High Economic Hardship Clusters (HH) — Hot Spot Tracts Statewide:
253
Low Economic Hardship Clusters (LL) — Cold Spot Tracts Statewide:
293
Tracts Improved (2013→2023)
58.4%
Tracts Worsened (2013→2023)
30.2%
Persistently High Hardship (2013–2023)
16.7%
Emerging Hot Spots (2013–2023)
2.7%
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 0.697 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: Persistent hot spot tracts are concentrated in the Phoenix corridor, particularly across Phoenix, Glendale, Tempe, as well as some areas Mesa. These are clustered together and surrounded by emerging hot spot activity, reinforcing the persistence of concentrated disadvantage across neighboring communities.
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.
Emerging Locations: Emerging hot spots are forming around the edges of the Phoenix corridor, particularly in areas surrounding Phoenix, Glendale, Tempe, and extending toward Mesa. These clusters appear to be expanding outward from historically disadvantaged neighborhoods, which suggests that rising housing costs, redevelopment, and displacement pressures may be pushing hardships and lower-income households into nearby tracts.
The majority of tracts improved over the decade-long window. However, aggregate improvement masks significant variation: 30.2% 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.
County Context: In Maricopa County, many improving tracts appear near persistently stable and higher-income areas such as Gilbert, Chandler, and Scottsdale. These areas are represented by the concentration of persistent cold spots on the map. At the same time, worsening and emerging hardship patterns around Phoenix, Glendale, Tempe, and Mesa suggest that some improvement may reflect displacement rather than true economic improvements. Rising housing costs and redevelopment pressures in Phoenix areas may be pushing lower-income households outward, contributing to uneven patterns of progress across the county.
Target: 149 Persistent Hot Spot tracts (16.7% of all Maricopa tracts): spatially concentrated, entrenched hardship confirmed by a Global Moran’s I of 0.697.
Persistent hot spot tracts are concentrated in the Phoenix corridor, particularly across Phoenix, Glendale, Tempe, and extending toward Mesa, where hardship is deeply embedded despite the county’s overall EH Index of -0.168. The high Moran’s I of 0.697 indicates strong spatial clustering, meaning these neighborhoods are not isolated and are part of a system of disadvantages. According to Galster and Tatian (2009), targeted place-based housing and neighborhood investment strategies, such as rehabilitating existing housing stock and expansion of affordable homeownership opportunities, can help stimulate stable market activity while avoiding rapid displacement. The Housing and Community Development (HCD) Division of the Maricopa County Human Services Department could lead the intervention that focuses on improving housing quality, neighborhood infrastructure, or access to credit in these corridors in order to disrupt long-term hardship while still managing the risks associated with rising property values. References Galster, G., & Tatian, P. (2009). Modeling housing appreciation dynamics in disadvantaged neighborhoods. Journal of Planning Education and Research, 29(1), 7–22.Target: 23 Emerging Hot Spot tracts (2.7% of all Maricopa tracts), new high-hardship clusters not present in 2013, signaling spatial expansion.
Emerging hot spot tracts are clustering around the existing persistent hot spots in the Phoenix and Mesa areas, mainly along the outer edges. This suggests there is an outward spatial expansion rather than isolated new areas of hardship. Galster and Tatian (2009) discuss how similar patterns are associated with spatial spillover dynamics where neighborhood change spreads across adjacent tracts and can signal early stages of market transition. An early-intervention strategy should therefore focus on continuous monitoring of these edge-adjacent tracts for accelerating price changes and shifts in borrower profiles, since these leading indicators can help identify where hardship clustering is expanding before it fully consolidates. References Galster, G., & Tatian, P. (2009). Modeling housing appreciation dynamics in disadvantaged neighborhoods. Journal of Planning Education and Research, 29(1), 7–22.Evidence base: 58.4% of tracts improved (2013→2023) but 30.2% worsened; Moran’s I = 0.697 confirms strong spatial clustering persists.
