Economic Hardship Across U.S. Counties
Economic Hardship (EH) Rankings — Arizona Counties
All Arizona Counties vs. U.S. Extremes
Economic Hardship Index: All Arizona Census Tracts (2023)
Decomposing the Economic Hardship Index
Economic Hardship Clusters (LISA)
Within-County Variation in Economic Hardship (EH) — All 15 Arizona Counties

High Economic Hardship Clusters (HH) — Hot Spot Tracts Statewide:

244

Low Economic Hardship Clusters (LL) — Cold Spot Tracts Statewide:

254

Economic Hardship Mobility: Maricopa Tracts (2013 → 2023)
Neighborhood Hardship Trajectories (2013–2019)

Tracts Improved (2013→2023)

57.5%

Tracts Worsened (2013→2023)

31.7%

Persistently High Hardship (2013–2023)

17.8%

Emerging Hot Spots (2013–2023)

2.8%

🔴 Areas of Persistent Concern
158 Persistent Hot Spot Tracts (17.8% of Maricopa tracts)

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 0.65 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.]

The 158 persistent hot spot tracts (17.8%) in Maricopa County are mainly concentrated in the south-central Phoenix corridor, including South Phoenix and parts of west Phoenix. These areas have remained statistically significant clusters of high hardship in both 2013 and 2019, which is supported by Global Moran’s I of 0.65, indicating high spatial clustering. This means hardship is not randomly distributed but concentrated in specific neighborhoods. These tracts typically align with higher poverty rates (often above the county average of 11.7%), lower median incomes, and limited access to jobs and infrastructure, reinforcing long-term disadvantage.

🟡 Early Warning Signals
24 Emerging Hot Spot Tracts (2.8% of Maricopa tracts)

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 24 emerging hot spot tracts (2.8%) are mostly forming along the outer edges of the urban core, particularly in Tempa and Mesa. These areas were not clustered in 2013 but became significant by 2019, showing that hardship is spreading outward. This pattern may be occuring because of rising housing costs in central areas pushing lower-income households into more affordable peripheral areas. For example, Maricopa County has a 34.4% renter burden rate, suggesting housing affordability pressures that may be driving this shift. Even though the percentage is small, it signals the early stages of spatial expansion of hardship.

🟢 Signs of Progress Read With Caution
57.5% of Maricopa tracts showed EHI improvement (2013→2023)

The majority of tracts improved over the decade-long window. However, aggregate improvement masks significant variation: 31.7% 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.

[TODO: Customize with your county’s specific context.]

While 57.5% of tracts improved between 2013 and 2023, a significant 31.7% of tracts worsened, showing uneven progress across the county. The Sankey diagram also shows that many tracts remain in the same hardship quintiles over time, especially those in Q4 and Q5. This suggests that improvement is not evenly distributed. Additionally, Maricopa’s EH index only improved slightly (from -0.211 to -0.145 after adding variables), indicating that underlying hardship still exists despite overall gains. This highlights the importance of verifying improvements with community-level data.

Recommendation 1

Target: 158 Persistent Hot Spot tracts (17.8% of all Maricopa tracts): spatially concentrated, entrenched hardship confirmed by a Global Moran’s I of 0.65.

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.

The south-central Phoenix corridor should be prioritized for investment since it contains the majority of the 158 persistent hot spot tracts (17.8%). These areas consistently fall into the highest hardship categories (Q4–Q5) and are supported by a strong clustering value (Moran’s I = 0.65). A coordinated effort led by Maricopa County and the City of Phoenix should focus on place-based strategies such as expanding affordable housing, improving public transit access, and increasing workforce development programs. Given that these tracts have remained high hardship across multiple years and index versions, long-term, multi-sector investment is necessary rather than short-term solutions.

Recommendation 2

Target: 24 Emerging Hot Spot tracts (2.8% 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.

