Economic Security
Unemployment Rate, by Race/Ethnicity

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Source: U.S. Census Bureau

What does this measure?

The unemployment rate for racial and ethnic groups in a geographic area. Unemployed individuals are those without jobs who are able, available and seeking work; the rate presents them as a share of the total labor force.

Why is this important?

Unemployment rates are a relatively timely indicator of current local economic conditions, particularly recent changes in the employment landscape that reflect the overall health of the economy.

How is Westchester County performing?

In 2016-20, unemployment in Westchester County was highest among African American workers at 7.5% followed by Hispanic workers at 6.1%, and Asian and white workers both at 5.1%. Westchester has somewhat less disparity than the state and nation due to lower unemployment rates for African American workers: 7.5% in Westchester compared with 9.2% in the nation and 8.9% in New York State. The unemployment rate for Hispanic workers in Westchester County was on par with the nation (6.2%) and lower than the state (7.4%)

Since 2000, the county's unemployment rate declined 1 and 1.5 percentage points among African American and Hispanic workers respectively, while unemployment rates for Asians and whites increased about 2.0 and 1.9 percentage points respectively.

Westchester County had the highest unemployment rate among African American and Asian workers compared to Nassau (6.3% for African Americans; 3.5% among Asians), Rockland (6.0% for African Americans; 3.6% for Asians), and Putnam (5.8% for African Americans; 2.3% for Asians). Westchester had the second highest unemployment rate among Hispanic workers behind Rockland at 7.3%.

Why do these disparities exist?

While traditional explanations for employment rate disparities focus on education and training gaps, whites tend to be employed at higher rates than Blacks and other people of color at every education level (high school, some college, bachelor's degree, etc.). This has led many researchers to focus on labor market discrimination as a primary cause of higher unemployment among people of color. However, it is also true that education levels are generally lower for people of color, suggesting that the education system's failure to equitably serve people of color is also a contributing factor.

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. The survey provides data on characteristics of the population that used to be collected only during the decennial census.

Data on unemployment by race and ethnicity is only available from the American Community Survey, and it is somewhat different from the total population unemployment data produced by the U.S. Bureau of Labor Statistics using responses to the Census Bureau's Current Population Survey. Two different survey methodologies are used (ACS responses are collected by mail, phone and in person; CPS uses phone and in-person interviews), CPS questions on employment are more detailed, and CPS requires that someone be "actively" searching for work (interviewing, calling contacts) in order to qualify as unemployed. In addition, the ACS estimates used here cover a 5-year period, compared to an annual average of monthly estimates presented in the general unemployment indicator.

