Gould Ellen, Ingrid. Impact of Foreclosures on Neighborhood Crime in Five Cities in the United States, 2002-2011. ICPSR34978-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2016-10-31. https://doi.org/10.3886/ICPSR34978.v1
Persistent URL: https://doi.org/10.3886/ICPSR34978.v1
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Smallest Geographic Unit:
New York (state),
New York City,
Date of Collection:
Unit of Observation:
All instances of reported crime and property foreclosures in New York, New York, Chicago, Illinois, Atlanta, Georgia, Miami, Florida, and Philadelphia, Pennsylvania between 2002 and 2011.
administrative records data
Data Collection Notes:
These data are part of NACJD's Fast Track Release and are distributed as they there received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except of the removal of direct identifiers. Users should refer to the accompany readme file for a brief description of the files available with this collections and consult the investigator(s) if further information is needed.
The purpose of the study was to examine whether and how foreclosures affect neighborhood crime in five cities in the United States.
Point-specific crime data was provide by the police departments from the following:
- New York Police Department for 2004-2010;
- Chicago Police Department via the City of Chicago Data Portal for 2001-2011;
- Miami Police Department for 2005-2011;
- Philadelphia Police Department for 2005-2010; and
- Atlanta Police Department for 2005-2011.
Researchers also created measures of violent and property crimes based on Uniform Crime Report (UCR) categories, and a measure of public order crime, which includes less serious offenses including loitering, prostitution, drug crimes, graffiti, and weapons offenses.
Variation in the foreclosure and data collection processes across states translated into differences in the foreclosure measures available in each state. In judicial states, courts collect data on foreclosure fillings. In non-judicial states like Georgia, courts do not gather data on foreclosure notices. The only available data in Atlanta are foreclosure auctions and sales out of real estate owned (REO), which come from the Fulton County Tax Assessors Office. Researchers obtain those data for the years 2002-2011. For the four other cities, researchers obtained information on the number of properties that became REO following a foreclosure auctions from mortgage deeds or assessor's offices. New York, Chicago, and Philadelphia also provide information about the timing of the foreclosure notice.
Additional data were collected on foreclosures in New York City. First, researchers obtained a count of the total number of properties on a blockface that entered foreclosure in the prior eighteen months, a measure called "cumulative foreclosure starts". Second, researchers constructed a measure of "active foreclosures", which captured the number of properties that remain in the foreclosure process. Researchers assumed a property in the foreclosure process if it met one of the three criteria: a) it has received a foreclosure notice (lis pendens) within the last 18 months and has not resold to a new owner; b) it received a foreclosure notice more than 18 months ago, but will be put for auction in the future; or c) it was under lender ownership (REO status) after going through a foreclosure auction. Finally, researchers also identified one particular subset of active foreclosures: those properties that either will go to auction or have already gone to auction and have to revert to lender ownership, or REO status.
Mode of Data Collection:
Description of Variables:
The Five City Data (City5_Ct data, 21 variables, n = 79,096) includes county and census tract identifiers, number of crimes, number of violent crimes, number of property crimes, number of public order crimes, number of foreclosures, number of real estate owned (REO) properties, number of foreclosures that will become REO, and dummy variables for each city (Atlanta, Chicago, New York, Miami, and Philadelphia).
The New York City longitudinal crime and foreclosure data are divided into six data files:
- File Crimelp_0408 (48 variables, n = 2,714,124) includes total number of crimes, total number of violent crimes, total number of property crimes, total number of public order crimes, number of burglaries and larcenies, number of Lis Pendens files, number of Lis Pendens that did no become REO, and number of REO, totals and lagged for six quarters;
- File Crimelp_covars_0408 (82 variables, n = 2,714,125) includes total number of crimes, total number of violent crimes, total number of property crimes, total number of public order crimes, number of burglaries and larcenies, number of Lis Pendens files, number of Lis Pendens that did no become REO, and number of REO, totals and lagged for six quarters, as well as the number of new building permits, demolition permits, serious building code violations, and active liquor licenses. Other variables include the total number of buildings on the block face, along with the number of each of the following an the block face: single family buildings, 2-4 family buildings, 5 plus unit rental buildings, condo buildings, co-op buildings, churches, educational buildings, stores and vacant lots;
- File Crimelp_ct_prec_alt (62 variables, n = 1,285,820) includes borough code and census tract, total number of crimes, total number of violent crimes, total number of property crimes, total number of public order crimes, number of Lis Pendens files and number of REO, totals and lagged for one quarter, as well as the number of new building permits, demolition permits, serious building code violations, and active liquor licenses. Additional variables include measures of crime (violent, property, public order) on contiguous block faces;
- File CRIMELP_CT_PREC_Final_reviewer (17 variables and 993,000 cases) includes total number of property crimes, total number of public order crimes, the number of new building permits, demolition permits, serious building code violations, and active liquor licenses;
- File Facebloc0408f (11 variables, n = 8,142,456) includes total number of crimes, total number of violent crimes, total number of property crimes and total number of public order crimes; and
- File Lpall_faceblocsf (10 variables, n = 10,468,764) includes precinct, total number of buildings, number of Lis Pendens filed, number of Lis Pendens filed that do not become REO, and number of REOs.
Presence of Common Scales: