1) The document reviews several studies that examine the relationship between immigration and crime in the United States and other countries. 2) The studies generally find that immigration does not have a significant relationship with increased crime rates, and may even contribute to decreased crime in some cases. 3) However, some studies found that increased immigration can be correlated with increased perceptions of crime and safety issues among native populations, even if actual crime rates remain unchanged or decrease.

1. Bhargava 1
Examining the Relationship Between Immigration and Crime in the United States
Jay Bhargava
PSC 2101
Professor Melissa Milne
December 15, 2014

2. Bhargava 2
In 2008, foreign-born individuals made up 35% of California’s adult population
but only 17% of its prison population (Riley). Adding to recent controversy on
immigration, Republican presidential candidate Donald Trump claimed “the worst
elements in Mexico are being pushed into the United States by the Mexican government”
(Walker). In 2010, only 33% of respondents in an NYT/CBS poll indicated that the
United States should welcome all immigrants (Chernus). This paper seeks to determine
whether anti-immigration rhetoric is based on facts. It will examine the relationship
between immigration population and crime.
Literature Review
In a 2014 article, “Crime and Immigration: Do poor labor market opportunities
lead to migrant crime” Brian Bell of the University of Oxford, examined whether levels
of immigration is related to levels of crime (Bell 1). His evidence indicated that there is
no link between immigration and crime across countries, particularly in a good labor
market, when immigrants find employment it leads to a significant reduction in their
criminal activity and in poor labor markets they were more likely to commit crime (Bell
1). The link between poor labor markets as a key determinant for the likelihood of
immigrant crime is similar for natives, in essence, unemployed and low skilled natives
are more likely to commit crimes than employed and high skilled natives (Bell 9). He
also identifies two additional tools policy makers should utilize when examining
immigration and crime. First, legalizing immigrants is effective in decreasing the
likelihood of them committing a crime. Second, point based immigration systems allow
nations to select the type of immigrants that can attain residence (Bell 9). For example, in
2004, the United Kingdom granted asylum seekers unrestricted access to its labor

3. Bhargava 3
markets. Prior to opening labor markets, estimates showed that a 1% point increase in
asylum seekers was associated with a rise of property crimes by 1.09%. After allowing
employment opportunities a 1% increase in asylum seekers resulted in a decrease of
property crimes to 0.39% (Bell 5).
In her 2013 article, Luca Nunziata tested the notion that immigration flows in the
2000s into Western Europe affected crime victimization and perception of criminality
among European Natives. Nunziata argues that previous empirical research in the United
States on this topic is limited to actual crimes reported, and do not take into account
crime perception. She hypothesizes that while there is no relationship between
immigration and crime, increased numbers of immigrants results in a rise in crime
perception among the native populations (Nunziata 699). This tied into why the native
Europeans held an unfavorable attitude towards immigrants during this period.
To test her hypothesis, Nunziata used survey data taken from the European Social
Survey (ESS henceforth), and from the European Labor Force Survey (LFS henceforth)
(Nunziata 701). The dependent variables, crime victimization and crime perception, were
measured by individual data from the first four waves of the ESS covering 16 European
countries every 2 years from 2002 to 2008 (Nunziata 702). Data on both crime
victimization and crime perception were gathered using surveys, which asked whether
respondents had been victims of a crime in the past 5 years, and if they felt safe at night.
Crime victimization was given a value of “yes or no” and crime perception was given
values of “very safe”, “safe”, “unsafe”, “very unsafe” (Nunziata 707). The independent
variable, immigration, was measured using the birthplace of survey respondents, and

4. Bhargava 4
share of immigrant flow measured by calculations of immigrant shares by region and
year by the LFS (Nunziata 708).
Empirical findings show that an increase in immigration does not affect crime
victimization (p< 0.01, R2
=. 060) (Nunziata 716). But it is associated with a fear of
crime (p< 0.01, R2
= .135) (Nunziata 719). In essence, Nunziata’s results indicate that
immigration has no significant effect on crime victimization in Western Europe, but it
induces an increase in the share of those natives who feel very unsafe, when adopting an
IV specification (Nunziata 723). A shortcoming was noted in that future research why
natives associate crime with immigration even though there seems to be no empirical
evidence, in particular within Western Europe (Nunziata 727). The Author does assert
that these relationships may exist because of casual empirical evidence available to the
public, or because they ignore third factors such as employment and education when
areas with immigrants are associated with high crime (Nunziata 728).
Another study in 2009 by Jacob Stowell, from the University of Massachusetts-
Lowell, as well as Steven Messner, Kelly McGeever, and Lawrence Raffalovich from the
University at Albany-State University of New York examined the relationship between a
drop in violent crime and immigration in metropolitan areas of the United States. Data on
the independent variable, immigration, came from the 1996 and 2004 Population Surveys
(Stowell et al 902) composed of summed z-score for the percent Latino and percentage of
population that are foreign born. Information for the dependent variable, violent crime,
was constructed using the Federal Bureau of Investigation’s (FBI) Uniform Crime Report
(UCR) measured by violent crimes per 100,000 people in 103 metropolitan regions.

