globalisation versus de-coupling: german emigration and the evolution of the atlantic labour market...

Explorations inconomic History
E
Explorations in Economic History 40 (2003) 387–418

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Globalisation versus de-coupling:German emigration and the evolution ofthe Atlantic labour market 1870–1913q

Oliver Grant

University of Oxford, Nuffield College, New Road, Oxford OX1 1NF, UK

Received 28 May 2002

Abstract

The decline of German emigration to the United States after 1895 was precipitate to a de-

gree not matched by other ‘‘old immigration’’ sources. The paper considers possible reasons

for this: the effect of land availability, relative growth rates of the US and German economies,

and the impact of the so-called ‘‘new immigration’’ from southern and eastern Europe. It con-

cludes that German immigration was unusually affected by competition from newer migrant

sources, due to skill similarities and similar patterns of settlement. However, the more rapid

growth of the German economy after 1895 and the movement of the land frontier into areas

less suited to German agricultural skills also played a part. It shows that the skills possessed by

migrants were an important factor in migrant earnings. The arrival in the US of large numbers

of immigrants with similar skill endowments and lower reservation wages made emigration to

the United States a less attractive option for potential German migrants after 1895.

� 2003 Elsevier Inc. All rights reserved.

Keywords: German emigration; United States immigration; Migrant skills; Migrant occupations

qThis article is based on Chapter 6 of my thesis, Grant (2000). I would like to thank my supervisors,

Charles Feinstein and Hartmut Pogge von Strandmann for many helpful suggestions. Comments on

earlier drafts were also received from James Foreman-Peck, Mark Thomas, Tom Nicholas, Hans-Joachim

Voth, participants at a seminar at St. Anthony�s College, Oxford, three anonymous referees, and the editor

of this journal. Thanks are due to all of these.

E-mail address: [email protected].

0014-4983/$ - see front matter � 2003 Elsevier Inc. All rights reserved.

doi:10.1016/S0014-4983(03)00047-0

mail to: [email protected]

388 O. Grant / Explorations in Economic History 40 (2003) 387–418

1. Introduction

The view of globalization as an inexorable process, which only World Wars and

their accompanying disruptions can interrupt, is well-established in the popular con-

sciousness. Economic historians have contributed to this view, particularly when as-sessing the movement of the World Economy in the nineteenth century. According

to Williamson and O�Rourke, in the late nineteenth century the Atlantic Economy

moved towards integrated factor and commodity markets. The main driving force

which produced real wage convergence was mass migration, not capital flows or

technological convergence.1

But the convergence story has some serious flaws. In particular there was little real

wage convergence between the largest economies. Using O�Rourke and Williamson�spreferred measure, there was only a small fall in real wage dispersion between Brit-ain, Germany and the United States between 1870 and 1913. Far from there being a

general ‘‘collapse of the wage gap between Europe and the New World,’’ real wages

in Britain and Germany remained stuck at around 65 and 52% of the US level re-

spectively.2 Removing these large countries turns the convergence story into one

which primarily concerns the smaller economies of the European and non-European

periphery: Ireland, the Scandinavian countries, Spain, South America. While this is

still an important story, the weight of these economies in world GDP was not as

large as that of Britain and Germany. Convergence was not ‘‘ubiquitous in thelate-nineteenth century Atlantic economy.’’

The lack of convergence between real wages in Britain and the United States

can be explained by the unusual status of the British economy: the familiar story

of the loss of technological leadership and intensified competition on world mar-

kets. The German case is more difficult to dismiss. Germany was, in many respects,

a successful economy: rates of growth in GDP were high, technological advance

was rapid. Yet the real wage gap with the United States was not reduced. There

are a number of factors which contributed to this. Germany�s decision to switchto agricultural protection held back grain imports and raised domestic food costs.

Germany also suffered from adverse terms of trade movements from the mid 1890s

onwards, which meant that rapid industrial growth was not translated into equiv-

alent rises in living standards. These were undoubtedly important influences. But in

themselves they would not have managed to hold back wage convergence, if migra-

tion had been sufficiently strong to have a major effect on wage levels in both

countries. This article will focus on the course of migration, and seek to explain

why this factor did not operate in such a way as to bring about real wage conver-gence.

For nearly half a century, from the mid 1850s to the early 1890s, Germany

provided more migrants to the United States than any other source. In 1895 Ger-

many lost this position and it was not regained. The fall in German emigration to

1 O�Rourke and Williamson (1999, pp. 165–166).2 Ibid p. 15.

O. Grant / Explorations in Economic History 40 (2003) 387–418 389

the United States was precipitate, falling 76% from 1881 to 1895. This discon-

nected the German labor market from developments in the Atlantic economy;

the main link between conditions in Germany and in those in the United States

was severed.

For Germany, the effect of the decline in emigration to the US was intensified bytwo additional factors. Firstly, the United States had always taken the bulk of Ger-

man migrants: 90% of all emigrants from 1871 to 1913 went to the US. British mi-

gration switched to the Empire, which took 65% of those leaving in 1911–1913 (up

from 28% in 1891–1900). By contrast, the percentage of German migrants going to

the United States did not drop below 80% in any year before 1914.3

Secondly, Germany began to take in substantial numbers of migrants from East-

ern and Central Europe. The result was that Germany became a country of net im-

migration, at an annual rate of 2.45 per thousand in the 1900–1913 period, at a timewhen Britain had an annual rate of net emigration of 3.31 per thousand. In this re-

spect Germany was well ahead of other European countries.4 Britain did not start to

make net gains through immigration until the 1970s. This development strengthened

ties between Germany and the more backward economies of eastern and central Eu-

rope. Germany was de-coupled from the ‘‘globalizing’’ Atlantic economy and in-

stead integrated with the economies of central Europe. This brought with it

advantages for German industry, which could export advanced industrial goods to

these markets. But it also brought increased supplies of unskilled labor which com-peted on German labor markets with German workers and held down wages.

2. Migration and factor price convergence

In the factor price convergence story migration involves the transfer of labor, an

undifferentiated factor possessing no special qualities or attributes. But in practice

migrants were not undifferentiated—many possessed specific skills which were inparticular demand in the recipient countries. Migration flows depend heavily on

the existence of pioneer groups who have strong reasons to move. These then ‘‘break

the ground’’ for others to follow, leading to the well-researched phenomenon of

chain-migration. The initial reasons may be political or religious, or they can be eco-

nomic. The perception of unique opportunities for specific packages of skills will en-

courage groups possessing these skills to move to areas where there is the prospect of

unusually high rewards.

It follows from this that the human capital aspect of migration is at least as im-portant as the unskilled wage gap, possibly even more so. To understand migrant

flows it is necessary to consider what skills migrants possessed and what the oppor-

tunities were for groups possessing these skills. These will be affected by industrial

3 British figures from Thomas (1973, p. 57); the German figures are calculations using figures for

migrant destinations from the Statistisches Jahrbuch des Deutschen Reichs.4 Hatton and Williamson (1996, p. 536).


developments leading to the rapid growth of particular industries, by geographical

factors such as climatic conditions in areas of current settlement, and by competition

from other migrant groups possessing similar skills especially if these are prepared to

work for lower wages.

Incentives to migrate will be highest when the distribution of skills possessed bythe country of origin differs radically from that in the recipient country. But as

the migrant flow continues, there will be a gradual convergence of the skill patterns

in the two countries. This will arise partly because of the build-up of the migrant

stock in the recipient country, and also because migrants will transfer skills to their

own children and to other workers in the industries or regions where they congre-

gate.

There are two implications of this view of migration which differ radically from

the conventional ‘‘factor price’’ driven model. The first is that ‘‘skill-transfer’’ migra-tion will be a limited flow of finite duration, which may come to an end long before

factor price equalization has been achieved. It is a response to a temporary imbal-

ance between skill distributions and opportunities. Once these have been rectified,

the flow will decline and, quite possibly, largely cease. The transfer of labor may well

be insufficient to make more than a small impact on the overall pattern of factor re-

turns in the two countries. The second implication is that in the declining phase the

size of the migrant stock will start to exert a negative effect on the migrant flow, con-

trary to the prediction of the ‘‘chain migration’’ models. As the recipient country be-comes saturated with the skills offered by a particular migrant group, there will be a

fall-off in the rate of migration.

The main finding of this paper is that the decline in German migration to the

United States after 1895 can be attributed to these factors. German migrants pos-

sessed specific skills and attributes which made them well suited to the require-

ments of the US labor market in the mid-nineteenth century: they had a

preference for agricultural work, particularly dairying; they had certain artisan

and tradesmen skills which were in demand in US cities at the time. But in the finaldecade of the century, German migrants faced increased competition from new

migrant sources, which had similar skills and patterns of settlement. The migrant

flow was brought to an end before it could have exerted a major influence on

factor returns.

