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© The Author(s) 2015. This article is published with open access at Springerlink.com
K. Wolf ()
Department of Demography & Max Planck Institute for Demographic Research,
Rijksuniversiteit Groningen,
Konrad-Zuse-Str. 1, 18057 Rostock, Germany
e-mail: wolf@demogr.mpg.de
S. Krapf
Institut für Soziologie und Sozialpsychologie (ISS), Universität zu Köln,
Greinstraße 2, 50939 Cologne, Germany
e-mail: krapf@wiso.uni-koeln.de
K. Wolf
Population Research Centre, Faculty of Spatial Sciences, University of Groningen,
Landleven 1, 9747 AD Groningen, The Netherlands
Köln Z Soziol (2015) (Suppl) 67:137–164
DOI 10.1007/s11577-015-0331-8
Persisting Differences or Adaptation to German
Fertility Patterns? First and Second Birth
Behavior of the 1.5 and Second Generation
Turkish Migrants in Germany
Sandra Krapf · Katharina Wolf
Abstract In this study, we use data of the German Mikrozensus to explore rst and
second birth behavior of migrants’ descendants. Whereas prior waves of the Mik-
rozensus only included respondents’ citizenship, in the survey years 2005 and 2009
also parental citizenship has been surveyed. This allows us to identify respondents’
migrant backgrounds, even if they have German citizenship. We distinguish those
who migrated as children (1.5 generation) from those who were born to Turkish
parents in Germany (second generation migrants). We compare both migrant gen-
erations to German non-migrants. Using discrete-time hazard models, our results
show that 1.5 generation migrants have the highest probability of having a rst and
second birth, while German non-migrants have the lowest birth probabilities. The
second generation lies in-between. This pattern also persists after taking the educa-
tional attainment of respondents into consideration. However, there seems to be an
adaptation of highly educated second generation Turkish migrants to non-migrant
Germans: we nd no signicant differences in the probability of having a rst birth
in the two groups. For second births, we do not nd this pattern which might be
related to the young age structure in the sample of second generation migrants.
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138 S. Krapf, K. Wolf
1 3
Keywords Migrants’ descendants · Fertility · Second generation ·
1.5 generation · Turkish migrants · Adaptation · Socialization · Germany
Fortdauernde Unterschiede oder Anpassung? Erst- und
Zweitgeburtsverhalten der 1,5ten und zweiten Generation türkischer
Migranten in Deutschland
Zusammenfassung In der vorliegenden Studie analysieren wir auf Basis des Mi-
krozensus das Erst- und Zweitgeburtsverhalten der Nachkommen türkischer Mi-
grantinnen in Deutschland. In früheren Wellen des Mikrozensus wurde zur Identi-
kation des Migrationshintergrundes lediglich die Staatsbürgerschaft erfragt. Die
Mikrozensuswellen 2005 und 2009 geben nun erstmals Auskunft darüber, welche
Staatsbürgerschaft die Eltern der Befragten haben, sodass sich Nachfahren von Mi-
granten auch identizieren lassen nachdem sie die deutsche Staatsbürgerschaft an-
genommen haben. In der Analyse unterscheiden wir zwischen türkischen Migrantin-
nen, die im Kindesalter migrierten (1,5te Generation), und jenen, die von türkischen
Eltern in Deutschland geboren wurden (zweite Migrantengeneration). Beide Grup-
pen werden Frauen in Deutschland ohne Migrationshintergrund gegenübergestellt.
Ergebnisse eines diskreten Hazardmodells zeigen, dass die 1,5te Migrantengenera-
tion die höchste und Nicht-Migrantinnen die niedrigste Wahrscheinlichkeit aufwei-
sen, ein erstes oder zweites Kind zu bekommen. Die Wahrscheinlichkeit einer Ge-
burt in der zweiten Migrantengeneration liegt zwischen denen der anderen beiden
Gruppen. Auch nach Kontrolle für das Bildungsniveau der Frau bleiben diese Mus-
ter bestehen. Allerdings scheint eine Anpassung hochgebildeter Migrantinnen der
zweiten Generation an das Verhalten von Nicht-Migranten stattzunden: Zwischen
beiden Gruppen sind unter den hochgebildeten Frauen keine signikanten Unter-
schiede in der Erstgeburtswahrscheinlichkeit zu nden. Beim Übergang zur zweiten
Geburt ist dieser Effekt eines hohen Bildungsstands weniger stark ausgeprägt.
Schlüsselwörter Nachkommen von Migranten · Fertilität · Zweite Generation ·
Generation 1,5 · Türkische Migranten · Adaption · Sozialisation · Deutschland
1 Introduction
On average Germany has experienced positive net migration in the last few decades,
and the stock of foreign people living in the country has been growing since the
mid-twentieth century (Destatis 2013, 2014). The majority of international migrants
arrived from Mediterranean countries (e.g., from Turkey, Italy, and Greece) in the
context of labor migration in the 1960s and early 1970s, and for family reunion there-
after. Today, migrants with Turkish roots form the largest immigrant group originat-
ing from a single country, representing 3.6 % of the total population in Germany
(Destatis 2012). The special situation of international migrants moving from one
cultural background to the other provides an insight into integration processes and
social change (Kalter 2003). Migrant behavior is often examined by focusing on the
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Persisting Differences or Adaptation to German Fertility Patterns? 139
1 3
question of whether migrants adapt to behavioral patterns in the receiving society. In
this vein, labor market integration (Granato and Kalter 2001; Konietzka and Seibert
2003; Seibert and Solga 2005), educational adaptation (Fick 2011; Groh-Samberg et
al. 2012; Segeritz et al. 2010), and patterns of life satisfaction among migrants (Sa
2010; Siegert 2013; Zapf and Brachtl 1984) have been under study. One aspect that
has been less explored is the demographic adaptation of migrants in Germany. This is
of specic interest for migrants from high fertility countries, such as Turkey. A large
body of international research has investigated the childbearing behavior of migrants,
showing that the timing of migration, the duration of stay, the reasons to migrate and
a person’s labor force participation affect migrant fertility (Andersson 2004; Anders-
son and Scott 2005, 2007; Cygan-Rehm 2011; Mayer and Riphahn 2000; Milewski
2007; Mussino and Strozza 2012; Toulemon 2004; Wolf 2014). These studies focus
on the rst migrant generation, i.e. those who migrated as adults.