5. Bhargava 5
Homicide, rape, aggravated assault, and robbery all constituted as violent crimes. UCR
data was taken from 1994-2004 (Stowell et al 900).
Results indicated that increases in the size of Latino/foreign born are associated
with significant decreases in the violent crime index (Stowell et al 907). Although this
relationship is significant, the author’s regression models suggest that increased
immigration accounts for just 6.16% of the observed crime drop (Stowell et al 907).
Earlier studies examined by the authors indicated that traditionally, immigration led to
increase in crime in an urban context. So given that the examined wave of immigration is
unlike those in the past, the results suggest that the foreign born population entering the
United States are somehow different (i.e., less likely to commit crime) than those of the
past era (Stowell et al 917). Another possibility may be that immigrant populations may
bring unique cultural changes, which improve the “general character” of their
communities (Stowell et al 917). The authors do note however, that including a
comparison between immigrant and native-born populations and their association with
violent crime may provide a clearer result in the future.
In their article, “Do Immigrants Cause Crime,” published in 2012, authors Milo
Bianchi, Paolo Buonanno, and Paolo Pinotti from the Journal of the Economic European
Association examined the empirical relationship between immigration in crime across
Italian provinces from 1990 till 2003 (Bianchi et al 1318). The authors seek to understand
the fears caused by rapid increase in immigration, cause political turmoil in neighboring
countries, and would result in increased crime rates in Italy (Bianchi et al 1319). They
hypothesize that theoretically, there are several reasons to expect a significant

6. Bhargava 6
relationship between crime and immigration. This may happen due to the fact that in
Italy; immigrants experience lower labor market conditions (Bianchi et al 1321).
Data was collected using all 95 provinces in Italy. The dependent variable, crime
rates, was defined as the number of crimes reported by the police to judicial authorities
over the total province population. This data was gathered from Italy’s National Institute
of Statistics (ISTAT). Reported crimes considered were property crime, violent crime,
and drug related crime over the period of 1990-2003 (Bianchi et al 1323). For
immigration, the independent variable, the authors drew directly from police
administrative records for the number of valid permit recorded across the total providence
population. The last three permit-checks took place in 1995, 1998, and 2002 involving
246, 217, 700 thousand individuals respectively.
Findings indicated the opposite effect than expected. Results found that
immigration and crime do not appear to have any significant relationship (p= 0.039, R2
=
0.220) (Bianchi et al 1325). However, there are exceptions in certain provinces across
Italy. But this could be attributed to tertiary reasons. For example, higher wealth in
Northern Italy, where 83% of immigrant crime occurs, could be a motivational factor for
increased violent and property crime (Bianchi et al 1325). The author’s note that their
results are limited in that they do not account for the effects of unofficial immigration on
crime (Bianchi et al 1342). Furthermore, an examination of crime across provinces
provides another limitation: the mobility of criminals. This is particularly true within
smaller provinces.
Aaron Chalfin conducted the final article included in this literature review in 2013
on the relationship between Mexican immigration to the United States and Crime Rates

7. Bhargava 7
using evidence from migration patterns caused by rainfall shocks in Mexico (Chalfin
221). The purpose of the paper was to investigate why there is consensus in empirical
literature that finds immigrants are more likely to participate in acts of crime, and if crime
levels increase when Mexicans are forced to migrate due to rainfall (Chalfin 221). Data
for the first independent variable, Mexican immigration, came from the 1986-2004
Current Population Surveys (CPS), which measured the number of Mexican immigrants
in United States cities through individuals who identified themselves as Mexican on the
survey. For the 12 cities used in this study, CPS data file comprised of 3,067,064
individuals of whom 6.8% are identified as individuals of Mexican origin (Chalfin 243).
Data for a second independent variable, rainfall was obtained from the MPP
environmental file. The file contains monthly rainfall data collected from 1941-2005. The
data for the dependent variable, crime, came from the Uniform Crime Reports (UCR)
from the FBI for the years 1986-2004 and included violent and property crime (Chalfin
243).
Chalfin found that the relationship between crime and immigration was not
significant, even when rainfall forced Mexicans to migrate (Chalfin 264). The researcher
argued that a perception exists that there is a link between Mexican immigration and
crime because these immigrants show characteristics associated with higher criminal
propensities (Chalfin 266). Chalfin noted that this paper does not solve the debate
whether Mexican immigrants destabilize employment markets for US natives causing a
rise in crime level, he suggested further research be conducted in relation to this
argument.

