Marriage Timing over the Generations
Frans van Poppel
K. Mandemakers International Institute of Social History, University of Amsterdam
, Cruquiusweg 31, 1019 AT Amsterdam,
C. Monden Department of Social Cultural Sciences, Tilburg University
, Room S 181, P.O. Box 90153, 5000 LE Tilburg,
) Netherlands Interdisciplinary Demographic Institute
, P.O. Box 11650, 2502 AR The Hague,
Strong relationships have been hypothesized between the timing of marriage and the familial environment of the couple. Sociologists have identified various mechanisms via which the age at marriage in the parental generation might be related to the age at marriage of the children. In our paper we study this relationship for historical populations. We use a dataset consisting of several hundreds of thousands of marriages contracted in three of the 11 Dutch provinces between 1812 and 1922. We identified the generational links between the brides, grooms, their parents, and grandparents. We studied (a) whether there is a relationship between ages at marriage of (grandfathers) fathers and sons, and ages at marriage of (grandmothers) mothers and daughters and (b) whether this relationship might be explained by social class. We find evidence for a clear effect of the family on age at marriage and substantial intergenerational transmission. The impact that the family of origin has on age at entry into marriage can partly be attributed to social class. We also observed positive effects of grandparents' age at marriage on their offspring's age at marriage.
Until the beginning of the twentieth century, late marriage and definitive celibacy
played a key role in the European economic-demographic system. Age of entry into,
and the number of women remaining definitively out of, marriage acted as
equilibrating forces via which the rate of population growth was adapted to
economic conditions (Flinn 1981). The age at entry into marriage was also a key
factor affecting the family organization and gender relations in European societies. It
determined the moment at which women left the labor force, property was
transferred across the generations, and residence changed, and it defined spousal
relations and the status of women (Mason 1993; Modell et al. 1976). Identifying the
mechanisms regulating the ages at which new couples were formed is therefore
essential for understanding the demographic regime of Europe in the past and for an
insight into the changes in family life over the past centuries.
In the classical sociological theories of modernization, the decreasing significance
that individuals attach to the family in which they are born is the driving force
behind the transformation of family life, including that of the age at marriage (Goode
1963; Shorter 1977). Couples increasingly deviated from the values, beliefs and
attitudes formed in the context of the family of origin for at least three reasons. First,
the family lost many of its former socialization functions: as a consequence, parents
had fewer opportunities to leave their marks on every aspect of the childs life.
Second, as a consequence of the rise of the welfare state, the power of parents to
impose their preferences on their offspring has declined. Third, parents view of their
role in the upbringing of their children has changed from an emphasis on discipline
to stimulating children to find their own way in life (Aris 1982).
Although statements about the effect of the shift from a family-based to an
individualbased orientation are frequently found in the historical and sociological literature,
studies in which the similarity of marriage characteristics over the generations are
studied are rare (Alter and Oris 1999; Anderton et al. 1987; Levine 1982). Historical
studies are often not of sufficient size to detect similarities in behavior between
generations because the usual techniques such as family reconstitutions rarely allow
researchers to follow populations over long periods of time, or they are based on
genealogies of atypical populations (Murphy and Wang 2002).
Empirical data on time trends in the degree of concordance between parental
behavior and the behavior of children are therefore rarely presented. A further
problem is that studies of the strength of the process of intergenerational
transmission usually apply to one community only. Recent research has shown the
importance of the roles macroeconomic factors and cultural characteristics play in
determining the size of individual differences in family behaviors. Reher (1998) has
suggested that where a deeply rooted cultural view that family and kinship represent
an important institution dominates, intergenerational transmission of family behavior
is more prominent than in areas characterized by rather weak family ties.
In this paper we study intergenerational transmission of the age at marriage over a
period of almost a century, and for three spatial-cultural contexts. We use information
on several children per family, on their parents and their grandparents. Studying the
similarity among siblings enables us to assess the total impact of the family and the
importance of intergenerational transmission. We use information from a large
database for three provinces of the Netherlands that has recently become available and
that allows us to address this issue in a way hitherto impossible. Our paper mainly has
a descriptive and exploratory character and examines whether intergenerational
transmission occurred and whether it varied over time and space.