In order to better understand the integration processes across migrant genera-
tions, we analyze fertility patterns of Turkish migrants’ descendants. In the 2000s,
children of labor migrants reached ages of 30 years or older. Although they have
not yet completed their reproductive phase, their fertility behavior in their thirties
is already indicative for overall fertility. This study compares non-migrant Germans
and descendants of Turkish migrants. We distinguish between the second generation,
i.e. those who have migrant parents but who were born in the country of destination,
and the so-called 1.5 generation, i.e. those who migrated as children. Our central
research questions are: How do rst and second birth patterns of non-migrant Ger-
mans, 1.5, and second generation Turkish migrants differ? Are fertility differences
between migrants and non-migrants caused by differences in the socio-economic
composition of the groups?
Analyzing those who migrated as children separately is promising in two respects.
On the one hand, selectivity issues or disruption arguments are less relevant for the
1.5 generation migrants because they did not take the decision to migrate themselves.
While the rst generation, who migrated as adults, might consciously time their deci-
sion to migrate and to start a family, for the 1.5 generation the migration and fertility
transitions can be assumed to be independent of one another. Their fertility should not
be distorted by migration timing, as is the case for migrants who arrived during their
childbearing years (Toulemon 2004; Wolf 2014). Accordingly, selection into migra-
tion is less relevant for the 1.5 generation and biases are avoided (Adsera et al. 2012).
On the other hand, contrasting second and 1.5 generation migrants allows us to single
out the effect of childhood socialization, as this is the main distinction of these two
groups. The 1.5 generation was partly exposed to family values in the country of ori-
gin whereas the second generation experienced their entire childhood in the country
of destination. Therefore, variations in fertility behaviour between the two groups are
likely to be the result of different socialization environments.
Our analyses are based on the German Mikrozensus. The large sample size allows
us to study the descendants of Turkish migrants as a single migrant group. We use
two Mikrozensus waves from the years 2005 and 2009. In other survey years, migra-
tion information was limited to citizenship and year of migration, which made it
impossible to identify second generation migrants with German citizenship. The
extended question program in 2005 and 2009 allows us to identify these second gen-
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140 S. Krapf, K. Wolf
1 3
eration migrants. Using the own-children method, we generate the age at childbirth.
We compare the transition to rst and second birth among women of the two migrant
groups to non-migrant western Germans, i.e. respondents who were born in Germany
and whose parents were non-migrants. By employing event history techniques, we
control for standard socio-demographic characteristics, such as education. Although
it would have been interesting to also analyze third birth behavior, only a very selec-
tive group is at risk of having a third birth as particularly the second but also the 1.5
generation are rather young (see Table 5 in the appendix).
2 Theoretical consideration
Especially those migrants who decide to stay are of great importance for the demo-
graphic development of a country because the group of stayers affect population
development. This leads to the question of how far integration progresses and what
the determinants are. A rst attempt to present a theoretical framework was made
by representatives of the Chicago School, who developed an approach to explain
assimilation processes in the US (Gordon 1964; Park and Burgess 1921). The clas-
sical assimilation theory describes the decline of an ethnic or racial distinction and
the cultural and social differences that express it (Alba and Nee 1997). Assimila-
tion was expected to be an inevitable, gradual process which increases over immi-
grant generations (Alba and Nee 1997; Zhou 1997). However, the theory received a
lot of criticism. It was argued that receiving societies are not homogenous and that
migrants might adapt to specic groups rather than to mainstream society, result-
ing in segmented assimilation (Portes and Zhou 1993; Rumbaut 1994). Moreover,
it was criticized that both classical assimilation and segmented assimilation theory
do not offer explicit mechanisms to explain assimilation processes, but they merely
describe empirical outcomes (Esser 2004, 2008). Others observed that the concept
of assimilation in general implies a dominance of the majority society (Bade and
Bommes 2004). Thus, in Europe since the 1980s, researchers prefer the normatively
more neutral concept of integration to the term assimilation (Aumüller 2009, p. 34).
Social integration can be conceptualized as a “process of inclusion and acceptance
of migrants in the core institutions, relations and statuses of the receiving society”
(Heckmann 2006, p. 18). The processes can refer to rst generation immigrants as
well as to their children and grandchildren (ibid.: p. 17).
The fertility patterns of migrants can serve as an indicator of integration into the
society in the country of destination (Coleman 1994). Fertility decisions are inu-
enced by both cultural and structural conditions (Lesthaeghe and Surkyn 1988; Let-
ablier et al. 2009; Rindfuss and Brewster 1996). The two mechanisms can differ
between countries, which might result in diverse fertility patterns across countries. If
migrants follow their home country’s predominant fertility behaviour, this can lead
to fertility differentials between migrants and non-migrants in the country of destina-
tion. A number of theoretical arguments have been suggested to explain the fertility
behavior of rst generation migrants, such as the socialization, adaptation, disrup-
tion, and selection hypotheses (Kulu 2005; Kulu and González-Ferrer 2013; Lind-
strom and Giorguli Saucedo 2007). However, there is less research on the fertility
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Persisting Differences or Adaptation to German Fertility Patterns? 141
1 3
behavior of migrants’ descendants. We argue that comparing second and 1.5 genera-
tion is promising because neither of the groups has taken the decision to migrate on
their own. Therefore, disruption effects do not play a role in their fertility patterns.