3. Reasons for the fall in German migration to the United States

Fig. 1 gives the story of German emigration to the United States. Only moves

from Germany to the United States are given, there are no figures for return migra-

tion before 1909. The chart includes two series for German migration to the United

States, one from German sources and the other from US immigration records. The

two sources agree relatively well. Between 1890 and 1900 there is little difference. Be-

fore 1890 the discrepancy is probably due to gaps in the German records. After 1900,

the difference is less easy to explain. The US authorities may have classified a number

of German-speaking immigrants from Russia as Germans. This could explain why


the discrepancy rose after 1900. Some travelers, intending to stay for a limited pe-

riod, may also be classified as immigrants in the US figures.5

The migration figures show three main peaks: in the early 1850s, in the late 1860s

and early 1870s, and in the 1881–1893 period. After this, German emigration to the

United States remained at a low level. The fall was a sudden one, although this wasnot unprecedented—there were other falls in the 1850s and 1870s which were as

steep—but what was new was that there was no recovery to the levels previously

reached. Instead the rate of migration remained low and fluctuated relatively little.

Fig. 1 also gives the US–German wage ratio, calculated from Williamson�s seriesin purchasing power parities. There was a major disturbance to this series in the

1860s, as a result of the American Civil War. Once allowance is made for this, it

is clear that there is no evident tendency for wages in the two countries to converge,

and that the reduction in migration does not appear to have been a response to anarrowing of the wage gap.6

The decline of German immigration was part of a general change in the structure

of US immigration. Table 1 gives some figures for other well-established migrant

sources, together with figures for the ‘‘new immigration’’ from eastern and southern

Europe.

The decline of German migration was paralleled by similar declines in migration

from other ‘‘old migration’’ sources, the Scandinavian countries being the main ex-

ception. The German decline was, however, considerably steeper than the decline inBritish or Irish immigration. Moreover, British and Irish emigrants shifted to other

destinations, such as Canada or Australia.

The table also suggests one possible explanation for the decline in migration from

Germany and other ‘‘old migration’’ sources: displacement by ‘‘new migration’’

sources. The total volume of immigration into the United States did not fall; the falls

in migration from Germany and other countries were more than made up by in-

creases in immigration from eastern and southern Europe.7

The exceptional nature of the decline in German migration is also revealed bymaking use of the equation estimated by Hatton and Williamson for the movement

of migration from various countries in the period 1850–1913. The equation is

5 T

Europ

throug

1900.6 Im

O�Rou7 T

setting

immig

Mit�1 ¼ �4:66� 3:58Sait � 6:07 logðWhit=Wf itÞ þ 0:32RNIit�2 þ 0:012MSTit

þ 0:40Mit1;

here are large discrepancies in statistics of German migration 1900–1913 for all the major non-

ean destinations. These are discussed in Burgd€oorfer (1929). One problem was German emigration

h British ports, but there is no obvious reason why this should only have caused difficulty after

portant studies on convergence in the international economy of the late 19th century include

rke et al. (1996) and Taylor and Williamson (1997).

he effect of the new immigration on labour markets was a major concern at the time, leading to the

up of the Immigration Commission, see Herbert (1990), also Jenks and Lauck (1926). The effect of

ration had on wages has been demonstrated by Goldin (1994).

Table 1

Gross emigration to the United States (annual averages)

1881–1895 1896–1910 % Change

‘‘Old migration’’

sources

Britain 61,398 40,142 )34.6Ireland 58,846 33,352 )43.3Scandinavia 60,073 62,069 +3.3

Other N.W. Europe 18,973 15,150 )20.3Germany 123,374 29,934 )75.8

‘‘New migration’’

sources

Central Europe 42,077 164,674 +291

Russia and Eastern

Europe

31,506 135,999 +332

Southern Europe 43,088 180,517 +319

Note. Figures from US Department of Commerce (1975, pp. 105–106); the terms ‘‘new’’ and ‘‘old’’

migrants are avoided by some on the grounds that the former implies a sense of inferiority, Hatton and

Williamson (1998, p. 129). They are used here on the grounds of convenience. Central Europe includes

Russian Poland, Austria–Hungary, and Serbia; Eastern Europe includes the rest of Russia, Romania,

Bulgaria, and Turkey in Europe.

Fig. 1. Annual German emigration to the United States and the US–German wage ratio. The left-hand

axis measures annual migration in thousands. The broken line gives German immigration from US

sources, US Department of Commerce (1975); the dotted line gives emigration to the United States as pub-

lished annually in the Statistishes Jahrbuch des Deutschen Reichs. The right-hand axis measures the US

German wage ratio, calculated from Williamson (1995, pp. 164–167). The source for the German wage

data is a series for unskilled building wages in Rostock, Nuremburg and Berlin, originally collected by

Robert Kuczynski, also published in Kuczyinski (1945) and Bry (1960).


Fig. 2. Actual and predicted migration from Germany to the United States, 1870–1913 (decade averages

as percentages of the total German population).


where Sa, share of agriculture in the country of origin; RNI, rate of natural popu-

lation increase; MST, migrant stock in the recipient country; Wh/Wf, wage ratio,

domestic to foreign.8

Fig. 2 gives the results when this is applied to the movement of German migration

to the United States. The figures are for gross migration only. As can be seen fromthe diagram, the equation (which works well for most countries) predicts only a

slight decline in German migration after 1900. Wages had not converged. Demo-

graphic pressure remained high (the German rate of natural population increase

peaked at 1.5% per annum in the years around 1900); the collapse which actually oc-

curred is not predicted by this equation.

The much greater fall in German migration to the United States suggests the op-

eration of some factor which had a disproportionate effect on potential German mi-

grants. There are four possible areas that are worth consideration:1. the effect of changes in agricultural conditions;

2. the effect of real wage movements;

3. the extent to which German migrants were in direct competition with new mi-

grants;

4. the effect of economic growth in Germany relative to the United States.

8 Hatton and Williamson (1996, p. 548, table 3, column 1), also Hatton and Williamson (1998).


If agricultural conditions were unusually important for German migrants then

they may have had a higher preference for agricultural work. The recorded occupa-

tions of migrants in the U.S. census returns show that relatively few found work in

agriculture immediately. German migrants had a stronger preference for farming

than some other groups, notably the British. By 1910 German migrants were twiceas likely as British migrants to be farmers, having started from a position of equality

in 1870. However, only a relatively small proportion of German migrants eventually

became farmers or farm workers. If the 4.9% of the German-born workforce who

were farm-workers in 1910 is added to the numbers for farmers, the total is only

22.3%, which is well below the equivalent figure for the US as a whole (35.1%). Most

German migrants were in non-agricultural jobs.9

However, this comparison may well under-estimate of the importance of agricul-

tural opportunities to German migrants. A much higher proportion may have emi-grated hoping to become farmers eventually. Moreover, the establishment of new

German-speaking agricultural settlements would have produced additional opportu-

nities for German artisans and tradesmen. If there had been a drop in the rate at

which such settlements were formed, then fewer jobs in related trades and industries

would have been created.

There were at least two agricultural changes which had an effect on German im-

migration. The first was an improvement in agricultural conditions within Germany,

which resulted from a general rise in world commodity prices, helped by tariff pro-tection for German agriculture. German land values rose by 27% between 1895 and

1905.10 The second was the movement of the area of recent settlement to more arid

areas further west, which were less well suited to German skills in areas such as dairy

farming. Texas, for example, accounted for 24% of the total increase in the farmed

area 1890–1910, but only 1.4% of German migrants 1899–1913 gave it as their in-

tended destination.11 The opportunities available in Texas, such as cotton-growing

and cattle-ranching, required skills which German migrants were unlikely to possess.

However, the movement of the area of settlement to the west did produce someopportunities which should have suited German farmers. One example was the ex-

pansion of sugar-beet production in California, Idaho, Utah and Colorado in the

1900s. Yet, although this was certainly an area of German expertise, it was Ger-

man-speaking migrants from Russia, along with Italians and Scandinavians, who

were the ones to take advantage, of this opportunity. While this evidence is anec-

dotal, it suggests that the rigors of pioneer agriculture were less attractive to German

migrants after 1900.12

9 Census results from US Department of Commerce (1975) and Hutchinson (1956).10 Source for German land prices is Hoffmann (1965, pp. 569–570).11 Migrant destinations from US Immigration Commission (1910–11); agricultural area from Dodd

(1993).12 Described in US Immigration Commission (1909–10, part 25, vol. 1) ‘‘Immigrant labour in

Californian Agricultural Industries,’’ Chapter 2, ‘‘Beet sugar in the West’’ and also in vol. 2 ‘‘Immigrant

Farmers in the Western States.’’


The issue of real wage convergence needs to be addressed in a way that broadens

the comparison to include as many occupations as possible. The ratio used in Fig. 1

is based on a series of figures for the wages of unskilled building workers in Berlin,

Rostock and Nuremberg, originally collected by Robert Kucyzinski. Kucyzinski also

compiled figures for a wider range of occupations in Europe and America, but theseare only available for a limited number of years. They do however make it possible

to consider the question of convergence for skilled as well as unskilled workers, and

for other areas besides construction.

