Measuring Poverty Using Census Bureau Data
NYC Open Data Week – March 25, 2026
VIDEO | AUDIO | RECAP EN / ES / FR | INFO | INDEX
Speakers: Joli Golden - Data Dissemination Specialist, U.S. Census Bureau; Brian Glassman - Poverty Statistics Branch Chief, U.S. Census Bureau; Monica Dukes - Data Dissemination Specialist, U.S. Census Bureau
Moderator: Joli Golden - U.S. Census Bureau
Introduction to the Census Bureau and the Session Focus
Joli Golden opened the session by introducing herself as a Data Dissemination Specialist with the U.S. Census Bureau. She explained that her work involves helping a wide range of users — including libraries, nonprofits, students, congressional offices, city agencies, and state agencies — understand and access Census data.
Golden described the presentation as a “deep dive into poverty,” intended to help participants understand:
The official poverty measure
The supplemental poverty measure (SPM)
Key Census Bureau poverty datasets
Public data tools for accessing poverty statistics
She introduced Monica Dukes, another Census Data Dissemination Specialist, and Brian Glassman, Chief of the Census Bureau’s Poverty Statistics Branch, both of whom assisted with audience questions during the session.
Golden also briefly reviewed the Census Bureau’s role as the largest federal statistical agency, highlighting its responsibility for conducting:
The decennial census
The American Community Survey (ACS)
The Economic Census
She emphasized that the Census Bureau often collects data later used and released by other federal agencies, including labor and economic statistics.
Defining Poverty – Official vs. Supplemental Poverty Measures
Golden explained that the Census Bureau releases two major poverty measures each year:
Official Poverty Measure (OPM)
Supplemental Poverty Measure (SPM)
Both measures evaluate whether people have enough resources to meet basic needs, but they define resources, family units, and needs very differently.
Official Poverty Measure (OPM)
The official poverty measure:
Assumes resources are shared only among people related by birth, marriage, or adoption
Uses pre-tax cash income only
Relies on a threshold derived from a 1963 minimum food diet multiplied by three and adjusted for inflation
Resources counted include:
Wages and earnings
Social Security
Unemployment income
Retirement income
Interest and dividends
Public assistance
The measure does not include:
SNAP benefits
Medicaid
Housing subsidies
Tax credits
Stimulus payments
Golden stressed that the official poverty threshold is geographically uniform. For example:
A family of two adults and two children had an official poverty threshold of $31,812 in 2024
The same threshold applied in both Mississippi and New York City
Supplemental Poverty Measure (SPM)
The supplemental poverty measure differs substantially.
SPM:
Expands the definition of resource-sharing units to include some unrelated household members such as unmarried partners
Accounts for geographic differences in living costs
Includes non-cash benefits and tax credits
Subtracts major expenses from available resources
Resources added include:
SNAP
WIC
Housing subsidies
School lunch benefits
Utility assistance
Tax credits
Resources subtracted include:
Childcare expenses
Taxes paid
Medical expenses
Child support payments
Golden explained that SPM thresholds vary by housing tenure and geography, producing much higher poverty thresholds in expensive metropolitan regions like New York City.
Household Composition Example
Golden used a hypothetical household to demonstrate differences between the two poverty measures.
The example household included:
An unmarried couple
A child
A grandmother
An unrelated roommate
Under the official poverty measure:
The unmarried partner was treated separately
The unrelated roommate was treated separately
Under the supplemental poverty measure:
The unmarried couple and related household members were grouped together
Only the unrelated roommate remained separate
Golden used this example to illustrate how family definitions can significantly affect poverty calculations.
Geographic Differences in Supplemental Poverty Thresholds
Golden demonstrated how SPM thresholds differ geographically by using Census spreadsheets containing metro-area supplemental poverty thresholds.