While for the rst generation it was argued that Turkish migrants are a selective
group with rather low socio-economic background, this should be of minor relevance
for the descendants of migrants. It has been shown that they also differ systematically
in their socio-economic situation from non-migrants in the country of destination.
However, the effect of the parents’ socio-economic background on children’s char-
acteristics should be similar for both the 1.5 and second generation, and comparing
the two groups should not lead to distortions due to selectivity. In the following, we
discuss how socialization, adaptation and composition effects might explain differ-
ences in fertility behavior among non-migrants, second, and 1.5 generation migrants.
2.1 Childhood socialization
Family values and gender role attitudes differ across countries (Nauck and Klaus
2007). Based on socialization theory, researchers expect that these social roles and
values are transmitted to each social group member via socialization (Goode 1964).
In the classic formulation of the theory, socialization is described as a process that
takes place largely within the family and during childhood (Parsons 1955). Family-
related norms and values are also transmitted during childhood within the family
(Putney and Bengtson 2002). In line with this, it has been shown that mothers pass
on their gender role attitudes (Moen et al. 1997), and their childbearing preferences
(Barber 2000) to their daughters.
Concerning international immigrants, it is argued that the home country’s norms
and values regarding fertility preferences persist even after migration. Empirical evi-
dence has shown that those who migrated from high fertility origin countries have
considerably higher fertility than non-migrants in the low fertility destination coun-
tries (Alders 2000 for the Netherlands; Andersson 2004 for Sweden; Kahn 1988 for
the US). However, fertility norms and values are also transmitted via the rst gen-
eration to their children. In line with this, it was found that rst generation migrants
transmit their higher child number ideals and lower age norms concerning the rst
child to their children (Nauck 2001; Nauck et al. 1997). Also for female migrants in
the Netherlands, studies have indicated that children reproduce their parents’ prefer-
ences for an early entry into motherhood (De Valk 2006; De Valk and Liefbroer 2007).
These attitudes are mirrored in fertility patterns: the second generation of Turkish
migrants shows higher rst birth rates than do the majority populations in several
European countries (Milewski 2011). Moreover, a study of Germany indicates that
second generation migrants are on average younger at rst birth than non-migrant
(western) Germans, but are older than rst generation migrants (Milewski 2010a).
Socialization arguments explain not only why migrants and their descendants
show different fertility behaviour than non-migrants. They also provide a framework
to explain why migrant generations are distinct. Based on the fact that the 1.5 genera-
tion was born in Turkey and the second generation migrants were born in Germany,
the two groups have partly different socialization experiences. Both groups are inu-
enced by the Turkish community and family in the country of destination. But those
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142 S. Krapf, K. Wolf
1 3
migrating as children were partly socialized in the country of origin, i.e. they were
exposed to their home countries’ norms to a larger extent than those born in the host
country. By contrast, the second generation experienced socialization entirely in the
receiving society. They maintained social contacts with both peers of Turkish origin
and non-migrant Germans during childhood and were thus exposed to German fam-
ily norms to some extent. Also their parents had been living longer in the receiving
society and might have adapted to the host country norms themselves. Because of
their different socialization experiences during childhood, we expect that 1.5 genera-
tion Turkish migrants are more likely to have a child than non-migrants and that the
second generation takes on an intermediate position between the two groups (hypoth-
esis 1).
2.2 Adaptation
While socialization arguments are usually employed to explain behavioural differ-
ences between migrant generations and non-migrants, adaptation arguments help us
to understand why fertility patterns converge. Adaptation consists of two different
mechanisms that are interrelated and affect one another (Frank and Heuveline 2005;
Kulu 2005; Rumbaut and Weeks 1986). On the one hand, the economic conditions
in the country of destination affect childbearing. From a neo-classical micro-eco-
nomic perspective, fertility decisions are the product of direct costs and opportunity
costs of children (Becker 1991; Hotz et al. 1997; Mincer 1963). Moving to a country
with better job perspectives for women and higher living costs increases the costs of
childrearing for migrants from less developed areas. Accordingly, they adapt their
fertility behavior toward lower fertility and later birth transitions. In line with this,
studies in Sweden have shown that women participating in the labour market have
largely the same fertility patterns—independent of migrant background (Andersson
and Scott 2005, 2007). On the other hand, fertility is determined by norms and values
concerning the ideal family size and the timing of parenthood. According to Hoffman
and Hoffman’s (1973) “Values of Children”-approach, the “value of children refers
to the functions they serve or the needs they fulll for parents” (ibid.: 46 f.). Empiri-
cally, it has been shown that the value parents attach to children differs systematically
across countries (Nauck 2007; Nauck and Klaus 2007). In a similar vein, the Second
Demographic Transition-approach links the cultural change seen in many European
countries over the last decades, marked by secular individualization trends, with
decreasing fertility levels (Lesthaeghe 1995; Sobotka 2008; Van De Kaa 1994). Non-
western migrants are exposed to these individualistic norms and values after migrat-
ing to European countries. They might adapt to the lower child number ideals and
preferences for later entry into parenthood prevalent in the country of destination.