Unemployment Rate by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County5.1%*7.5%6.1%5.1%
Nassau County3.5%6.3%3.6%3.8%
Putnam County2.3%***5.8%***4.9%**4.6%
Rockland County3.6%*6.0%*7.3%*5.2%
New York State4.9%8.9%7.4%4.6%
Mount Vernon3.1%***7.1%*5.8%**5.0%**
New Rochelle3.0%***5.8%**7.9%*7.0%*
Peekskill9.4%***3.4%***4.5%***7.6%***
Rye City6.0%***0.0%***12.0%***2.7%**
White Plains4.5%***6.6%***6.4%*5.5%*
Yonkers6.7%**8.3%*7.0%6.0%
Westchester County Towns
Bedford8.5%***0.0%***3.2%***3.3%***
Cortlandt4.7%***2.4%***4.0%***8.9%**
Eastchester3.1%***11.6%***0.0%***2.8%*
Greenburgh4.5%***10.0%*5.2%***4.2%*
Harrison10.8%***6.6%***3.0%***4.5%*
Lewisboro11.2%***0.0%***7.6%***3.3%**
Mamaroneck11.0%***4.6%***2.4%***5.9%**
Mount Kisco3.6%***0.0%***5.9%***4.8%***
Mount Pleasant4.3%***17.1%***8.7%**4.1%*
New Castle9.3%***12.2%***0.0%***3.9%***
North Castle2.1%***17.9%***1.9%***3.6%***
North Salem0.0%***0.0%***0.0%***6.9%***
Ossining3.3%***7.4%***2.1%***3.6%*
Pelham1.6%***12.2%***0.0%***4.5%**
Pound Ridge4.0%***0.0%***0.0%***2.9%***
Rye0.8%***9.7%***7.5%*6.9%*
Scarsdale0.5%***0.0%***3.1%***3.7%**
Somers0.0%***0.0%***4.2%***2.9%**
Yorktown8.1%***10.7%***7.7%***4.7%**
Westchester County Villages
Ardsley0.0%***28.9%***0.0%***12.9%***
Briarcliff Manor4.4%***16.1%***7.1%***5.0%***
Bronxville4.1%***0.0%***0.0%***4.0%***
Buchanan0.0%***0.0%***0.0%***6.2%***
Croton-on-Hudson3.8%***0.0%***6.0%***7.0%***
Dobbs Ferry0.0%***14.2%***16.6%***5.0%**
Elmsford11.8%***16.5%***1.2%***3.0%***
Village of Harrison10.8%***6.6%***3.0%***4.5%*
Hastings-on-Hudson0.0%***0.0%***0.0%***3.5%***
Irvington11.4%***0.0%***0.0%***3.8%***
Larchmont7.5%***0.0%***0.0%***13.5%***
Village of Mamaroneck5.5%***6.2%***3.7%***4.1%**
Village of Mount Kisco3.6%***0.0%***5.9%***4.8%***
Village of Ossining3.6%***5.5%***1.7%***2.2%***
Village of Pelham2.7%***6.1%***0.0%***6.1%***
Pelham Manor0.0%***28.3%***0.0%***2.5%***
Pleasantville0.0%***0.0%***3.2%***5.7%***
Port Chester0.0%***12.3%***8.0%*6.7%**
Rye Brook0.0%***0.0%***3.1%***8.5%***
Village of Scarsdale0.5%***0.0%***3.1%***3.7%**
Sleepy Hollow0.0%***0.0%***11.2%***5.1%***
Tarrytown5.3%***8.3%***0.8%***3.2%***
Tuckahoe3.0%***14.9%***0.0%***0.5%***

Source: U.S. Census Bureau
Notes: 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 Unemployed by Race/Ethnicity, 2016-20
AsianBlack or African AmericanHispanicWhite
Westchester County1,667*5,7717,91616,160
Nassau County2,5115,5934,32518,194
Putnam County28***113***395**2,130
Rockland County379*1,269*2,131*5,357
New York State43,265130,697134,499293,565
Mount Vernon30***1,678*329**358**
New Rochelle85***490**1,033*1,631*
Peekskill33***92***273***398***
Rye City29***0***103***169**
White Plains124***242***692*1,006*
Yonkers470**1,770*2,8402,909
Westchester County Towns
Bedford29***0***54***221***
Cortlandt34***45***165***1,554**
Eastchester53***49***0***387*
Greenburgh232***650*426***1,390*
Harrison112***41***62***504*
Lewisboro27***0***24***202**
Mamaroneck114***27***66***727**
Mount Kisco10***0***123***202***
Mount Pleasant47***161***420**737*
New Castle82***38***0***303***
North Castle9***41***13***188***
North Salem0***0***0***161***
Ossining38***134***140***457*
Pelham7***57***0***215**
Pound Ridge4***0***0***78***
Rye6***126***885*1,082*
Scarsdale6***0***12***226**
Somers0***0***49***277**
Yorktown86***130***207***778**
Westchester County Villages
Ardsley0***33***0***215***
Briarcliff Manor8***10***20***166***
Bronxville9***0***0***96***
Buchanan0***0***0***51***
Croton-on-Hudson6***0***35***264***
Dobbs Ferry0***32***169***234**
Elmsford31***132***15***31***
Village of Harrison112***41***62***504*
Hastings-on-Hudson0***0***0***142***
Irvington27***0***0***102***
Larchmont20***0***0***380***
Village of Mamaroneck21***27***108***318**
Village of Mount Kisco10***0***123***202***
Village of Ossining30***82***101***157***
Village of Pelham7***21***0***162***
Pelham Manor0***36***0***53***
Pleasantville0***0***18***190***
Port Chester0***126***819*568**
Rye Brook0***0***24***337***
Village of Scarsdale6***0***12***226**
Sleepy Hollow0***0***328***151***
Tarrytown24***26***10***150***
Tuckahoe16***29***0***13***

Source: U.S. Census Bureau
Notes: 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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