Chicago listings: the headline and the street-level picture [duplex]

[NiaRose]

The Chicago listings I saved are not moving together at all. They run from $488,000 to $732,000, mostly duplexes, and the typical listing in my sample has been visible for 70 days. Some disappear quickly while others sit.

My working theory is that very local supply explains much of the gap, but I may be combining properties that are not truly comparable. What are people seeing at street level, and which factors would you separate first?

 

[SimpleWall]

I would split the sample before drawing anything from the 70 days. Are these all the same kind of duplex, or are you mixing duplex condos with entire two-unit properties? Then narrow by neighbourhood boundary, condition and price band. Local supply matters, but only after the listings are genuinely competing for the same buyers.

 

[blueprint.solid]

What does “visible for 70 days” include: active listings only, or also pending, withdrawn and relisted stock? That distinction could change the picture. I would also compare each listing with recent completed sales nearby rather than treating the full $488,000–$732,000 bracket as one market.

 

[bram_bloom]

Seller motivation may be the missing variable. Two similar homes can follow different paths if one owner prices for a prompt sale and the other waits before making a cut. Note the date and size of each price change, not just total time listed. A stale listing that was reduced recently is in a different position from one holding firm for 70 days.

 

[SimpleWall]

Agreed on splitting the property types, though I am less convinced that supply is the main explanation. Condition can overwhelm the inventory count. A renovated place and one needing substantial work may share a postcode and asking-price range but attract buyers with very different budgets, financing options and tolerance for uncertainty.

 

[kai_cole]

Withdrawn stock is worth tracking separately. If owners remove homes rather than accept lower offers, active inventory can look tighter without showing stronger demand. I would compare the number of new listings entering each small area with the number going pending, selling, or being withdrawn over the same period.

 

[kai_cole]

A simple sheet could make this manageable: property subtype, small area, original ask, current ask, first-listed date, price-cut dates, condition, status and final sale price where available. Group listings by the week they first appeared. That avoids comparing a fresh listing with one that has already spent months testing the market.

 

[wide_yard]

I would not lean too heavily on completed sales alone. They reflect deals agreed earlier and may miss a recent change in buyer behaviour. Current competing listings and recent pending activity are useful alongside them. If several near-identical properties arrive at once, that matters even when the older completed sales still look healthy.

 

[OrlaIves]

Financing could also separate apparently similar duplexes. The buyer’s intended use and the property’s configuration may affect which options are available, so the pool of realistic buyers may not be equal across the sample. I would flag any listing where occupancy, condition or setup could complicate financing, then see whether those are concentrated among the stale homes.

 

[route.local]

The practical test seems to be three smaller comparisons rather than one Chicago-wide conclusion: like-for-like property type, genuinely local competing supply, and similar condition/financing profile. Then examine price-cut timing and withdrawals within each group. If the 70-day figure survives that sorting, it means more; if it breaks apart, the original sample was masking several different markets.