Initially, the concept of adaptation was used to explain adjustment processes of
rst generation immigrants in the short-term. The degree of adaptation was assumed
to increase the longer a migrant resides in the receiving society (Hervitz 1985; Kahn
1988; Lindstrom and Giorguli Saucedo 2002; Singley and Landale 1998; Stephen
and Bean 1992). But adaptation theory can also be translated to immigrants’ chil-
dren. For their entire adult life, both the 1.5 and the second migrant generation are
exposed to the normative and economic conditions in the country of destination.
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Persisting Differences or Adaptation to German Fertility Patterns? 143
1 3
They might thus experience cultural adaptation via social contacts with the major-
ity population, affecting their childbearing preferences. Migrants’ descendants are
subject to the receiving society’s institutions and labour markets, which impacts the
opportunity structure and thus childbearing. In line with this, it has been shown that
across Europe second generation migrants reported higher ideal ages at parenthood
than the rst generation (Holland and De Valk 2013).
The adaptation of norms and values somehow contradicts the socialization theory
in its original sense, where fertility preferences are assumed to be based on childhood
socialization and stay constant over the life course. Nevertheless, socialization can be
seen as a lifelong process, as individuals change their preferences and attitudes even
after the beginning of adulthood (Mortimer and Simmons 1978; Settersten Jr. 2002).
With a focus on the adult life, the adaptation theory states that the relevance of the
conditions in the receiving society exceed the inuence of the fertility preferences
absorbed during childhood socialization. Both second and 1.5 generation migrants
were exposed to German norms and conditions their entire adult lives, thus we have
no reason to expect differences between 1.5 and second generation Turkish migrants
(hypothesis 2).
2.3 Compositional effects
Turkish migrants have a different socio-economic, cultural and demographic back-
ground than non-migrant Germans, and these aspects are relevant for childbearing
decisions. Therefore, the composition of migrant groups could be responsible for
fertility differentials. In addition to cultural factors, such as religion, language, and
family orientation, the differences between migrants and non-migrants in the country
of destination lie particularly in the socio-economic sphere. One indicator to approxi-
mate the socio-economic status of a person is his or her level of educational attain-
ment. From a micro-economic perspective, higher educational levels are related to
higher opportunity costs and lead to lower fertility (Schultz 1969). This negative
effect is also reected in elevated postponement of rst births among highly educated
and career-oriented women (Gustafsson 2001). Concerning higher order births, the
relationship seems to be more complex. For some western European countries, it has
been shown that education was positively related to second and/or third birth risks
(Kreyenfeld and Konietzka 2008; Lappegård and Rønsen 2005; Tesching 2012).
For migrants and their descendants, it has been found that on average second gen-
eration migrants attend school longer than rst generation migrants (Dustmann et
al. 2012), while the educational gradient among non-migrant Germans, the second,
and the 1.5 generation persists (Fick 2011). Following the composition hypothesis
these educational differences would account for differences in fertility patterns of
migrants and non-migrants. Based on such compositional effects, there are no rea-
sons to expect that differences in birth risks among non-migrant Germans, 1.5 and
second generation Turkish migrants persist after accounting for the effect of educa-
tion (hypothesis 3).
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144 S. Krapf, K. Wolf
1 3
3 Turkish migrants and their descendants in Germany
Immigration from Turkey to Germany was induced by large labor shortages in
Germany after World War II. To acquire foreign workers, the German government
initiated agreements with several Mediterranean countries: Italy (1955), Spain and
Greece (1960), Morocco (1963), Portugal (1964), Tunisia (1965) and former Yugo-
slavia (1968). The contract on coordinated labor migration from Turkey to Germany
was signed in 1961. Most labor migrants from Turkey came from agrarian regions
and had vocational qualications for jobs in craft industries. Thus they had higher
qualications than the average Turkish population, but lower education than the aver-
age non-migrant German (Treichler 1998). Once in Germany, labor migrants lled
mostly unskilled and semi-skilled jobs in industry (Seifert 1997). After the oil price
shock and the resulting recession in 1973, the recruitment agreements were termi-
nated. In the following phase, the only option to emigrate legally from Turkey to
Germany was to rely on the right of family reunication or to ask for political asy-
lum. For family reunication, an immigrant living in Germany was allowed to bring
a foreign spouse and children up to age 15 to the country. As a result, the size of the
foreign population in Germany increased and its composition changed (Heckmann
2003). Before 1973, immigrants were primarily workers aged between 20 and 40,
most of them men. Later, more and more women and children migrated for family
reunion (Münz et al. 1999).
Today, Turkish migrants and their descendants represent 3.6 % of the total German
population (Destatis 2012). About half of them belong to the rst immigrant genera-
tion and migrated themselves, the second generation makes up the other half (Desta-
tis 2012). Turkish migrants and their descendants primarily live in western Germany,
particularly in urban areas (Haug et al. 2009). In regard to religion, Turkish migrants
form quite a homogeneous group, as more than 80 % are Muslim (Haug et al. 2009).
On average, rst generation Turkish migrants show lower educational degrees than
non-migrant Germans (Müller and Stanat 2006; Segeritz et al. 2010). In addition,
vocational qualication is low. Among Turkish women of the rst migrant genera-
tion, fewer than 10 % have a vocational degree that is recognized in Germany. This
is partly due to the limited transferability of degrees, because roughly 4 % of Turkish
rst generation women have a vocational degree that is not recognized in Germany.
