Transcript Module 13 Modeling the Age and Age Composition of Late 19th

Michael J. Greenwood
Many, many papers and books have dealt with historical U.S. immigration
from Europe. These contributions have made solid contributions and
have greatly improved our understanding of why migration occurred
from Europe to the Americas during the 19th and early 20th centuries.
However, virtually all of these studies were concerned with the volume
and rates of movement. Hatton and Williamson ask a much less
studied question: “Who were the migrants?” “Who” could refer to
numerous migrant characteristics, such as age, sex, occupations, and
marital status.
I decided to study the migrant characteristics that I could extract from
published U.S. immigration statistics. My first historical study
concerns age composition.
Most historical studies use 12 European source countries as the origins of
U.S. immigration because we have data for these countries. The data
are not pristine. They are characterized by many problems that must be
acknowledged and dealt with in some way or other.
For the 12 source countries, 3 consistent age groups are available for study
annually for the period 1873-1898:
1. under 15,
2. 15-40, and
3. over 40.
The data indicate considerable differences in the age composition of U.S.
immigration from the various countries. Note the differences across
countries as well as the differences across time for a given country.
Source: Bureau of Statistics (1903, 4358-4360).
Table 1
Age Composition of U.S. immigration from 12 source countries, 1873 and 1898
______________________________________________________________________________
___________________________
Total Immigrants
Percent aged 15-40 Percent aged over 40
Country
1873-98
1873
1898
1873
1898
1873
1898
Belgium
43,651
1,176
695
72.9
63.3
9.6
18.4
Denmark
161,252
4,931
1,946
69.0
79.1
11.4
9.4
France
142,810
14,798
1,990
64.8
72.7
19.1
15.9
Germany
2,455,519
149,671
17,112
61.6
70.2
12.9
12.3
Ireland
1,304,275
77,344
25,128
73.2
88.7
9.3
6.2
Italy
834,202
8,757
58,613
67.4
64.2
15.8
15.4
Netherlands
96,392
3,811
767
50.8
58.9
15.3
15.4
Norway
330,054
16,247
4,938
46.7
79.6
29.7
10.2
Spain
14,515
541
577
74.5
71.9
13.5
21.5
Sweden
682,767
14,303
12,398
62.8
84.0
15.6
7.6
Great Britain 1,502,759
89,482
12,893
62.8
67.1
14.3
15.9
Portugal
22,759
24
1,717
70.8
63.1
16.7
12.6
1. Younger immigrants have more years to contribute to the U.S. economy
(i.e., they have longer expected working lives).
2. Younger immigrants assimilate more rapidly, in part because they learn
English more quickly.
3. Because they learn English more rapidly, their labor productivity and
earnings also grow more rapidly. Thus, younger individuals not only
contribute to the U.S. economy over a longer time period, but also they
contribute more on an annual basis.
4. Birth rates of women are highest for roughly the same ages that
migration propensities are highest. Thus, age in combination with sex
increases the potential population of second generation immigrants.
5. Through the marriage market, even young male migrants may
influence subsequent population growth.
6. Skill is a function of age, so older immigrants tend to arrive with higher
skill levels.
7. Older immigrants who do not participate in the work force may
constitute a burden.
8. Very young immigrants impose costs on society that are not recovered
for some years. These costs are mainly due to education.
Dorothy Swain Thomas in her 1938 discussion of “age ” differentials
argues that “of all the gaps in our knowledge of the operation of ageselective migration, the most important are:
1. Our lack of precise information as to the operation of varying
economic and social structure upon age selection…
2. Our lack of precise information as to the operation of distance
as a factor limiting or extending the range of age-selective migration…
3.Our lack of any information at all as to the operation of
upswings and downswings in economic conditions upon age-selective
migration.”
To this day, very little analytical work has ever been done to address these
issues. Thus, I attack them in the context of historical U.S. immigration
from Europe, where countries rather than communities provide the
spatial dimension.
I estimate 3 models, one for the migration rate of the 15-40 age group, a
second for the migration rate of the over 40 age group, and a third for
composition (percentage of immigrants 15 and over who were 14-40).
Each models contains 3 sets of variables:
1. Differential economic opportunity,
2. Cost of migrating, and
3. Control variables.
1.
