High Economic Hardship Clusters (HH) — Hot Spot Tracts Statewide:
267
Low Economic Hardship Clusters (LL) — Cold Spot Tracts Statewide:
269
Tracts Improved (2013→2023)
53.7%
Tracts Worsened (2013→2023)
31.1%
Persistently High Hardship (2013–2023)
17.8%
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 0.684 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.
[TODO: Identify the specific geographic corridor in your county where these tracts are concentrated.]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.
[TODO: Identify where emerging hot spots are forming in your county and what may be driving displacement.]The majority of tracts improved over the decade-long window. However, aggregate improvement masks significant variation: 31.1% 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.
[TODO: Customize with your county’s specific context.]Target: 158 Persistent Hot Spot tracts (17.8% of all Maricopa tracts): spatially concentrated, entrenched hardship confirmed by a Global Moran’s I of 0.684.
TODO: Write your first recommendation. Name the specific geographic corridor, cite the hardship index values, and propose a concrete place-based intervention with a named responsible entity.
For this recommendation we will be focusing on a few census tracts in the Mesa area. These tracts are all concentrated in the same area: 4213.02, 4214, and 4215.01. Economic hardship increased from 2013 to 2019 in all 3 tracts. The first increased from 0.942 to 1.414, the second increased from 1.229 to 1.387, and the third increased from 1.04 to 1.11. Because these are all persistent hot spots that experienced an increase in hardship, we would want to implement a comprehensive community development approach. This includes things like housing, econmic development, schools, and health. Place-based examples housing initiatives for displaced residents, specific entities providing intervention include House of Refuge in southeast Mesa. This organization provides housing for those experiencing homelessness.Target: 24 Emerging Hot Spot tracts (2.7% of all Maricopa tracts), new high-hardship clusters not present in 2013, signaling spatial expansion.
TODO: Reference the displacement paradox, identify where these clusters are forming, and propose an early-intervention or monitoring strategy.
For emerging hot spots, we want to focus on prevention. The emerging hot spots I am reporting on are all adjacent to the persistent hot spots that I mentioned in the policy brief above. We can specifically see an increase in econmic hardship in an emerging hotspot in census tract 4210.02 when the index increased from 0.52 to 0.989. Because we want to focus on prevention we want to consider interventions such as small business lending, proactive tenant protection, and code enforcement. Protecting residents with initiatives like Caring Transitions of Mesa East can help residents who may be experiencing potential displacement due to neighboring gentrification, this initiative is specifically for seniors. The displacement paradox coincides with emerging hot spots. What makes it a paradox is that if more money is put into the census tract, this may cause existing residents to be displaced (into areas of emerging hot spots) as the potential for gentrification increases in neighboring areas, such as tract 427.05 (an emerging cold spot).Evidence base: 53.7% of tracts improved (2013→2023) but 31.1% worsened; Moran’s I = 0.684 confirms strong spatial clustering persists.
TODO: Using the trajectory map and mobility Sankey, make a forward-looking data-monitoring or cross-sector coordination argument.
In terms of data-monitoring for the future, we want to specifically pay attention to mesa where there are several emerging hot spots as well as paying attention to areas of persistent hardship which is far more widespread throughout the Phoenix area, especially in the central and south portion of the valley. Public sector entities that need to work together in terms of intervention for persistent areas and prevention for emerging areas include: Arizona Department of Health and Human Services and the Department of Economic Security. Both of these can work together to provide comprehensive health education in addition to food security, medical assistance, and all of the other services DES provides. In addition, private sector entities like banks can work with businesses in terms of loan lending for emerging hot spot areas. When looking at the sankey diagram, out of all of the hardship areas, 1 tract moved from Q4 to Q1 and 6 tracts from Q4 to Q2 (low hardship). Most tracts remained in their hardship category with some moving to stable from Q4 to Q3 (38). If any hardship areas are to be analyzed in terms of monitoring improvement, we may want to focus on the tracts I just listed to see if there are any interventions that could be used in other hardship areas. Many thick bands are evident between the Q4 and Q5 areas indicating persistent hardship between the groups. These areas need focused multi-tiered community development and intervention.The baseline EHI consists of 3 measures: Poverty + Unemployment + Income (inv.)
Current index: 7-component EHI: Poverty + Unemployment + Income (inv.) + Renter Burden + Low Ed. Attainment + Food Insecurity (SNAP) + Transp. Disadvantage
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 Renter Burden + Low Ed. Attainment + Food Insecurity (SNAP) + Transp. Disadvantage shift which tracts or corridors are flagged?
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?
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.