However, these levels also reect the fact that obtaining vocational qualication was
less common in their regions of origin in the past, particularly for women. A large
share of rst generation Turkish women, about 85 %, never obtained any vocational
degree (Stichs 2008). This low level of qualication also affects migrants’ position
in the labor market. It was found that immigrants in Germany have easier access to
blue-collar jobs than to white-collar jobs (Seifert 1996). The picture is different for
the second migrant generation. Because they grew up and obtained their educational
degrees in Germany, their qualications do not need to be transferred to the German
system. On average, they obtain higher educational degrees and vocational education
more often than do rst generation migrants. However, compared to non-migrant
Germans, their educational and vocational status remains lower (Müller and Stanat
2006; Segeritz et al. 2010; Stichs 2008). The 1.5 generation lies in between, in that
they obtained a higher educational status than their parents, but are on average less
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Persisting Differences or Adaptation to German Fertility Patterns? 145
1 3
educated compared to the second generation (Fick 2011; Segeritz et al. 2010; Seibert
2008).1 Altogether, socio-economic differences among Turkish migrants of the 1.5
and second generation and German non-migrants persist, and may possibly explain
fertility distinctions in these groups.
In addition to the socio-economic status, family norms and values in the country
of origin play an important role for migrant fertility. In the case of Turkish migrants,
their religious and cultural factors differ considerably from those prevalent in Ger-
many. In Turkey, social change has been dramatic since the beginning of the twen-
tieth century, resulting in large disparities across social groups, who experience this
change at different paces (Nauck 2002). There is no homogeneous development in
Turkish society, as a situation of continuity and change has led to a hybridity of west-
ern and indigenous values (Kavas und Thornton 2013). In Turkey there is a strong
belief in the concept of marriage, which is shown by undiminished marriage rates
and the still extensive inuence of parents on partner selection and marriage (Nauck
und Klaus 2008). Intergenerational ties are still strong and it is expected that chil-
dren help their parents when they are old (Nauck 2002). Nevertheless it has been
reported that the value of children has been shifted from a focus on the economic
advantage of children, e.g. in form of (material and non-material) help for parents,
toward children’s psychological value (Kagitcibasi und Ataca 2005). The psycho-
logical value of children lies in the emotional rewards expected from having children,
which is often related to a lower number of children (Nauck und Klaus 2007). In
line with this, Turkish society has seen a sharp fertility decline since the beginning
in the mid-twentieth century. The average total fertility rate (TFR) fell from 6.62 in
the period 1950–1955 to 2.16—close to replacement level—in 2005–2010 (United
Nations 2012). Despite the strong reduction in period fertility, only 10 % of women
age 35 were childless in the year 2003 (Yavuz 2008), and a survey among university
students in Ankara has shown that the social acceptance of childlessness is still low
(Çopur und Koropeckyj-Cox 2010).
Compared to a TFR in Germany of approximately 1.4 since the 1970s, fertility
in Turkey is still high. But within Turkey, there are large differences across ethnic
groups. Particularly Kurdish women show much higher rates of having a higher order
birth than do women of other ethnicities (Yavuz 2008). Moreover, there is also a
strong educational gradient: women with high education have lower fertility than
those with less education (Yavuz 2008; Nauck 2002). In addition, fertility behav-
ior differs by region. Women living in urban regions experience the transition to
rst, second, and third childbirth less often and later in their life course compared to
women living in rural areas (Eryurt and Koç 2012), and fertility rates are still consid-
erbaly higher in the east than in the west of the country (Nauck und Klaus 2008). The
heterogeneity of fertility patterns in Turkey across regions and ethnic groups makes
it difcult to evaluate socialization arguments. Unfortunately, our data contain no
information on the region of origin nor on the social environment of a person.
1 It should be noted that the denition of the 1.5 generation migrants differ across studies. Seibert (2008)
denes 1.5 generation migrants as those who arrived in Germany before age 15. Segeritz et al. (2010) and
Fick (2011) refer to those who arrived in Germany by school starting age (6 years).
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146 S. Krapf, K. Wolf
1 3
4 Data and methods
4.1 Data
Our analyses are based on pooled cross-sectional data from the German Mikrozensus
of the years 2005 and 2009. In these two years, the household survey’s obligatory
question program was extended. Prior to that, migrants could be identied only on
the basis of citizenship and place of birth, meaning that descendants of migrants who
were born in Germany and who had German citizenship could not be identied. In
the 2005 and 2009 questionnaires a number of items refer to parents’ migration sta-
tus, which allows us to distinguish the second generation even if respondents have
German citizenship.
The Mikrozensus is a one-percent sample of all German households, covering
standard socio-demographic characteristics such as age, citizenship, region of resi-
dence, educational attainment, etc. The scientic use le contains a 70 % subsample
of the Mikrozensus data. While other studies often pool migrants from different coun-
tries of origin, the large sample size of the Mikrozensus enables Turkish migrants to
be differentiated from other migrant groups. Moreover, in comparison with other
surveys, nonresponse is of minor relevance in the Mikrozensus because participation
is not voluntary; respondents are required by law to submit information. Unfortu-
nately, the detailed information collected in the survey refers only to the household
members, not to persons who do not live in the household. Therefore, no complete
fertility histories are provided. Instead, the number of children born per woman needs
to be estimated via the number of co-residing children. We reconstructed women’s
fertility histories by means of the so-called “own-children method”, based on the
year of birth of the mother and the year of birth of each child living in the household.
This procedure might underestimate the true number of children a person has, espe-
cially in cases where a child has already left the parental home. It has been shown for
respondents living in western Germany that the numbers of children calculated on
basis of the “own-children method” are largely consistent with the reported numbers
of biological children up to a maternal age of 40 in the Mikrozensus 2008 (Krapf
and Kreyenfeld 2015). This limits our analysis to children co-residing with women
in the age range 18 to 40 years, i.e. childbirths that take place beyond age 40 are
not considered. Another limitation of the data is related to the fact that respondents’
characteristics refer only to the time of interview, which means we cannot account
for time-varying covariates.
