Housing Affordability and Material Hardship Experiences during the COVID-19 Pandemic
Forrest Hangen
Sophia Fox-Dichter
Yung Chun
Michal Grinstein-Weiss
Budgeting 101
Income
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Basic Needs
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Expenses
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Basic Needs
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Income
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Housing
Food
Medical
Other
Budgeting 103
Income
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Housing
Food
Material Hardship
Medical
Other
Budgeting 104
Income
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Cost-burdened
Medical
Food
Housing
Other
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Low-income
Income
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Other
Medical
Food
Housing
Other
Medical
Food
Housing
Income
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Cost-burdened
Low-income
Other
Medical
Food
Housing
Income
<
< 80% of AMI
Housing Affordability
Income
>
Other
Medical
Food
Housing
Is it a burden to pay for this housing?financialHousing Affordability
Housing
Income
>30%
>50%
<2/3 of Federal Poverty Level
(FPL)
Income
Housing
Ratio Measures
Residual Measures
Housing
Affordability
Ratio Measures
>30%
>50%
Residual Measures
<2/3 of FPL
Low-income
< 80% of AMI
Material
Hardship
Ratio Measures
>30%
>50%
Residual Measures
<2/3 of FPL
Low-income
< 80% of AMI
Material
Hardship
How accurate is this relationship?
Housing
Affordability
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
1. At least one member of your household has:
- Qualified for unemployment or should qualify
- Lost income
- Owed large expenses, OR
- Had other financial hardships
2.Your household income is below a certain amount, based on where you live
3. At least one member of your household is experiencing housing instability, which means they are at risk of becoming homeless or would have trouble finding a stable place to live
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
2.Your household income is below a certain amount, based on where you live
3. At least one member of your household is experiencing housing instability, which means they are at risk of becoming homeless or would have trouble finding a stable place to live
1. Financial hardship or income loss
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
3. At least one member of your household is experiencing housing instability, which means they are at risk of becoming homeless or would have trouble finding a stable place to live
1. Financial hardship or income loss
2. Low income
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
1. Financial hardship or income loss
2. Low income
3. Housing instability
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
1. Financial hardship or income loss
2. Low income
3. Housing instability
Material Hardship
COVID-19 Pandemic
Emergency Rental Assistance (ERA)
1. Financial hardship or income loss
2. Low income
3. Housing instability
Material Hardship
Initial Research Questions
Q1: How accurate are simple measures of housing affordability or income level at identifying material hardship?
Q2: What factors matter for predicting material hardship?
Q3: Can we use those factors to better predict material hardship?
Initial Research Questions
Q1: How accurate are simple measures of housing affordability or income level at identifying material hardship?
Q2: What factors matter for predicting material hardship?
Q3: Can we use those factors to better predict material hardship?
Initial Research Questions
Q1: How accurate are simple measures of housing affordability or income level at identifying material hardship?
Q2: What factors matter for predicting material hardship?
Q3: Can we use those factors to better predict material hardship?
Initial Research Questions
Q1: How accurate are simple measures of housing affordability or income level at identifying material hardship?
Q2: What factors matter for predicting material hardship?
Q3: Can we use those factors to better predict material hardship?
Initial Research Questions
Q1: How accurate are simple measures of housing affordability or income level at identifying material hardship?
Q2: What factors matter for predicting material hardship?
Q3: Can we use those factors to better predict material hardship?
Preliminary Qs & Results
Data & Methods
Social Economic Impacts of COVID-19 Survey (SEICS)
conducted by the Social Policy Institute at Washington University in St. Louis (2021)
Nationally Representative
5 waves
April 2020 and June 2021
~5000 / wave
19593 total
Data & Methods
Housing Affordability
Ratio >30%
Ratio >50%
Residual < 1/2 of FPL
Residual <2/3 of FPL
Income
<80% of AMI
Material Hardship
Trouble paying rent/mortgage
Eviction or foreclosure
Trouble paying utility bill
Food insecurity
Financial Trouble
Data & Methods
AUC
Efficiency
Coverage
Harmonic Mean of Coverage and Efficiency
Data & Methods
AUC
(Area under the ROC Curve)
How well does measure distinguish between positive and negative instances
.5 = no better than chance
Efficiency
Coverage
Harmonic Mean of Coverage and Efficiency
Data & Methods
AUC
(Area under the ROC Curve)
How well does measure distinguish between positive and negative instances
.5 = no better than chance
Efficiency
n individuals who experienced a hardship and are
burdened
n burdened indivuduals
How well does measure identify those who experience a hardship?
Coverage
Harmonic Mean of Coverage and Efficiency
Data & Methods
AUC
(Area under the ROC Curve)
How well does measure distinguish between positive and negative instances
.5 = no better than chance
Efficiency
n individuals who experienced a hardship and are
burdened
n burdened indivuduals
How well does measure identify those who experience a hardship?
Coverage
n individuals who experienced a hardship and are
burdened
n hardship individuals
How well does measure identify everyone who experienced a hardship?
Harmonic Mean of Coverage and Efficiency
Data & Methods
AUC
(Area under the ROC Curve)
How well does measure distinguish between positive and negative instances
.5 = no better than chance
Efficiency
n individuals who experienced a hardship and are
burdened
n burdened indivuduals
How well does measure identify those who experience a hardship?
Coverage
n individuals who experienced a hardship and are
burdened
n hardship individuals
How well does measure identify everyone who experienced a hardship?
Harmonic Mean of Coverage and Efficiency
reciprocal of the arithmetic mean of the reciprocals
How well does measure balance coverage and efficiency?
