Movers and stayers. Household context and emigration from ...

Paper for session “Migration”
at the Swedish Economic History Meeting,
Gothenburg 25-27 August 2011
Movers and stayers. Household context and emigration from Western
Sweden to America in the 1890s
Anna-Maria Eurenius, Dept. of Economic History, University of Gothenburg, Sweden.
anna-maria.eurenius@econhist.gu.se
First draft, please do not quote
Abstract
Emigration from Europe to North America in the 19th and early 20th century was of great
societal importance and has inspired many studies at the aggregate level. We know less
however about the individual and household level characteristics of migrants and the extent
to which migration was selective. This paper deals with the importance of household
structure and socioeconomic status for individual decisions to migrate. The design of the
study implies a case control study of longitudinal individual level data for a random sample
of emigrants in 1891 compared with a control group of stayers. Data are from the Swedish
census 1890 and parish records for the period 1855-1891 for Halland county in Western
Sweden. The indicator variable is emigration in 1891 (or not) and the explanatory variables
describe individual characteristics (sex, age, marital status, occupation), household features
(fathers occupation, survival of parents) and the individual’s position in the household (birth
rank in relation to surviving siblings). Also information about previous emigration in the
family is available for analysis.
1

1. Introduction
Establishing the determinants of out-migration, i.e. what makes individuals leaving one
place of residence for another, has for long been one of the major themes in migration
studies. From an economic theory point of view the decision whether to move or not is a
rational choice of the best option when the benefits (e.g. higher earnings) and costs (e.g.
moving costs or psychic costs) of a migratory move have been calculated and compared. If
the net gain from migration is positive, the individual decides to move; if it is negative, the
decision is to stay. In this way, migration is an investment in higher net earnings in the
future. Factors influencing the decision to move in this strand of literature are sex, age,
marital status, human capital, earnings and employment (Sjaastad, 1962; Todaro 1969). For
younger persons not only the own employment and earnings could be assumed to be
important, also the possible support from the parental household and the competition over
family resources with siblings could be assumed to count. Theory of chain migration predicts
that the tendency to migrate is influenced by previous cohorts of migrants from the family or
location (Carlsson, 1976).
Although theory on migration determinants is basically at the micro level, studies of
oversees migration in the 19 th century typically deals with macro data (Bohlin and Eurenius,
2010; Hatton and Williamson, 1993, 1998). The reason for this is simply lack of individual
level data. Emigration was a rare event, even in the 19 th century. At the most 1 % of the
population moved during a year, usually substantially fewer. Calculating based on individual
level data the importance of possible determinants of a rare outcome requires a large risk
population. Modern Swedish register data allows such calculations since they could be
made for the entire population or regional parts of it. For the period before the 1970s such
data is not available though, and historians have to use databases of local populations of
much smaller size, which makes it difficult to study the determinants of emigration.
This study takes another approach, and attaches to an epidemiological method used in
medical studies of rare outcomes: the case-control design. It implies that a group of
emigrants is compared with a control group of non-emigrants across a number of potential
determinants. The methods requires that the two groups could be randomly drawn from the
populations of movers and stayers, which is possible using the census of 1890 and the
migration register of 1891.
2

2. Data
2.1 Sources
This study is performed on data from the county of Halland in the southwest of Sweden,
which was the county with highest emigration rates during the period 1880 – 1910. The
yearly average emigration rate in Halland was approximately 10 persons per thousand
inhabitants. The same rate for the whole nation during that period was just below 6 persons.
The study is based on individual data, which makes it possible to analyze the impact of
factors reflecting human capital, household structures and socioeconomic status had on the
decision to migrate.
The sources are the 1890 census and church records such as catechetical examination
records and migration registers. In the catechetical examination records the household
members were listed by the parish priest every year. The purpose was to examine the
biblical knowledge and reading skills of those living in the household. The records included
basic lists of all household members and their birth years and birth parishes. Information on
changes in the household since the previous record such as births, deaths and migration
were also noted in the records. The catechetical examination records contained information
on migration both into and out from the parish, and also within the parish. The priest
recorded, when, where to and from where someone moved. When a person moved into or
out from the parish he or she had to take out a change of address-certificate. It was issued
by the parish priest who also recorded all moves during the year in the migration register.