There are three main conclusions which can be drawn from Table 2. The first is

that the real wage gap is larger for construction than for manufacturing, so the ratio

shown in Fig. 1 may overstate the difference between Germany and the United

States. The second is that, whereas there is a larger wage gap for skilled building

workers than for unskilled in construction, this does not appear to be the case inmanufacturing. However, there are some major differences by industry and by skill

Table 2

Real wage ratios (converted using purchasing power parities) for different occupations, US–Germany,

1890–1893 averages compared to 1900–1903

1890–1893 1900–1903 1890–1893 1900–1903

Construction-skilled Manufacturing-skilled

Bricklayers 2.91 2.94 Cabinet-makers 1.71 1.40

Plasterers 2.33 2.53 Wood carvers 1.47 1.36

Carpenters 1.89 2.01 Machinery

operators

(furniture)

1.29 1.20

Painters 2.08 2.59 Pattern-makers

(foundries)

1.86 1.92

Plumbers,

Electricians,

2.64 2.95 Foundry operators 1.48 1.67

Gas-fitters Mechanical

engineers

1.76 1.74

Stonemasons 3.13 3.09 Boiler-makers 2.01 2.05

Compositors 1.65 1.68

Printing press

operators

1.82 1.91

Unweighted

average

2.50 2.69 Unweighted

average

1.67 1.66

Construction-unskilled Manufacturing-unskilled

Bricklayers

assistants

2.33 2.54 Foundry assistants 2.14 2.14

Laborers 1.77 1.72 Laborers

(engineering)

1.46 1.60

Unweighted

average

2.05 2.13 Unweighted

average

1.79 1.87

Note. Figures calculated from Kuczyinski (1913), who made use of the results of a US Labor De-

partment survey of earnings for different occupations in 12 US cities and attempted to provide equivalent

figures for Germany.


category. The third is that there is no general trend towards wage convergence. In

fact there is a widening of the gap in 13 categories, while it narrows in only 6.

The table shows that premia were higher in some categories than others. Where

skills were in short supply in the United States, or demand was high, US wages were

as much as three times as high as in Germany. In other sectors the difference wasmuch less. This shows that the skill endowments of potential migrants can be impor-

tant. If these were applicable in industries with high growth rates then migration

flows would tend to increase, or be maintained at a high level.

To summarize, it does not appear that real wage convergence either at the aggre-

gate level given in Fig. 1, or at the disaggregated level shown in Table 2, was a factor

in the fall in German emigration. Changes in agricultural conditions probably played

a role—the shift of the area of recent settlement to the west may well have reduced

opportunities for German migrants—but the general conclusion on this point is thattoo few German migrants ended up in farming for this to have been the whole story.

The main focus of the article will be on the remaining points: the impact of the new

immigration and the effect of changing economic conditions inside Germany and the

United States.

The next two sections will look at the first of these points. Much depended on the

characteristics of new migrants: their skills and the areas they chose for settlement. If

they had similar skills to German migrants (or both were unskilled) then they com-

peted for the same jobs, and, assuming that the new migrants were prepared to ac-cept lower wages, the effect would be to deter potential German migrants. If

Germans had different, or complementary, skills, then their position would be less

affected and could even be enhanced.13

Geography also mattered. If labor markets were not perfectly integrated, then a

migrant group with a distinct geographical profile would be less affected than one

which had tended to go to the cities and regions also favored by the new migrants.

4. Skill differences and the course of migration

Although the popular myth is that American industrialization was the product of

Yankee ingenuity and a largely unskilled immigrant workforce, in the early stages

American industry owed a lot to skill transfer brought about by migration.14 The

twenty industry studies published as part of the 1911 Immigration Commission Re-

port provide examples of this process at work: the Cornish in mining, the Welsh in

iron and steel, migrants from Lancashire in textiles, from France in silk, from Bel-gium in glass manufacture, from Cuba in cigars and tobacco: groups such as these

13 This point is debatable. A flood of unskilled migrants might encourage the development of ‘‘de-

skilled’’ mass production technology, which would hit the position of skilled workers in the medium term,

even if the immediate effect had been to raise skill premia. On the other hand, mass production machinery

requires skilled workers to build the machinery in the first place.14 Erickson (1957).


bought particular skills and knowledge which were not otherwise available in the

United States at the time.

One example which is particularly striking is the plate glass industry. In the mid

1880s the Belgian system of manufacture was introduced in Pennsylvania. The result

was the importation of large numbers of Belgian workers, for, as the ImmigrationCommission report put it: ‘‘There were no skilled American workmen to be secured

as the plate glass industry was new in America. The importation of foreign workmen

was thus indispensable in establishing the plate glass industry in this country.’’15 The

report gives instances of factories which were initially dominated by Belgian work-

ers: 40% of the workers in a factory in Arnold, Pennsylvania in 1892; 50% in another

in Creighton, Pennsylvania; 75% of the employees of a works in Jeanette, Pennsyl-

vania, up to 1903.

But the dominance of the Belgians did not last. The strength of their unions wasbroken in a series of strikes and lockouts in the early 1900s, and they were replaced

by more recent migrants (Poles, Italians and Slovaks) who were cheaper and less un-

ionized. By 1908 most of the Belgian workers had left the industry.

What makes this example stand out is the fact that, in general, Belgian migration to

theUnited States was not large; Belgiumwas a small country and had one of the lowest

rates of emigration of all European countries in the period. It was however one of the

first industrializing economies in continental Europe, and so an important source of

advanced industrial skills. By contrast, although Germany provided a much largernumber ofmigrants, the census returns show that relatively few of these were advanced

industrial occupations. Table 3 gives themost common occupations forGerman immi-

grants in 1870, defined as thosewith a density ofGerman immigrantsmore than 3 times

their share in the workforce as a whole (an index of over 300).16

The table shows a number of ‘‘clusters.’’ One is in the production and retailing of

food, alcohol and tobacco. Another is in crafts like copper-working, engraving, gun-

and lock-making, and carpentry. Music and musical instruments and retailing and

tailoring of clothing are two additional clusters. In farm work, German migrantshad a relative skill advantage in dairy farming, which affected the regional distribu-

tion of German migration.17 The figures in parentheses give the results for British

immigrants which are very different. Only three of the occupations have British in-

dices of over 200 (copper-workers, engravers and gun and locksmiths). By and large

British immigrants offered a different pattern of skills to their German counterparts.

This impression is confirmed by Table 4 which gives the most common occupations

for British immigrants.

In this table the list is dominated by industrial occupations. Some of the differ-ences with Germany are quite marked. British immigrants were 10 times more likely

15 US Immigration Commission (1909–10, part 12) , ‘‘Glass manufacturing’’ p. 27.16 Figures for Tables 3–5 were taken from Hutchinson (1956, pp. 82–84); the 1870 census provided a

particularly detailed breakdown of immigrants by occupation. Later censuses did not provide comparable

data.17 The importance of artisan trades in German immigration has been noted by Walker (1964) and

Kamphoefner (1987).

Table 3

Most popular occupations for German immigrants relative to all workers in 1870

Germans British

Piano makers 596 (134)

Bakers 587 (134)

Traders and dealers in clothing 565 (143)

Musicians 551 (174)

Restaurant-keepers 505 (146)

Cigar-makers 491 (118)

Butchers 446 (195)

Basket-makers 424 (111)

Peddlers 423 (139)

Traders and dealers in cigars and tobacco 422 (85)

Wood-turners and carvers 416 (181)

Cabinet-makers 412 (99)

Milkmen and women 411 (89)

Confectioners 397 (157)

Copper-workers 392 (320)

Gun- and lock-making 382 (229)

Bar-keepers 365 (128)

Distillers and rectifiers 360 (114)

Traders and dealers in liqueurs and wines 341 (137)

Dairymen and women 336 (106)

Coopers 320 (70)

Engravers 315 (426)

Tailors and seamstresses 307 (123)

Barbers and hairdressers 301 (66)

Note. Indices of relative concentration, a value of 100 shows that the German-born proportion equals

the proportion for all workers (figures for British migrants in brackets). Figures from Hutchinson (1956,

pp. 82–84); the 1870 census provided a particularly detailed breakdown of immigrants by occupation.

Later censuses did not provide comparable data.


to become miners, 33 times more likely to work in a print works and 16 times more

likely to work in a knitting or hosiery mill. The timing of industrialization is impor-

tant in the two countries. Britain had a large number of relatively mature industries,

creating a reservoir of skilled industrial labor.18 Germany, however, was an economyin the early stages of industrialization without a large pool of industrial skills. The

qualities of German migrants were, in the main, the skills of artisans and small

tradesmen.

If we consider the least common German occupations, given in Table 5 (defined as

those where the density of German immigrants was below a third of their level in the

18 These US census results have broader implications. They show that Britain was exporting industrial

skills as well as the (rather better known) export of capital. They suggest that both flows may have been a

response to the existence of superior opportunities outside British industry in the period. They also show

that, for all the supposed deficiencies of Victorian technical education, Britain had an exportable surplus

of industrial skills. These observations are supported by US immigration figures, which are available for a

later period. In 1904–1910 3875 British engineers emigrated to the United States (Irish not included). This

was more than any other country contributed. Germany was next with 1770.

