Transcript Crime and Immigration: Further Evidence on the Connection

Why are Immigrants' Incarceration Rates
So Low? Evidence on Selective
Immigration, Deterrence, and Deportation
Kristin F. Butcher
Federal Reserve Bank of Chicago
Anne Morrison Piehl
Rutgers University and NBER
How do Immigrants Fare in the
United States?
 Immigrants have tended to have low wages in
the U.S. (recent change at high end)
 Men aged 25-64, immigrant-native wage
differential:
1970: 0.009 1980: -0.097
1990: -0.166
 most recent earn 38% lower in 1990 (Borjas 1995)
 male immigrants earn 19% less in 2000 (Borjas 2004
and Borjas & Friedberg 2004)
 Poor labor market outcomes have led to
concerns about immigrants adding to the
“underclass” and thus the population with poor
social outcomes.
Reasons to Think Immigrants
Contribute to the Crime Problem
 Immigrants share characteristics in
common with the native born population
that is disproportionately incarcerated.
 Cities with greater shares of immigrants
have higher crime rates.
 Those with poor labor market outcomes
are disproportionately likely to engage in
criminal activities.
Cross-sectional Experience
Overall crime rate, moving avrg '89-91
Overall m etropolitan area (MA) crim e rates by fraction im m igrant,
1990
14,000
13,000
12,000
11,000
10,000
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55
Fraction immigrant, 1989
Figure 4. Predicted
Institutionalization for Immigrants
0.08
Predicted Fraction Institutionalized
0.07
0.06
0.05
Prediction based on age
0.04
Prediction based on age, race/ethnicity, and education
0.03
0.02
0.01
0
1980
1990
Year
2000
Changes in 1990s
 1996 Anti-Terrorism and Effective Death
Penalty Act –Among other things, greatly expanded list of
crimes for which non-citizens could be deported, made it
retroactive, imposed mandatory detention following conclusion
of prison term.
 1996 Personal Responsibility and Work
Opportunities Reconciliation Act –Among other
things curtailed non-citizens access to welfare programs
(originally for all non-citizens, later amended to grandfather in
those already here at time of law’s passage).
 Large numbers of immigrants.
 Crime rates down 30% over the decade.
 Incarceration rates up 63% over decade.
Today’s Paper
 Examine how immigrants’
institutionalization rates compare to
those of the native born.
 Examine how these change across
cohorts and over time.
 Discuss the potential reasons for
these changes: deportation,
deterrence, self-selection.
Results Preview
 We will see that immigrants have lower
institutionalization rates than the nativeborn – about 1/5 the size.
 This gap is much bigger in 2000,
suggesting improvement along this
dimension.
 Direct effect of deportation appears to be
small; positive selection of migrants
appears to have increased over time.
Model of Immigrant Self-Selection
 Roy (1951) reformulated in Borjas (1987)
 I=(m1-m0-p) + (e1-e0)
 m1, m0, are mean log wages in host and source
countries
 e1, e0 are deviations of earnings in the two countries
 P is cost of migration divided by the wage in the
source country (“time cost” of migration)
 I>0 individual migrates, I<0 individual stays
 Borjas used this model to explain changes in
cohort quality of immigrants to U.S. over last
few decades.
 US attracts high skilled from compressed
earnings distributions, low skilled from unequal
Model of Immigrant Self-Selection
continued
 In Borjas, migration cost is constant across
individuals, but suppose it varies with quality
of social networks (Chiquiar and Hanson 2005,
Hanson forthcoming).
 -> those with productive networks have lower wage
threshold for migration.
 Further suppose, I=f(m1,m0,p,e1,e0,d), d is expected
policy environment.
 -> shift in policy may shift migrant selection
 If migration decision depends on multiple
factors, can get very different implications
across different dimensions of “skill.”
Data: U.S. Censuses, ’80, ’90, ‘00
 We examine institutionalization among 1840 year old men. (In 1980, 70% of this
group are in correctional facilities).
 Demographics in Table 1.
 Highlights:




Fraction immigrant tripled (6% - 17%)
Education differs; improvements for natives.
