Are Lima coastal homes really taking 99 days to find a buyer?

F

FairView

First-time buyer
I reviewed this month’s Lima coastal-home listings between PEN 1,335,000 and PEN 2,002,000. The homes still advertised have been on the market for roughly 99 days on average, with many of the longer-running cases appearing to need maintenance.

Is that a fair picture of buyer demand, or is the active sample skewed because quicker sales have disappeared? I’m especially interested in recent completed sales, withdrawn stock and when price cuts occurred.
 
The active sample is almost certainly skewed toward slower listings. Your 99 days measures the age of homes still online, not necessarily how long a typical completed sale took. I’d follow one group of listings over time and separate completed, withdrawn and still-active homes. Otherwise a withdrawal can look like continued inventory or simply vanish without explaining why.
 
How tightly have you drawn the neighbourhood boundaries? “Coastal Lima” may combine areas that buyers do not treat as substitutes. I’d also split condition into more than maintained versus needs work. A dated but usable home could behave differently from one requiring substantial work. And are you counting total listing age through price cuts, or only time since the latest asking price?
 
I wouldn’t conclude that maintenance explains most outliers yet. Financing can slow a buyer even when the property itself is sound, while an unmotivated seller may leave an ambitious price online for months. Price-cut timing should help distinguish those cases: a long delay before the first reduction says something different from repeated reductions followed by a deal.
 
Agreed on seller motivation, though it may be difficult to observe directly. One useful proxy could be whether the asking price changes while the listing description and condition remain the same. I’d also want new-listing volume for this month. If supply rose suddenly, the active pool could become younger or older without any meaningful change in completed-sale speed.
 
A simple table would make this clearer. Give each property its first-seen date, neighbourhood, initial and current asking prices, visible condition, and latest status: active, completed or withdrawn. Keep relisted homes linked where you can identify them rather than treating every appearance as new. Then compare the median as well as the average; a handful of stubborn listings may be pulling that 99-day figure upward.
 
That helps. I was treating the 99 days too much like a completed-sale timeline when it is really the age of the remaining inventory. I’ll rebuild the sample by narrower neighbourhood boundaries, preserve the original listing date through price changes, and separate completed deals from withdrawals. I’ll also avoid assigning maintenance as the cause unless the pricing history supports it.
 
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