One can assume a certain underestimation of the emigration rates in the registers since the
priests not always could separate emigration and domestic migration. The 1884 Emigration
Ordinance made the data more reliable. Emigrant agents were then prohibited to convey
any travels abroad if they could not present proper migration certificates for all emigrants to
the police authority.
The source material has made it possible to collect the necessary information to get as
complete picture as possible of the living conditions of every individual in this study from
birth until the year 1890.
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2.2 The study design and sample
Even though Halland showed the highest emigration rates in Sweden, the overall probability
to emigrate still was very small. On average one percent of the population in Halland
emigrated each year during 1880 - 1910, which means that the necessary size of a random
sample reflecting the real circumstances would be far too extensive. A suitable method for
this study is therefore to perform a case-control study. The purpose of such a study is to
identify and evaluate factors that may have an impact on an event by comparing groups of
individuals that will execute the event (the “cases”) with groups that will not execute the
event (the ”controls”) but are otherwise similar. This method is often used in epidemiological
studies where individuals who have, for example, a disease are compared with a group that
don´t have the disease regarding earlier exposure to different factors.
Thus, the design of this study is as follows:
Event: Emigrate to North America 1891
Study population:
Men and women living in the countryside in the county of Halland, born 1856 – 1876,
amounted to 42 382 persons.
Sample of movers (the “cases”):
As a first step all emigrants from Halland 1891 living in the countryside were identified. This
was done by searching the migration registers for 1891 in every one of the 88 countryside
parishes in Halland. It proved to be 1 500 persons emigrating. Then, all emigrants born
1856 – 1876, i.e. in ages 15-35, with North America as destination were sorted out and
summed up to 1 150 individuals. At last a random sample was conducted by extracting
every tenth of that group, which finally resulted in 115 emigrants constituting the “cases” in
the study.
Sample of stayers (the “controls”): The group of controls was made as a random sample of
200 individuals from the study population in the same birth cohorts as the sample of movers.
To access all relevant persons the sample was based on the census 1890.
4

The starting point for this study is 1890. The “cases” emigrated to North America in 1891
while the “controls” did not. To determine what influenced the decision on whether to move
or not a rather significant amount of information has been collected for every individual. This
has been done starting with the census 1890 and then by extracting data from church
records. The aim has been to track every individual back to their place of birth and the
family of origin. Mobility among young people in the countryside was still large during the
latter part of the 1800s and changing employments often also meant changing place of
residence. This has sometimes made the tracing rather complicated. The number of
observations in the study may seem rather limited in this first draft. This is due to the
extensive time required to locate each individual and to excerpt all necessary data.
2.3 The variables
The independent variables in this study can be divided into two groups. The first group
consists of variables that reflect the individual’s human capital. A general view within
migration research is that young unmarried people with no land of their own were the most
anxious to emigrate. They were considered to have had more to gain from migration than
other groups and less ties to the home country. The variables sex, age, marital status and
the individual´s own profession represent this.
The other group of variables reflects household structure and socioeconomic status. The
assumption here is that the propensity to emigrate was dependent on the parents’ social
status and the individual´s position in the family. This could for instance have an impact on
the future prospects to be able to stay on the family farm or in other ways being favored with
regard to inheritance. Variables representing such aspects are father’s occupation, whether
one or both parents were alive in1890, and the number of older siblings alive in 1890.
The importance of previous emigration for emigration rates is well known, and lots of
emigrants in the latter part of the 1800s travelled with prepaid tickets or had received crucial
information from previous emigrants to “the New World”. Therefore, the final variable
captures the family history of previous migration, i.e. the existence of previously migrated
siblings or parents.