Hypotheses on the Role of Intergenerational Transmission in
Nineteenthand Twentieth-Century Society
The literature on intergenerational transmission of family behavior distinguishes a
number of mechanisms that might explain why children adopt the familial behavior
of the parental generation: value socialization, social control, transmission as a side
effect of other processes that cause similarities between parents and children, and
genetic transmission (Axinn and Thornton 1992; Barber 2001; Glass et al. 1986).
Evolutionary biologists interested in revealing the importance of different
lifehistory traits in affecting fitness and longevity have frequently observed strong
positive correlations between female age at first reproduction and longevity in
premodern societies. Various authors have tried to separate the intergenerational
correlations in age at first reproduction in genetic effects and non-genetically
inherited effects. It is suggested that the selection gradient on age at first
reproduction has changed over time as a consequence of changes in environmentally
caused variation and cultural transmission of this life-history trait (Kirk et al. 2001;
Pettay et al. 2005). Since the age at reproduction in historical populations is to a
large degree dependent on the age at marriage (Anderton et al. 1987), the study of
the intergenerational transmission of age at marriage offers an opportunity to test the
effect of cultural changes.
In historical populations in particular, value socialization, social control, and the
indirect effect of social class similarity between parents and children might cause a
similarity between the ages at marriage of parents and children. The role of genetic
factors is considered less relevant partly because some randomness in the outcomes
will result from the fact that a marriage requires two people.
As marriage was a legally and socially defined turning point in peoples lives,
parents imposed culturally embedded expectations specifying appropriate ages for
this transition and age ranges outside of which this transition was considered
inappropriate (Hogan and Astone 1986). Couples knew that it was important to stick
to these rules. To affect the age at marriage of their children, parents had available a
variety of forms of social control, allowing them to protect the family property,
business, and honor, including the legal requirements for parental consent, the
transmission of property, parental supervision, dowries, and the manipulation of
interaction opportunities (Aris 1982).
A close correspondence between ages at marriage of parents and children could
also result from the fact that ages at marriage strongly depended on the social class
to which individuals belonged (Wrigley et al. 1997:123125) and that social class
was to a large degree transmitted from the parental to the childs generation.
We hypothesize that the degree to which ages at marriage of the parental and child
generation in the Netherlands were correlated changed over time, and varied
between regions, social class, and gender.
We assume that the strength of the intergenerational transmission of age at
marriage has decreased over the nineteenth and early twentieth centuries. This is in
contradistinction with the results of studies on the transmission of fertility, which
show an increase in the genetic influence on fertility (Kohler et al. 1999; Murphy
1999). Socialization to an ever-increasing degree took place outside the family
environment and was delegated to formal institutions. Increasingly the family
organized itself in terms of the children and their future, and the parents chief
psychological and material investment consisted in helping the children get ahead
(Aris 1982). A loss of social control of parents over the attitudes and behavior of
their children has taken place owing to a rise of individual paid labor, a declining
importance of inheritance and employment within family businesses, and the rise of
the welfare state.
We expect regional differences in our data because the three provinces varied in
the importance that was attached to the family and to paternal authority. Differences
in family ideology, family structure, and family relations between, on the one hand,
the western and northern part of the Netherlands (the coastal areas) and, on the other
hand, the south and east (Wichers 1965) have been related to differences in religious
composition. In the Catholic south, solidarity between generations and parental
authority was stressed. Parents and the local clergy exercised a much tighter control
over adolescents. For these reasons we expect that the transmission of age at
marriage over the generations was considerably stronger in the southern Catholic
province of Limburg than in the mixed eastern province of Overijssel and in the
Protestant province of Zeeland. Another relevant factor is that households in the
south and east were larger and of a more complex structure than those in the north
and west. Owing to specific inheritance practices (De Haan and Hoppenbrouwers
1994), the parental generation in Overijssel had more possibilities for social control
than parents in Zeeland or Limburg. Given these factors, we expect that in the
province of Zeeland behavioral transmission between generations was less strong
than in the other two provinces.
