Data Sources: NYU Furman Center’s Housing Needs Assessment Report

This list covers only issues and language specific to the Housing Needs Assessment Tool.
Otherwise, information on all other data sources can be found here.

Census: American Community Survey (ACS)

Topics:

 Demographics, Race, Poverty, Income

Source:

 US Census Bureau

Years Available:

 2020

Geographies:

 County, Place (City), Core Based Statistical Area (metro area), State, Nation

For more information:

 https://www.census.gov/programs-surveys/acs

Description:

Throughout this report unless otherwise noted, all race categories in the report include people of Hispanic ethnicity, and all categories described as “Hispanic” include Hispanic people of any race. Race categories were chosen to ensure consistency among categories across the entire report.

Demographic data for 2007-2011, 2012-2016, and 2017-2021 is from the U.S. Bureau of the Census’ American Community Survey (ACS). This survey replaced the long form from the Decennial Census in 2010. Rather than distributing both a short survey and the long form in 2010, the U.S. Census Bureau instead distributed the short survey as the Decennial Census. Beginning in 2000, the U.S. Census Bureau began administering the new ACS Survey, which is comprised of many of the questions from the old Census long form. With the release of the 2005-2009 ACS data, the ACS data includes small geographic estimates. The ACS data provides demographic, social, economic and housing characteristic estimates on a rolling basis, whereas the 2010 and 2020 Decennial Census provides counts of the population and their basic characteristics (sex, age, race, Hispanic origin, and homeowner status) as a snapshot in time. The move from the long form on the Decennial Census to the ACS format allows data consumers to enjoy annually updated detailed population characteristics, rather than having to wait for the Decennial Census data release. The ACS differs from the Decennial Census in that it is not an enumeration (complete count) of the population, however. Instead, the Census Bureau collects ACS data from a sample of the population, and it provides a margin of error for every ACS estimate. Margins of error are not shown on PolicyMap, but users are encouraged to visit the Census’ website with questions about ACS estimates shown on PolicyMap.

Throughout this report unless otherwise noted, all race categories in the report include people of Hispanic ethnicity, and all categories described as “Hispanic” include Hispanic people of any race. Race categories were chosen to ensure consistency among categories across the entire report.

< Back to list of datasets

Census: American Community Survey (ACS) Average Neighborhood Poverty Rates for Federally-Subsidized Housing

Topics:

 Average Neighborhood Poverty Rate, Federally Subsidized Housing, HUD

Source:

 US Census Bureau, US Department of Housing and Urban Development (HUD)

Years Available:

 2020

Geographies:

 County, Place (City), Core Based Statistical Area (metro area), State, Nation

For more information:

 https://www.census.gov/programs-surveys/acs/ https://www.huduser.gov/portal/datasets/assthsg.html/

Description:

The average neighborhood poverty rate for the typical federally subsidized housing unit of each program type is calculated as the weighted average of the poverty rates of the census tracts where each type of assisted housing is located within a jurisdiction. Neighborhoods are approximated as census tracts, and average tract poverty is the percentage of households with incomes at or below the federal poverty line.

Currently we use ACS 2016-2020 5-year data to get the share of people below poverty in each tract and use HUD and LIHTC data from 2020.

PolicyMap worked with Reinvestment Fund’s Policy Solutions team to develop these estimates.

< Back to list of datasets

Census: American Community Survey (ACS) Average Neighborhood Poverty Rate by Race/Ethnicity

Topics:

 Average Neighborhood Poverty Rate, Race, Ethnicity

Source:

 US Census Bureau

Years Available:

 2020

Geographies:

 County, Place (City), Core Based Statistical Area (metro area), State, Nation

For more information:

 https://www.census.gov/programs-surveys/acs

Description:

The average neighborhood poverty rate for the typical member of each race and ethnic group is calculated as the weighted average of the poverty rates of the census tracts where members of each race/ethnic group live. Neighborhoods are approximated as census tracts, and average tract poverty is the percentage of resident households with incomes at or below the federal poverty line.

A neighborhood’s poverty rate–calculated as the share of a given census tract’s residents that have incomes at or below the federal poverty level–is a commonly used proxy for overall neighborhood quality and access to educational or economic mobility opportunities. Neighborhood poverty rates of 30 to 40 percent or higher are typically considered high and potentially detrimental to individual and family health and well-being, while neighborhood poverty rates at or below ten percent are associated with a range of positive long-term outcomes for adults and children.