The 24 emerging hot spot tracts (2.8%) in west and southwest Maricopa County should be treated as early warning areas. These clusters likely reflect displacement from central Phoenix, especially given the county’s 34.4% renter burden and rising housing costs. To prevent these areas from becoming future persistent hot spots, local governments should implement early interventions such as rent stabilization policies, affordable housing incentives, and real-time monitoring of housing and hardship trends. Addressing these areas early is critical since the data already shows an increase in worsening tracts (31.7%).

Recommendation 3

Evidence base: 57.5% of tracts improved (2013→2023) but 31.7% worsened; Moran’s I = 0.65 confirms strong spatial clustering persists.

TODO: Using the trajectory map and mobility Sankey, make a forward-looking data-monitoring or cross-sector coordination argument.

Although 57.5% of tracts improved, the fact that 31.7% worsened and 17.8% remained persistently high hardship shows that inequality is still strongly embedded spatially. The trajectory map and Sankey diagram highlight that many tracts remain stuck in high-hardship categories over time, reinforcing the Moran’s I of 0.65. Moving forward, policymakers should adopt continuous monitoring systems, such as annual updates to the hardship index, and improve coordination across sectors like housing, public health, and transportation. A shared regional data system would help determine whether improvements reflect real economic mobility or displacement patterns.

🔬 Index Sensitivity Reflection

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

Current index: 5-component EHI: Poverty + Unemployment + Income (inv.) + Renter Burden + 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 Renter Burden + Food Insecurity (SNAP) shift which tracts or corridors are flagged?

[TODO: Describe what changed in the spatial cluster map and Hot Spot tract counts after adding your component. Be specific cite numbers and identify geographic areas.]

In context of Maricopa county, after adding renter burden and food insecurity to the index, the share of tracts that improved dropped from 63.9% to 57.5%, while those that worsened increased from 29.4% to 31.7% indicating the expanded index captures additional hardship. Spatially, new hot spots appear in areas like Sun City and Surprise in the northwest, as well as around Tempe and just north of Phoenix’s downtown core. In broader context of Arizona state, hot spots increased from 201 to 244 and northwest, west and mid-eastern areas doing better while metropolitian areas like Phoenix, Tucson and Tempe picking up more hot spots. These shifts suggest that hardship is no longer confined to traditional inner-city areas but is spreading into suburban and transitional neighborhoods, likely driven by rising housing costs and cost-of-living pressures. Maricopa’s EH index also increased from -0.211 to -0.145, reinforcing that overall measured hardship rises when these additional factors are included.

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?

[TODO: Identify which Persistent Hot Spot corridors remained flagged regardless of index composition. Explain what this robustness tells us about entrenched hardship in those areas.]

The area around the south-central Phoenix corridor, Glendale area and eastern Maricopa county (Tempe and Mesa) remained a persistent hot spot across both versions, with about 158 tracts (17.8%) consistently identified. The strong clustering (Moran’s I = 0.65) also did not change, reinforcing that hardship is spatially concentrated. For broader Arizona, northeastern areas predominantly indian reservation remained in the hot spot. This consistency across different index specifications increases confidence that these areas are truly disadvantaged and not just sensitive to how the index is constructed.

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.

[TODO: Compare resource targeting under each index. Argue which composition is more appropriate for policy, citing specific tracts or neighborhoods and the dimension of hardship your added component captures.]

Using the baseline index (poverty, unemployment, and income) would likely focus resources mainly on historically disadvantaged areas like central and south Phoenix. However, the expanded index shifts some attention toward newer areas of concern, particularly in the western and southwestern parts of the county, where housing cost burden and food insecurity are more prominent. For example, even though Maricopa County ranks relatively low in hardship statewide (around 14th out of 15 counties after expansion), the added variables reveal more localized stress that the baseline index misses. Also, Overall, the expanded index provides a more complete picture of hardship and is better suited for policy because it captures both traditional economic disadvantage and newer cost-of-living pressures, leading to more targeted interventions.