Mexico City: are 73-day listings stale, or is my sample mixing markets?

P

paper.round

Buyer
The mix of homes in my notes has raised a bigger question: does the 73-day figure mean anything when many of the properties are country homes grouped under Mexico City?

Asking prices run from MX$4,392,000 to MX$6,588,000. I want to distinguish sellers who are ready to negotiate from homes that have lingered because of location, condition, building reserves or financing difficulties. Has anyone tracked an original asking price through reductions, withdrawal and eventual sale? It would also help to know whether financed buyers are completing at a different pace from cash buyers.
 
Seventy-three days alone cannot tell you much if withdrawn and relisted properties appear new again. I would compare the original listing date, any price changes and the eventual completed price. Otherwise quick sales and vanished listings get mixed together.
 
What does “Mexico City” cover in your notes? Country homes could sit in very different submarkets from urban houses, even when portals group them under the same broad location. Commute time and the exact neighbourhood boundary may explain more than seasonality.
 
I’m also unsure about the reserves theory. It makes sense where homes share buildings or managed facilities, but less so for a standalone country home. Condition, unfinished work and whether buyers can finance the property may be the more useful split.
 
I wouldn’t accept seasonality as the main answer without seeing when new-listing volume rose. A 73-day typical exposure could simply reflect sellers holding ambitious prices while motivated, correctly priced properties disappear quickly.
 
Build a small table with neighbourhood, property type, condition, first-seen date, latest price, withdrawal date and commute time to the destination that matters to you. Leave completed price blank unless it can be confirmed. That should expose where the sample is mixing unlike homes.
 
Kai’s boundary question is important. Even two listings described with the same broad location may offer completely different daily journeys. Are your commute notes based on distance, a map estimate, or actual travel at the hours you would use the route?
 
One more complication: listing age is not necessarily seller age. A home can change agent, disappear briefly or return with different photos. I’d keep “first observed” separate from the current advertisement’s stated age.
 
Seller motivation may be the missing variable. An occupied home with no urgency can sit at an aspirational number, while another seller accepts movement quickly. Price-cut timing is useful: a reduction after little interest means something different from repeated small edits.
 
Agreed, though cuts can also be cosmetic. I’d record the percentage change from the first observed price rather than just counting reductions. More importantly, compare properties that are genuinely substitutable for a buyer; the full MX$4,392,000–MX$6,588,000 bracket may be too broad for one conclusion.
 
Does your sample record whether properties are habitable now? “Country home” can hide a large condition range. A cheaper property needing substantial work may remain visible because buyers are comparing total cost and disruption, not merely the asking price.
 
A useful test would be to freeze today’s active group and revisit it rather than continually adding fresh listings. Mark each one as still active, reduced, withdrawn or apparently completed. That avoids the sample changing underneath the 73-day figure.
 
I’d also separate cash-sensitive issues from physical condition. Financing delays or uncertainty can shrink the buyer pool even when a house looks fine. You do not need to assume why; just note whether the listing or agent indicates restrictions and verify anything important independently.
 
Sam’s fixed cohort would help with the seasonality claim. If new supply arrives but the older cohort remains, that points toward pricing or property-specific friction. If both enquiries and completions shift together, seasonality becomes more plausible—but the present notes cannot distinguish those stories.
 
Don’t treat every withdrawal as a failed sale. Some may return, some may be taken off for reasons unrelated to demand, and some could have completed without a visible result. Keep “withdrawn” as its own outcome instead of quietly classifying it as sold or unsold.
 
For an actual purchase decision, I’d narrow this to three to five realistic alternatives. Visit at the relevant commute time, compare condition, ask when each was first marketed and request the history of asking-price changes. The broad market question is less useful than knowing why those specific homes remain available.
 
And for properties with shared management, ask about reserves and planned work rather than inferring strength from a single figure. For standalone homes, redirect that attention to maintenance and access. The original theory may explain part of the sample, but it cannot sensibly explain all of it.
 
There is also a negotiation trap here: an old listing does not guarantee a flexible seller. Time on market becomes leverage only when paired with evidence of motivation—vacancy, meaningful reductions or a stated timeline. Otherwise the seller may simply continue waiting.
 
The emerging answer seems to be that 73 days is a prompt for investigation, not a market verdict. Split the homes by precise area, commute, condition, financing suitability and shared-management exposure; then track cuts and withdrawals in a fixed cohort. That should reveal whether you have stale stock or several different markets bundled together.
 
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