Economic Security
People Living in Poverty, by Race/Ethnicity

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Source: U.S. Census Bureau

What does this measure?

The proportion of people in various racial and ethnic groups with incomes below the poverty line. Poverty thresholds vary by family composition and year. In 2020, the threshold for a four-person family with two children was $26,246.

Why is this important?

The percentage of people in poverty in various racial and ethnic groups is a measure of the overall economic health of these groups and may reflect disparities in access to economic opportunity. It also indicates the level of need for social and government supports.

How is Westchester County performing?

Poverty rates were highest in Westchester County in 2016-20 among African American and Hispanic populations, at 15% and 13% respectively, compared to Asian residents and white populations, both at 6%. Racial and ethnic disparities in poverty in Westchester were similar to the state and nation. Although Westchester's poverty levels were lower for all groups, rates for African Americans and Hispanics were about twice the level as for whites and Asians, just as in the state and nation.

Poverty rates for African Americans and Hispanics in Westchester declined by 3 and 7 percentage points respectively, from 2000 to 2016-20. Rates for Asian and whites remained flat.

Among comparison counties, Westchester had the highest poverty rate among African Americans and the second highest rate among Hispanics behind Rockland at 17%. In Putnam County and in most municipalities within the county, the populations of African Americans and Hispanics were generally too small for reliable estimates of the poverty rate.

Why do these disparities exist?

These large and persistent disparities in poverty rates are the result of historic and current policies and practices that disadvantaged people of color. Research has connected slavery and the inability of black Americans (even after emancipation) to fully participate in economic life to the wealth and income gaps still present today. In addition, these differences are attributed to the complex interplay of conditions including gender, occupation, family structure, education, employment status, wages, incarceration, unemployment and discrimination. African American workers across industries tend to earn lower wages than their white and Asian American peers. While education, especially the absence of a high school diploma, increases the likelihood of poverty, education credentials do not eliminate racial disparities. African Americans experience unemployment at twice the rate of whites regardless of education level. Also, the disproportionate and systemic incarceration of Black and Latinx males decreases job prospects and increases the likelihood of poverty.

Notes about the data

The multi-year figures are from the Census Bureau's American Community Survey. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval).

The survey provides data on characteristics of the population that used to be collected only during the decennial census. Poverty status is not reported for people in institutions, including college dormitories and military barracks, and people in living situations without conventional housing.

People Living in Poverty by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County6%15%13%6%
Nassau County4%7%10%4%
Putnam County16%***8%**8%*5%*
Rockland County3%**11%*17%16%
New York State14%20%21%10%
Mount Vernon6%***15%20%**11%*
New Rochelle12%***17%*13%*7%*
Peekskill10%***19%**14%**7%*
Rye City1%***19%***4%***4%**
White Plains12%***13%*17%*6%*
Yonkers9%**17%17%9%
Westchester County Towns
Bedford2%***27%***8%***8%**
Cortlandt2%***10%***5%**5%*
Eastchester14%***14%***4%***4%*
Greenburgh2%***12%**8%*4%*
Harrison6%***15%***8%***4%**
Lewisboro8%***33%***1%***6%***
Mamaroneck1%***5%***12%***5%**
Mount Kisco0%***37%***8%***5%***
Mount Pleasant12%***14%***11%**5%*
New Castle4%***0%***0%***3%***
North Castle6%***0%***1%***1%***
North Salem0%***7%***6%***4%***
Ossining2%***10%***10%**7%*
Pelham2%***7%***13%***3%**
Pound Ridge0%***5%***1%***0%***
Rye6%***15%***11%*7%*
Scarsdale1%***3%***4%***2%***
Somers1%***4%***0%***3%**
Yorktown0%***4%***7%***4%*
Westchester County Villages
Ardsley0%***2%***3%***1%***
Briarcliff Manor2%***20%***0%***3%**
Bronxville25%***0%***4%***7%***
Buchanan0%***0%***0%***7%***
Croton-on-Hudson0%***0%***1%***3%***
Dobbs Ferry0%***0%***5%***3%***
Elmsford4%***24%***16%**8%***
Village of Harrison6%***15%***8%***4%**
Hastings-on-Hudson3%***6%***14%***3%***
Irvington0%***100%***0%***7%***
Larchmont0%***29%***4%***2%***
Village of Mamaroneck0%***4%***10%***5%***
Village of Mount Kisco0%***37%***8%***5%***
Village of Ossining1%***10%***11%**9%**
Village of Pelham3%***11%***15%***1%***
Pelham Manor0%***0%***8%***5%***
Pleasantville8%***6%***6%***7%***
Port Chester4%***20%***12%*8%**
Rye Brook15%***10%***1%***7%***
Village of Scarsdale1%***3%***4%***2%***
Sleepy Hollow0%***11%***13%***8%***
Tarrytown0%***7%***4%***7%**
Tuckahoe14%***29%***9%***3%***

Source: U.S. Census Bureau
Notes: Data not shown where sample sizes were too small. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