8. Bhargava 8
Patrick Thomas’s “Theoretical Articulation on Immigration and Crime” published
in 2011 reviewed the contributions of social, and cultural perspectives to the
understanding of immigration and crime (Thomas 382). In this paper, Thomas examined
several hypotheses, which are meant to expand the knowledge on crime and immigration
(Thomas 382). Three of these hypotheses are pertinent to the question posed by this
paper. First, he drew on “Ethnic differences in Integral Crime Patterns,” published in
2005 by D.J. Smith. Smith shared an example of lower crime rates between South Asian
in the United Kingdom partly due to traditional family (Thomas 387). This led the author
to theorize “Immigrant crime varies inversely with extended family relationships, net of
other individual- and community-level effects” (Thomas 387). Thomas then suggested
that many immigrants could have difficulty with cultural and legal immersion when
arriving in a new country, and could commit crimes out of ignorance. Through this
argument he hypothesized that crime may have a stronger correlation with recent
immigrants, but the relationship grows weaker as they adjust to their new country of
residence (Thomas 391). Finally, Thomas pointed to a 2009 study “Exploring the
Connection between Immigration and Crime Rates in the US” by Ousey, G. C., &
Kubrin, C. E. This study found diminished violent crime rates as immigration increased
between 1980-2000 (Thomas 394). As such, Thomas concluded that crime varies
inversely with immigration concentration, all else equal.
To conclude, studies have generally shown that there is a lack of relationship
between immigration and crime. Many of the studies did draw a link between increased
immigration and xenophobia. Aaron Chalfin found that there is no significant correlation
between immigration and crime (Chalfin 266). Brian Bell found that higher levels of

9. Bhargava 9
crime in immigrant communities could often be attributed to other factors, such as labor-
market opportunities (Bell 9). Nunziata found that while there is no link between
immigration and crime, immigration does lead to the perception among natives that more
crimes will be committed (Nunziata 728), her results were matched by researchers from
Italy (Bianchi et al 1323). Researchers at the University of Massachusetts-Lowell and the
University at Albany-State University of New York found evidence, which suggests that
some immigrant populations led to a lower crime rate (Stowell et al 917), while Patrick
Thompson added to this assertion, claiming that in ideal conditions, immigration is
inversely related to crime, all else equal (Thompson 394)
Data Analysis
Research tested the relationship between immigration and crime, in particular
property crime. Two variables tested are both ratio variables, comprised of percentage
values that will indicate a directional relationship. The null hypothesis states that there is
no relationship between immigration and property crime within the United States. The
independent variable, immigration, was attained from the 2000 and 2013 US census
report. The Dependent Variable, property crime, was attained from the 2000 and 2013
Uniform Crime Report (Henceforth UCR).
Univariate Analysis
The US census is congressionally mandated to count every household in the
United States. For each census, many households return their consensus forms by mail;
census workers operate across the country to account for the remaining households (US

10. Bhargava 10
Census Bureau). Research from this paper utilized data collected from 2000 and 2013.
The sample size included every respondent across the 50 United States and the District of
Columbia who identified his or herself as foreign born.
The independent variable, Immigration, was defined as the change in number of
foreign born US residents in each state, represented by a percentage change. Central
tendency was measured using the mean or mathematical average, which equated to
49.535 percent. A comparison of the mean and median (45.535 and 49.300 percent,
respectively) values indicated that they were close enough to assume there weren’t any
extreme outliers. Examination of the frequency distribution table and z-scores (see Table
1 below), confirmed this assumption. Variability was measured by computing the
standard deviation or average distance of the values from the mean, which equated to
22.500 percent. 68% (mean value of 49.535 percent plus or minus one standard deviation
value of 22.500) of the values were between 27.033 percent and 72.033 percent.
Table 1. Frequency Table for Percentage Change in Foreign Born from 2000-2013
IMMIGRATION --PERCETAGE CHANGE IN US IMMIGRATION 2000-2013
Mean: 49.535 Std.Dev: 22.500 N: 51
Median: 49.300 Variance: 506.270 Missing: 0
Range Freq. % Cum.% Z-Score
13.3 - 13.3 1 2.0 2.0 -1.610
14.0 - 14.0 1 2.0 3.9 -1.579
16.1 - 16.1 1 2.0 5.9 -1.486
16.2 - 16.2 1 2.0 7.8 -1.482
16.3 - 16.3 1 2.0 9.8 -1.477
17.8 - 17.8 1 2.0 11.8 -1.410
18.2 - 18.2 1 2.0 13.7 -1.393
18.7 - 18.7 1 2.0 15.7 -1.370
21.8 - 21.8 1 2.0 17.6 -1.233
26.2 - 26.2 1 2.0 19.6 -1.037
30.4 - 30.4 1 2.0 21.6 -0.850

