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:

253

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

293

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

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%

🔴 Areas of Persistent Concern
149 Persistent Hot Spot Tracts (16.7% 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 0.697 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.

[TODO: Identify the specific geographic corridor in your county where these tracts are concentrated.]
🟡 Early Warning Signals
23 Emerging Hot Spot Tracts (2.7% 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.]
🟢 Signs of Progress Read With Caution
58.4% of Maricopa tracts showed EHI improvement (2013→2023)

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.

[TODO: Customize with your county’s specific context.]
Recommendation 1

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.

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.

[Based on the ‘Neighborhood Hardship Trajectories (2013 - 2019), the persistent hot spots appear to be predominantly located around Phoenix and Glendale areas, as evidenced by the positive hardship index values for the tracts in that sphere. Given that these tracts remain hot spots over time, it is indicative that these neighborhoods might suffer from institutional and historic barriers that inhibit socioeconomic development, thus ideal treatment should be oriented at a tract level as opposed to individual-based interventions. With this in mind, a potential recommendation is expanding the accessibility to public transportation. If residents lack their proper vehicle, they may rely on public transit for school and work, however, financial costs and limited transit opportunities might create additional barriers. Thus, within the hot spot tracts in Phoenix, Valley Metro could explore reduced fare or free transit options for low-income riders. This policy could abate potential monetary constraints impacting hot spot residents’ public transportation accessibility, thereby promoting greater ridership for job and school opportunities.]
Recommendation 2

Target: 23 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.

[Based on the ’Neighborhood Hardship Trajectories (2013 - 2019), emerging hot spots appear to be developing around Mesa and Tempe, alongside some parts of Phoenix. As these tracts have not solidified into hot spot clusters, they represent a critical opening for policy intervention before neighborhood conditions worsen. It is imperative to explore how and why conditions have changed over time that reflect the rise in hardship. Particularly, the displacement paradox, which refers to how low-income residents are driven out from their previous neighborhoods due to gentrification, could result in hardship declining in certain neighborhoods, while hardship increases in other areas as low-income residents migrate. To account for this, one potential monitoring strategy is to track shifts in rent and income increase, which could provide an insight into demographic and housing changes. Furthermore, items such as tenant protections and rental assistance could be tied to the metrics under the monitoring strategy, which would allow for proactive responses before displacement intensifies.]
Recommendation 3

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.

[While 58.4% of tracts improved between 2013 and 2023, 30.2% of tracts worsened, so it is important to be cognizant of why exactly hardship transformed in certain tracts, especially due to looming gentrification concerns. This requires the monitoring of local conditions in a more comprehensive manner, as opposed to exclusively relying on the index without observing ground information. For instance, the mobility sankey diagram shows that two Q4 and ten Q4 tracts in 2013 moved to the Q1 and Q2 intervals, respectively, by 2023. Moving from the quantile mobility with the second largest hardship onto the quantiles with the least and second least hardship is a significant transformation. Given this momentous change, these tracts warrant further scrutiny, specifically as changes in metrics like rent increases, income increases, racial / ethnic turnover, etc can be monitored to assess whether gentrification enabled the change in hardship, or if there was actual sustained change.]
🔬 Index Sensitivity Reflection

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?

[While the number of persistent hot spots between the baseline and expanded index only decreased by one (150 vs 149), the location of the clusters between those models did change slightly. In both models, persistent hot spots are predominantly clustered around Phoenix and Glendale, however, more of the tracts in Mesa under the baseline are categorized as persistent hot spots, whereas some of those tracts are considered emerging hot spots in the expanded index. In return, there are some tracts north of Phoenix that are classified as persistent hot spots in the expanded model, but characterized as emerging hot spots in the baseline.]

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?

[Between the two indices, persistent hot spots consistently appear in the Phoenix and Glendale areas. The total amount of persistent hot spots is almost the same between the models, only differing by one, showing that at a collective level, the grand total is very similar. The consistency across the different index compositions suggests that certain tracts suffer from such entrenched hardship, that even as hardship is weighed through different variables, they still appear as persistent hot spots across different models.]

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.

[If a policymaker targeted place-based investments using the baseline index compared to the expanded index, the persistent hot spots are largely still within Phoenix and Glendale, so there likely would not be significant variation there. However, the emerging hot spots between the models are slightly varied. Under the expanded model, policymakers would likely target more areas in Mesa and northeast Glendale, which are labeled as emerging hot spots, so these are areas that can strongly benefit from place-based investments before hardship becomes further entrenched. Altogether, the expanded index is the more appropriate model for policy-making as it is inclusive of more relevant latent constructs, which helps the model reduce statistical noise, while also functioning as a more comprehensive representation of hardship.]