Number of People Living in Poverty by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County3,81420,37331,15933,349
Nassau County6,20111,43222,49336,915
Putnam County336***244**1,261*4,040*
Rockland County597**4,203*9,61635,368
New York State235,557588,597759,8281,199,897
Mount Vernon88***6,1282,302**1,518*
New Rochelle613***2,669*3,140*2,799*
Peekskill48***1,081**1,439**672*
Rye City12***54***53***567**
White Plains522***908*3,148*1,936*
Yonkers1,106**6,44513,0928,765
Westchester County Towns
Bedford18***86***288***1,110**
Cortlandt19***327***375**1,460*
Eastchester444***79***95***934*
Greenburgh189***1,279**1,153*2,456*
Harrison142***94***242***828**
Lewisboro34***30***7***690***
Mamaroneck12***47***538***1,093**
Mount Kisco0***149***309***431***
Mount Pleasant262***215***936**1,644*
New Castle74***0***0***433***
North Castle49***1***9***129***
North Salem0***12***21***167***
Ossining44***252***1,150**1,523*
Pelham14***76***198***286**
Pound Ridge0***5***2***18***
Rye97***332***2,274*2,007*
Scarsdale24***7***45***275***
Somers3***13***10***499**
Yorktown0***84***333***1,109*
Westchester County Villages
Ardsley0***4***9***42***
Briarcliff Manor8***11***0***190**
Bronxville105***0***19***382***
Buchanan0***0***0***108***
Croton-on-Hudson0***0***6***211***
Dobbs Ferry0***1***71***201***
Elmsford21***298***362**150***
Village of Harrison142***94***242***828**
Hastings-on-Hudson9***4***80***194***
Irvington0***106***0***347***
Larchmont0***20***19***124***
Village of Mamaroneck1***28***478***763***
Village of Mount Kisco0***149***309***431***
Village of Ossining18***223***1,097**1,101**
Village of Pelham14***76***161***72***
Pelham Manor0***0***37***214***
Pleasantville22***9***62***393***
Port Chester20***324***2,210*1,292**
Rye Brook76***7***12***583***
Village of Scarsdale24***7***45***275***
Sleepy Hollow0***49***628***385***
Tarrytown3***36***95***565**
Tuckahoe115***76***68***141***

Source: U.S. Census Bureau
Notes: Data not shown where sample sizes were too small. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.








INDICATORS TREND | WESTCHESTER
Early Prenatal Care, by Mother's Race/Ethnicity 1
Increasing
Infant Mortality Rate, by Race/Ethnicity 10 Not Applicable*
Children with Elevated Blood Lead Levels 0
Maintaining
Children Receiving Subsidized Child Care -1
Decreasing
Children Living in Poverty, by Race/Ethnicity 1
Increasing
Disengaged Youth, Ages 16 to 19 -1
Decreasing
Single-Parent Families, by Race/Ethnicity 1
Increasing
Single Female-Headed Households 0
Maintaining
Contributions as a Percentage of Income 0
Maintaining
Voter Registration Rate 1
Increasing
Voter Participation Rate 1
Increasing
Serious Crimes -1
Decreasing
Victims of Domestic Violence -1
Decreasing
Arrest Rates, by Race/Ethnicity 10 Not Applicable*
Households With Internet Access, by Race/Ethnicity 10 Not Applicable*
Households without Vehicles -1
Decreasing
Means of Transportation to Work, by Race/Ethnicity -1
Decreasing
Air Quality 1
Increasing
Population Density 0
Maintaining
Water Quality of the Long Island Sound 1
Increasing
Open Space in Westchester County 1
Increasing
Change in Total Population 1
Increasing
Change in Population, by Race/Ethnicity 1
Increasing
Change in Population, by Age -1
Decreasing
People with Disabilities 1
Increasing
Language Diversity 1
Increasing
People 65 or Older Living Alone 1
Increasing
Change in Total Jobs -1
Decreasing
Change in Jobs by Sector 10 Not Applicable*
Business Ownership, by Race/Ethnicity 10 Not Applicable*
Average Salary by Sector 10 Not Applicable*
Median Household Income, by Race/Ethnicity 0
Maintaining
Female to Male Earnings Ratio 0
Maintaining
Unemployment Rate, by Race/Ethnicity 1
Increasing
People Living in Poverty -1
Decreasing
People Living in Poverty, by Race/Ethnicity 0
Maintaining
Seniors Living in Poverty 0
Maintaining
Seniors Living in Poverty, by Race/Ethnicity 1
Increasing
Food Insecurity -1
Decreasing
Households Receiving SNAP, by Race/Ethnicity 0
Maintaining
Public Assistance 0
Maintaining
People Receiving Supplemental Security Income 1
Increasing
Homeownership Rate, by Race/Ethnicity 1
Increasing
Cost of Homeownership, by Race/Ethnicity 10 Not Applicable*
Overall Housing Cost Burden -1
Decreasing
Cost of Rent, by Race/Ethnicity 10 Not Applicable*
Rent Burdened Households -1
Decreasing
Homelessness, by Race/Ethnicity 10 Not Applicable*
Homelessness, by Sex 10 Not Applicable*
Per-Student Spending 0
Maintaining
Student Suspensions -1
Decreasing
Student Performance on Grade 3 English, by Race/Ethnicity 1
Increasing
High School Cohort Graduation Rate, by Race/Ethnicity 1
Increasing
College Admission Rate, by Race/Ethnicity 1
Increasing
College Enrollment Rate, by Race/Ethnicity -1
Decreasing
Education Levels of Adults, by Race/Ethnicity 1
Increasing
People Without Health Insurance -1
Decreasing
Mortality Rate, by Race/Ethnicity 10 Not Applicable*
Mortality Rate from Chronic Lower Respiratory Disease, by Race/Ethnicity 10 Not Applicable*
Diabetes Mortality, by Race/Ethnicity 10 Not Applicable*
Suicide Rates, by Race/Ethnicity 10 Not Applicable*


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