She showed comparisons between:
National supplemental poverty thresholds
New York Metropolitan Statistical Area thresholds
The New York metro region included:
New York City
Newark
Jersey City
Surrounding suburban counties
The presentation showed that:
Renters in New York faced the highest supplemental poverty thresholds
Owners without mortgages faced lower thresholds
National thresholds remained substantially below New York regional thresholds
Golden emphasized that SPM attempts to reflect real-world cost differences across housing markets.
Akron, Ohio Case Study
Golden presented a detailed example of a family of four renting an apartment in Akron, Ohio in 2023.
The family had:
$35,000 in pre-tax income
Under the official poverty measure:
The family was not considered poor because income exceeded the official threshold of $30,900
Under the supplemental poverty measure:
SNAP benefits and taxes were incorporated
Childcare and work expenses were deducted
Effective resources fell to $25,700
The family was considered poor because resources fell below the supplemental threshold of $33,763
Golden stressed that although such differences receive attention, most households are classified consistently under both systems.
Appropriate Uses of Each Poverty Measure
Golden explained that each poverty measure serves different analytical purposes.
Official Poverty Measure Uses
The official measure is best for:
Long-term national trend analysis
Federal grant eligibility
Standardized national comparisons
because official poverty data extend back to 1959.
Supplemental Poverty Measure Uses
The supplemental measure is better suited for:
Evaluating government assistance programs
Examining geographic cost differences
Measuring effects of tax credits and benefits
Comparing metropolitan areas and regions
SPM data are available beginning in 2009.
National Poverty Trends and Pandemic Effects
Golden reviewed national poverty statistics for 2024.
According to the Census Bureau:
Official poverty rate: 10.6%
Supplemental poverty rate: 12.9%
Charts displayed long-term trends for both measures.
Golden highlighted the dramatic temporary decline in supplemental poverty rates during the COVID-era stimulus period.
As stimulus payments and expanded tax credits boosted household resources:
Supplemental poverty rates dropped sharply
After many pandemic-era supports expired:
Supplemental poverty rates increased again
The supplemental poverty measure consistently remained above the official poverty measure throughout most of the period shown.
State-Level Differences Between OPM and SPM
Brian Glassman joined the discussion to explain a state-level map comparing official and supplemental poverty rates.
He explained that some states showed:
Higher SPM rates than official rates
Lower SPM rates than official rates
No statistically significant difference
Glassman stressed that all poverty estimates include statistical uncertainty because they are survey-based estimates.
He also mentioned an upcoming Census Bureau working paper analyzing households classified as poor under one measure but not the other, examining demographic differences between those groups.
Major Census Poverty Datasets
Golden then shifted into a detailed overview of the major Census Bureau datasets used to measure poverty.
Current Population Survey Annual Social and Economic Supplement (CPS ASEC)
Golden described the CPS ASEC as:
The official source of national poverty estimates
The longest-running Census poverty survey
Available back to 1959
The survey:
Samples approximately 90,000 addresses annually
Is conducted during February–April
Supports national one-year estimates and state-level three-year averages
The Census Bureau’s annual poverty reports are based on this dataset.
Golden highlighted an America Counts article demonstrating how educational attainment strongly correlates with higher earnings and lower poverty rates using CPS ASEC data.
She also introduced the Census Bureau’s Microdata Access Tool (MDAT), which allows advanced users to directly analyze CPS microdata.
American Community Survey (ACS)
Golden described the ACS as the “gold standard” of Census Bureau data.
The ACS:
Samples approximately 3.5 million addresses annually
Collects roughly 2.2 million responses
Produces detailed demographic, housing, and economic data
ACS releases include:
One-year estimates for populations above 65,000
Five-year estimates for smaller geographies such as census tracts and small towns
Golden emphasized that the ACS now provides:
20 years of historical data
allowing researchers to study long-term patterns such as persistent county-level poverty.
She referenced ACS-based work showing concentrated persistent poverty in parts of the United States, noting that Bronx County was the primary New York county appearing prominently in those analyses.
Survey of Income and Program Participation (SIPP)
Golden described SIPP as a longitudinal survey that follows the same households over time.