5

Table 1 shows the variables reflecting individual characteristics. The first one is the
individual´s sex. The distribution between men and women is virtually equal for the total
sample, which correspond to the population in Halland as a whole. The second variable is
the individual´s age. Just above 75 % of all emigrants from Halland in 1891 were in the age
15-35 years. This corresponds well with the figures for the total amount of emigrants from
Sweden and this is why only individuals in that age span are included in the study. To
investigate any difference in the propensity to emigrate within this age group, the population
is divided into four 5-year groups. Next variable is marital status and it is clear that the vast
majority in the study was unmarried. High marriage age was something that was
characteristic not only for Sweden, but also for the rest of Western Europe. Moreover, the
average marriage age in Halland tended to be among the highest in Sweden. Next variable
is the individual´s occupation. The data is extracted from the 1890 census and the
occupational titles are coded by the HISCO system. Since the sample is rather small it was
necessary to merge similar occupations into only four categories. The first group represents
landowners and includes peasants, freeholders and tenants. The second group represents
the landless and includes crofters, cottagers and lodgers. The third group is very diversified
and includes all other occupations but primarily maids, farm hands and farm workers. The
forth group consists of sons and daughters still living in the parental home having not yet
really entered into employment and therefore lacking occupational titles in the records.
Table 2 shows the group of variables reflecting household structure and socioeconomic
status. The first one is the father´s occupation at the individual´s time of birth, capturing the
impact of the socioeconomic status of the parental household on the individual’s likelihood
of emigration later in life. The occupational categories are constructed in the same way as
the variable showing the individual´s occupation, with the one difference that the fourth
group represents the poorest in society, the paupers. The next group of variables reflects
the impact of the presence of parents in 1890 on the probability of migration in 1891. Four
categories are compared: both parents being alive, either father or mother being dead, and
both parents being dead. The next variable also concerns the family structure. The number
of older siblings alive in 1890 reflects the impact of parity on future possibilities to stay at
home and perhaps take over the farm one day. The variable is categorized into four groups
with increasing numbers of siblings. The last variable captures the importance of previously
migration of family members. Here family refers only to siblings and parents, and not more
distant relatives. The variable is divided into two categories; those with a family history of
6

previous migration, and those without any previously migrated parents or siblings. All
variables are constructed as dummies.
Table 3 and 4 report the distribution of the variables within the two samples. The tables
show that there are differences between movers and stayers, for instance in the distribution
of gender, marital status, parental presence and previous family migration history. Next, we
will test whether such bivariate associations between potential determinants and emigration
remain in a multivariate analysis.
7

3. Results
The purpose of a case-control study is to identify and evaluate different factors that may
have an impact on the probability that an event will occur. To measure the extent to which
there is an association between the event and the different independent variables the odds
ratio. The odds for a certain event to happen is the probability for that event to occur divided
with the probability for the event not to occur. The relative odds for the event to occur is
expressed as the odds ratio, i.e. the odds of a specific category divided by the odds of the
reference category. Since the odds of the reference category is set to 1, an odds ratio > 1
indicates that the probability is larger for the category in question than for the reference
category, while an odds ratio < 1 indicate a smaller probability. The odds ratio cannot,
however, be automatically interpreted in terms of probability and percentages. One way to
make it easier to interpret the results is to determine the anti logarithm of the odds ratios.
Then it is possible to think of the relations in terms of percentage changes.
Two regressions have been estimated. The first one is based on the variables reflecting
individual characteristics and the results are displayed in Table 3 and 4. Table 3 shows the
odds ratio and Table 4 the marginal effects of each variable, expressed as percentage
changes. As can be seen there are some variables that shows significant results. If we look
at the variables reflecting the gender and marital status the probability to emigrate is 17 %
lower for women than for men and 28 % lower for married than for unmarried persons.
Another factor that seems to have had a rather strong effect on the emigration decision is
the individual´s own profession. Compared to the group of landowners the probability for
emigration among the landless group was almost 42 % higher. As to the influence of age, it
is clear from the Tables that being 30-35 years was associated with a 15 % lower likelihood
of emigration compared to the reference category (15-20 years).
Controlling for factors reflecting individual characteristics, variables capturing household
structure and socioeconomic status has been added in the second regression and the
results are presented in Table 5 and 6. As before Table 5 shows the odds ratio and Table 6
the marginal effects. The variables from the previous regression are showing similar results.
The probability to emigrate among females are now almost 20 % lower than for men and
married people show 27 % lower probability to move than unmarried persons. The current
occupation among the individuals is still important and has increased its impact. Now we
8

can see that except for the landless group, which shows a probability to move that is almost
50 % higher than the landowners, the probability of emigration of people in other
occupations is almost 40 % higher than the reference category. The influence of the age
variable is still rather week, but the overall picture is a negative association of age and
emigration, which is clearest for the age group 30-35.