TODO: Using the trajectory map and mobility Sankey, make a forward-looking data-monitoring or cross-sector coordination argument.
**The results point to a system that is changing but not redistributing evenly. Even though 58.4% of tracts improved between 2013 and 2023, the strong Moran’s I (0.697) show that both improvement and decline are geographically clustered instead of randomly spreading. The trajectory map reinforces this long-standing spatial inequality as persistent hot spots around Phoenix, Glendale, Tempe, and Mesa remain tightly grouped, while persistent cold spots cluster in Gilbert, Chandler, and parts of Scottsdale.*
The Sankey diagram shows that most mobility is concentrated in the middle quintiles, Q3 and Q4. However, Q1 and Q5 show relatively low movement and strong persistence. This suggests that change is happening at the margins of neighborhoods with moderate conditions and extreme conditions are harder to move, as they either stay highly advantaged or highly disadvantaged. This supports a forward-looking monitoring and coordination strategy that focuses on transition zones around persistent clusters instead of treating tracts like isolated units. Because mobility is concentrated in Q3 and Q4, and spatial clustering remains strong, agencies should build a cross-sector systems that include housing, education, public health, and economic development to track these mid-quintile and additional boundary tracts for early signals of either upward movement into opportunity or downward movements into persistent hardship.The baseline EHI consists of 3 measures: Poverty + Unemployment + Income (inv.)
Current index: 5-component EHI: Poverty + Unemployment + Income (inv.) + Low Ed. Attainment + Food Insecurity (SNAP)
After adding your extra component(s), answer the following (minimum 2 sentences each):Q1: What changed spatially?
Compare Hot Spot tract counts and cluster map patterns between your expanded index and the 3-component baseline. Did adding Low Ed. Attainment + Food Insecurity (SNAP) shift which tracts or corridors are flagged?
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?
The most robust persistent hot spots across both index specifications remain concentrated in the core urban corridors of Phoenix, Glendale, Mesa, and Tempe. These locations consistently appear as high-hardship clusters in both the 3-component and 5-component indices, even though the 5-component model slightly reclassifies some surrounding tracts into emerging rather than persistent hot spots. The overall geographic boundaries of these clusters remain largely stable, with only minor expansion on the western edge of Glendale and some local reclassification effects. This consistency across index specifications suggests that these areas are not random when it comes to configuring how hardship is measured. Instead, the consistency reflects deeply entrenched and structurally persistent disadvantages. In other words, even when additional dimensions like education and food insecurity are added, the same corridors remain identified as high-hardship zones, reinforcing the reliability of these measures and indicating that these tracts represent long-term, multi-dimensional factors of socioeconomic stress. Q3: Policy implications of index choiceIf 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.
If a policymaker used the 3-component baseline instead of the 5-component expanded EHI, resource allocation would shift modestly but meaningfully at the margins rather than completely changing core target areas. Both indices consistently prioritize the main urban hardship corridor across Phoenix, Glendale, Mesa, and Tempe, so major funding would still concentrate in these regions. However, the expanded index redistributes which specific tracts along transition zones within those corridors are prioritized. For example, Census Tract 3184 and 4212.01 are classified as high hardship in the baseline but lose HH status in the expanded index, meaning they could be deprioritized under a more multidimensional measure. In contrast, Census Tract 1125.10 and 820.08 only appear as HH in the 5-component index, suggesting they would newly receive attention when education and food insecurity are included. These shifts are highly visible in north Phoenix, the west side of Glendale, and parts of the Mesa corridor, where some tracts move from persistent to emerging hot spots or cross the HH threshold entirely. Overall, the expanded index better captures the full burden of economic hardship because it adds education and food insecurity, which identify vulnerabilities not fully reflected in income, unemployment, and poverty alone. This makes it more appropriate for policy purposes, since it reduces the risk of overlooking structurally disadvantaged tracts that may not appear severely deprived under income-based measures alone.