1. 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

2. 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: 0.0091980: -0.0971990: -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.

3. 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.

4. Cross-sectional Experience

5. Figure 4. Predicted Institutionalization for Immigrants

6. 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.

7. 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.

8. Results Preview  We will see that immigrants have lower institutionalization rates than the native- born – 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.

9. Model of Immigrant Self-Selection  Roy (1951) reformulated in Borjas (1987)  I=(             are mean log wages in host and source countries     are deviations of earnings in the two countries is cost of migration divided by the wage in the source country (“time cost” of migration)  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

10. 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,  =f(        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.”

11. Data: U.S. Censuses, ’80, ’90, ‘00  We examine institutionalization among 18- 40 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.

12. Figure 3. Fraction Immigrant in Institutions

13. Figure 5. Institutionalization by Age

14. Table 2. Institutionalization across Cohorts 1980 19902000 Natives 0.0135 0.02170.0345 Immigrants 0.0042 0.01070.0068 1996-20000.0037 1991-19950.0050 1985-19900.00680.0072 1980-19840.01170.0106 1975-19790.00290.01170.0096 1970-19740.00360.01280.0141

15. 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 -0.0089 1975-79-0.0082-0.0073-0.0075-0.0082 1970-74-0.0012-0.0031-0.0052-0.0062

16. 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.

17. 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.

18. 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 -0.0031

19. 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).

20. 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.

21. 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

22. 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.

23. Table 4c. Movers Only (1)(2)(3)(4) 1985-90-0.0030-0.0013-0.0015-0.0019 1980-84-0.0044-0.0011 -0.0014 1975-79-0.0051-0.0010 -0.0012 1970-74-0.0034-0.0000-0.0003-0.0007

24. 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.

25. Table 5. Constant Exposure Time (1)(2)(3)(4) Fewer than 5 years -0.0110-0.0054-0.0047-0.0051 5 - 10 years -0.0142-0.0067-0.0054-0.0058

26. 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.

27. Extra Slides: Data Validity

28. 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.

29. 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.

30. Appendix 1. Effect of Assumptions on Relative Undercount (of noninstitutionalized) Undercount Ratio Immigrants : Native-born Fraction Institutionalized 19902000 1:10.01050.00679 2:10.01040.00678 3:10.01020.00678 37:10.00670.0065

31. Figure 6. Changes in Metropolitan Area Crime Rate by Changes in Fraction Immigrant (1990 to 2000) -4,000 -3,000 -2,000 -1,000 0 1,000 -0.020.000.020.040.060.080.10 Change in fraction immigrant Change in overall crime rate regression line weighted by MA population t=-1.82

32. 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.