Background
The City of Dallas, as part of its participation in the National League of Cities’ (NLC) Cities Addressing Fines and Fees Equitably (CAFFE) Initiative cohort, addressed disparities with pet care civil citations. NLC worked with the Dallas Animal Services (DAS)to review fines and fees related to its Pet Animal at Large charges. Through a dedicated city team consisting of the Office of Equity and Inclusion, the Office of Community Care & Empowerment, and Dallas Animal Services, $12,513 in outstanding debt was reduced for residents. Additionally, policy analysis through a consultant provided recommendations for alternatives to paying outstanding fines and policy recommendations to address disparities in assessing fines and fees.
NLC utilized public Census data and a financial burden model to identify key characteristics of those who would be disproportionately impacted by fines/fees and most likely to benefit from reform. NLC uses a data-driven approach to paint the picture of financially burdened households and validate and challenge existing assumptions.
Findings
In Dallas, the burden model illustrated that over half of the burdened households are concentrated in five out of 21 statistical areas around the city. The city team identified areas in the South as areas of concern for their programming, with nearly half of the burdened households concentrated in those areas.
More Than One Third of Households Burdened by Fines Sit Within Three PUMAs in Dallas
DISTRIBUTION OF HOUSEHOLDS BURDENED BY FINES, BY PUMA IN DALLAS
Note: PUMA refers to a Public Use Microdata Area, a US Census Bureau-designated area comprising at least 100,000 people. Data shown here is sourced from the PUMAs that overlap with the City of Las Vegas, including portions of PUMAs that may also exist outside the city limits. Households Burdened by Fines are those whose fines are more than 80% of their disposable income. Due to data limitations, it was not possible to link assessed fines to specific households, and the statistical analysis therefore assumes the size of a fine and a household’s income are not related. However, this may not be true for all fines.
The model also highlights some key characteristics of the burdened population such as:
- Extreme burdened households have monthly incomes 4.5x below the average, and their housing and utilities costs comprise 60% of that income.
- Single parents and women, those under 30 or over 60 years of age, those with one or fewer vehicles (likely associated with income), and those with no formal higher education are more likely to face fee/fine burden than other residents.
Individuals Burdened by Fines Are More Likely to be Under 30 or Over 60 Years Old Than Individuals Overall
DISTRIBUTION OF HOUSEHOLDS, BY AGE GROUP AND FINE BURDEN
Note: Bars may not add up to 100% across groups because individuals below 18 have been excluded. Data shown here is sourced from PUMAs that overlap with the City of Dallas, including portions of PUMAs that may also exist outside the city limits. Individuals Burdened by Fines are those whose fines are more than 80% of their disposable income. Due to data limitations, it was not possible to link assessed fines to specific households. Therefore, the statistical analysis assumes that the size of a fine and a household’s income are unrelated. However, this may not be true for all fines.
One in Five Households Burdened by Fines Do Not Have a Vehicle
DISTRIBUTION OF HOUSEHOLDS, BY NUMBER OF VEHICLES AND FINE BURDEN
Note: Data shown here is sourced from the PUMAs which overlap with the City of Dallas, including portions of PUMAs which may also exist outside the city limits. Households Burdened by Fines are those whose fines are more than 80% of their disposable income. Due to data limitations, it was not possible to link assessed fines to specific households, and the statistical analysis therefore assumes the size of a fine and a household’s income are not related, though this may not be true for all fines.
Individuals Burdened by Fines Are Less Likely to Finish Higher Education
DISTRIBUTION OF INDIVIDUALS, BY EDUCATIONAL ATTAINMENT AND FINE BURDEN
Note: Bars may not add up to 100% across groups because some categories, like “Other,” have been excluded for improved clarity. Data shown here is sourced from the PUMAs that overlap with the City of Dallas, including portions of PUMAs that may also exist outside the city limits. Individuals Burdened by Fines are those whose fines are more than 80% of their disposable income. Due to data limitations, it was not possible to link assessed fines to specific households, and the statistical analysis therefore assumes the size of a fine and a household’s income are not related, though this may not be true for all fines.
Burdened households are more likely to have limited resources at home, and access to public resources may be hampered due to language barriers, lack of internet at home and fewer vehicles in the household.
Households Burdened by Fines Are More Likely to Receive SNAP and Not Have Health Insurance Than Households Overall
DISTRIBUTION OF HOUSEHOLDS, BY POPULATIONS FACING BARRIERS AND FINE BURDEN
Note: Data shown here is sourced from the PUMAs that overlap with the City of Dallas, including portions of PUMAs that may also exist outside of the city limits. Households Burdened by Fines are those whose fines are more than 80% of their disposable income. Due to data limitations, it was not possible to link assessed fines to specific households. Therefore, the statistical analysis assumes that the size of a fine and a household’s income are unrelated. However, this may not be true for all fines.
Conclusions
These findings highlight the need for further policy analysis to address disparities in assessing fines and fees and drafting recommendations on payment alternatives. Without appropriate interventions to support households, a fine could potentially trigger a cycle of debt. Adjusting fines, providing financial literacy services, and establishing payment plans to reflect the ability to pay represent an equitable solution for residents who would otherwise be financially burdened.
Methodology
The data set used in this analysis includes multiple variables on social, economic, housing and demographic characteristics of the U.S. population. Utilizing the 2018-2022 Five-Year American Community Survey (ACS) Public Use Micro Data Sample (PUMs), we calculate the disposable income of households by subtracting housing and utilities costs from the household income. Based on the ACS, we utilized the following variables for calculating housing and utilities costs: Condo Fees, Electricity, Fuel, Gas, Home Insurance, Mobile Home, Mortgage, Property, Rent, Tax and Water.
The City of Dallas team identified that the average debt from fines/fees they helped relieve in their pilot program was $782.07. By dividing this amount by the household disposable income for each unit in the dataset, we calculated the financial burden as a percentage of monthly disposable income. Of note, this model assumes that fines and fees are assigned equally, independent of household income.
We can then sort houses into five cohorts based on the percentage. Households in the highest range (80%-100%) are defined as “Extremely Burdened.”
After identifying the cohorts, we analyze the differences in various demographic and economic indicators available in the PUMs dataset between the “Extreme Burden” group and the rest of the population.
Furthermore, the PUMS dataset is broken down into areas (PUMAs) that roughly represent no more than 100,000 individuals. The municipal boundaries of the City of Dallas overlap with 21 PUMAs, as shown in the map below.
How to Use the Map
Use the plus (+) and minus (-) buttons in the lower right-hand corner of the map to zoom in and out. Use the search function to find a specific address or location.
Learn More about CAFFE
City governments can be champions of strengthening financial security for families through reimagined debt collection practices, equitable ability-to-pay processes and increased access to financial empowerment services. Learn more about Cities Addressing Fines and Fees Equitably on our initiative page.
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