Table 4

Most popular occupations for British migrants relative to all workers in 1870

British Germans

Miners 787 (84)

Iron and steel: rolling mill operatives 653 (155)

Print-works operatives 635 (19)

Knitting and hosiery mill operatives 627 (38)

Silk-mill operatives 550 (36)

Bleachers and dyers 519 (215)

Actors 472 (111)

Potters 471 (191)

Tool and cutlery makers 469 (188)

Woolen-mill operatives 465 (68)

Steam-engine makers 461 (134)

Steam-boiler makers 436 (126)

Engravers 426 (315)

Carpet-makers 403 (165)

Machinists 392 (137)

Quarrymen 384 (143)

Cotton-mill operatives 375 (16)

Pattern-makers 356 (129)

Iron and steel: workshop operatives 351 (95)

Iron and steel: furnace operatives 340 (113)

Brass foundry men 329 (145)

Plumbers and gas-fitters 326 (83)

Copper-workers 320 (292)

Gardeners and nurserymen 313 (298)

Engineers and firemen 309 (92)

Paper-layers 301 (194)

Note. Sources and definitions as for Table 3.


working population as a whole), these include a number of occupations where

knowledge of local conditions would be important (pilots and fishermen) and where

English-speaking was an advantage (lawyers, bank officials, railroad clerks and

workers in telegraph companies). The least common occupations for British mi-

grants all featured on the German list as well. Unskilled agricultural labor was

avoided by both groups. On the other hand British immigrants were 23 times morelikely to work in cotton mills.

Although German migrants were not particularly heavily represented in industrial

occupations in general there were some new industries where German skills were in

demand. Two of these categories appeared for the first time in the 1880 census: em-

ployees in chemical works, where German migrants accounted for 22% of those em-

ployed, and sugar-refining, where the German proportion was 46% (German

migrants were 6.5% of the gainfully employed male population in this year). These

were both areas in which German industry had made significant technological pro-gress around the middle of the century.19

19 1880 census results from Hutchinson (1956, tables 25a and 25b).

Table 5

Least popular occupations for German migrants relative to all workers in 1870

Germans British

Pilots 33 (83)

Bank officials 31 (63)

Fishermen and oystermen 31 (68)

Agricultural laborers 30 (27)

Dentists 28 (61)

Clerks and book-keepers on railroads 28 (145)

Farm and plantation overseers 20 (30)

Lawyers 19 (45)

Print-work operatives 19 (635)

Employees of telegraph companies 18 (82)

Cotton-mill operatives 16 (373)

Straw workers 10 (59)

Turpentine laborers 1 (2)

Note. Sources and definitions as for Table 3.


The Immigration Commission report on sugar refining in Boston states: ‘‘ when

the sugar-refining industry began to assume some importance in Boston a demandwas created for skilled sugar workers. This demand was supplied by German work-

men who came to operate the refineries. Some came direct from Germany and others

came from London and Bristol, England. Up to the Civil War the skilled workers in

the industry were practically all Germans.’’20 German domination of sugar-refining

did not last. By 1908 first and second generation German immigrants were only 15%

of the workforce in the plants surveyed by the immigration commission.21

The industry most dominated by German migrants was brewing. In 1880 61% of

brewers and malsters had been born in Germany. In this case the industry was notnew, but there was a shift from top-fermented ales and porters to bottom-fermented

lagers, and this led to the employment of large numbers of German workers.

The butchery skills of German migrants gave them an important role in the estab-

lishment of the Chicago meat-packing industry. According to the immigration com-

mission report on this industry: ‘‘in the early days of the industry, during the years

1875–1880, the Irish and the Germans were considered the best butchers and natu-

rally predominated in this occupation. . .. it was contended that only an Irishman

knew how to cure meat and only a German could make a sausage.’’22 However,in this industry the arrival of new migrants (Poles and Bohemians from 1880 on-

wards) led to a reduction of the numbers of Germans employed. The contention

of the Immigration Commission that older migrants (and American workers) in this

and other industries were ‘‘displaced’’ was contentious at the time and has remained

so since. The industry studies show that this was not always a harmful process. In the

Chicago meat-packing industry ‘‘the Irish and Germans have long since ceased to do

20 US Immigration Commission (1909–10, part 16), ‘‘Sugar refining’’ p. 619.21 Ibid. p. 693.22 US Immigration Commission (1909–10, part 11), ‘‘Slaughtering and meat packing’’ p. 199.


the common labor of the industry and those that remain in the industry are em-

ployed as foremen or skilled workers.’’23 Those that left either went to other cities

to set up the industry there, or moved on to become farmers.

In other industries there was direct displacement, especially where new machinery

made it possible to employ larger numbers of unskilled workers. Even so, the oldermigrant communities frequently retained a strong position in the more skilled occu-

pations. An example of this was the glass industry where German workers were dis-

placed (along with the Belgians) as a result of the mechanization of plate glass and

bottle manufacture but retained a strong position in the tableware section.

Yet, although migrants already established in the industry were able to move ‘‘up

the ladder’’ in some cases, this was more difficult for new arrivals. The displacement

of Germans already living in the United States is a different issue from the displace-

ment of potential migrants living in Germany. Unless these had skills which enabledthem to move directly into better paid occupations, they would face direct competi-

tion from new migrants. There was a danger of being permanently stuck on the lower

rungs of the ladder.

The importance of skills acquired through a period of employment in the same

industry prior to migration can be demonstrated using the results of the industry sur-

veys undertaken by the immigration commission. These provided information on

earnings for 195,343 migrants in 1908. The data are for 688 groups, representing

51 nationalities in 38 categories (drawn from 19 industries some of which were fur-ther subdivided by region or by product).24

A series of regressions were run, in which the dependent variable was the loga-

rithm of group average weekly earnings in dollars for male workers aged 18 years

and over. The results are given in Table 6. The first column gives results obtained

when a set of 38 industry dummies was used; in the second column a full set of

51 dummies for each nationality was added (the dummy coefficients are not

reported). 25

The results are remarkably similar for all variables included in column 2: literacy,speaking English, having previous experience and being resident for at least five

years, all these factors have the effect of raising earnings by 20–21%. The coefficients

are somewhat reduced by the inclusion of the nationality dummies, but they are still

significant. This shows that the results are robust, and that they do measure genuine

effects from the specified variables rather than unmeasured nationality traits. In the

final column, the dummies are dropped and the earnings of workers born in the

23 Ibid. p. 201.24 Data taken from the statistical reports included in each volume of US Immigration Commission

(1909–10). The numbers reporting in the different categories varied. Thus, in the eastern area of the Iron

and Steel Industry report, 3289 male German employees were surveyed, reporting length of residence, 2815

of these had their earnings recorded (and were aged 18 and over), 2190 reported their occupation prior to

migration, 3267 had their literacy recorded and 3263 had their ability to speak English reported. This data

source has been used before, by Higgs (1971) and Hatton and Williamson (1998, Chapter 7). Other studies

of immigrant earnings include Hourwich (1922), McGouldrick and Tannnen (1977) and Hatton (1997).25 A ‘‘resident for over 20 years’’ variable was also included. The results were not significant and the

variable was dropped without much effect on the results.

Table 6

Regressions of group average weekly earnings on group characteristics

With industry

dummies

With industry

and nationality

dummies

No dummies

1 2 3

Constant 2.418 (48.89) 2.494 (34.01) 0.199 (2.14)

Characteristics of immigrant workers

Resident for less than 5 years )0.182 (6.07) )0.157 (4.39) )0.119 (3.95)

Employed in the same Industry before

migration

+0.183 (8.54) +0.150 (5.47) +0.131 (6.57)

Able to read and write +0.188 (4.78) +0.138 (2.87) +0.235 (5.42)

Able to speak English +0.194 (6.30) +0.169 (4.46) +0.233 (7.16)

Industry characteristics:

Log of earnings of white US-born

workers.

+0.748 (22.80)

Number of observations 688 688 688

Standard error of equation 0.103 0.100 0.126

R2 0.781 0.808 0.655

Adjusted R2 0.767 0.779 0.653

F test of regression 57.67 27.93 259.01

Residual sum of squares 6.86 6.01 10.80

Note. T ratios in parentheses. Dependent variable is the log of average earnings for each group

(including all sources, piece work as well as hourly rates of pay), in dollars, for male workers aged 18 and

over; ‘‘US-born workers’’ are white male workers, aged 18 and over, born in the United States whose

father was also born in the US.


United States are included to pick up the normal variation in earnings by industry.

This has some effect on the coefficients: the importance of literacy and ability to

speak English is increased, while the impact of previous employment and length of

residence is somewhat reduced.

The estimated coefficients indicate that migrants employed in the same industryprior to migration had wage premia of between 16 and 20% over similar workers

who had no previous experience. This would represent a significant increase in the

incentive to migrate. An unskilled German worker might expect an increase in real

earnings of 92% following migration; one with previous employment would expect

an increase of 123–130%. The calculations also indicate that human capital transfer,

especially from the ‘‘old migrant’’ sources (the new migrant groups were less likely to

have previous employment), was a factor in American industrialization, and one for

which US entrepreneurs were prepared to pay a premium.German earnings were not as high as some other ‘‘old migrant’’ groups. Table 7

gives some of the characteristics of these groups, together with average earnings and

a weighted average of the earnings of US-born workers of US-born parents,

weighted by the distribution of the migrant group.26 This table shows the importance

26 Calculated from the survey results given in US Immigration Commission (1910–11).

Table 7

Averages for the ‘‘old migrant’’ groups (all industries, weighted by numbers reporting)

% Resident

<5 years

% Previous

employed

% Literate % Speaking

English

Average

earnings

Earnings of

US-born

Germans 12.9 29.7 97.4 88.1 $13.24 $13.67

Irish 8.0 17.1 94.3 100.0 $12.59 $13.19

British 17.3 61.7 98.4 100.0 $14.74 $13.29

Scandinavians 23.1 12.3 98.8 82.5 $14.63 $14.06

Other sources 17.1 22.2 86.4 81.1 $11.72 $12.06

Note. Calculated from the survey results given in US Immigration Commission (1910–11).


of the high rate of previous employment among British migrants: 61.7% had worked

in the same industry prior to emigration. This was more than any other migrant

group with the exception of the French: 69.9% of French migrants had previously

been employed in the same industry.27

The German level of previous employment was lower than the British, which ac-

counts for a difference of 6.4% out of the total difference of 11.3% between British

and German average earnings. The other explanatory variables add 3.4% for a totalexplained difference of 9.8%, but this still leaves an unexplained gap. The distribu-

tion by industry was not an important factor; as can be seen the average earnings

of US-born workers were lower when calculated using British weights instead of

German weights. So the British had an additional advantage, which made it easier

to obtain higher paid jobs.

