The document tests Agnew's macro-strain theory as an explanation for juvenile crime rates using data from 93 cities. It measures community strain through factors like poverty, unemployment, welfare rates, and family strain through divorce rates. Regression analysis found that economic strain had a positive relationship with violent juvenile crime rates, supporting the hypothesis and Agnew's theory, but divorce rates did not significantly correlate with juvenile crime. The study provides preliminary evidence that community strains like poverty and unemployment can help explain differences in juvenile violent crime rates between areas.

1. • Further research for the utility of community level strain as
an explanation for juvenile crime rates would be to possibly
take Agnew’s micro strain and compare it to Agnew’s macro
strain to see if there is a outcome that expresses causal
factors of juvenile violent crime.
Discussion and Conclusion
Independent Variables
Statistics and Tables • In Agnew’s macro strain theory states that variables such as
income, poverty, unemployment, welfare, occupation,
education, inequality, owner-occupied dwellings, and
substandard housing are reasons why community crime occurs.
• In our data our independent variable economic strain was
measured by (percent divorce percent, below poverty, percent
welfare, percent unemployment, percent rent of 35% of
income) according to the theory it shows and increase in
community crime .
• We hypothesizes that high levels of economic strain would
show a high level of juvenile violent crime.
• We added in divorce rates as a level of community strain
because Agnew’s explains how family destruction can cause
high levels of strain.
• In conclusion our results showed that our hypothesis was
supported, as well that factors from Agnew’s maco theory were
supported.
Future Research
* Percent Divorce
* Percent Below Poverty
* Percent Welfare
* Percent Unemployment
* Percent Rent of 35% of Income
Background
Research Questions*
 Dependent Variables: Juvenile crime rates, ( violent crime rates)
 We used NIBRS 2013 along with the American Community
Survey data (2013) for 93 cities. NIBRS data was converted to city
level.
Data
Dependent Variables*
Noteworthy Results
While Agnew’s general strain theory has been found to help
explain why individual juveniles engage in crime, Agnew’s
macro-level strain theory has not been tested as an explanation
for juvenile crime rates. In this exploratory study, we examined
community level strains as predictors of juvenile rates. We
converted NIBRS 2013 extract files to city-level data to match
with American Community Survey data (2013) for 93 cities. We
used OLS regression to test the relationship of economic strain
in the community (percent poverty, percent unemployment,
percent of rents 35% of income, and percent receiving welfare)
and family strain (percent divorced) to juvenile crime rates.
 We found that economic strain had a positive effect on violent juvenile
crime rates ( p=.000).
 We did not find a significant relationship between percent divorce and
violent juvenile crime rates.
Juvenile Delinquency: A Test of Agnew’s Macro-Strain Theory
Abigail Hillman, Rachael Farrier, Beau Estaya, Chloe Pillus
Department of Criminology & Criminal Justice, Northern Arizona University, Flagstaff, Arizona USA
* How is community strain associated with juvenile crime rates
specifically violent crimes?
Work Cited
• National Archive of Criminal Justice Data, National Incident-Based Reporting System, 2013:
Extract Files. ICPSR36121-v1. Ann Arbor, MI: Inter-university Consortium for Political and
Social Research [distributor], 2015-08-04. http://doi.org/10.3886/ICPSR36121.v1 available
from http://www.icpsr.umich.edu/icpsrweb/DSDR/studies/36121#datasetsSection.
• U. S. Census Bureau. (2013). American Community Survey 2009-2013 ACS 5 Year Data Profiles.
Retrieved (October 10, 2015), from https://www.census.gov/acs/www/data/data-tables-and-
tools/data-profiles/.