ZIP 17002 Foreclosure, Tax-Lien & Distress Report
Huntingdon County, Pennsylvania · High Vacancy market
Huntingdon County, Pennsylvania's ZIP 17002 registers 19/100 composite distress, which DLRadar reads as low. The most distinctive pressure shows up in construction/permit lag (66/100), structural risk (43/100), institutional ownership (13/100). institutional ownership (13/100) and mortgage stress (9/100) stay muted. Structural exposure scores 43 and live distress 3 on the 0–100 scale.
Prices here sit in a expansion phase: values rose 5.5% over the trailing year, at 32/100 phase confidence. Even climbing markets leave specific parcels in distress; the scoring isolates them.
505 residents call 17002 home, typically aged 34. Home values center near $180,300, an affordability ratio of 2.5× — accessible. Educational attainment sits at 9% bachelor's-or-above. Vacancy runs 18.7%, above the national norm and a classic distress-and-opportunity signal. Median household income is $71,157, near the U.S. median near $78,000. 12.0% of residents fall below the poverty threshold. Owners hold 84% of homes, renters 16%. Rent burden reaches 26% of tenant households. There are about 183 housing units across 17002. DLRadar's demographic-stress index for the area reads 28/100.
Taken together, 17002 profiles as an active-distress market where motivated-seller and below-market acquisitions concentrate. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.
Distress signal breakdown — ZIP 17002
Tax delinquency, institutional ownership, insurance pressure, NFIP/flood, construction lag, price dislocation and auction velocity — plus the 0 individual distressed properties (owner, address, APN, per-property score and exit read) are in the full DLRadar report.
ZIP 17002 Stress Report snapshot
Live ZIP-level distress, market-phase, housing and bank-pressure read — the same report attached to every property.
Nearby ZIPs in Huntingdon County
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Deterministic. Every signal traces to a public dataset · methodology