Housing Stability Score
2
/100
Composite Score • Higher is stronger
Scores use a consistent four-component framework built from public, reproducible data sources.
Housing-first durability lens
U.S. Housing Stability Intelligence
City Profile
Fullerton profile describes structural housing sustainability conditions for local residents using standardized national methodology.
Housing Stability Score
2
/100
Composite Score • Higher is stronger
Scores use a consistent four-component framework built from public, reproducible data sources.
Housing-first durability lens
Trend Direction
Stable
Trend direction compares this snapshot with the prior published score; movement within three points is treated as stable.
Media Summary
Fullerton, CA currently has a 2 / 100 Housing Stability Score with a stable trend signal. The score is a structural housing sustainability measure, not a forecast of future prices.
Citation Language
Fullerton, CA has a 2/100 Housing Stability Score (highly pressured), 2/100 national percentile, and 0 point change versus the prior published snapshot.
Housing Stability Score
2
Highly pressured relative housing sustainability score on a 0-100 scale.
National Rank
#30,694 of 30,973
Same-state rank: #1,428 of 1,598. Higher scores indicate stronger relative stability.
Score Movement
0
Point change versus the prior published score snapshot.
Leading Signal
Supply Pressure
Highest component score in the four-part housing stability framework.
These drivers summarize the main score movement, strongest support, and clearest pressure point for this location.
Score Driver
The composite score moved 0.0 points versus the prior published snapshot, which is within the stable range for this methodology.
Component Driver
Supply pressure is the strongest component at 24 / 100, so it contributes the most support to the current housing stability score.
Component Driver
Market volatility is the main constraint at 2 / 100, so users should read that component as the clearest pressure point in this location.
Score Driver
This score uses 10 observed local inputs and 4 inherited county inputs out of 14 model inputs; 0 inputs are filled from comparable benchmarks when direct observations are unavailable.
Every location includes standardized component evaluation so cross-location comparison stays structurally consistent.
Affordability Stability
Evaluates whether housing costs align sustainably with local income over time using rent burden, price-to-income, and cost growth relative to wages.
Component Score: 4 / 100
State: 35 / 100 percentile (below-average relative stability)
National: 4 / 100 percentile (low relative stability)
Market Volatility
Measures housing price consistency and resistance to boom-and-bust cycles that can destabilize long-term resident outcomes.
Component Score: 2 / 100
State: 3 / 100 percentile (low relative stability)
National: 2 / 100 percentile (low relative stability)
Supply Pressure
Tracks whether housing availability keeps pace with demand through inventory, construction pace, and local supply balance conditions.
Component Score: 24 / 100
State: 36 / 100 percentile (below-average relative stability)
National: 24 / 100 percentile (below-average relative stability)
Ownership Sustainability
Assesses long-term ownership viability through expense escalation, tax burden pressure, insurance overlap, and distress indicators.
Component Score: 6 / 100
State: 31 / 100 percentile (below-average relative stability)
National: 6 / 100 percentile (low relative stability)
State Comparison
State benchmark: 12 / 100 percentile (higher is more stable), placing this location below most comparable places in this state.
National Comparison
National benchmark: 2 / 100 percentile (higher is more stable), placing this location below most comparable places nationwide.
Scoring uses public, reproducible county-level datasets including ACS, BLS LAUS, FHFA HPI, and Census housing estimates, applied through the same framework across affordability stability, market volatility, supply pressure, and ownership sustainability.
Snapshot Date: 2024-12-30 • Data Update Status: Succeeded • 2026-05-08 21:30 UTC
City coverage combines local city observations with county-level inherited signals when direct city series are unavailable.
Observed Local
10
Inherited Inputs
4
Imputed Inputs
0
Coverage Share
100%
Total model inputs this run: 14