in s r h f p a ing th in search of peace: assessing the ... · rl results – m d c rmexico and...
TRANSCRIPT
In S r h f P A ing th In Search of Peace: Assessing the Impact of Violence on Migration from
A h d SLatin America to the United States
Steven Elías Alvarado and Douglas S. MasseyUniversity of Wisconsin, Madison
Princeton University
OOrganization
R i l fRegional focusTheoretical foundationsC i l i dCross national crime dataData & description of sampleM h dMethodsResultsDi iDiscussionLimitations & next steps
2
R l fRegional focus
Mexico
3
R l fRegional focus
Mexico
Guatemala
4
R l fRegional focus
Mexico
Guatemala
Nicaragua
5
R l fRegional focus
Mexico
Guatemala
Nicaragua
Costa Rica
6
Th Theory says…
l International migrationWorld systems theory may be most applicable
Economic/socio-cultural integrationEconomic/socio cultural integration
7
Th Theory says…
l International migrationWorld systems theory may be most applicable
Economic/socio-cultural integrationEconomic/socio cultural integration
Theory on crime in and of itself (Neapolitan 1997)
Modernization theory, opportunity theory, dependency theory, culture/historic traditions, micro-level factors
8
Th Theory says…
l International migrationWorld systems theory may be most applicable
Economic/socio-cultural integrationEconomic/socio cultural integration
Theory on crime in and of itself (Neapolitan 1997)
Modernization theory, opportunity theory, dependency h l /h d l l f theory, culture/historic traditions, micro-level factors
U.S. migration more strongly predicted by violence than economic conditions (Lundquist and Massey than economic conditions (Lundquist and Massey 2005)
Violence as proxy for political motivations
9
C l d Cross national crime data
hQuite touchy(1) Definitions often vary (time and place)
10
C l d Cross national crime data
hQuite touchy(1) Definitions often vary (time and place)
(2) C ’ (2) Countries’ participation varies
11
C l d Cross national crime data
hQuite touchy(1) Definitions often vary (time and place)
(2) C ’ (2) Countries’ participation varies
(3) Inconsistent reporting in overlapping surveys
12
R h QResearch Question
h h lWhat is the impact of violence in Latin America on first migration to the U.S.?
13
R h QResearch Question
h h lWhat is the impact of violence in Latin America on first migration to the U.S.?
H h ld h dHousehold heads
14
R h QResearch Question
h h lWhat is the impact of violence in Latin America on first migration to the U.S.?
H h ld h dHousehold heads
Males onlyFirst migration overwhelmingly maleFirst migration overwhelmingly male
15
DData
( )Mexican Migration Project (MMP)
16
DData
( )Mexican Migration Project (MMP)
Latin American Migration Project (LAMP)
17
DData
( )Mexican Migration Project (MMP)
Latin American Migration Project (LAMP)
National-level homicide data
18
DData
( )Mexican Migration Project (MMP)
Latin American Migration Project (LAMP)
National-level homicide data
19
Mexican Migration Project (MMP)
E h f l d h d Ethno-survey of social, demographic, and economic characteristics of household heads in 118 representative communities throughout 8 ep ese tat ve co u t es t oug out Mexico
20
Mexican Migration Project (MMP)
E h f l d h d Ethno-survey of social, demographic, and economic characteristics of household heads in 118 representative communities throughout 8 ep ese tat ve co u t es t oug out Mexico
Retrospective year-by-year life histories of household heads’ migration experiences
21
DData
( )Mexican Migration Project (MMP)
Latin American Migration Project (LAMP)
National-level homicide data
22
Latin American Migration Project (LAMP)
S l l f MMSimilar sampling frame as MMP
23
Latin American Migration Project (LAMP)
S l l f MMSimilar sampling frame as MMP
Incorporates: Guatemala, Nicaragua, and Costa Rica among other countries in Caribbean Rica … among other countries in Caribbean, Central, and South America
Costa Rica - 7 communities
Guatemala - 11 communities
Nicaragua - 9 communities
24
DData
( )Mexican Migration Project (MMP)
Latin American Migration Project (LAMP)
National-level homicide data
25
Homicide data
C d ll ibl d il Canvassed all possible data sources to compile year-by-year national level data on homicide rates
United Nations Office of Drugs and Crime, Crime Trends Survey