Key characteristics include:
Began in 1983
Approximately 50,000 sampled addresses
Tracks respondents for roughly four years
SIPP is especially useful for studying:
Chronic poverty
Episodic poverty
Program participation over time
Golden explained that SIPP can identify households that move in and out of poverty over time rather than remaining continuously poor.
Small Area Income and Poverty Estimates (SAIPE)
Golden then introduced SAIPE, which provides:
Model-based poverty estimates
Data for states, counties, and school districts
Estimates from 1995 onward
SAIPE combines:
ACS data
Administrative data
to generate more granular poverty estimates.
The dataset is particularly important because:
The U.S. Department of Education uses it to allocate Title I funding
Golden demonstrated the SAIPE tool live, filtering:
New York State counties
Under-18 poverty rates
County-level poverty counts
She showed that:
Kings County and Bronx County had especially large numbers of children living in poverty
according to SAIPE estimates.
Using data.census.gov
A substantial portion of the session focused on demonstrating data.census.gov, the Census Bureau’s primary public data portal.
Golden described the platform as:
A central repository for Census data
Supporting tables, maps, charts, downloads, APIs, and geospatial analysis
She walked through a live example using:
ACS five-year estimates
Table S1701 (poverty status in the past 12 months)
County-level poverty data for New York State
Golden demonstrated how users can:
Filter by geography
Filter by dataset
Remove margins of error
Map poverty rates
Generate charts
Change variables dynamically
She highlighted Bronx County as having the highest poverty percentage among New York counties in the demonstration map at approximately 27.8%.
Mapping SNAP Data
Golden also demonstrated how users can map SNAP participation data at the census tract level using data.census.gov.
Using an address near Chinatown in Manhattan, she showed how users can:
Select census tracts interactively
Overlay boundaries such as community districts
Map SNAP participation variables
Compare neighborhood-level poverty-related indicators
Audience Questions – Census Data Infrastructure
During Q&A, participants asked about the infrastructure underlying data.census.gov.
Golden explained that the platform is a proprietary Census Bureau-built system, though it may incorporate some off-the-shelf software components.
She contrasted it with older Census tools such as:
American FactFinder
DataFerrett
which have now largely been replaced by data.census.gov.
Audience Questions – Poverty Table “Cheat Sheets”
Audience members also asked whether a master list or “cheat sheet” exists for all poverty tables.
Golden and Glassman explained that:
No single exhaustive poverty-table cheat sheet exists
Users can search tables by subject or keywords within data.census.gov
Census staff are available to assist researchers seeking specific poverty tables
Closing Remarks
Golden concluded by encouraging organizations to contact Census Bureau staff for customized trainings, presentations, and support related to Census data and poverty statistics.
RESOURCES
data.census.gov — the Census Bureau’s main data platform for maps, charts, and tables, demonstrated live by Joli Golden
Census Bureau Poverty topics page — central hub for poverty estimates, surveys, and guidance on choosing the right data source
Supplemental Poverty Measure (SPM) — the measure that factors in tax credits, government assistance, geography, and key expenses
Small Area Income and Poverty Estimates (SAIPE) Program — model-based poverty estimates for states, counties, and school districts, used for Title I allocations
SAIPE Interactive Data Tool — the interactive application Joli demonstrated for exploring county and school-district poverty data
Survey of Income and Program Participation (SIPP) — the longitudinal survey used to measure chronic and episodic poverty over time
Poverty in the United States: 2024 — the official poverty report drawn from the CPS ASEC, produced by Brian Glassman’s branch
Many U.S. Counties Had High Poverty Rates Over 20 Years — America Counts story by Craig Benson, referenced during the ACS discussion
Census Academy — free courses, Data Gems, and recorded webinars on using Census Bureau data
Exploring the Microdata Access Tool (MDAT) — video tutorial on the MDAT, the advanced microdata tool Joli linked for the audience