(Ellen and Turner, 1997; Jargowsky, 2003; Chetty, Hendren and Katz, 2018.)

Chetty, Hendren & Katz 2018: https://www.aeaweb.org/articles?id=10.1257/aer.20150572

Ellen and Turner 1997: https://www.tandfonline.com/doi/abs/10.1080/10511482.1997.9521280

Jargowsky 2003: https://www.brookings.edu/wp-content/uploads/2016/06/jargowskypoverty.pdf

PolicyMap worked with Reinvestment Fund’s Policy Solutions team to develop these estimates.

< Back to list of datasets

Census: Public Use Microdata Sample (PUMS)

Topics:

 Distribution of Renter Households and Affordable Rental Units by Income, Share of Renter Households Moderately or Severely Cost Burdened by Race/Ethnicity, Severely Crowded Households, by Race/Ethnicity

Source:

 US Census Bureau

Years Available:

 2020

Geographies:

 Public Use Microdata Area (PUMA), State, Nation

For more information:

 https://www.census.gov/programs-surveys/acs/microdata.html

Description:

The Census Bureau releases an anonymized sample of the American Community Survey person and household survey responses as “microdata.” This microdata can be used to calculate estimates not available in the published American Community Survey data. To preserve anonymity, the Public Use Microdata Sample (PUMS) data is only available at a distinct large geography called a Public Use Microdata Area (PUMA), as well as the state level. PolicyMap calculates estimates for custom client reports using PUMS 5-year data. Any estimates at geographies other than the PUMA- or State-level were arrived at by combining survey results from PUMAs that overlap a given area.

PolicyMap and Reinvestment Fund’s Policy Solutions created these reliability flags by calculating the coefficient of variation for PUMS indicators. These flags signal to the users of the Housing Needs Assessment Tool when the PUMS indicators should be used with caution due to small population sizes. Estimates that are “reliable” will have standard errors that are 15% or less of the estimate. Estimates labeled as “use with caution” will have standard errors between 15% and 30% of the estimate. Estimates with standard errors greater than 30% of the estimate will be suppressed.

Data reliability flags were determined based on the US Census’ documentation on Accuracy of the Data (link “Accuracy of the Data” here: https://www2.census.gov/programs-surveys/acs/tech_docs/pums/accuracy/2016_2020AccuracyPUMS.pdf/ ).

< Back to list of datasets

Census: Dissimilarity Index

Topics:

 Separation, Segregation, Race, Black, White, Asian, Latino Households

Source:

 US Census Bureau

Years Available:

 2020

Geographies:

 Core Based Statistical Area (CBSA, or metro area) except Puerto Rico

For more information:

 https://www.census.gov/programs-surveys/acs/ https://www.dartmouth.edu/~segregation/IndicesofSegregation.pdf/

Description:

The Dissimilarity Index is calculated for Black/white and/or Latino/white, Asian/white pairs where non-Hispanic whites and at least one other Black/Latino/Asian group represents 5% or more of total CBSA population. Index values between 0 and 30 are generally assumed to indicate more integrated communities and low levels of segregation, while values between 31 and 60 indicate moderate segregation and values between 61 and 100 indicate high levels of segregation (Massey and Denton, 1993, p. 20. Massey Douglas S, Denton Nancy. American Apartheid: Segregation and the Making of the Underclass. Cambridge, MA: Harvard University Press; 1993.) The Dissimilarity Index compares census tract locations of two groups–in this case, non-Hispanic white households and either Black, Asian, or Latino households–within a jurisdiction, to measure the two group members’ relative separation (high dissimilarity) or integration (low dissimilarity) across all residential tracts. Dissimilarity index values range between 0 and 100, and represent the share of one group that would need to relocate to new census tracts in order to achieve the same residential distribution as the second group. The Dissimilarity Index presented in this report is calculated for core-based statistical areas (CBSAs) for pairs of race/ethnic groups when non-Hispanic white households and Black, Latino, and/or Asian households represent at least 5% of total jurisdiction population. CBSAs in Puerto Rico are excluded from this analysis.

PolicyMap worked with Reinvestment Fund’s Policy Solutions team to develop this index.

< Back to list of datasets