Data & Methods
AUC
(Area under the ROC Curve)
How well does measure distinguish between positive and negative instances
.5 = no better than chance
Efficiency
n individuals who experienced a hardship and are
burdened
n burdened indivuduals
How well does measure identify those who experience a hardship?
Coverage
n individuals who experienced a hardship and are
burdened
n hardship individuals
How well does measure identify everyone who experienced a hardship?
Harmonic Mean of Coverage and Efficiency
reciprocal of the arithmetic mean of the reciprocals
How well does measure balance coverage and efficiency?
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Predictive Validity
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Good news!
Predictive Validity
Factors Predicting Material Hardship
Logistic Regression Models
HA or Income Measure
Household Size
Children
Renter
Age
Job Loss
Race/Ethnicity
Geographic Region
Factors Predicting Material Hardship
Logistic Regression Models
HA or Income Measure
Household Size
Children*
Renter
Age*
Job Loss
Race/Ethnicity*
Geographic Region
Factors Predicting Material Hardship
Logistic Regression Models
HA or Income Measure
Household Size
Children
Renter
Age
Job Loss
Race/Ethnicity
Geographic Region
Original Measures
| 30% | 2/3 of FPL | 80% AMI | |
|---|---|---|---|
| % identified | 18.77% | 13.20% | 43.17% |
| AUC | 0.604 | 0.613 | 0.653 |
| Efficiency | 43.14% | 53.74% | 35.95% |
| Coverage | 34.78% | 30.48% | 66.67% |
| HM | 38.51% | 38.90% | 46.72% |
Original Measures + Job loss
| 30% + Job | 2/3 + Job | 80% + Job | |
|---|---|---|---|
| % identified | 33.97% | 29.48% | 52.83% |
| AUC | 0.676 | 0.685 | 0.653 |
| Efficiency | 41.83% | 45.74% | 35.59% |
| Coverage | 61.04% | 57.91% | 80.77% |
| HM | 49.64% | 51.11% | 49.41% |
Original Measures + Job loss
| 30% + Job | 2/3 + Job | 80% + Job | |
|---|---|---|---|
| % identified | 33.97% | 29.48% | 52.83% |
| AUC | 0.676 | 0.685 | 0.653 |
| Efficiency | 41.83% | 45.74% | 35.59% |
| Coverage | 61.04% | 57.91% | 80.77% |
| HM | 49.64% | 51.11% | 49.41% |
Original Measures + Job loss
| 30% + Job | 2/3 + Job | 80% + Job | |
|---|---|---|---|
| % identified | 33.97% | 29.48% | 52.83% |
| AUC | 0.676 | 0.685 | 0.653 |
| Efficiency | 41.83% | 45.74% | 35.59% |
| Coverage | 61.04% | 57.91% | 80.77% |
| HM | 49.64% | 51.11% | 49.41% |
Factors Predicting Material Hardship
Decision Tree Classifier
Threshold that best separates positives from negatives
Factors Predicting Material Hardship
Decision Tree Classifier
Job loss?Yes = at Risk
No
Income < 73% of AMI
No
Yes = at Risk
DT Thresholds
| 31.75% + Job | $34,834 + Job | 73.25% AMI + Job | |
|---|---|---|---|
| % identified | 36.11% | 46.53% | 51.26% |
| AUC | 0.692 | 0.710 | 0.722 |
| Efficiency | 43.72% | 40.77% | 38.75% |
| Coverage | 63.79% | 76.67% | 80.27% |
| HM | 51.88% | 53.24% | 52.27% |
DT Thresholds
| 31.75% + Job | $34,834 + Job | 73.25% AMI + Job | |
|---|---|---|---|
| % identified | 36.11% | 46.53% | 51.26% |
| AUC | 0.692 | 0.710 | 0.722 |
| Efficiency | 43.72% | 40.77% | 38.75% |
| Coverage | 63.79% | 76.67% | 80.27% |
| HM | 51.88% | 53.24% | 52.27% |
DT Thresholds
| 31.75% + Job | $34,834 + Job | 73.25% AMI + Job | |
|---|---|---|---|
| % identified | 36.11% | 46.53% | 51.26% |
| AUC | 0.692 | 0.710 | 0.722 |
| Efficiency | 43.72% | 40.77% | 38.75% |
| Coverage | 63.79% | 76.67% | 80.27% |
| HM | 51.88% | 53.24% | 52.27% |
DT Thresholds
| 31.75% + Job | $34,834 + Job | 73.25% AMI + Job | |
|---|---|---|---|
| % identified | 36.11% | 46.53% | 51.26% |
| AUC | 0.692 | 0.710 | 0.722 |
| Efficiency | 43.72% | 40.77% | 38.75% |
| Coverage | 63.79% | 76.67% | 80.27% |
| HM | 51.88% | 53.24% | 52.27% |
DT Thresholds
| 31.75% + Job | $34,834 + Job | 73.25% AMI + Job | |
|---|---|---|---|
| % identified | 36.11% | 46.53% | 51.26% |
| AUC | 0.692 | 0.710 | 0.722 |
| Efficiency | 43.72% | 40.77% | 38.75% |
| Coverage | 63.79% | 76.67% | 80.27% |
| HM | 51.88% | 53.24% | 52.27% |
Takeaways
ERA Eligibility Requirements provided High Coverage, but Lower Efficiency
30% Ratio Measure Generally Underperformed
Residual & Income Measures Show Promise
Future Directions
Explore more general thresholds (ACS to SEICS)
Use panel data to understand shifts in validity through pandemic
Your Suggestions!
Examine geographic and racial inequities
Thank You
Forrest Hangen
hangen.f@northeastern.edu
forresthangen.com