Among the variables added in the second regression there are especially two that stand out
because they represent large effects that are highly statistically significant. It is rather
obvious that the variable reflecting the numbers of previous emigrants in the family has a
strong impact on the decision to emigrate. The probability of emigration was 32 % higher for
individuals with a family emigration history compared to those without. The other variable is
the one showing the effect of both parents being dead or alive in 1890. It turns out that the
propensity to emigrate was 22 % lower if both parents were dead compared to if they were
both alive. Having one or the other of the parents widowed does not seem to have had that
much effect on migration decisions though. The coefficients of the variables of father´s
occupation and number of older siblings alive in 1890 were not statistically significant for this
sample.
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4. Discussion
When trying to understand people´s choices in different situations, one quickly realizes that
most decisions are influenced by many considerations and circumstances. People are
unique and affected by a wide variety of factors. Such a crucial decision as to emigrate to
North America in the late 1800´s was of course based on careful considerations that were
exclusive to each potential emigrant. Most research on determinants of migration has been
conducted on an aggregated level data. As being performed on individual level data this
study is an attempt to, in a more intrusive way, approaching the individual reasons behind a
person´s decision to move or to stay.
The results show that the factors most decisive for the decision to migrate were those
primarily related to the individual’s life situation. Young people with some kind of
employment and income but with no family or farm of their own were those who were most
prone to emigrate. This outcome was perhaps not so surprising. A little bit more unexpected
was, on the other hand, the fact that the social background didn´t seem to have had any
impact on the migrant decision. To emigrate meant for most people an opportunity to
improve or maintain their social status. This was probably an issue within most social
classes in times with a growing population in combination with scarce working opportunities.
The presence of parents seems, however, to have been of great importance for the
propensity to emigrate. Both parents being alive meant probably more support when making
the crucial decision. Partly through economic contributions and also perhaps by reducing
the pressure and expectations of taking care of a widowed parent or younger siblings.
The family history of previous migration was also a factor that had a very clear impact on the
decision to migrate. Any siblings or parent, regardless of the family´s social status, that
already had made the trip had a great influence on new presumptive emigrants back home.
In addition to financial support, which was very frequent, they could contribute with useful
information about “the New World” or also perhaps by helping out with a job or a place to
stay.
This study is a first draft with preliminary data analyses. It will eventually be extended with a
larger number of observations. The idea is to make a sample of 250 movers and 500
stayers. It would then be interesting to adjust the variables and perhaps to change
categorizations. It could also be of interest to test interactive associations between different
variables.
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Tab.1 Variables reflecting human capital
Tab.2 Variables reflecting household structure
and socioeconomic status
Variables Frequence Percent Variables Frequence Percent
Sex
Fathers occupation
male 157 50.16 landowner 179 56.83
female 158 49.84 landless 76 24.13
Total 315 100.00 other occ. 57 18.10
Age pauper 3 0.95
15-­‐20 127 40.32 Total 315 100.00
21-­‐25 67 21.27 Parents alive 1890
26-­‐30 71 22.54 Both parents
31-­‐35 50 15.87 Yes 115 36.83
Total 315 100.00 No 199 63.17
Marital status Total 315 100.00
married 55 17.46 Father
unmarried 260 82.54 father alive 279 88.57
Total 315 100.00 father dead 36 11.43
Own occupation Total 315 100.00
landowner 24 7.62 Mother
landless 13 4.13 mother alive 255 80.95
other occ. 78 24.76 mother dead 60 19.05
missing 200 63.90 Total 315 100.00
Total 315 100.00 Both parents
dead 1890
Yes 20 6.35
No 295 93.65
Total 315 100.00
Numbers of older
siblings alive 1890
0-­‐1 158 50.16
2-­‐3 94 29.84
4-­‐8 63 20.00
Total 315 100.00
Previous migrants
mighist
0 226 71.75
1-­‐7 89 28.25
Total 315 100.00
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Tab.3. Distribution of movers and stayers.
Variables reflecting human capital
Tab.4.Distribution of movers and stayers.