The vast majority of people of foreign origin migrated to western Germany and
continue to live there (Destatis 2012; Münz et al. 1999). As fertility patterns differ
between eastern and western Germans (Huinink et al. 2012), we compare those with
Turkish background to non-migrants living in western Germany, excluding respon-
dents living in eastern Germany from our analyses. Moreover, we do not consider
respondents who are not of a Turkish or German background. This leaves us with a
sample of 85,570 respondents, the vast majority of which are non-migrant Germans
(82,651) and two smaller samples of 1.5 generation migrants (1130) and second gen-
eration migrants (1789).
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Persisting Differences or Adaptation to German Fertility Patterns? 147
1 3
4.2 Methods
In a rst descriptive step, we use Kaplan-Meier survival curves to compare the fertil-
ity behavior of respondents of migrant origin and non-migrant Germans. In the mul-
tivariate analyses, we run discrete-time hazard models. For the transition to rst birth,
the process time is the age of woman. The information on the age at rst birth is gen-
erated based on the difference between the mother’s birth year and the year of birth of
the oldest child in the household. For the transition to second birth, the duration since
birth of the rst child denotes the process time. It is calculated using the difference
in the birth year of the oldest and the second-oldest child living in the household.
As the yearly birth information does not allow us to distinguish between twin births
and two consecutive births in a time frame smaller than 12 months, we excluded the
respective respondents from the analysis of second births. Because our time scale
is discrete, and assuming that the underlying latent time variable was continuous,
we specied the hazard rate as complementary log-log (cloglog) function (Allison
1982). The data are organized in person-year format, with each person potentially
contributing one entry per year. Cases are censored in the year a woman gives birth
or when a respondent has not yet had a rst (second) birth at time of the interview.
To identify whether education has a different effect on fertility patterns among
non-migrant Germans and the descendants of migrants, we also interact the level of
education with migrant status (two-way interaction). Moreover, we run three-way
interactions in order to account for the fertility intensities by age according to edu-
cational group. It has been shown that women with lower educational levels have
their highest rst birth risks in their mid-twenties, while those with higher education
levels enter motherhood at later ages on average (Tesching 2012). In order to exam-
ine whether these age patterns differ according to migrant background, we interact
the level of education, migrant status and the age of rst birth. It has to be noted that
for this model we reduced the number of age groups to three (18–25, 26–32, 33–40
years). This was necessary because of the small sample size, especially for respon-
dents of Turkish origin in the high education group. Due to sample size issues we also
refrain from running the three-way-interaction for second births.
4.3 Explanatory variables
In the multivariate analyses, the key variable is the migration background of a
woman. We dene three groups: non-migrants include respondents who were born
in Germany and whose parents have or had exclusively German citizenship. Second
generation migrants were born in Germany, but their parents have or had Turkish
citizenship.2 The third group comprises generation 1.5, who were born in Turkey,
migrated to Germany as a child and who have or had Turkish citizenship. Respon-
dents are categorized as 1.5 generation if they migrated before age 15. It would have
2 In order to clearly distinguish between second and third generation migrants, we would need information
not only on parents’ citizenship but on their place of birth, which is not available for all respondents in the
Mikrozensus. However, we argue that third generation Turkish migrants are only reaching adulthood now
and thus are only to a minor extent considered in the age groups under study.
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148 S. Krapf, K. Wolf
1 3
been interesting to investigate the behavior of those with one Turkish and one Ger-
man parent, but this group was too small for any meaningful analysis and was there-
fore excluded from the sample. Also those who had a parent with other than Turkish
or German citizenship were not considered in the analyses.
Both the woman’s birth cohort and age at birth are relevant determinants of fertil-
ity decisions. We dene three cohorts: born in 1965–1972, 1973–1979 or 1980–1991.
The age at birth was generated and grouped into four categories (18–24 years, 25–29
years, 30–34 years and 35–40 years). In our sample, the migrant groups differ regard-
ing their age structure. Respondents of the second generation are younger than 1.5
generation migrants and non-migrant Germans. For both the 1.5 and the second gen-
eration, we nd that the majority of observations in our sample for the transition to
a rst birth belong to the birth cohort 1970–1979. While more than one third of the
second generation belong to the youngest cohort (born 1980–1991), this is the case
for only about 14 % among generation 1.5 (see Table 3 in the appendix). The reason
for this is simple: Turkish women immigrating after 1973 came primarily in the con-
text of a family reunion (Münz et al. 1999). They arrived with their children under
age 16 years, who belong to the generation 1.5. Second generation migrants were
generally born after that time, and in the two Mikrozensus waves of 2005 and 2009
they had not yet reached the age of 40 years (see Table 3 in the appendix). As only a
small number of second generation migrants in the data were born before 1965, we
restrict the sample to those born afterwards. This leaves us with respondents born
between 1965 and 1991.
In the analyses of the transition to second birth, the focus is on the age of rst child
at time of second birth. It has been shown that non-migrants have their rst child later
than those of migrant origin. In order to evaluate differences in birth timing between
Turkish migrant’s descendants and non-migrant Germans, we also control for the age
at rst birth.
Another variable of interest is education. As mentioned before, the variables in the
Mikrozensus are available only for the time of interview. Assuming that the wom-
en’s school education was completed in early adulthood, we create three catego-
ries for education: lower secondary or no school degree (low), secondary education
(medium) and higher secondary education (high). The number of respondents who
were enrolled in school at the time of the interview was very small. As this group
had not yet gained a degree, we categorized them into the lower secondary school
group. The descriptive statistics show that in our sample, non-migrant Germans have
the highest level of education compared to 1.5 and second generation migrants. This
is the case for both the sample for the rst birth and the sample for the second birth
analyses (see Tables 3 and 4 in the appendix). While only a small share of respon-
dents of the 1.5 generation had high education (rst birth sample: 17.7 %, second
birth sample: 6.2 %), this share has increased for the second generation (rst birth
sample: 29.8 %, second birth sample: 9.2 %).