Changing racial and ethnic distributions.
Citizenship correlated with time in the country
and has declined over time.
Figure 3.
Fraction Immigrant in Institutions
0.18
0.16
0.14
Fraction Immigrant
0.12
0.1
Fraction Immigrant Non-Institution
Fraction Immigrant Institution
0.08
0.06
0.04
0.02
0
1980
1990
Year
2000
Figure 5. Institutionalization by Age
0.045
0.04
Fraction Institutionalized
0.035
0.03
Native-born 2000
Native-born 1990
0.025
Native-born 1980
Recent Immig 2000
0.02
Recent Immigs 1990
Recent Immigs 1980
0.015
0.01
0.005
0
18
19 20
21 22
23 24
25 26
27 28
29 30 31
Age
32 33
34 35
36 37
38 39
40
Table 2.
Institutionalization across Cohorts
1980
1990
2000
Natives
0.0135
0.0217
0.0345
Immigrants
0.0042
0.0107
0.0068
1996-2000
0.0037
1991-1995
0.0050
1985-1990
0.0068
0.0072
1980-1984
0.0117
0.0106
1975-1979
0.0029
0.0117
0.0096
1970-1974
0.0036
0.0128
0.0141
Table 3. Stacked Logit
(0)
(1)
(2)
(3)
(4)
Immigrant -0.0251
1996-00
-0.0208
-0.0137
-0.0116
-0.0117
1991-95
-0.0192
-0.0130
-0.0111
-0.0113
1985-90
-0.0162
-0.0118
-0.0105
-0.0108
1980-84
-0.0094
-0.0083
-0.0083
-0.0089
1975-79
-0.0082
-0.0073
-0.0075
-0.0082
1970-74
-0.0012
-0.0031
-0.0052
-0.0062
Three Hypotheses
 Deportation
 In 1994 and 1996, expanded list of crimes for
which could be deported.
 Increased resources for deportation.
 Concerned with mechanical effect on
institutionalization rates.
 Deterrence
 Due to above or general increase in punishment.
 Selection
 Changes in welfare, criminal justice, or economy
could have made US less attractive to certain
potential migrants.
Use Cohort / Time Variation
 To test hypotheses, need estimates of
institutionalization of cohorts that
vary by period.
 Run separate logits by year and
compare cohort effects across
periods.
Ii  a90 + b390 ( c85-90 )i + ... + b990 ( c50-59 )i + 0 ( X )i + ei 0
Ii  a00 + b100 ( c96-00 )i + b200 ( c91-95 )i + b300 ( c85-90 )i + ... + b800 (c60-64 )i + 00 ( X )i + ei 00
Table 4. Synthetic Cohort
(1)
(2)
(3)
(4)
1985-90 -0.0074 -0.0043 -0.0039 -0.0043
1980-84 -0.0086 -0.0042 -0.0036 -0.0041
1975-79 -0.0098 -0.0042 -0.0036 -0.0040
1970-74 -0.0075 -0.0025 -0.0025 -0.0031
Deportation Laws and Probability of
Institutionalization of Noncitizens
 “[M]andatory detention now applies to
almost all noncitizens . . . Deportable on
crime-related grounds” (Legomsky 1999).
 INS has removed fewer than 20% of
criminal aliens under criminal justice
supervision (Shuck & Williams 1999).
 Noncitizens served longer prison terms than
natives or other foreign born (Butcher &
Piehl 2000).
 Sanctuary laws also restrict enforcement of
deportation orders (LeDuff 2005).
Citizenship
 Those who just arrived have rates of
“take up” of less than 10%; after 20
years it is 70%.
 2000 recent arrivals have the lowest
rates of all.
 Rates did not increase over years.
 No appearance of negative selection
into citizenship.
Table 4b. Citizens Only
(1)
(2)
(3)
1985-90 -0.0137 -0.0065 -0.0054
1980-84 -0.0140 -0.0072 -0.0060
1975-79 -0.0137 -0.0072 -0.0060
1970-74 -0.0144 -0.0072 -0.0061
Deterrence
 If migration selects people especially
responsive to incentives, might be
more deterred by policy changes.