However, German wages were higher than those for Irish immigrants and the

groups in the ‘‘other sources’’ category. Part of this can be explained by their longer

period of residence, high literacy, and relatively high rate of previous employment.28

The main anomaly in this table were the Scandinavians, whose earnings were higher

than predicted, and higher than US-born workers in the same industries, despite a

relatively low level of previous employment.

Comparison of the nationality dummies estimated from the equation given in col-

umn 4 in Table 6 shows that the earnings of the new migrant groups were below

those of the old migrant groups with similar characteristics employed in the same in-

dustries. This was not just due to the fact that so many of these were recently arrived,

or could not speak English. On average the new migrant groups accepted wages 5.6%below those for similar workers which had emigrated from England. But other

groups had low wages. Irish workers had wages 6.7% below similar English workers;

Germans had wages 2.7% below the English. Irish wages were below those for Poles

who were 5.0% below the English level but above the Greeks and Southern Italians,

27 Amongst British migrants, the Welsh had the highest rate of previous employment, 74.2%, which

therefore exceeded the French level.28 Immigrant groups did not assimilate at the same rate; Kamphoefner has called the Germans

‘‘Musterknaben’’ (star pupils) in this respect, Kamphoefner (1999).


who were the most disadvantaged of the new migrant groups (9.9 and 9.1% below

the English level respectively). 29

This comparison understates the effect of the new migration, as it takes no ac-

count of dynamic effects on wage levels. Wage levels in industries where there were

large influxes of new migrants would have been reduced, leading to falls for all work-ers, not just the new migrant groups.30 The influx of a new group of migrants pre-

pared to accept lower wages threatened the position of the old migrants. The

problem was not so great for those already settled in the United States. They had

made some progress towards assimilation, and would receive the benefits of longer

residency and an ability to speak English. By contrast, newly arrived migrants would

find themselves competing in the same labor markets, and wages in these would be

affected. There were two ways to avoid this: one was to choose a different area of

settlement, another was to offer a distinctive pattern of skills. Broadly speaking,the first option was the one chosen by Scandinavian migrants, the second applied

to migrants from Britain. A third option was to continue migrating, but accept lower

wages. The nationality dummies indicate that this was what happened to the Irish.

Their earnings ranked below those of many new migrant groups (12 of the 16

‘‘new migrant’’ groups had higher estimated dummies). A final option was to cease

to emigrate. And this, it seems, was the one chosen by potential migrants from Ger-

many.

Skill patterns can be observed from the statistics collected by the US immigrationauthorities, which recorded occupations prior to migration. Table 8 is based on a

classification of these as professional, skilled and unskilled.31

This table shows that, for the most part, the new migrants were less skilled than

English or, to a lesser extent, German migrants. Jewish migrants, who had a quite

distinctive skill pattern, were the main exception.32 It also shows that such skills

as were possessed by the new migrants were more likely to be in handicrafts than

in industry, producing a pattern which is closer to the German one than the English.

Very few ‘‘new migrants’’ possessed industrial skills similar to those offered by

29 The nationality dummies are given in Grant (2000, p. 214).30 The data provided by the Immigration Commission are not suited for the study of the impact of new

migration on wages in particular industries or regions. This question has been addressed in Goldin (1994)

which shows here was a substantial negative impact on wages in cities with a high concentration of

immigrants, 1890–1914. Moreover, regional studies of this type will not pick up the overall effect of

immigration on wage levels in the economy as a whole, see the discussion of this point in Borjas (1994, pp.

1695–1700).31 Calculated from US Immigration Commission (1910–11, pp. 100–176); the distinction between

skilled and unskilled is largely that used by the immigration authorities; the subsequent division into

categories (industrial, handicrafts, etc.) follows the author�s classification. The table gives results for the

four largest ‘‘old migrant’’ groups, and the seven largest ‘‘new migrant’’ groups (‘‘nationalities’’ are as

classified by the US immigration authorities).32 Jewish migrants had handicraft skills, and those of tradesmen and merchants. It might be thought

that these would not be appropriate to the requirements of the US economy circa 1910, but this was not

necessarily the case. There were 1013 Jewish photographers admitted 1904–1910, out of a total of 2631 (all

nationalities), an intriguing figure in view of subsequent Jewish success in the cinema industry.

Table 8

Occupations of migrants prior to departure (as percentages of migrants 1899–1910 excluding those with-

out an occupation)

Old migrants New migrants

Irish Scandi-

navians

German English Jewish Italian,

North

Italian,

South

Polish

Professional 1.5 1.3 3.9 11.3 1.2 0.7 0.4 0.2

Farmers 0.3 2.5 3.0 2.4 0.1 1.2 0.9 0.5

Total professional

and farmers

1.8 3.8 6.9 13.7 1.4 1.9 1.3 0.6

Skilled—industrial 2.3 2.4 4.7 19.7 3.0 4.4 0.9 0.8

Skilled—handicrafts 5.7 9.5 19.1 16.7 63.0 6.5 10.7 5.1

Skilled—transport,

services, and retailing

5.0 9.1 10.2 14.5 8.2 1.8 5.0 0.4

Skilled—unclassified 0.5 0.5 0.9 3.0 1.6 0.2 0.1 0.1

Total skilled 13.4 21.5 35.0 53.9 75.9 12.9 16.7 6.5

Unskilled—farm

workers

4.8 7.6 18.0 2.5 1.7 11.0 34.1 30.5

Unskilled—

non-agricultural

80.1 67.0 40.2 29.8 21.1 74.2 47.9 62.3

Total unskilled 84.8 74.6 58.2 32.3 22.8 85.2 81.9 92.9

Note. Calculated from US Immigration Commission (1910–11, pp. 100–176); the distinction between

skilled and unskilled is largely that used by the immigration authorities; the subsequent division into

categories (industrial, handicrafts, etc.) follows the author�s classification. The table gives results for the

four largest ‘‘old migrant’’ groups, and the four largest ‘‘new migrant’’ groups (‘‘nationalities’’ are as

classified by the US immigration authorities).


English migrants. Moreover, a not insubstantial number of English migrants had

professional skills and these were not matched by any other group.

This point is confirmed by correlation analysis comparing the distributions of mi-

grants by previous occupation for all 73 occupational categories.33 The correlations

between German occupations and those of the 7 largest new migrant groups are con-

sistently higher than those for English migrants. They are higher than the correla-

tions recorded for Irish migrants when compared to all of the new migrant groups

with the exception of the northern Italians. Comparison with Scandinavian migrantson the other hand shows no consistent difference between German and Scandinavian

migrants: both nationalities had skill distributions which were closer to those of the

new migrant groups than those possessed by the English or the Irish.

It is probable that an eventual decline in German emigration was inevitable given

the skills offered by German migrants. Migration can be seen, at least in part, as the

transfer of skills, aptitudes, technical knowledge: human capital in the broadest

sense. This makes it a process which will not continue indefinitely; there is a

saturation point. For example, there is a limit to the demand for the services ofGerman confectioners. Moreover, since these skills are transferable (to children, to

33 Data from US Immigration Commission (1910–11, pp. 101–177). The full set of correlation

coefficients is given in Grant (2000, p. 216.).


apprentices and to other workers), as the stock of German-born confectioners in the

US rises, there will also be a rise in the flow of US-born German-trained, confection-

ers onto the market. The initial stock of skills differed substantially between coun-

tries. As mobility rose, with falling transport costs, there was a redistribution of

this stock to accord more closely with the tastes of consumers and the needs of in-dustry. But this was a stock adjustment, of limited duration. Eventually, a ‘‘skill sat-

uration effect’’ kicked in, and migration fell.

It is also notable that the skills possessed by German immigrants were those of

Handwerker, artisans and small tradesmen, and not associated with large scale indus-

try. There was a short period when migrants possessed of such abilities could make

substantial gains by moving to the United States. This would have come to an end at

some point, however the arrival of large numbers of ‘‘new migrants,’’ with similar

attributes and a willingness to accept lower wages, brought this moment forward.By contrast, the industrial skills possessed by British migrants remained in demand

as the United States industrialized, and this was not affected by the ‘‘new immigra-

tion.’’

This leaves a number of unanswered questions. Germany was not particularly

short of industrial skills, and the comparisons presented in Table 3 showed that

skilled industrial workers could have made substantial gains through migration,

gains which were just as large as those available to unskilled workers. But, by

and large, German skilled industrial workers did not emigrate to the UnitedStates.