Variables reflecting household
structure and socioeconomic status
Movers Stayers Movers Stayers
Variables Freq. Percent Freq. Percent Variables Freq. Percent Freq. Percent
Sex
Fathers occupation
male 73 63.48 84 42.00 landowner 61 53.04 118 59.00
female 42 36.52 116 58.00 landless 34 29.57 42 21.00
Total 115 100.00 200 100.00 other occ. 19 16.52 38 19.00
Age pauper 1 0.87 2 1.00
15-­‐20 55 47.83 72 36.00 Total 115 100.00 200 100.00
21-­‐25 26 22.61 41 20.50 Parents alive 1890
26-­‐30 26 22.61 45 22.50 Both parents
31-­‐35 8 6.96 42 21.00 Yes 82 71.30 117 58.50
Total 115 100.00 200 100.00 No 33 28.70 83 41.50
Marital status Total 115 100.00 200 100.00
married 5 4.35 50 25.00 Father
unmarried 110 95.65 150 75.00 father alive 12 10.43 24 12.00
Total 115 100.00 200 100.00 father dead 103 89.57 176 88.00
Own
occupation Total 115 100.00 200 100.00
landowner 1 0.87 23 11.50 Mother
landless 5 4.35 8 4.00 mother alive 17 14.78 43 21.50
other occ. 32 27.83 46 23.00 mother dead 98 85.22 157 78.50
missing 77 66.96 123 61.50 Total 115 100.00 200 100.00
Total 115 100.00 200 100.00 Both parents
dead 1890
Yes 4 3.48 16 8.00
No 111 96.52 184 92.00
Total 115 100.00 200 100.00
Numbers of older
siblings alive 1890
0-­‐1 50 43.48 108 54.00
2-­‐3 39 33.91 55 27.50
4-­‐8 26 22.61 37 18.50
Total 115 100.00 200 100.00
Previous migrants
mighist
0 64 55.65 162 81.00
1-­‐7 51 44.35 38 19.00
Total 115 100.00 200 100.00
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Tab.3. Logistic regression Number of obs = 315
Wald chi2 (17) = 44.43
Prob > chi2 = 0.000
Log pseudolikelihood= -­‐ 184.23411 Pseudo R2 = 0.1088
Robust
emig1891 Odds Ratio Std.Err. z P>IzI (95% Conf. Intervall)
female .4543143 .1166348 -­‐3.07 0.002 .2746817 .7514204
agegroup2 .9086888 .2954152 -­‐0.29 0.768 .4804953 1.7184670
agegroup3 1.0155670 .3361883 0.05 0.963 .5308005 1.9430600
agegroup4 .4618341 .2218729 -­‐1.61 0.108 .1801169 1.1841800
married .1918288 .1299455 -­‐2.44 0.015 .0508519 .7236367
ownprof2 5.9886110 6.5530290 1.64 0.102 .7012940 51.1389800
ownprof3 4.7449950 4.9670100 1.49 0.137 .6098278 36.9202300
ownprof4 2.4578430 2.6897470 0.82 0.411 .2877659 20.9927300
Tab.4. Marginal effects after logit
y = Pr(emig1891) (predict)
´=0.32538841
variable dy/dx Std.Err. z P>IzI (95% C.I.)
