Phoenix apartments: are fees really causing the long listing times?

anika_vale

Real estate agent
Established
I have compared asking prices and visible marketing periods in our preferred parts of Phoenix, but I still cannot tell whether the 102-day figure reflects costs, condition or repeated relisting.

We are searching mostly for apartments between $772,000 and $1,158,000 in two neighbourhoods. Monthly service charges initially looked like the clearest explanation for why some properties move and others linger, although a citywide average may be disguising major differences between buildings.

Before widening the search, I want to compare recent completed sales with withdrawn stock, price reductions and property condition at building level. Should the monthly charge be assessed mainly against the final sale price, or against what it actually covers and any building-specific financing risk? I would also welcome a way to identify relisted properties so they do not distort the marketing-time comparison.
 
Your theory is plausible, but 102 days of listing visibility does not necessarily equal 102 days with a motivated seller. Some properties may have been withdrawn, relisted or left at an aspirational price.

I’d start with completed sales in each building or its closest comparable buildings. Compare the monthly charges, condition and final sale price, then note when unsuccessful listings first reduced their asking price.
 
Which two neighbourhoods, and how tightly have you drawn their boundaries? A few streets can change the comparison, especially if your sample mixes different building types.

Also, by “apartments” and “service charges,” do you mean condos with HOA dues? If so, compare what those dues cover rather than treating the monthly figure alone as the deciding factor. Buyer financing may also vary by property or building.
 
I’m not convinced the charges explain most of the gap. They are easy to spot in a spreadsheet, while condition and seller motivation are harder to quantify. A dated property with no early price adjustment can sit even if its recurring costs look reasonable.

The useful missing detail is new-listing volume. If fresh alternatives keep appearing, older listings may need a meaningful reduction before buyers reconsider them.
 
I’d make a separate table for each neighbourhood, then split it again by building and condition. Track original price, current price, first reduction date, days visible, monthly charges, withdrawn status and any completed sale you can reasonably match.

After that, ask agents about the sellers behind the longest-running listings: are they genuinely trying to move, or merely testing the market? Treat the answers cautiously, but motivation could explain why apparently similar properties behave differently.
 
Nadia’s approach should expose whether 102 days is a market pattern or an artefact of the sample. I’d add one column for financing-related differences and another for what the recurring charges include.

The main caution is not to force a single explanation across both neighbourhoods. One may be driven by building costs, while the other is simply carrying overpriced or poorly presented inventory. Closed sales and withdrawn properties should help distinguish those cases.
 
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