One possible reason could have been that it was more difficult for migrants who

did not speak English as their first language to get skilled jobs on arrival even if they

had the necessary experience or qualifications. The Immigration Commission report

on the woolen industry in Lawrence, Massachusetts, records that while the cruder

processes (spinning and drawing) had been taken over by recent arrivals, in the

dressing shop (where the warp was prepared for the looms) ‘‘the work is such that

only those understanding English can be employed.’’34 German migrants did manageto get these jobs eventually. Indeed three-fifths of the workers in the dressing shop in

question were of German origin. But a period of assimilation would have been re-

quired; an obstacle not faced by British migrants.

The points made in this section can be summarized as follows. Firstly, skill en-

dowments varied between migrant groups both as regards the overall level of skill

and the areas to which they were appropriate. Secondly, migrants who had previ-

ously been occupied in the same industry prior to migration received higher wages.

It seems reasonable to attribute this to the value of the skills and knowledge trans-ferred with the migrant. It follows that the relative scarcity of the skills possessed

by potential migrants was an important factor in the assessment of the likely re-

turns from migration, which leads to the third point that the skills possessed

by German migrants were in areas that brought them into competition with new

migrants.

34 US Immigration Commission (1909–10, part 4), ‘‘Woollen and worsted manufacturing’’ p. 772.


5. Geography and the pattern of settlement

A similar approach to the correlations of migrant occupations produces correla-

tions of intended migrant destinations (as declared to the immigration authorities).

Table 9 gives these for two of the main ‘‘new migrant’’ sources, comparing these tothe destinations given by English, German and Scandinavian immigrants.

The group which stands out from this analysis is the Scandinavians, whose in-

tended destinations differed significantly from both the ‘‘new migrant’’ groups.

The Germans and the English did not have such a distinctive pattern of settlement.

The states preferred by German migrants tended to be those which were also receiv-

ing large numbers of new migrants: New York, Pennsylvania, Illinois, Ohio and New

Jersey were the top five. These were also popular destinations for new migrant

groups. English migrants also went to these states, but many Scandinavians wentelsewhere.

Scandinavian migrants went in disproportionate numbers of to a range of north-

ern states from Washington (State) to Minnesota. Out of the top ten Scandinavian

destinations there were five states which took relatively few new migrants: Wiscon-

sin, Iowa, Washington (State) and North and South Dakota. German migrants also

went to these states but in smaller numbers relative to the total flow, apart from the

Dakotas, a favorite German destination. New England on the other hand took rel-

atively few Scandinavians and proportionately more Germans.Given the very different skill endowments of English migrants, the geographical

pattern of settlement was probably less important. Compared to the Germans, there

were relatively large numbers going to the west. English migrants faced much lower

barriers to assimilation, and therefore were less constrained in their choice of desti-

nation. They were not restricted to areas where English migrant communities had

already been established. English mining skills may also have played a factor in this.

But this analysis answers one question only to raise another. If it is accepted that

the reason why Scandinavian migration held up so well was the geographical patternof settlement, then why did the Germans not adopt a similar pattern? It is not as if

the German and Scandinavian patterns were that different; some German migrants

did go to the areas in the north-west favored by the Scandinavians. To have shifted

to a Scandinavian pattern would have involved a re-balancing of existing flows, not

the breaking of new ground.

One reason lay in the activities of pioneer groups. The involvement of Scandina-

vian migrants in logging, the lumber trade, and related activities such as turpentine

Table 9

Correlations of migrant numbers by intended migrant destinations 1890–1910 (51 US States)

Germans English Scandinavians

Southern Italians 0.915 0.921 0.641

Poles 0.884 0.822 0.585

Note. Data from US Immigration Commission (1910–11); there are records of intended destinations

for 754,375 Germans, 408,624 English, 586,306 Scandinavians, 949,064 Poles and 1,911,933 southern

Italians.


manufacturing, meant that they had a head start in some of the north-western states.

This then encouraged other groups to follow in areas where the lumbermen had led

the way. So, Scandinavian communities were established in these areas before the ar-

rival of the new migrants began to affect conditions further east. By contrast the Ger-

mans preferred lowland areas where they could practice their traditional farmingskills.

The importance of unusually favorable opportunities in creating a wider distribu-

tion of migrant communities can be illustrated by comparing the patterns of Polish

and southern Italian settlement. Even bearing in mind the point that there were twice

as many southern Italian migrants surveyed in the statistics, it is clear that the Ital-

ians were more widely dispersed. Only 2.5% of Polish migrants had intended desti-

nations outside the north-east, but 5.6% of southern Italians did. 35 The reason

lay in the different agricultural skills possessed by the two groups. The dry land skillsof the Italians, which were also suited to crops such as cotton or tobacco, meant that

they could make use of opportunities which did not suit other migrant groups. By

contrast, Polish migrants brought with them farming skills which were similar to

those already supplied by Germans or Scandinavians.

A wide geographical pattern of settlement depends on having pioneer groups, able

and willing to undertake the task of setting up communities in new areas. Relatively

few migrants came into this category. Most preferred to go to established settlements

where their language was spoken, and where there were support networks. Manymoved in response to information about jobs passed back from these settlements.

The pioneer groups moved to exploit unusual opportunities, or in response to pres-

sure at home: famine, severe over-population or religious persecution. This was an

established pattern of German settlement in the United States in the seventeenth,

eighteenth and early nineteenth centuries. But these conditions no longer held in

the 1870–1910 period. A lack of pioneer groups restricted the regions of German set-

tlement, and relatively few moved outside the established areas.36

6. Time series analysis

Time series analysis makes it possible to examine the role of general economic

conditions in the various countries. When economic growth is strong in the recipient

country, conditions will favor immigration: unemployment will be low, more jobs

will be created, wages may rise. Similarly, when growth is strong in the countries

of origin, potential immigrants may prefer to seek employment in domestic industryrather than migrating abroad. Estimation of time-series equations for migration

should make it possible to see if a previously established pattern of migration linked

35 Defined as the states north of the Ohio and east of the Mississippi.36 Regional studies have shown the importance of pioneer groups in attracting subsequent migrants;

Kamphoefner (1987), Wegge (1997, 1998), R€ooßler (1995) and Reich (1998) are some examples.


to economic conditions was disturbed by the ‘‘new immigration’’ of the 1890s, and if

this disturbance was greater for Germany than for other countries.

In a Todaro-type model, expected gains from migration are wf � pðefÞ � wd

� pðedÞ � mc, where wf and wd are anticipated wages in the foreign and the domestic

economy, pðefÞ and pðedÞ are the expected probabilities of finding employment athome and abroad, and mc is the cost of migration. If the probability of finding em-

ployment, pðeÞ, can be approximated using registered unemployment ðUÞ, so that

pðeÞ ¼ ð1� UÞ, then the equation can be estimated using relative wages and relative

unemployment rates.

Registered unemployment in pre-1914 labor markets was probably not so well re-

lated to the migrants� anticipated probability of employment. Figures often come

from trade union sources, which may not reflect conditions in the less unionized,

or informal, sectors, which is where most migrants would tend to find work initially.There could have been a considerable amount of unrecorded under-employment in

an informal urban sector or in agriculture. Moreover, in a competitive labor market,

unemployment is caused by a mismatch between worker expectations and the wage

levels that employers are prepared to offer. In a well-functioning labor market, with-

out major structural imbalances, such mismatches will not last long. So, unemploy-

ment will be a reflection of short-term economic fluctuations, not job creation over

the medium term, which may be the most important factor in migrant decision-mak-

ing. The demand for migrant labor over the medium term (Lmt) is given by the rela-tionship between actual per capita GDP (Yt) and the trend rate of productivity

growth (Y �t ): Lmt ¼ f ðYt=Y �

t Þ. This can be estimated using the deviation of per capita

GDP from trend, a measure of the strength of economic activity.

This approach implies a strong ‘‘matching function’’ element to migration. Mi-

grants move when they are confident that jobs will be available. In practice, it

may not differ so much from the Todaro-type model (using relative unemployment

rates) for the good reason that many of the figures for pre-1914 unemployment are in

fact estimates which use the deviation of GDP from trend to fill in missing years.This was the approach used by Romer for the United States.37 German unemploy-

ment figures from trade union sources are only available from 1887 onwards, so fig-

ures for earlier years would also have to be estimated using this technique.

Fig. 3 shows annual figures for German migration to the United States, and plots

these against figures for the deviation of US and German GDP from trend. The fig-

ure strongly suggests that migration was influenced by economic conditions. The

peak migration years of the 1880s, for example, coincided with a period when the

US economy was well above trend, and the German economy well below. Thedecline in migration in the 1890s took place at a time when the US economy was

below trend and the German economy was recovering. After 1900, the relationship

became a less strong one. The US economy was well above trend in 1906–1907, and

37 Romer (1986).

Fig. 3. Annual German emigration to the United States (in 10,000�s) compared to German and US per

capita GDP relative to trend 1870–1913. GDP deviations obtained from the regression of the log of

GDP per capita on time, 1870–1913, data from Maddison (1991); German migrant numbers taken from

US Department of Commerce (1975, pp. 105–106).


the German economy was below in 1901–1902, but neither produced a return to the

emigration levels of the pre-1895 period.38

Table 10 gives the results of equations estimated for annual migration to the Uni-

ted States from Britain, Germany and the Scandinavian countries. The dependentvariable is the total number of immigrants from each destination per head of popu-

lation resident in the country of origin, taken from US sources. There is no allow-

ance for return migration, so the figures are for gross migration.

