These census tracts had statistically significant high-hardship clustering in both 2013 and 2019. The pattern is not random: a Global Moran’s I of 0.693 confirms that hardship is spatially concentrated, not scattered. Tracts in this category share infrastructure deficits, limited employment access, and concentrated poverty that reinforce one another across neighborhood boundaries.

Implication: Individual-level interventions alone are unlikely to move the needle. Place-based, multi-sector investment is required.

Geographic Corridor: These tracts are primarily clustered in North and West Philadelphia, located in the central and southwest portions of the county.

These tracts were not significant hardship clusters in 2013 but became statistically significant by 2019, representing the spatial expansion of hardship beyond historically distressed cores. This is an early warning signal that hardship is spreading, not contained.

Displacement paradox: Some “improving” tracts nearby may be gentrifying, pushing lower-income households outward into these emerging clusters. Declining hardship scores do not necessarily mean existing residents are better off.

These emerging hot spots are forming at the boundaries of persistent hot spots in both North and West Philadelphia. Near North Philadelphia, located centrally within Philadelphia County, the emerging hot spots are forming in suburban areas. In both regions, hot spots are dissolving near the emerging hot spots, suggesting displacement-based gentrification could be occurring.

The majority of tracts improved over the decade-long window. However, aggregate improvement masks significant variation: 34.7% of tracts worsened over the same period. The data cannot distinguish genuine economic uplift from population turnover: a tract with a declining hardship index may simply have replaced lower-income residents with higher-income newcomers.

Data limitation: Before drawing conclusions from improving scores, ground-truth verification through community engagement and displacement tracking is essential. For example, gentrification has been an ongoing issue throughout Philadelphia county.

Target: 62 Persistent Hot Spot tracts (16.6% of all Philadelphia tracts): spatially concentrated, entrenched hardship confirmed by a Global Moran’s I of 0.693.

Recommendation: North Philadelphia accounts for some of the highest levels of hardship within the county. Census Tract 165, for example, had a hardship index of 1.417 in 2019, while Tract 175 had an index of 1.465. Because these are persistent hot spots, single program interventions aren’t likely to be sufficient; comprehensive community development is needed. Investing in Community-Based Education programs would prepare students for future careers while strengthening their sense of social responsibility and empowering the community.

Target: 7 Emerging Hot Spot tracts (2% of all Philadelphia tracts), new high-hardship clusters not present in 2013, signaling spatial expansion.

Recommendation: A significant number of properties in these emerging hot spots are being purchased by companies with the intention of renovating and reselling the property at a much higher price point, well above affordability for the average income in the area. Limiting the number of residential properties that a commercial entity can purchase in these areas each year would reduce the frequency at which this occurs. Additionally, housing stability initiatives for long time residents could take the form of rent or mortgage payment assistance, especially in times of higher than average unemployment.

Evidence base: 53.6% of tracts improved (2013→2023) but 34.7% worsened; Moran’s I = 0.693 confirms strong spatial clustering persists.

Recommendation: The trajectory map and mobility Sankey show that hardship in Philadelphia is actively shifting, with persistent high hardship clusters remaining entrenched while new high hardship areas emerge. Apparent improvements may reflect displacement rather than true improvement, making one-time analyses insufficient. Ongoing monitoring of housing cost burden, property ownership patterns, and displacement risk is needed to identify early-stage decline in new emerging hot spot areas. Because hardship is spatially clustered and driven by interconnected, structural factors, single sector interventions are unlikely to be effective. Coordinated strategies across housing, workforce development, education, and public health are necessary to respond to these dynamics and prevent further spatial expansion of hardship.

The baseline EHI consists of 3 measures: Poverty + Unemployment + Income (inv.)

Current index: 5-component EHI: Poverty + Unemployment + Income (inv.) + Food Insecurity (SNAP) + Transp. Disadvantage

Q1: What changed spatially?
Compare Hot Spot tract counts and cluster map patterns between your expanded index and the 3-component baseline. Did adding Food Insecurity (SNAP) + Transp. Disadvantage shift which tracts or corridors are flagged?

The expanded index flagged additional tracts in the southwest and central portions of the county as persistent hot spots. Some tracts considered dissolving or emerging hot spots by the 3-point index are shown to be persistent by the 5-point index. Under the 3-point index, 12.6% of Philadelphia County tracts are considered persistent high hardship, but when using the 5-point index it jumps to 16.6%. Additionally, while the 5-point index does show more persistent and emerging cold spots, especially in the northeast and south central parts of the county, it shows a total of 53.6% of tracts improving from 2013 to 2019, while the 3-point index shows 61.3% of tracts improving.

Q2: What stayed the same?
Which Persistent Hot Spot areas appear robustly across index specifications? What does consistency across different index compositions tell us about the reliability of hardship diagnoses in those tracts?

Persistent hot spot clusters remained in largely the same locations under both indexes, with only slight shifts in their boundaries. Persistent cold spots showed a similar pattern. This consistency suggests that, in general, hardship diagnoses across the county are a reasonably reliable method for identifying the most distressed and most advantaged areas, but that multiple indexes should be compared to establish cluster boundaries as accurately as possible.

Q3: Policy implications of index choice
If a policymaker targeted place-based investments using the baseline index versus your expanded index, would resource allocation differ? Name specific tracts or geographic corridors and argue which composition better captures the full burden of economic hardship for policy purposes.

While the persistent hot spot cluster in the center of the county is very similar between the two indexes, the southwest cluster appears far less significant when using the 3-point index. This could meaningfully affect resource allocation. Considering both indexes identify emerging hot spots on the borders of the southwest cluster, the 5-point index provides a more complete picture of early-stage hardship. It’s far more cost effective to address hot spots as they’re emerging, rather than waiting until they’ve become deeply entrenched and systemically reinforced. Using the 3-point index increases the risk of under-targeting this portion of the county.