I pulled a small Madrid sample priced from €482,100 to €723,100. Median marketing time is about 111 days, but condition makes the average noisy. The sheet says four-bed while several entries are tagged warehouse/property, so classification may also be distorting the reported 8.1% movement. Do buyers negotiate over energy performance, or just skip the listing?
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Madrid sample: is the 8.1% rise meaningful, and does energy performance affect offers?
- Thread starter grain.brisk
- Start date
Is the 8.1% based on asking prices or completed sales? If it is listing movement, withdrawn stock and reductions could make the direction look stronger than the actual market.
solid_chart
First-time buyer
Also split the 111 days by condition. A median for renovated and work-heavy properties together may describe neither group particularly well.
TrueBlueprint
Real estate agent
I would not assume buyers simply move on. A motivated buyer may negotiate, while a buyer already stretched by financing may avoid uncertain improvement costs altogether.
grand_beam
Landlord
Neighbourhood boundaries could be doing as much work as condition. A small Madrid sample can change character quickly if one boundary includes a different type of building or buyer.
Freja’s question is the key one. I’d build separate columns for original asking price, latest asking price, completed price where available, withdrawal, condition and energy information. Then the 8.1% can be interpreted rather than repeated.
neat_creek
Landlord
Exactly. No information may create uncertainty, whereas clearly weak performance gives a buyer something specific to price. Those are different behaviours even if both extend marketing time.
liv_equity
Seller
Seller motivation matters too. An energy-related offer reduction only tells you about demand if the seller had a realistic reason to accept it.
By the time a buyer is deciding whether to offer, energy performance may already have become a price issue rather than just a search filter. In the €482,100–€723,100 range, someone who sees obvious work ahead may reduce the offer to preserve a renovation budget. Whether that tells us much about demand still depends on the seller’s willingness to negotiate and the property’s wider condition.
Both can be true: some buyers disappear before viewing, and the remaining buyers negotiate. Listing data mostly shows the second group, so the first effect is easy to miss.
The useful comparison would be enquiry-to-viewing behaviour, but absent that, time to first price cut might provide a limited clue. It still would not isolate energy from presentation and initial pricing.
fair_field
Homeowner
Do you know whether 111 days is measured from first publication or the latest relisting? Relisted property can look fresh while having a much longer exposure history.
avery.drew
Seller
Another complication is new-listing volume. If more good-condition stock arrived during the period, weaker properties could remain available longer without buyers consciously negotiating on energy.
I would first remove any warehouses if the intended question is four-bedroom homes. If warehouses are intentional, then remove the bedroom framing. Mixing them makes every later conclusion fragile.
Agreed on classification, but don’t discard the odd entries silently. Keep them in a separate group; the tagging error itself may explain why the headline movement looks unusual.
A clean first pass could have three groups: confirmed four-bedroom homes, confirmed warehouses, and unresolved property records. Only calculate movement and marketing time for the confirmed groups.
Then compare energy information within each condition group, not across the whole sample. Otherwise poor-condition stock will make energy look more influential than it may be.