Equations for British and German migration are estimated using both ‘‘matching

model’’ (columns 1 and 3) and ‘‘Todaro-type’’ (columns 2 and 4) equations. Scandi-

navian unemployment data are not available, so only a matching model is estimated.

The complexity of the equations was necessary to obtain satisfactory results given

the high level of autocorrelation. The tests for residual auto-correlation show thatthe hypothesis of residual auto-correlation can be rejected at a high level of proba-

38 The observation that the migrant flow was responsive to changes in economic conditions in the

United States (which is confirmed by econometric analysis) indicates that the agents who were alleged to

promote immigration, and much criticized by the Immigration Commission for this, in fact did a good job

matching immigrants to employment opportunities. They had no interest in promoting moves at times

when there were no jobs available. Unemployed migrants would be unable to repay the loans which had

paid for the passage: US Immigration Commission (1909–10, vol. 2 pp. 375–88). See also Marschalck

(1973) for a discussion of the background to German emigration.

Table 10

Regression results for the analysis of migration to the United States 1870–1913

German

migration

British

migration

Scandinavian

migration

1 2 3 4 5

Constant )0.466 3.934 )0.161 2.895 2.231

(0.31) (1.34) (0.36) (2.79) (0.89)

Lagged dependent variable (lagged one year) +0.935 +0.895 +0.845 +0.602 +0.742

(8.83) (7.30) (5.77) (3.87) (4.86)

Lagged dependent variable (lagged two years) )0.494 )0.449 )0.137 )0.089 )0.298(3.22) (2.65) (0.99) (0.74) (3.12)

Log of the wage ratio with the +3.88 )0.15 +1.70 +0.05 +0.340

United States (lagged one year) (1.83) (0.04) (1.33) (0.04) (0.15)

Home country GDP (deviation from trend in

current year)

+0.23 +5.59 +15.36

(0.05) (1.72) (1.51)

Home country GDP (deviation from trend lagged

one year)

)3.54 )9.66 )27.40(0.89) (2.76) (2.23)

US GDP (deviation from trend current year) +8.24 +7.01 +20.52

(2.32) (2.43) (3.14)

US GDP (deviation from trend lagged one year) )2.395 )1.414 +2.08

(0.49) (0.60) (0.32)

Home country unemployment (in logs current year) +0.151 )0.471(1.57) (3.07)

Home country unemployment (in logs lagged

one year)

+0.161 +0.673

(2.39) (4.23)

US unemployment (in logs current year) )0.779 )0.648(2.50) (1.93)

US unemployment (in logs lagged one year) )0.164 )0.384(0.34) (0.97)

New immigration effect (in logs lagged one year) )2.20 )3.18 )0.22 )1.55 +0.11

(2.72) (3.60) (0.48) (3.34) (0.05)

Number of observations 42 42 42 42 42

Standard error of the equation 0.512 0.504 0.417 0.378 1.191

Residual sum of squares 8.64 8.40 5.74 4.72 46.86

F Test of regression 31.01 32.05 20.70 26.04 18.73

R2 0.883 0.886 0.834 0.863 0.820

Adj. R2 0.854 0.858 0.794 0.830 0.776

Durbin–Watson 1.82 1.60 2.28 2.10 2.13

F Test for autocorrelation lags 1.976 1.215 2.254 0.144 0.342

one to two [p value] [0.158] [0.311] [0.122] [0.866] [0.713]

Normality test of residuals (v2) 19.37 9.54 0.34 1.53 0.11

[p value] [0.000] [0.009] [0.842] [0.466] [0.946]

Note. All t statistics are corrected for heterocedasticity. Dependent variable is the annual numbers migrating in

each year, per thousand resident population in the country of origin, for each nationality, US Department of

Commerce (1975, pp. 105–106); population figures from Maddison (1991). Wage data taken from Williamson (1995,

pp. 164–167). GDP deviations are residual values obtained from the regression of the log of GDP per capita on time,

1870–1913, for each country of origin, data fromMaddison (1991); Scandinavian figures refer to the combined GDP

of Denmark, Norway and Sweden; US figures from Romer (1989, pp. 22–23). British unemployment figures are

from Feinstein (1972) table 57; German figures 1887–1913 are from Bry (1960, pp. 325–326); prior to 1887 they are

estimates using the relationship between unemployment and the movement of GDP for 1887–1913; US figures are

from Romer (1986, p. 31). ‘‘New migration effect’’ is estimated using immigration from eastern and southern Europe

as a percentage of all immigrants admitted excluding immigrants from the country of origin, US Department of

Commerce (1975, pp. 105–106). P value for the auto-correlation test, lags 1–2, tests the hypothesis of significant

autocorrelation (low p value to accept). P value for the normality test of residuals (v2) tests the hypothesis of non-normality of the residuals (low p value to accept).



bility. Breusch–Pagan tests indicated heteroscedasticity problems for the German

equations so all results are given using heteroscedasticity-corrected standard errors.

The results confirm the point made visually in Fig. 3: migration was strongly af-

fected by economic conditions in the United States, and in the countries of origin.

Migrant decisions appear to have been well-informed and responsive to changes ineconomic circumstances. These were not random or accidental movements.

For the purposes of this study the most important results are those for the ‘‘new

migration effect.’’ These show that there is a significant negative effect on German

migration from this factor in both the ‘‘matching model’’ equation (column 1) and

the ‘‘Todaro-type’’ equation (column 2). There is no significant effect on Scandina-

vian migration (column 5). The results for British emigration are more equivocal: the

‘‘matching model’’ equation (column 3) shows no significant effect but the ‘‘Todaro-

type’’ equation (column 4) does produce a significant negative coefficient.Comparison of the British and German results shows a much larger effect from

the new immigration on migration from Germany. The ‘‘matching model’’ equations

(columns 1 and 3) produce estimated coefficients which are 10 times as large for Ger-

many as for Britain. With the ‘‘Todaro-type’’ equations (columns 2 and 4) the esti-

mated coefficient is twice as large for German migration. The reduction in German

emigration relative to population was substantially larger.

One difficulty with the German results given in column 1 is the insignificance of

the coefficients for German GDP in column 1. The zero hypothesis for these twovariables cannot be rejected (the p value to reject the hypothesis is 0.388). Looking

back at Fig. 3, it is clear that there was, at times, a negative correlation between US

economic activity and the state of the German economy. In the period up to 1900 the

German economy tended to boom when the US slowed down and vice versa. This is

confirmed by correlation analysis which shows that there was a strong negative re-

lationship between US and German GDP: a correlation coefficient of )0.566. Therewas, indeed, a significant negative correlation between German GDP (especially if

lagged one period) and migration to the US (a coefficient of )0.465), indicating that,on this analysis, the movement of German GDP did influence emigration rates. This

effect, however, is obscured by the collinearity between the two sets of GDP vari-

ables.

In Table 11, the robustness of the German results is tested by the inclusion of ad-

ditional variables. The first is the migrant stock: the numbers born in Germany as a

percentage of the total US population. This variable is included in some migration

equations on the grounds that a larger migrant stock will improve the flow of infor-

mation back to the country of origin, implying a positive coefficient. However, the‘‘skill saturation effect’’ mentioned earlier suggests that the coefficient could also

be negative, once the skill transfer process had run its course. The results shown

by these regressions support this view. In this period, the migrant stock had a neg-

ative effect on German migration.

The second variable is Hoffmann�s index of German land prices. If German mi-

grants came predominantly from those desiring to find agricultural occupation either

in Germany or in the United States, then an improvement in German agriculture

would be expected to hold back migration. A negative coefficient is found, which

Table 11

Regression results for the analysis of German migration to the United States 1870–1913

1 2 3 4 5

Constant 4.79 25.26 24.92 31.58 35.85

(2.15) (2.62) (3.08) (3.25) (3.55)

Lagged dependent variable (lagged one year) +0.829 +0.734 +0.642 +0.747 +0.733

(7.38) (5.58) (4.90) (6.74) (6.64)

Lagged dependent variable (lagged two years) )0.383 )0.298 )0.211 )0.274 )0.281(2.91) (2.48) (1.79) (1.97) (2.08)

Log of the wage ratio with the +2.31 +2.45 +2.10 )0.33 )0.24United States (lagged one year) (1.19) (1.36) (1.20) (0.10) (0.08)

German GDP (deviation from trend in

current year)

)3.06 )5.62 )8.17(0.86) (1.82) (2.52)

German GDP (deviation from trend

lagged one year)

)3.97 )1.36 )6.63(1.18) (0.52) (1.91)

US GDP (deviation from trend in current year) +5.97 +3.58 )1.91(2.03) (1.44) (0.86)

US GDP (deviation from trend lagged one year) )2.48 )1.11 )0.35(0.61) (0.33) (0.14)

German unemployment (in logs current year) +0.224 +0.313

(2.12) (3.09)

German unemployment (in logs lagged one year) +0.133 +0.188

(2.54) (2.92)

US unemployment (in logs current year) )0.388 )0.246(1.16) (0.80)