We also expect differences between social classes in the degree of transmission of
ages at marriage over the generations. The more resources parents had, the better
able and the more willing they were to manipulate the timing of their childrens
marriages. As property was the basis for status and political power, the upper class,
the peasantry, and the petty bourgeoisie had a clear interest in and the opportunity to
influence the age at marriage of their children (Mitterauer and Sieder 1982:134
138). In the lower social classes, parents with no or little property were hardly able
to delay a childs marriage since wage earning gave their offspring a certain degree
of economic independence.
Finally, we assumed that there were differences in the degree of intergenerational
transmission according to the sex of the child and according to the paternal versus
the maternal line. Barber (2001) has argued that daughters are generally more
strongly socialized by their mothers, and as a consequence might be more likely to
look to their mothers as role models. Traditionally, in Western society, women have
been more subject than men to parental control, particularly in the area of sexual
behavior. Both factors would suggest that the strength of transmission would be
greater among women than among men. On the other hand, in nineteenth-century
society, the patriarchal principle was dominant, ensuring greater power, prestige, and
influence for males. This would suggest that transmission via the paternal line was
more likely than via the maternal line (see also Buss 1994).
Data and Variables
We used data derived from marriage certificates that relate to all marriages
contracted in the period 18121922 in three Dutch provinces: Zeeland in the
southwestern part of the coastal zone, Limburg in the southeast, and Overijssel in the
central eastern part of the country.
We have tried to link each marriage record to the marriage records of the parents
and siblings of the bride and groom. This linkage was based on the combination of
surnames and Christian names of both parents, as given in the childs and the
parents marriage certificates, allowing for small deviations. Both age at marriage
and year of marriage of the child were used to reduce the number of pairs of parents
that were eligible for linkage. The total number of marriages in the database was
574,000, of which 220,000 were in Overijssel, 190,000 in Limburg, and 164,000 in
Zeeland. We were able to link 71.2% of these marriages to the marriage records of
the parents. There is only a small change over time in the proportion of the total
number of marriages represented by the individual provinces, with Overijssel
showing a small increase and Zeeland a small decrease.
For the province of Limburg we found a substantially lower proportion of linked
marriage records over the generations (52%). In this province the Christian names of
parents were sometimes only given as initials, in which case linkage was almost
impossible. In addition, the dialect and the mixing of populations from Germany as
well as from French-speaking Belgium had a negative effect on the linkage
procedure because of spelling errors in foreign names and migration. Our final
sample for Limburg is more selective than in the other provinces. It is possible that
as a consequence we observed a higher or lower degree of transmission in the ages at
marriage between generations here than was really the case.
In the analysis we use information from the marriage records on age at marriage,
year of marriage, year of birth, social class, urban/rural character of the place in which
the marriage occurred, and the number of married siblings. For each family we only
know the number of married children that could be linked to their parents. Therefore,
the number of married siblings used in the analysis is a proxy for the real number of
married and unmarried siblings. Because this variable is highly skewed we truncate
the number of married siblings in the final models at seven to prevent misspecification
of the multilevel models. Multilevel models can be sensitive to highly skewed
variables. In less than 4% of the families, the number of siblings is higher than seven.
We therefore hardly lose any information by setting values of 8 and higher to 7,
whereas the estimates of the variance components become more stable.
Social class was determined on the basis of information about the occupation of
grooms, as given on the marriage records. These historical occupational titles were
classified into an abridged version of a social class scheme recently proposed by Van
Leeuwen and Maas (2005), known as HISCLASS. We employ the following
categories in our analyses: upper class, white-collar middle class, skilled workers,
farmers, lower-skilled workers, unskilled workers, and farm workers. In the analysis,
skilled workers serve as the reference category; all other categories are entered as
We constructed two analytic samples. It stands to reason that information on three
generations backwards is most common for people marrying in the last part of the
period studied and that this kind of information is not available for people marrying
in the beginning of the registration period. Moreover, for the earliest part of the
registration period, we are more likely to link children who married young to parents
who married young as well. In other words, the chance of linking is higher for
children whose parents married most recently (because old marriages are not in the
registry). Since this could bias our analysis, we included two-generation marriages
from 1840 onwards and three-generation marriages from 1860 onwards. In both
samples, we excluded second and higher-order marriages (about 16% of all
The two-generation sample is restricted to those brides and grooms for whom we
have complete information on their own and their parents age at marriage and on
their own (i.e., the grooms) and their fathers social class. Only marriages from
families for which we have information on at least two siblings are included. This
results in a final number of cases for the two-generation sample of 336,999
marriages in 102,704 families. The number of marriages is 111,957 in Zeeland,
149,921 in Overijssel, and 75,121 in Limburg.