11. Bhargava 11
35.0 - 35.0 1 2.0 23.5 -0.646
35.1 - 35.1 1 2.0 25.5 -0.642
35.5 - 35.5 2 3.9 29.4 -0.624
35.7 - 35.7 1 2.0 31.4 -0.615
36.6 - 36.6 2 3.9 35.3 -0.575
38.8 - 38.8 1 2.0 37.3 -0.477
40.7 - 40.7 1 2.0 39.2 -0.393
41.2 - 41.2 1 2.0 41.2 -0.370
41.8 - 41.8 1 2.0 43.1 -0.344
42.2 - 42.2 1 2.0 45.1 -0.326
47.1 - 47.1 1 2.0 47.1 -0.108
49.1 - 49.1 1 2.0 49.0 -0.019
49.3 - 49.3 1 2.0 51.0 -0.010
50.7 - 50.7 1 2.0 52.9 0.052
53.6 - 53.6 1 2.0 54.9 0.181
54.3 - 54.3 1 2.0 56.9 0.212
54.9 - 54.9 1 2.0 58.8 0.238
56.6 - 56.6 1 2.0 60.8 0.314
57.5 - 57.5 1 2.0 62.7 0.354
57.6 - 57.6 1 2.0 64.7 0.358
60.9 - 60.9 1 2.0 66.7 0.505
62.5 - 62.5 1 2.0 68.6 0.576
63.7 - 63.7 1 2.0 70.6 0.630
65.0 - 65.0 1 2.0 72.5 0.687
65.8 - 65.8 1 2.0 74.5 0.723
66.4 - 66.4 1 2.0 76.5 0.750
67.1 - 67.1 1 2.0 78.4 0.781
68.2 - 68.2 1 2.0 80.4 0.830
68.8 - 68.8 1 2.0 82.4 0.856
71.0 - 71.0 1 2.0 84.3 0.954
74.2 - 74.2 1 2.0 86.3 1.096
74.3 - 74.3 1 2.0 88.2 1.101
81.2 - 81.2 1 2.0 90.2 1.407
81.7 - 81.7 1 2.0 92.2 1.430
84.4 - 84.4 1 2.0 94.1 1.550
85.6 - 85.6 1 2.0 96.1 1.603
91.7 - 91.7 1 2.0 98.0 1.874
99.4 - 99.4 1 2.0 100.0 2.216
The UCR are official data on crime in the United States, reported by the Federal
Bureau of Investigation (FBI) (fbi.gov). The report is published annually, and data is
reported by law enforcement agencies to the FBI, which then compiles the report

12. Bhargava 12
(fbi.gov). Data used in this paper, was collected in 2000 and 2013, and includes all
property crimes in the 50 United States and the District of Columbia reported by law
enforcement agencies to the FBI in both years.
The dependent variable, property crimes, includes the offenses of burglary,
larceny-theft, motor vehicle theft, and arson. The objective of the crime is the taking of
property or money, but no force or threat of force is committed against the victim
(FBI.gov). This research presents the change in property crimes committed per 100,000
populations from 2000-2013, represented by a percentage change. Central tendency was
measured using the mean or mathematical average, which equated to -23.135 percent. A
comparison of the mean and median (-23.135 and –23.970 percent, respectively) values
indicated that they were close enough to assume there weren’t any extreme outliers.
Examination of the frequency distribution table and z-scores (see Table 2 below),
confirmed this assumption. Variability was measured by computing the standard
deviation or average distance of the values from the mean, which equated to 8.778
percent. 68% (mean value of -23.135percent plus or minus one standard deviation value
of 8.778) of the values were between -31.913 percent and -14.357 percent.
Table 2. Frequency Table for Percentage Change in Property Crimes Committed in
US per 100,000 2000-2013
PROPERTY CRIME – PERCERNTAGE CHANGE IN PROPERTY CRIME
COMMITTED IN US PER 100,000 2000-2013
Mean: -23.135 Std.Dev.: 8.778 N: 51
Median: -23.970 Variance: 77.060 Missing: 0
Range Freq. % Cum. % Z-Score
-38.37 - -38.28 1 2.0 2.0 -1.736
-37.37 - -37.28 1 2.0 3.9 -1.622
-36.47 - -36.38 2 3.9 7.8 -1.519