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Persisting Differences or Adaptation to German Fertility Patterns? 149
1 3
5 Results
5.1 Descriptive Results
As a rst step, we compare rst and second births based on survival curves. How-
ever, using yearly time information results in an overestimation of the Kaplan-Meier
survival estimates. In order to reduce this overestimation, we imputed a random birth
month. Figure 1 describes the pattern of the transition to rst and second births on
basis of the pooled Mikrozensus data for the years 2005 and 2009. The rst panel
shows the estimated Kaplan-Meier survival curves for rst births. For Germans, the
median age at rst birth was reached at 31.3 years. For 1.5 generation migrants the
median age was 24.3, while for second generation migrants it was 27.3 years. This
shows that the 1.5 generation migrants in Germany had their rst childbirth ear-
lier compared to non-migrants, while second generation migrants lie in between. In
our sample, second generation migrants are still quite young; only few of them had
reached ages above 38 at time of interview. The level of childlessness at age 37 is
highest among non-migrants, lower for the second generation and lowest for the 1.5
Fig. 1 Survival curves. Non-
migrant Germans, 1.5 and
second generation migrants.
Female respondents of birth
cohorts 1965–1991. (Source:
Mikrozensus 2005 and 2009,
unweighted. Authors’ own
illustration)
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150 S. Krapf, K. Wolf
1 3
generation. In order to investigate whether the different cohort composition of the
three groups under study is responsible for the different fertility patterns, we com-
pared the survival curves by ve year birth cohorts (born 1965–1969, 1970–1974,
1975–1979, 1980 − 984). Although the number of exposure and occurrences was
small, this sensitivity check revealed that within each cohort, the second generation
remained on the intermediate position found in Fig. 1.3
The second panel of Fig. 1 illustrates the transition to second birth. Here, the
process time of interest is the duration since rst birth. For all three migrant status
groups, the likelihood of having a second child is highest one to four years after the
rst child was born. The curves for the three groups follow a similar pattern for these
rst four years, with the 1.5 having the second birth a bit faster than the other two
groups. For Germans, the process slows down after four years, while for Turkish
descendants it continues. On average, this divergence of the survival curves after four
years since rst birth suggests longer birth spacing intervals for Turkish descendants
compared to non-migrant Germans.
In sum, women with Turkish origin seem to start childbearing earlier and space
their subsequent births further apart than do non-migrant Germans. Also, for the tran-
sition to second births, sensitivity checks for each birth cohort supported our results.4
5.2 Multivariate Analyses
This section presents the results of the discrete-time hazard models on the transition
to rst and second births (see Tables 1 and 2). The covariates for the rst and second
birth models are introduced to the regression models stepwise, hence the results are
presented as average marginal effects (AME), which are preferable to odds ratios
when interpreting results of nested models (Best und Wolf 2012; Mood 2010). For
our categorical independent variable, the AME indicates by how much the predicted
probability of having a child changes on average for the respective variable value.
Model 1a shows a hump-shaped effect of age: The annual probability to have
a rst birth is low for respondents under age 25, rises for those between 25 and
34 years, and diminishes again for those in the age group 35 to 40 years. For birth
cohort, we nd a negative effect: Women born earlier have a higher annual prob-
ability of having a rst birth than those born in younger birth cohorts. This indi-
cates that there is an on-going postponement of rst births. Concerning the migration
background of respondents, we dened second generation migrants as a reference
category in order to not only show the difference between those with Turkish ori-
gin and non-migrants, but also to evaluate whether there are signicant differences
between the two migrant generations. Our results indicate that the annual probability
of non-migrant Germans is lower (AME = − 0.037), while that of the 1.5 generation
migrants is higher (AME = 0.032) compared to respondents of the second generation
(reference). In Model 1b, we additionally control for respondents’ education. We nd
a negative educational gradient: the higher the school education, the lower the annual
probability of having a rst birth. The effect of migration status is slightly reduced
3 Results available upon request.
4 Results available upon request.
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Persisting Differences or Adaptation to German Fertility Patterns? 151
1 3
compared to model 1 but remains signicant. This reveals that fertility differentials
of non-migrants, second and 1.5 generation migrants are not fully explained by the
educational composition of the three groups.
In order to identify whether the effect of education on rst births differs across
migrant generations, in Model 2 we include a two-way interaction effect of migrant
background and educational attainment. Figure 2 displays the AME graphically with
the second generation as reference group. The corresponding numbers are shown in
Table 6 in the appendix. It reveals that Germans have the lowest annual probability
of having a rst birth, followed by second generation Turkish migrants, while respon-
dents of the 1.5 generation have the highest annual probability of having a rst child.
However, the difference between the three migrant status groups converges over
school education. While the difference is largest among women in the low education
group, it is less pronounced for women with medium education and diminishes for
those with high education. Among highly educated women the three migrant status
groups do not differ regarding their annual probabilities of having a rst birth.
Other studies have shown that each education group follows different fertility
patterns over age (Tesching 2012). In order to identify how these patterns vary for
migrants and non-migrants, we estimated three-way interaction models of education,
migrant status, and age. Due to the small sample size, the occurrence of rst birth in
some categories was rare and therefore we reduced the number of age groups from
four to three (cf. Table 7 in the appendix). Figure 3 shows the results of the three-way
interaction by migrant status (Table 8 in the appendix presents these numbers). We
display predicted probabilities because we are interested in the absolute probabilities
Table 1 Determinants of the transition to rst births. Discrete-time hazard model. Average marginal ef-
fects. (Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
Model 1a Model 1b
Age
18–24 − 0.038*** − 0.041***
25–29 Ref. Ref.