The second analytic sample is restricted to those brides and grooms for whom we
have information on three generations. We included all cases in which complete
information was available about own age at marriage, parents age at marriage,
maternal and paternal grandparents age at marriage, and grooms and fathers social
class. After selecting only marriages from families with information on at least two
siblings, our three-generation sample includes 88,661 individuals (nested within
26,152 families). This is about 15% of the original data base. For various reasons
mentioned earlier we found a lower number of intergenerational links in Limburg
(10,529 marriages after final selection) than in the other two provinces (37,763
marriages in Zeeland and 40,369 in Overijssel).
Correlations between childrens and parents age at marriage give an indication of
the strength of the intergenerational transmission. However, for a proper test of
intergenerational transmission, we have to use multivariate multilevel models. The
bivariate association between childrens and parents age at marriage could be partly
spurious since there are other factors, such as social class, that parents and children
have in common and that directly affect age at marriage of both the parents and their
children. Standard multivariate regression models do not suffice in this case because
they cannot deal with the unique information on multiple siblings per family.
Multilevel models (Snijders and Bosker 1999) are particularly well suited to analyze
this type of data. We use multilevel models that allow us to (a) estimate the total
family effect on age at marriage and (b) obtain correct estimates for the effects of
family characteristics on childrens age at marriage.
Intergenerational transmission of age at marriage implies a positive correlation
between siblings age at marriage. After all, siblings whose parents married at a
higher age would all be expected to marry relatively late, whereas siblings from
parents who married at an early age should marry relatively young. In multilevel
models, differences among families and differences among individuals are estimated
simultaneously (Snijders and Bosker 1999). The model assesses how much of the
total variation in age at marriage is attributable to the common family environment
shared by married siblings and how much is attributable to factors unique to the
individual siblings. The larger the family variance component relative to the
individual component, the stronger the total family effect on age at marriage. An
estimate of the correlation between siblings is obtained by dividing the family
variance component by the total variance (Snijders and Bosker 1999:46). This
estimate is called intraclass correlation and has two interpretations. First, it can be
interpreted as the correlation between the ages at marriage of two randomly drawn
siblings from one randomly drawn family. Second, it simply is the proportion of the
total variance in age at marriage due to the familyin other words, indicating the
size of the total family effect.
We estimate three models to test our hypotheses. Our first model includes an
intercept and a linear effect of year of marriage. We add year of marriage because
strong period effects could bias our estimates of the family effect. Nonlinear
specifications of the period effect did not improve the model, nor did it affect the
coefficients in the subsequent models. This first model estimates how much of the
total variance in age at marriage is due to family differences and how much is due to
individual characteristics. The intraclass coefficient shows us how important the
family was for the age at marriage.
In the subsequent model, we add individual and family characteristics that
determine age at marriage in order to take into account compositional differences
between families (e.g., some families have sons only, and since, on average, males
marry at an older age, this would make the family effect look bigger than it really is).
The proportional reduction of the family variance component after adding these
characteristics to the model tells us what part of the total family effect can be
attributed to these family and individual factors.
In the final model, we enter parents ages at marriage for the two-generation
sample and parents and grandparents ages at marriage for the three-generation
sample. This allows us to estimate which part of the family effect is brought about
by intergenerational transmission. Parents and grandparents ages at marriage are
specified as linear effects. The coefficients for parents and grandparents ages at
marriage give a direct estimate of the magnitude of the intergenerational
transmission. These coefficients can be interpreted as they would be in standard
(ordinary least squares) regression models. See Sieben (2001) and Kalmijn et al
(2006) for similar applications of multilevel models to assess family effects. In
addition to parents and grandparents ages at marriage, model 3 includes a linear
effect of the number of siblings and a linear effect of year of marriage. Rural place of
marriage of the father and the groom and gender (male) are entered as simple
dummy variables. Two sets of dummy variables are entered into the model for
grooms social class and fathers social class, respectively. In both cases, the
category of skilled workers serves as the reference group.