13. Bhargava 13
-35.87 - -35.78 1 2.0 9.8 -1.451
-34.57 - -34.48 1 2.0 11.8 -1.303
-33.97 - -33.8 1 2.0 13.7 -1.234
-32.27 - -32.18 1 2.0 15.7 -1.041
-32.17 - -32.08 1 2.0 17.6 -1.029
-30.47 - -30.38 1 12.0 19.6 -0.836
-30.17 - -30.08 1 2.0 21.6 -0.801
-29.47 - -29.38 1 2.0 23.5 -0.722
-29.27 - -29.1 1 2.0 25.5 -0.699
-28.37 - -28.28 1 2.0 27.5 -0.596
-27.57 - -27.48 1 2.0 29.4 -0.505
-27.17 - -27.08 1 2.0 31.4 -0.460
-26.77 - -26.68 1 2.0 33.3 -0.414
-26.37 - -26.28 1 2.0 35.3 -0.369
-26.17 - -26.08 1 2.0 37.3 -0.346
-26.07 - -25.98 1 2.0 39.2 -0.334
-25.27 - -25.18 1 2.0 41.2 -0.243
-24.87 - -24.78 1 2.0 43.1 -0.198
-24.57 - -24.48 1 2.0 45.1 -0.164
-24.47 - -24.38 1 2.0 47.1 -0.152
-24.27 - -24.18 1 2.0 49.0 -0.129
-23.97 - -23.88 1 2.0 51.0 -0.095
-23.27 - -23.18 1 2.0 52.9 -0.015
-22.97 - -22.88 1 2.0 54.9 0.019
-22.37 - -22.28 2 3.9 58.8 0.087
-22.27 - -22.18 1 2.0 60.8 0.098
-21.67 - -21.58 2 3.9 64.7 0.167
-21.27 - -21.18 1 2.0 66.7 0.212
-20.97 - -20.88 1 2.0 68.6 0.247
-20.07 - -19.98 1 2.0 70.6 0.349
-19.57 - -19.48 1 2.0 72.5 0.406
-19.47 - -19.38 1 2.0 74.5 0.417
-19.27 - -19.18 1 2.0 76.5 0.440
-17.97 - -17.88 1 2.0 78.4 0.588
-17.47 - -17.38 1 2.0 80.4 0.645
-16.67 - -16.58 1 2.0 82.4 0.736
-16.17 - -16.08 1 2.0 84.3 0.793
-14.77 - -14.68 1 2.0 86.3 0.953
-11.37 - -11.28 1 2.0 88.2 1.340
-11.07 - -10.98 1 2.0 90.2 1.374
-8.77 - -8.68 1 2.0 92.2 1.636
-8.07 - -7.98 1 2.0 94.1 1.716
-5.17 - -5.08 1 2.0 96.1 2.046
-2.87 - -2.78 1 2.0 98.0 2.308
-1.87 - -1.78 1 2.0 100.0 2.422

14. Bhargava 14
Bivariate Analysis
The analysis studied the relationship between the amount of immigration into the
United States, and property crimes committed in the United State in order to determine
whether claims that immigrants cause crime levels to rise is warranted. The working
hypothesis is: H0 – There is a positive relationship between immigration and crime. The
null hypothesis is: H1: There is no relationship between immigration and crime. As
indicated in Figure 1 below, there appears to be a weak, positive, and linear relationship
between immigration and property crime; in the United States, as immigration increases,
so does property crime.
Figure 1: Visual Representation of the relationship between Immigration and
Property Crime.
Regression and correlation were employed to test whether the sample linear
relationship translates to the population (see Figures 2 – 2.2). Variance was analyzed
between observed and expected scores an indicated significance between the relationship
(F = 4.990, P= 0.03). The least-squared regression line’s slope value (b = 0.119) is
-40
0
P
R
O
P
C
R
I
M
E
%
10 100
I M M I %
Line Equation Y = -29.010 + 0.119 X
r = 0.304* Prob. = 0.016 N = 51 Missing = 0