Differential economic opportunity
a. relative real wage, t-1 (i/US)
b. relative growth of GDP (US/i)
c. percent manufacturing
d. percent agriculture
Cost of migrating
a. total migration prior 2 years
b. birthrate in i
c. English spoken in i
d. Southern Europe
e. distance from i
Control variables
a. population 15-39 of i
The marginal migrant
Sources: Relative (international) real wage (Williamson, 1995); relative growth of GDP (Maddison, 2003); percent manufacturing in i (Mitchell, 1992); percent agric
Table 2
Means and Standard Deviations
_______________________________________________________________________
_______________
Variable
Mean
Std. dev.
Relative real wage, t-1 (i/US)
0.424
0.152
Relative growth of GDP, avg. t-1 to t-3 (US/i)
1.020
0.035
Percent manufacturing in i
0.237
0.068
Percent agriculture in i
0.475
0.188
3
Total migration prior 2 years (x10 )
24.751
35.789
Birthrate in i (per thousand)
31.612
4.465
English spoken in i
0.167
0.373
Southern Europe
0.250
0.434
Distance from i to U.S. (x103)
3.670
0.315
6
Population of i, 15-39 (x10 )
6.192
6.084
Population of i, over 39 (x106)
4.593
4.528
2
Percent pop. 15 and over that was 15-39 (x10 )
0.379
0.013
-3
Migration rate, 15-40 (x10 )
5.210
7.490
Migration rate, over 40 (x10-3)
0.844
1.158
Percent of immigrants 15 and over that was 15-40
85.771
6.073
Table 3
Emigration rates and the age composition of U.S.-bound migrants 15 to 40 and over 40,
1873-1898: Hausman-Taylor instrumental variable estimates
M i g r a t i o n
Age
R a t e s
Composition
Variable
15-40
Over 40
15-40
Differential econ. Opportunity
Relative real wage, t-1 (x1)
-6.391
-4.657
13.653
(1.249)
(4.836)
(2.008)
Relative growth of GDP (x1)
13.422
1.405
-6.473
(1.960)
(1.120)
(0.746)
Percent manufacturing in i (x1)
2.602
-6.975
68.107
(0.264)
(3.710)
(4.995)
Percent agriculture in i (x1)
12.820
-4.593
24.112
(2.472)
(4.399)
(3.068)
Cost of Migrating
Total migration prior 2 years
0.060
0.012
0.005
(x2)
(5.718)
(6.179)
(0.410)
Birthrate in i (x2)
-0.632
-0.016
-1.106
(4.698)
(0.587)
(5.537)
English spoken in i (z2)
9.061
1.480
-4.011
(2.378)
(1.601)
(0.424)
Southern Europe (z1)
-5.928
-1.156
3.829
(2.185)
(1.835)
(0.626)
Distance from i (z1)
4.655
1.585
-1.789
(1.072)
(1.516)
(0.167)
Control variables
Population 15-39 (over 39) of i
-0.416
-0.129
0.060
(x1)
(2.597)
(2.530)
(0.446)
Constant (z1)
-8.521
0.236
99.117
(0.514)
(0.060)
(2.521)
Test for exogeneity of HT
instruments
0.570
0.999
0.829
Let’s summarize the findings along the lines of the issues raised by D.
Thomas.
1. We lack precise information as to the operation of communities of
varying economic and social structure upon age selection.
My findings:
a. Older potential migrants were discouraged by relatively welldeveloped manufacturing sectors in source countries.
b. Younger migrants tended to originate in source countries that
were more agricultural.
c. Older migrants tended to come from less agriculturally
oriented countries.
2. We lack precise information as to the operation of distance as a factor
limiting or extending the range of age-selective migration.
My findings
a. Older migrants tended to come from more distant countries.
b. Younger migrants also tended to come from more distant
countries, so composition was not much influenced by
distance.
3. We lack any information at all as to the operation of upswings and
downswings in economic conditions upon age-selective
migration.
My findings
a. Both younger and older migrants responded to economic
incentives, but in different ways:
i. Older potential migrants were discouraged from
leaving high-wage countries.
ii. Younger persons responded strongly to superior job
opportunities in the U.S.