Finally, we test our specific hypothesis by adding interaction effects to model 3.
For instance, to test whether intergenerational transmission of age at marriage has
become weaker we add two interaction effects; one for fathers age at marriage and
one for mothers age at marriage by year of marriage. We enter interaction effects
separately for each specific hypothesis.
Table 1 and Fig. 1 give an overview of the characteristics of the two- and
threegeneration samples. The average ages at marriage confirm that there were strong
regional differences in age at marriage, with Limburg having the highest and
Zeeland the lowest ages at marriage. On average, brides in Limburg were 2 years
older when they married compared with brides from Zeeland.
Table 2 gives us a first indication of the degree to which there was intergenerational
transmission of age at marriage. This table shows the correlations between the ages
at marriage of the various parties involved in the marriage: brides, grooms, their
fathers and mothers, and the paternal and maternal grandparents. We observe
significant and, at least for parents and children, quite substantial positive
correlations. In Limburg, the correlation between ages at marriage is higher than
in Overijssel and even more so than in Zeeland. Over time, the relation between ages
at marriages has become stronger, a result that runs contrary to our expectations. A
more detailed analysis, not shown here, makes it clear that the correlation between
childrens age at marriage and parents age at marriage increased during the final two
decades of the nineteenth century. In the last years of the observation period (after
1900), the increase seemed to stabilize.
Multivariate Multilevel Regression Models
Is there evidence for a family effect on age at marriage? We first answer this
question by looking at the family variance components in Table 3. The baseline
model (model 1) in Table 3 separates total variation in age at marriage into an
Table 1 Descriptive statistics for the three- and two-generation samples
Fig. 1 Grooms and fathers social class for the two- and three-generation samples. (a) Grooms social
class, two-generation sample; (b) Grooms social class, three-generation sample; (c) Fathers social class,
two-generation sample; (d) Fathers social class, three-generation sample
individual component and a family component. In our sample, 32% of the total
variation can be attributed to family factors that married siblings have in common.
This proportion can also be interpreted as the intraclass correlation coefficient. In
other words, the estimated correlation between the ages at marriage of two randomly
drawn siblings from a randomly drawn family is 0.324. This indicates that there is a
substantial family impact on age at marriage.
To what extent is the family effect on age at marriage caused by differences
among families in sex composition, social class of the offspring, fathers social class,
and place of marriage? This question is answered by comparing model 2, in which
we add individual and family characteristics, with the baseline model. The reduction
of the family variance component when comparing model 1 with model 2 is 20%.
This means that a fifth of the total family effect on age at marriage is due to
differences among families in sex composition, number of siblings, social class, and
place of marriage.
Do parents and grandparents ages at marriage also contribute to the total family
effect on age at marriage? In other words, are there effects of parents age at
marriage on their offsprings age at marriage, and can these effects explain part of
the total family effect? To answer these questions fathers and mothers ages at
marriage are introduced in model 3 for the two-generation sample. The coefficients
from this model are shown in Table 4. We observe that both fathers and mothers
ages at marriage have a significant positive effect on childrens ages at marriage
independent of other family effects. The reduction of variance at the family level
increases from 20% to 27%. The results for the three-generation sample are very
similar. For this sample, we add parents as well as grandparents ages at marriage.