female* -­‐.1718420 .05553 -­‐3.09 0.002 -­‐.280669 -­‐.063014
agegro2* -­‐.0208119 .06998 -­‐0.30 0.766 -­‐.157974 .116350
agegro3* .0033959 .07288 0.05 0.963 -­‐.139449 .146240
agegro4* -­‐.1516970 .08245 -­‐1.84 0.066 -­‐.313298 .009904
married* -­‐.2816659 .08231 -­‐3.42 0.001 -­‐.442997 -­‐.120335
ownprof2* .4190828 .21752 1.93 0.054 -­‐.007252 .845418
ownprof3* .3618337 .23501 1.54 0.124 -­‐.098781 .822449
ownprof4* .1869687 .21202 0.88 0.378 -­‐.228576 .602513
(*) dy/dx is for discrete change of dummy variable from 0 to 1
Referencecategories
Sex
male 0
Age
agegroup1 age 15-­‐20
Marital status
unmarried 0
Own
profession
ownprof1 landowner
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Tab.5. Logistic regression Number of obs = 315
Wald chi2 (17) = 67.01
Prob > chi2 = 0.0000
Log pseudolikelihood= -­‐ 168.66074 Pseudo R2 = 0.18414
emig1891 Odds Ratio Robust Std.Err. z P>IzI (95% Conf. Intervall)
female .3912056 .1100272 -­‐ 3.34 0.001 .2254256 .6789015
agegroup2 .9397356 .3533390 -­‐ 0.17 0.869 .4497337 1.9636130
agegroup3 .9880561 .3453016 -­‐ 0.03 0.973 .4980895 1.9599990
agegroup4 .4968527 .2406173 -­‐ 1.44 0.149 .1923115 1.2836600
married .2013318 .1435586 -­‐ 2.25 0.025 .0497700 .8144366
ownprof2 9.0232470 9.3913990 2.11 0.035 1.1733620 69.3895000
ownprof3 5.6706180 4.9658660 1.98 0.048 1.0191010 31.5532000
ownprof4 2.2106180 2.0339820 0.86 0.389 .3641885 13.4184200
fathprof2 1.5093190 .4574814 1.36 0.174 .8332550 2.7339090
fathprof3 .9857108 .4114410 -­‐ 0.03 0.972 .4349641 2.2338070
fathprof4 2.1913310 2.1651340 0.79 0.427 .3159964 15.1961500
fathalive .6656765 .2855080 -­‐ 0.95 0.343 .2871995 1.5429180
mothalive .7608942 .2740482 -­‐ 0.76 0.448 .3756215 1.5413390
parsdead .2575026 .1884071 -­‐ 1.85 0.064 .0613737 1.0803910
oldsibl2 1.4092720 .4533082 1.07 0.286 .7502333 2.6472400
oldsibl3 .97996180 .3398076 -­‐ 0.06 0.953 .4966494 1.9336080
mighist26 3.9835630 1.1953760 4.61 0.000 2.2123080 7.1729500
Tab.6. Marginal effects after logit y = Pr(emig1891) (predict) ´=.31230751
variable dy/dx Std.Err. z P>IzI (95% C.I.)
female* -­‐.1995471 .05876 -­‐3.40 0.001 -­‐.314714 -­‐.08438
agegro2* -­‐.0132588 .07961 -­‐0.17 0.868 -­‐.169292 .142775
agegro3* -­‐.0025774 .07487 -­‐0.03 0.973 -­‐.149322 .144167
agegro4* -­‐.1352704 .08421 -­‐1.61 0.108 -­‐.300317 .029776
married* -­‐.2674039 .08300 -­‐3.22 0.001 -­‐.430083 -­‐.104724
ownprof2* .4959770 .17530 2.83 0.005 .152393 .839561
ownprof3* .3981666 .19246 2.07 0.039 .020949 .775384
ownprof4* .1622580 .17793 0.91 0.362 -­‐.186483 .510999
fathpr2* .0915736 .06881 1.33 0.183 -­‐.043286 .226433
fathpr3* -­‐.0030857 .08932 -­‐0.03 0.972 -­‐.178155 .171983
fathpr* .1862159 .24596 0.76 0.449 -­‐.295861 .668293
fathale* -­‐.0818561 .08033 -­‐1.02 0.308 -­‐.239292 .07558
mothale* -­‐.0567247 .07222 -­‐0.79 0.432 -­‐.198276 .084827
parsdead* -­‐.2180483 .07904 -­‐2.76 0.006 -­‐.372972 -­‐.063125
oldsibl2* .0754232 .07227 1.04 0.297 -­‐.066225 .217071
oldsibl3* -­‐.0043374 .07414 -­‐0.06 0.953 -­‐.149652 .140977
mighist* .3153291 .06771 4.66 0.000 .182623 .448035
(*) dy/dx is for discrete change of dummy variable from 0 to 1
Referencecategories
Sex
Father´s profession
male 0 fathprof1 landowner
Age
Parental
lifstatus1890
agegroup1 age 15-­‐20 parentsalive both parents alive 1890
Marital status
Older siblings 1890
unmarried 0 olsibl1 0-­‐1 older siblings alive 1890
Own profession
Previous migrants
ownprof1 landowner No previous migrants 0
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Appendix
Sources of data
1890 census
Churh registers from the county of Halland:
Cathechetical examination registers for 1856 -1891
Migration registers for 1891
References
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