 General deterrence should affect
citizens and noncitizens, as we saw in
Table 4.
 Compare native-born movers to
immigrants to see if migration selects
for responsiveness.
Table 4c. Movers Only
(1)
(2)
(3)
(4)
1985-90 -0.0030 -0.0013 -0.0015 -0.0019
1980-84 -0.0044 -0.0011 -0.0011 -0.0014
1975-79 -0.0051 -0.0010 -0.0010 -0.0012
1970-74 -0.0034 -0.0000 -0.0003 -0.0007
Changes in Immigrant Selection
 Perhaps migration itself selects for
positive outcomes on criminal justice,
and changes in the 1990s increased
the extent to which this is true.
 Would expect those arriving after
1996 to have the largest change if
the legislation from mid-1990s is
driving the change in selection.
Table 5. Constant Exposure Time
(1)
Fewer
than 5
years
5 - 10
years
(2)
(3)
(4)
-0.0110 -0.0054 -0.0047 -0.0051
-0.0142 -0.0067 -0.0054 -0.0058
Conclusions
 Immigrants are much less likely to be institutionalized
than natives; 1/3 to 1/5 as likely by 2000.
 A version of the Roy model shows that policy changes
may lead to increasingly positive selection.
 Deportation is not driving these findings; naturalized
citizens show the same patterns as immigrants overall.
 Native movers act somewhat like immigrants.
 Those already in the country and newly arrived
immigrants reduced their relative incarceration
probability over the decades.
 The process of migration appears to select for
responsiveness to incentives.
 Results suggest that immigration decision should be
modeled over multiple dimensions.
Extra Slides: Data Validity
Enumeration and Group Quarters
 Enumeration generally done by
administrators for those in institutions.
 Thought to be quite good by Census
staff.
 If anything, undercount of
institutionalized immigrants will be lower
in 2000 than 1990 due to new incentives
to report to INS.
Undercount of Noninstitutionalized
 If undercount in immigrant communities was
less severe in 2000 than in 1990, then
denominator artificially increased and
improvements we see are overstated.
 Robinson et al. (2002) used demographic
analysis to estimate undercount at 1.65% in
1990 and 0.12% in 2000.
 Because this analysis cannot be done for
immigrants, we show how our estimates
change for different assumptions of undercount
for immigrants relative to natives.
Appendix 1. Effect of Assumptions on
Relative Undercount (of noninstitutionalized)
Undercount Ratio
Immigrants : Native-born
Fraction Institutionalized
1990
2000
1:1
0.0105
0.00679
2:1
0.0104
0.00678
3:1
0.0102
0.00678
37:1
0.0067
0.0065
Figure 6. Changes in Metropolitan Area
Crime Rate by Changes in Fraction
Immigrant (1990 to 2000)
1,000
Change in overall crime rate
0
-1,000
-2,000
regression line weighted by MA population
t=-1.82
-3,000
-4,000
-0.02
0.00
0.02
0.04
Change in fraction immigrant
0.06
0.08
0.10
Other Migration Concerns
 Lubotsky (2000) notes re-entrants may be
classified as recent arrivals.
 In wage studies, this leads to
overstatement of secular decline in wages.
 For our setting, if low earners more likely to
be incarcerated then “recent immigrants”
biased up. But it is not clear we can infer
this from wage studies.
 If crime-prone immigrants migrate home
before committing crimes, our results
accurately reflect crimes but not criminality.
Figure 1: Institutionalization and Real Hourly Wages, 2000, by Country
0.04
0.035
U.S.
Fraction Institutionalized
0.03
Dom Rep
Jamaica
0.025
Cuba
0.02
Colombia
Germany
0.015
Haiti
0.01
Italy
Mexico
Canada
El Salvador
0.005 Guatemala
Vietnam
Phil.
England
China
Korea
10
12
14
16
Iran
Japan
India
Taiwan
0
18
Real Hourly Wage
20
weighted regression
line w/o U.S.
22
24
26