Table 2 Correlations between
age at marriage of (grand)parents
The family effect is somewhat stronger in the three-generation sample. The four
coefficients show that grandparents ages have a positive and significant effect on
their grandchildrens ages at marriage. Nevertheless, grandparents ages at marriage
hardly contribute to the reduction of the family variance component; there is about
Table 3 Variance components at the family and individual level from multilevel models regressing age at
marriage on individual and family characteristics
Model 1 =Year of marriage and province; model 2 = model 1 + individual variables (male, rural place of
marriage, grooms social class) + family variables (fathers social class, rural place of marriage, number of
siblings); model 3 = model 2 + parents age at marriage + grandparents age at marriage
Table 4 Multilevel model regressing age at marriage on individual and family characteristics for the
twoand three-generation samples
All coefficients are significant at the p<0.01 level unless indicated otherwise. Significance levels of a
Wald-test are reported for the two sets of dummy variables for fathers social class and grooms social
class. The models also control for a linear effect of year of marriage
b Unstandardized regression coefficient, SE standard error, ref. reference category, ns not significant
*p<0.001 for both two and three generations; **p<0.05
1% extra reduction of the family variance component compared with a model that
includes only parents ages at marriage (results not shown).
What is the magnitude of the intergenerational transmission of age at marriage?
The coefficients for parents and grandparents ages at marriage in Table 4 indicate
the magnitude of the intergenerational transmission of age at marriage. In the
threegeneration model, for instance, a 1-year increase in mothers age at marriage is
associated with an increase of 0.17 years, or 2 months, in her childs age at marriage.
To give an idea of how large the effects of parents ages at marriage are, we can
compare the effect of the ages of parents with the effect of social class. For example,
the three-generation multivariate model shows that the average age of marriage is
0.72 years (almost 9 months) higher when the groom is a farmer than when the
groom is a skilled worker. This is about a 5-year age difference in mothers age at
marriage, which is associated with a 10-month increase in childs age at marriage
(5 0.17 years = 10 months). The effects of the grandparents ages at marriage are
five to eight times smaller than the effects of parents ages at marriage. The
magnitude of the total intergenerational transmission over three generations can be
illustrated with a numerical example. If we take parents and grandparents into
account, then the effect of all of them having married 5 years later than average is
associated with their offspring marrying 1.7 years later than average.
In additional analyses not shown here, we estimated the total family effect for
each province separately. In a model only including years of marriage and using the
two-generation sample, the total family effect differs among the three provinces in
the following way. In Zeeland, the intraclass coefficient is 0.28, whereas it is 0.33
and 0.37 in Overijssel and Limburg, respectively. In the three-generation sample, we
observe a similar ranking of the three provinces.
Specific Hypotheses about Intergenerational Transmission
Finally, in a series of additional models we test specific hypotheses by adding
interaction effects to model 3. For reasons of presentation these models are not shown
in the tables. Instead, we summarize the outcomes of the tests for these hypotheses.
First, we tested whether the effects of parents ages at marriage decline over time.
Contrary to our expectation, the interaction between marriage year and mothers age
at marriage was significant and positive (unstandardized regression coefficient b =
0.002, p < 0.001). This suggests that the effect of mothers age increased over the
studied period. Also, the interaction between fathers age at marriage and year of
marriage was significant and positive (b = 0.002, p < 0.001). This means that the
effect of fathers age increased as well.
We also tested whether the effects of parental ages differed by sex of the child.
Interaction effects between sex and parents ages at marriage show that mothers age
at marriage affected sons and daughters in the same degree (b = 0.000, p = 0.99),
whereas the effect of fathers age at marriage was stronger for sons than for
daughters (b = 0.07, p < 0.001).
The final two interaction effects tested social class differences in intergenerational
transmission of the age at marriage. We looked at fathers social class only and
found very little support for the hypothesis that intergenerational transmission was
stronger among farmers than among other social classes. In fact, we found the
opposite: intergenerational transmission of age at marriage was smaller among
farmers than among other classes (b = 0.027, p < 0.001). We found no support for
the hypothesis that intergenerational transmission was lower in the class of unskilled
workers compared with all other classes (b = 0.002, p < 0.83). We found similar
results for these interactions in the two-generation and three-generation samples.
