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University of Pennsylvania University of Pennsylvania
ScholarlyCommons ScholarlyCommons
2017 ADRF Network Research Conference Presentations
ADRF Network Research Conference Presentations
11-2017
Administrative Data Research Facility Linked HMDA and ACS Administrative Data Research Facility Linked HMDA and ACS
Database Database
Jun Zhu Urban Institute
Follow this and additional works at: https://repository.upenn.edu/
admindata_conferences_presentations_2017
Zhu, Jun, "Administrative Data Research Facility Linked HMDA and ACS Database" (2017). 2017 ADRF Network Research Conference Presentations. 8. https://repository.upenn.edu/admindata_conferences_presentations_2017/8
This paper is posted at ScholarlyCommons. https://repository.upenn.edu/admindata_conferences_presentations_2017/8 For more information, please contact [email protected].
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Administrative Data Research Facility Linked HMDA and ACS Database Administrative Data Research Facility Linked HMDA and ACS Database
This presentation is available at ScholarlyCommons: https://repository.upenn.edu/admindata_conferences_presentations_2017/8
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Administrative Data Research Facility Linked HMDA and ACS Database
Jun ZhuHousing Finance Policy Center
Urban Institute
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Challenges for research:• Publicly available government data is messy and hard to aggregate
up and link to geographic levels • Researchers need to download data and use the installed statistical
software to analyze the data
Our solution:• Create a relational database across geographies by crosswalking
data• Databases can either be downloaded on the initial web interface or
spun up into the spark social science platform for analysis.
Background
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Product DetailsLINKED DATASETS
• Most of the variables from American Community Survey (ACS) and Home Mortgage Disclosure Act (HMDA) linked by geographies
• Data Dictionary to define these variables
SPARK SOCIAL SCIENCE PLATFORM• Push button launch of platform from website• Platform includes tutorials, access to linked data and manual
WEB INTERFACE• Basic, open-source website offering download of data/data
dictionary and a way to launch the analytics platform• Critical information about the project, including guidance on how to
cite linked data
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Public Web InterfaceProject information, links to publications, links
to resources.
Linked DatasetsFor download
Data DictionaryFor download
Spark PlatformButton launches platform
Tutorials Data
Product Details
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Sloan Website • https://adrf.urban.org/
• Data can also be analyzed in the Spark for Social Science platform
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Spark
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Methodology• We have linked the two datasets on geographic level.
Census Tract(HMDA)
PUMA(ACS)
Census Tract 2000 to Census Tract2010
PUMA 2000 to Census Tract2010
Census Tract 2000 to PUMA2010
PUMA 2000 to PUMA 2010
Census Tract 2010 to Zipcode 2010
PUMA 2010 to CBSA 2013
PUMA 2010 to County 2014
• If the direct crosswalk is not available from the website, we did some manipulations to create a new crosswalk
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Geographic Levels Available From 2001
• There are 6 databases at different geographic levels.
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Data structure
HMDA VariablesACS Housing Variables
ACS Household Variables
ACS Person Variables
Number of families• Number of families in the household
Multiple generations• Number of generations in the household
Household Income
Sex• Whether the respondent is male or female
Grade Attained• Grade or level of recent schooling
Transportation Time (minutes)
• In the dataset, we have included both the raw variables from HMDA and ACS, as well as some variables which we constructed
Mortgage Status• If there is a mortgage owned free and clear
Bedrooms• Number of bedrooms in the house
Monthly Mortgage Payment
Agency• Supervisory/regulatory agency of institution
Loan purpose• Purchase, refinance, home improvement
Loan Amount
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Variable Types
Categorical Variables • Variable with codes
Numerical Variables
• Mean• Percentiles (P10, P25, P50, P75, P90)• Standard deviation
Categorical-Categorical • Variable with codes
Categorical-Numerical
• Mean
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Data Dictionary• We have a detailed data dictionary available which
covers all the data types, variables, and definitions
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Sample Use Case• What is the black homeownership rate in Atlanta?• Original Way: (1) go to IPUMS. (2) find the race/ethnicity variable
and ownership variables. (3) find the geographic level variables.
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Answer This Question using IPUMS
• Pick the years.• Search for the crosswalk (PUMA 2000 to PUMA 2010)• Calculate the total households and homeowners using
crosswalk
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Or with the ADRF3 Simple Steps:• Use the CBSA database• Search for CBSA (12060) for Atlanta• Find the cross tab variable: race1_HH_B_ownership_1 and single
categorical variable: race1_HH_B
Year HH_Black Owner_BlackBlack
homeownership rate
2005 532,991 271,159 50.9%2006 546,690 288,162 52.7%2007 567,361 309,523 54.6%2008 572,848 308,427 53.8%2009 566,727 298,689 52.7%2010 602,219 311,240 51.7%2011 610,884 305,327 50.0%2012 619,959 299,822 48.4%2013 631,399 296,475 47.0%2014 643,395 305,015 47.4%2015 660,484 303,386 45.9%
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Developing a Housing Affordability Index• A New housing affordability index
• How many renters earn as much income as an owner who just purchased a 1-4 unit home in the same area?
• Renter income: ACS; Borrower income: HMDA
•PA= Likelihood that a renter’s income falls in a specific income level A•QA= Likelihood that a renter’s income is enough to get a mortgage and purchase a home, given his/her specific income level A
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Affordability Index Inputs Using ADRFIncome Level PA QA PA*QA
1 2.07 0.00 0.002 9.15 0.00 0.003 8.91 0.78 0.074 13.83 2.13 0.295 9.51 7.56 0.726 8.43 16.86 1.42
… … … …16 6.33 87.40 5.5317 0.00 89.53 0.0018 2.56 91.47 2.3419 0.00 93.22 0.0020 0.00 93.99 0.0021 0.00 95.54 0.0022 0.00 100.0 0.00
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Affordability Index Using ADRF
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Using the database for empirical studies• Different geographic level variables can be easily added in
the regressions to control the local market conditions. � Unemployment rate by race at county level
� Percentage of minority population at zipcode level
� Average mortgage borrower income at census tract level
� Average loan amount at CBSA level
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Future Work• We hope that the process of doing these crosswalks is
helpful to researchers in all fields• In the next phase of our project, we plan to include more
datasets• We are planning to update the most recent 2016 HMDA
and ACS data.