US unemployment (in logs lagged one year) )0.223 )0.207(0.55) (0.56)

New immigration effect (in logs lagged one year) )4.48 )6.22 )4.20 )5.97 )8.30(3.74) (3.88) (3.74) (4.49) (4.58)

Migrant stock (in logs lagged one year) )0.771 )1.756 )2.196 )1.598 )1.765(3.49) (3.24) (4.25) (3.11) (3.40)

German land prices (in logs lagged one year) )3.74 )3.16 )4.84 )5.67(2.37) (2.46) (3.24) (3.47)

Time )0.063 +0.037

(3.30) (2.36)

Number of observations 42 42 42 42 42

Standard error of the equation 0.459 0.430 0.393 0.452 0.430

Residual sum of squares 6.75 5.74 4.63 6.34 5.54

F Test of regression 35.24 5.74 4.63 6.34 5.54

R2 0.908 0.921 0.937 0.914 0.925

Adj. R2 0.883 0.897 0.914 0.886 0.897

Durbin–Watson 1.851 1.91 1.99 1.66 1.97

F Test for autocorrelation lags 1.585 2.691 3.970 1.516 2.448

one to two [p value] [0.222] [0.085] [0.030] [0.236] [0.105]

Normality test of residuals (v2) 9.81 4.66 3.48 5.04 3.13

[p value] [0.007] [0.097] [0.176] [0.080] [0.209]

Note. As for Table 10. Migrant stock is the numbers born in Germany as a percentage of the total US

population, data from US Department of Commerce (1975, p. 117), figures for years between censuses are

estimates using annual migration figures and estimated return rates and mortality rates. Land prices are

from Hoffmann (1965, p. 569–570).



confirms that agricultural conditions had a particular importance for German migra-

tion, additional to the influence exerted by the general movement of the German

economy as represented by the GDP or unemployment variables. The third variable

is a simple time trend. As the ‘‘new immigration’’ tended to rise over time, this var-

iable could pick up effects due to other time-related variables. The inclusion of a timetrend tests this effect.

These additional variables do not have an adverse effect on the coefficients estimated

for the ‘‘newmigration effect.’’ The coefficients shown inTable 11 are rather larger than

those given in columns 1 and 2 of Table 10. The t ratios are also strengthened. The time

series results confirm that German migration was particularly affected by the new im-

migration from eastern and southern Europe. This fits in with the results presented in

previous sections, showing that the skill pattern of German migrants, and the mixture

of intended destinations, brought them into direct competition with the newmigrants.We can conclude thatGermanmigrationwas likely to bemore affected by the increased

arrivals from eastern and southern Europe than migration from other sources.

A problem revealed by the diagnostic tests given in Table 10 was a lack of normal-

ity in the German residuals; the hypothesis of non-normality could be accepted with

a high degree of probability. Examination of the residuals showed that this was due

to the fall of German emigration to low levels post 1895. This produced a number of

relatively small negative residuals. The inclusion of the additional variables in Table

11 resulted in an improvement in the shape of the residuals: the hypothesis of non-normality can be rejected at the 5% level for all columns except column 1. This con-

firmed the validity of the reported results.

Analysis of the variables (Table 12) shows that the variables covering migration,

economic activity, unemployment and the wage ratio are all stationary in first differ-

ences. The migrant stock is not, which affects the results given in Table 12. However,

the fact that all the variables are I(1) does not in itself guarantee the validity of the re-

sults. The variablesmust forma cointegrated set. The results of the analysis of residuals

from the cointegrating equations (Table 13) show that this is the case for the ‘‘matchingmodel’’ equations forGermanmigration to theUnited States. The residuals are indeed

Ið0Þ, but the results for the other equations are not so satisfactory. The ‘‘Todaro-type’’equations, using unemployment, do not produce residuals which are Ið0Þ, nor do the

‘‘matching model’’ equations involving British and Scandinavian migration.

The finding that new migration had an adverse effect on German migration is a

safe one in statistical terms. At least one of the equations that show this result (col-

umn 1 of Table 10) is obtained from a cointegrated set. The result for Scandinavian

migration is not obtained from a co-integrated set, but this does not affect the gen-eral conclusion that the ‘‘new immigration’’ cannot be shown to have had an adverse

effect on Scandinavian emigration.

The British results given in column 3 of Table 10 (a ‘‘matching model’’ equation)

are from a data set which is close to being cointegrated, even if the residuals cannot

be shown to be definitely Ið0Þ. This finding, that there only a weak and insignificant

negative effect on British migration, is therefore a more satisfactory one than the re-

sult in column 4, which appears to show a much stronger effect. This uses a ‘‘Todaro-

type’’ equation with unemployment variables. The balance of probabilities suggests

Table 12

Unit root tests on variables

Variable Country Dickey–Fuller tests

on absolute values

(v2)

Dickey–Fuller tests

on first differences

(v2)

Migration Germany 1.88 4.63**

Migration Britain 2.63 5.16**

Migration Scandinavia 2.25 5.03*

GDP (deviation from trend) USA 2.84 6.63**

GDP (deviation from trend) Germany 1.63 6.27**

GDP (deviation from trend) Britain 2.80 5.49**

GDP (deviation from trend) Scandinavia 1.21 6.39**

Unemployment USA 2.09 5.60**

Unemployment Germany 6.32** 11.52**

Unemployment Britain 2.43 4.56**

Wage ratio with USA Germany 3.36* 7.77**

Wage ratio with USA Britain 2.17 6.20**

Wage ratio with USA Scandinavia 1.93 6.39**

New migration effect Germany 0.79 6.29**

New migration effect Britain 0.42 5.72**

New migration effect Scandinavia 0.68 5.90**

Migrant stock Germany 2.09 2.40

Note. ��Signifies result significant at the 5% level, �signifies result significant at the 10% level.

Table 13

Results of cointegrating regressions

Variable Regressed on Results of tests on residuals:

Durbin–

Watson

Dickey–

Fuller

Augmented

D.F.

(5 periods)

German migration GDP variables and wage ratio 1.79 4.36** 3.72**

British migration GDP variables and wage ratio 1.54 3.22 2.49

Scandinavian migration GDP variables and wage ratio 1.55 2.76 1.53

German migration Unemployment variables and

wage ratio

1.68 1.93 1.13

British migration Unemployment variables and

wage ratio

1.78 2.70 1.39

Note. ��Signifies result significant at the 5% level.


that there was, at most, a small negative effect on British migration to the United

States from the new immigration, considerably less than the impact on German

migration.

7. Conclusions

The main conclusions reached by analysis presented in this article are that the newimmigration had a significant negative effect on German emigration to the United

Table 14

Explaining the fall in German annual emigration to the United States, comparing 1870–1895 with 1896–

1913

‘‘Matching model’’ (column 1—Table 10) ‘‘Todaro-type model’’ (column 2—Table 10)

Change due to relative movement

of the two economies

)17,900 Change due to relative

unemployment

+8800

Change due to ‘‘new immigration’’ )59,000 Change due to ‘‘new immigration’’. )86,200Total predicted fall )76,900 Total predicted fall )77,400Actual fall )74,050 Actual fall )74,050


States. The eastern movement of the process of industrialization in Europe in the

nineteenth century brought into play forces which increased labor mobility in the

countries of eastern and southern Europe. Expectations were raised, traditional in-

stitutions which promoted immobility were eroded, improved communications made

migration attractive and affordable.39 These factors increased the links between Ger-

many and the labor markets of eastern and central Europe. At the same time, these

same countries became important sources of immigrants into the United States. Ger-man immigration was particularly affected, due to similarities in skill endowments

and in the geographical pattern of settlement which made the ‘‘new immigrants’’ di-

rect competitors in US labor markets. The results given in columns 1 and 2 of Table

10 can be used to provide estimates of the size of this effect. The model was first

solved for the long run solution, and these values were applied to the two periods

before and after 1895. These calculations are given in Table 14.

The first column gives the predicted effect using the coefficients from column 1 of

Table 10. The ‘‘new immigration’’ effect is estimated to account for 77% of the totalpredicted fall in German emigration. In the second column, based on the ‘‘Todaro-

type’’ model of column 2 in Table 10, the estimated effect is larger. US unemploy-

ment in 1896–1913 was lower than in 1870–1895, so the overall predicted effect from

relative unemployment is positive. Combined with the higher estimated coefficient

for the new immigration effect, this means that 111% of the predicted fall in migra-

tion is due to the effect of the ‘‘new immigration.’’ Both models show that the new

immigration was a major factor behind the fall in German emigration to the United

States. These developments reinforced the ‘‘continental’’ nature of the German labormarket, insulating it from the forces driving the process of convergence in the Atlan-

tic economies.

Globalization in the late nineteenth century Atlantic economy had most effect on

the smaller countries: Ireland and the Scandinavian economies. The impact of migra-

tion was proportionately greater for these countries. Even though large numbers left

Britain and Germany, these were not sufficient to bring about wage convergence with

the United States. The decline in German emigration combined with other factors, in

particular the decision to protect agriculture, to hold back the globalization process,despite the increasing integration of world commodity and capital markets. In the

39 These arguments are expounded in Massey (1988).


German case, factor price convergence was not an automatic consequence of rising

world trade volumes and greater factor mobility.

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