Conclusion and Discussion
In this study, we examined to what extent there was intergenerational transmission of
age at entry into marriage in three regions in the Netherlands in the late nineteenth
and early twentieth centuries. Using a unique database, we found evidence of a clear
family effect on age at marriage and substantial intergenerational transmission. In
some families children tended to marry at younger ages, whereas children from other
families married on average at older ages. The total impact that the family of origin
had on age at entry into marriage can partly be attributed to social class and
intergenerational transmission of age at marriage. Although its contribution to the
total family effect was relatively small, the degree of intergenerational transmission
was substantial. Children whose parents married at an older age were more likely to
marry at an older age than children whose parents married at a younger age. We even
observed positive effects of grandparents ages at marriage on their offsprings age at
marriage. Brides and grooms from a family in which parents and grandparents
married 5 years later than average married 1.7 years later than average themselves.
We showed that intergenerational transmission of age at marriage is not a spurious
association produced by social-class effects on age at marriage and the social
reproduction of class positions. Some class effects on age at marriage in our data
were opposite to our expectations: intergenerational transmission was weaker among
farmers than among other social classes. As far as changes through time are
concerned, our hypothesis was also not confirmed: it appeared that the effect of
mothers age and of fathers age actually increased over time. Especially during the
last decades of the nineteenth century, there seems to have been an increase in the
correlation between childrens and parents ages at marriage.
One might suggest that these remarkable results, concerning the role of time and
social class, could be the result of our using a linkage procedure that might lead to
biased estimates. We therefore ran our final model on a sample that included only
marriages from 1900 to 1915. We included marriage data only if they were available
for two or more siblings in this period, and only if the bride or groom was 30 years
of age or younger at the time of marriage. In this sub-sample, biases because of
linkage problems are very unlikely. We obtained similar results to the ones for the
bigger samples and, most important, the effects of parental age at marriage and the
total family impact did not differ substantially from those in the bigger sample.
The fact that in the course of time no decrease in the degree of transmission took
place while social classes with high levels of social control did not show higher levels
of intergenerational transmission suggests that not social control but socialization was
the main factor behind the transmission of behavior over the generations and that
socialization became an increasingly important factor in the transmission process.
Substantial cultural components in the transmission of life course characteristics
over the generations have been found in earlier studies, but to our knowledge, age at
first marriage has hardly ever been included among these traits (except for Anderton
et al. 1987). For social and cultural reasons, age at first reproduction was strongly
affected by age at first marriage. The appropriate age to marry depended on the age
at which individuals were not only physically but also economically and socially
mature (Macfarlane 1986:211216). This made age at first reproduction strongly
dependent on cultural and social and economic factors as well. Kirk et al. (2001)
argue that there may have been a real decrease in the selection gradient on age at first
reproduction in the recent past thanks to improvements in diet and sanitation and the
introduction of effective contraception. As a consequence, women can now
reproduce more successfully at older ages and have greater control over their family
size, and a relaxation of the selection on age at first reproduction is the result. Our
study shows that in the pre-industrial and industrial populations that we compared
there was hardly any change over time in the strength of transmission of a human
life course characteristic that is strongly related to age at first reproduction.
Estimates of the heritability of life-history traits such as age at first reproduction
for male human populations have seldom been made. Pettay et al. (2005) observed
much higher heritability of female life course characteristics compared with male
ones. Their expectation was that in monogamous study populations reproductive
traits depended heavily on female qualities and were physiologically under female
control. In our study the effect of fathers age at marriage was indeed weaker than
that of the mothers age, but male traits did show a high heritability as well. Pettay
and colleagues identify economic resources and physical attributes, such as body
height, as the male traits correlated with attractiveness to females that have a
significant heritability in modern human populations. Our study indeed showed the
importance of one of these attributes, social class, in linking ages at marriage over
the generations but at the same time made clear that other factors play a role as well.
To identify what factors in the socialization process were the most important ones, more
detailed data on family circumstances are needed: for example, the religious background
of the couple and their income. Information on these characteristics will in the near future
become available in historical projects currently underway. Adding these presently
unmeasured family factors will probably explain a major part of the total family effect.
Acknowledgments Constructive comments by three anonymous referees are gratefully acknowledged.
Marco van Leeuwen (International Institute for Social History, Amsterdam) placed HISCLASSs basic
coding list at our disposal. We wish to thank the Zeeuws Archives, the State Archives of Limburg
(Rijksarchief Limburg), and the Historic Centre Overijssel for placing their data at our disposal.