15. Bhargava 15
significantly different than 0. The Pearson’s correlation coefficient (r = 0.304) confirms a
weak positive relationship exists between immigration and property crime.
Figure 2. Variance Analysis of variables Immigration and Property Crime
Dependent Variable: PROPCRIME%
N: 51 Missing: 0
Multiple R-Square = 0.092 Y-Intercept = -29.010
Standard error of the estimate = 8.448
LISTWISE deletion (1-tailed test) Significance Levels: **=.01, *=.05
Source
Sum of
Squares
DF
Mean
Square
F Prob.
REGRESSION 356.116 1 356.116 4.99 0.03
RESIDUAL 3496.886 49 71.365
TOTAL 3853.002 50
Column1 Column2 Column3 Column4 Column5
Unstandardized
b
Standardize d
Beta
Standard Error
b
t
IMMI% 0.119 0.304 0.05 2.234 *
Figure 2.1: Correlation Coefficient
IMMI% PROPCRIME%
IMMI% 1 0.304 *
PROPCRIME% 0.304 * 1
Figure 2.2 Means, Standard Deviations, and Number of Cases for each Variable
N Mean Standard
Deviation
Immi% 51 49.535 22.500
Propcrime% 41 -23.135 8.778

16. Bhargava 16
Conclusion
The result of this analysis rejects the null hypothesis that there is no relationship
between immigration and crime. However, after examining further statistical evidence,
this relationship is weak. Only 9.2 percent of the variability in a state’s property crime
rate can be explained by immigration (r2
= 0.092). Furthermore, if you increase
immigration in any state by 1%, there will be an increase of 0.119% in property crime.
Though the bivariate analysis indicates there is a relationship between a state’s
immigration and crime, the weakness shows that there could be many variables in
addition to immigration that influence property crime. An example may be
unemployment, which increased after the 2008 recession and may have encouraged
property crime in particular.
There are potential shortcomings to the data. Firstly, this research does not
include unofficial immigrants into this study. It would be interesting to examine whether
the legality of immigration affects the propensity to commit crime. Second, the study
only examines property crime; it might be worthwhile to examine different types of crime
such as violent crime. The limitations of this study do not conclusively prove a
relationship between immigration and crime, to solve this debate; further research of
greater magnitude must be conducted.

17. Bhargava 17
Works Cited
- Riley, Jason. "The Mythical Connection Between Immigration and Crime." Wall
Street Journal, The Wall Street Journals. 15 Jul. 2015. Web.
- Walker, Hunter. " Donald Trump just released an epic statement raging against
Mexican immigrants and 'disease." Business Insider. Business Insider, 6 Jul.
2015. Web.
- Chernus, Ian." Why are so many Americans Scared of Undocumented
Immigrants?” AlterNet. AlterNet, 10 May. 2015. Web.
- Bell, Brian. “Crime and Immigration: Do poor labor market opportunities lead to
migrant crime.” IZA World of Labor (2014): 1-10. Web.
- Nuziata, Luca. "Immigration and Crime: Evidence from Victimization
Data." Journal of Population Economics 28.3 (2015): 697-736. Web.
- Stowell, I Jacob., Steven F. Messner, Kelly F. McGeever, and Lawrence R.
Raffalovich. "Immigration and the Recent Violent Crime Drop in the United
States: A Pooled, Cross-Sectional Time-Series Analysis of Metropolitan
Areas." Criminology 47.3 (2009): 889-928. Web.
- Bianchi, Mili., Paolo Buonanno, Pablo Pinotti. “Do Immigrants Cause Crime.”
Journal of European Economic Association 10.6 (2012): 1318-1347. Web.
- Chalfin, Aaron. “What is the Contribution of Mexican Immigration to U.S. Crime
Rates? Evidence from Rainfall Shocks in Mexico.” American Law and Economic
Review 16.1 (2014): 220-268. Web.
- Thomas, Patrick “Theoretical Arguments on Immigration and Crime.” Homicide
Studies 15.4 (2011): 382-403. Web.

18. Bhargava 18
- Property Crime." fbi.gov. N.p., n.d. Web. 10 Dec. 2015. <https://www.fbi.gov/
about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/property-crime>.
- “State Immigration Data Profiles.” U.S. Census. Migration Policy Institute. Web.
10 December 2015.
- “Uniform Crime Report.” Data. Federal Bureau of Investigations. Web. 10,
December 2015.