. I would also preserve the date each observation was collected so later revisions do not silently rewrite November’s picture. Any relevant policy announcement or implementation date can be noted, but it should not be credited with a market move without enough post-change transactions.
 
The citywide framing is still the weak point for me. A duplex is not a uniform product across Bogotá, and mixing neighbourhoods can create an apparent discount simply because the completed-sales mix differs from the active-listing mix. Results should be shown separately for the areas actually tracked, with raw counts beside each figure.
 
Taken together, the evidence supports “possible selectivity,” not yet “market shift.” The next step is to rebuild the comparison using matched areas and property types, disclose the sample size, separate original from final asking prices, and retain the revision history. If the gap and faster movement of well-presented duplexes persist beyond the November 2025 snapshot, the seasonal-noise explanation becomes less convincing.
 
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