World Health OrganizationPan American Health Organization (WHO affiliate)g (W )INTERPOLNational PoliceD hi di it d h i th C t l Demographic diversity and change in the Central American isthmus , Pebley & Rosero-Bixby (1997)
26
Homicide data
C d ll ibl d il Canvassed all possible data sources to compile year-by-year national level data on homicide rates
United Nations Office of Drugs and Crime, Crime Trends Survey
World Health OrganizationPan American Health Organization (WHO affiliate)g (W )INTERPOLNational PoliceD hi di it d h i th C t l Demographic diversity and change in the Central American isthmus , Pebley & Rosero-Bixby (1997)
27
Homicide data
C d ll ibl d il Canvassed all possible data sources to compile year-by-year national level data on homicide rates
United Nations Office of Drugs and Crime, Crime Trends Survey
World Health OrganizationPan American Health Organization (WHO affiliate)g (W )INTERPOLNational PoliceD hi di it d h i th C t l Demographic diversity and change in the Central American isthmus , Pebley & Rosero-Bixby (1997)
28
Homicide data
C d ll ibl d il Canvassed all possible data sources to compile year-by-year national level data on homicide rates
United Nations Office of Drugs and Crime, Crime Trends Survey
World Health OrganizationPan American Health Organization (WHO affiliate)g (W )INTERPOLNational PoliceD hi di it d h i th C t l Demographic diversity and change in the Central American isthmus , Pebley & Rosero-Bixby (1997)
29
Homicide data
C d ll ibl d il Canvassed all possible data sources to compile year-by-year national level data on homicide rates
United Nations Office of Drugs and Crime, Crime Trends Survey
World Health OrganizationPan American Health Organization (WHO affiliate)g (W )INTERPOLNational PoliceD hi di it d h i th C t l Demographic diversity and change in the Central American isthmus , Pebley & Rosero-Bixby (1997)
30
Outcome
First migration to U.S.
Outcome
First migration to U.S.
Lagged so as to capture previous year’s h ’characteristics’ impact on migrating to U.S.
Outcome
First migration to U.S.
Lagged so as to capture previous year’s h ’characteristics’ impact on migrating to U.S.
1979 – 2003Reliable homicide data halts at 2003
M h d lMethodology
l lDiscrete time survival analysis
34
M h d lMethodology
l lDiscrete time survival analysis
Homicide series modifications
35
M h d l h d Methodology – homicide
( )(1):Linear interpolation to fill in gaps for homicide
F h l f G l d NiFew holes for Guatemala and Nicaragua
36
M h d l h d Methodology – homicide
( )(1):Linear interpolation to fill in gaps for homicide
F h l f G l d NiFew holes for Guatemala and Nicaragua
(2):S h d 3 i Smoothed 3-year moving averages
37
M h d l h d Methodology – homicide
(1)(1):Linear interpolation to fill in gaps for homicide
Few holes for Guatemala and NicaraguaFew holes for Guatemala and Nicaragua
(2):Smoothed 3-year moving averagesy g g
(3):Divided by maximum value for each country
Placed countries on same scale, 0 – 1.0
38
D SDescriptive Stats
Migration Homicide Smoothed Fractional Migration Homicide Smoothed Homicide
Fractional
Homicide
Mean S.D. Mean S.D. Mean S.D. Mean S.D.Mean S.D. Mean S.D. Mean S.D. Mean S.D.
Pooled Sample
.0025 .05 33.75 15.14 33.76 13.22 .84 .18
M i 0025 05 34 14 4 21 34 14 4 03 89 11Mexico .0025 .05 34.14 4.21 34.14 4.03 .89 .11
Costa Rica .001 .03 10.04 1.43 10.04 1.28 .82 .11
G l 001 04 54 48 45 09 54 98 3 29 43 29Guatemala .001 .04 54.48 45.09 54.98 37.29 .43 .29
Nicaragua .0008 .03 44.05 22.81 44.02 15.79 .62 .22
39
R lResults
l d lPooled sample
40
R lResults
l d lPooled sample
Country specific samples
41
R lResults
l d lPooled sample
Country specific samples
42
R l l d lResults – pooled sample
Smoothed Homicide Fractional HomicideSmoothed Homicide Fractional Homicide
Violence Indicator B S E B S EViolence Indicator B S.E. B S.E.
S.H. rate -.012† .006 ---- ----
Fractional Hom. Rate
---- ---- -.802* .352
Controls: Age, Age2, Minors in household, own farmland, own real estate, own business, years of g , g , , , , , yschooling, spouse’s schooling, family in U.S., unskilled manual worker, skilled manual worker, unemployed, spouse employment status, GDP relative to U.S., U.S. Contra involvement, Costa Rica, Guatemala, Nicaragua
† p<.10, *p.<.05, **p<.01, ***p<.001
43
R l l d lResults – pooled sample
Smoothed HomicideSmoothed Homicide
Violence Indicator B S.E.
S.H. rate*Costa Rica -.0325 .1518
S H *G l 0125 0187S.H. rate *Guatemala .0125 .0187
S.H. rate*Nicaragua .0169 .0247
l 2 h h ld l d lControls: Age, Age2, Minors in household, own farmland, own real estate, own business, years of schooling, spouse’s schooling, family in U.S., unskilled manual worker, skilled manual worker, unemployed, spouse employment status, GDP relative to U.S., U.S. Contra involvement, Costa Rica, Guatemala, Nicaragua
† p< 10 *p < 05 **p< 01 ***p< 001
44
† p<.10, p.<.05, p<.01, p<.001
R l l d lResults – pooled sample
Fractional HomicideFractional Homicide
Violence Indicator B S.E.
F.H. rate*Costa Rica .2557 1.9426
F H *G l 6623 1 5179F.H. rate *Guatemala -.6623 1.5179
F.H. rate*Nicaragua .3632 1.2702
l 2 h h ld l d lControls: Age, Age2, Minors in household, own farmland, own real estate, own business, years of schooling, spouse’s schooling, family in U.S., unskilled manual worker, skilled manual worker, unemployed, spouse employment status, GDP relative to U.S., U.S. Contra involvement, Costa Rica, Guatemala, Nicaragua
† p< 10 *p < 05 **p< 01 ***p< 001
45
† p<.10, p.<.05, p<.01, p<.001
R lResults
l d lPooled sample
Country specific samples
46
R l M d C RResults – Mexico and Costa Rica
Mexico Costa RicaMexico Costa Rica
Violence Indicator B S E B S EViolence Indicator B S.E. B S.E.
Fractional Hom. Rate
-1.091 † .599 -2.668** 1.080RateControls: Age, Age2, Minors in household, own farmland, own real estate, own business, years of schooling, spouse’s schooling, family in U.S., unskilled manual worker, skilled manual worker, unemployed, spouse employment status, GDP relative to U.S.
† < 10 * < 05 ** < 01 *** < 001† p<.10, *p.<.05, **p<.01, ***p<.001
47
R l G l d NResults – Guatemala and Nicaragua
Guatemala NicaraguaGuatemala Nicaragua
Violence Indicator B S E B S EViolence Indicator B S.E. B S.E.
Fractional Hom. Rate
-1.145 .847 4.238** 1.419Rate
U.S. Contra Involvement
---- ---- .008*** .001Involvement
Controls: Age, Age2, Minors in household, own farmland, own real estate, own business, years of schooling, spouse’s schooling, family in U.S., unskilled manual worker, skilled manual worker, unemployed, spouse employment status, GDP relative to U.S.
5
48
† p<.10, *p.<.05, **p<.01, ***p<.001
Predicted Probabilities of Migration to U S b F l H d RU.S. by Fractional Homicide Rate
0.006
0.007
0 003
0.004
0.005
MexicoCosta RicaGuatemala
0.001
0.002
0.003Nicaragua
00 0.2 0.4 0.6 0.8 1
Fractional Homicide Level
49
Predicted Probabilities of Migration to U S b F l H d RU.S. by Fractional Homicide Rate
0.006
0.007
0 003
0.004
0.005
Costa RicaNicaragua
0.001
0.002
0.003
00 0.2 0.4 0.6 0.8 1
Fractional Homicide Level
50
DDiscussion
Ni U S i i b di d b Nicaraguan U.S. out-migration may be mediated by refugee status
51
DDiscussion
Ni U S i i b di d b Nicaraguan U.S. out-migration may be mediated by refugee statusCosta Rican out-migration may be to someplace elseg y p
52
DDiscussion
Ni U S i i b di d b Nicaraguan U.S. out-migration may be mediated by refugee statusCosta Rican out-migration may be to someplace elseg y pHomicide rate per 100K much smaller in Costa Rica than other countries
Change in rate ma not be big enough to cause migration to Change in rate may not be big enough to cause migration to U.S.
53
L & Limitations & next steps
d lAdjust for population structure (e.g. proportion age 15-25)
54
L & Limitations & next steps
d lAdjust for population structure (e.g. proportion age 15-25)
Include El Salvador
55
L & Limitations & next steps
d lAdjust for population structure (e.g. proportion age 15-25)
Include El Salvador
Multilevel survival analysis
56