30–34 0.009*** 0.010***
35–40 − 0.024*** − 0.025***
Cohort
1965–1972 0.007*** 0.003***
1973–1979 Ref. Ref.
1980–1991 − 0.013*** − 0.013***
Migration background
German − 0.037*** − 0.025***
1.5 generation Turkish 0.032*** 0.022***
2nd generation Turkish Ref. Ref.
School education
Low 0.017***
Medium Ref.
High − 0.024***
Person years 732,371 732,371
Number of events 31,784 31,784
*p < = 0.10 ; * *p < = 0. 05 ; * * * p < = 0.01
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152 S. Krapf, K. Wolf
1 3
Fig. 2 Interaction migration background and education. Transition to rst birth. Discrete-time hazard
model (Model 2). Average marginal effects. (Source: Mikrozensus 2005 and 2009, unweighted. Authors’
own illustrations. Notes: Controlled for mother’s age, cohort)
Table 2 Determinants of the transition to second births. Discrete-time hazard model. Average marginal
effects. (Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
Model 4a Model 4b
Years since rst birth
1-<2 − 0.242*** − 0.242***
2-<4 Ref. Ref.
4-<7 − 0.079*** − 0.078***
7-<10 − 0.232*** − 0.232***
10+ − 0.264*** − 0.264***
Mother’s age at rst childbirth
18–24 − 0.002 0.005
25–29 Ref. Ref.
30–34 − 0.030*** − 0.036***
35–40 − 0.071*** − 0.080***
Birth cohort
1965–1972 − 0.002 0.001
1973–1979 Ref. Ref.
1980–1991 − 0.046*** − 0.044***
Migration background
German − 0.019 − 0.024*
1.5 generation Turkish 0.054*** 0.057***
2nd generation Turkish Ref. Ref.
School education
Low − 0.006
Medium Ref.
High 0.042***
Person years 70,768 70,768
Number of events 17,613 17,613
*p < = 0.10 ; * *p < = 0. 05 ; * * * p < = 0.01
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Persisting Differences or Adaptation to German Fertility Patterns? 153
1 3
of having a rst child for all our age and educational groups. This allows us to iden-
tify age patterns for women with low, medium or high education in each migration
status group. Average marginal effects, by contrast, would show the average effect
of age and education on the probability of having a rst child in comparison to one
specic reference group (e.g., second generation migrants). This would not reveal
the age patterns for childbearing in each migrant group—which was the focus of our
three-way interaction model. The rst panel of Fig. 3 presents the pattern of non-
migrant Germans. For highly educated German women the probability of having a
rst birth rises with increasing age. They postpone rst birth and have the highest
annual fertility probability in the age group 33–40 years. They are also more likely
to have a rst birth in this age category compared to other education groups. By
contrast, rst childbirth among non-migrants with low or medium education is high-
est in the medium age group of 26–32 years. The pattern for descendants of Turkish
migrants differs markedly from that of German non-migrants: Panel 2 of Fig. 3 shows
that the probability of rst birth of the 1.5 generation with high education remains
low across all age groups. Women with a low educational level seem to show higher
annual probabilities for rst birth in the younger age groups. By contrast, women in
Fig. 3 Three-way interaction
of migration status, education
and age. Transition to rst
birth. Discrete-time hazard
model. Predicted probabili-
ties. (Source: Mikrozensus
2005 and 2009, unweighted.
Authors’ own illustrations)
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154 S. Krapf, K. Wolf
1 3
the medium education category are more likely to give birth with increasing age. For
the second generation (Panel 3 in Fig. 3), we nd yet another pattern. The annual
probability of having a rst child among highly educated women is again lowest
compared to other education groups and peaks at ages 26–32 years. Women with
lower levels of education show nearly constant birth probabilities over age, while
women with a medium level of education have highest probabilities of rst birth in
the oldest age group.
To summarize, the nding for highly educated non-migrant Germans indicate a
postponement of rst childbirth into higher ages, as was also found in previous works
on western countries (Blossfeld and Huinink 1991; Ní Bhrolcháin and Beaujouan
2012). For Turkish descendants, we see no postponement of rst births among the
highly educated, but their fertility level remains low across all age groups compared
to those with lower education. For both the 1.5 and second generation migrants, the
pattern for women with a medium level of education seems to resemble that of highly
educated Germans, showing an increasing probability of having a rst birth over age.
This effect is more pronounced among Turkish descendants of the second genera-
tion. For the interpretation, however, we have to keep in mind that the results, espe-
cially for highly educated women in the highest age group, refer to a small number
of women in our sample (see also Table 7 in the appendix). This is related to two
aspects: First, a smaller number of Turkish origin women have higher education.
Second, Turkish migrants’ descendants are still very young and are only now reach-
ing the ages of 35 and above.
Table 2 presents the results of the discrete-time hazard model on the transition to
second birth. In these models the process time is the duration since rst birth. It is
shown that the probability of second birth is highest two to four years after rst birth.
Before and after that, the probability is lower. We also control for maternal age at
rst birth. In line with other studies (e.g. Kreyenfeld 2002), we nd that women who
had their rst child after age 30 have lower annual probabilities of having a second
child compared to those who were younger. Model 4a indicates a higher probability
of second birth for the 1.5 generation (AME = 0.054) and no signicant difference
for non-migrant Germans compared to respondents of the second generation (refer-
ence). In Model 4b, we control for the educational attainment of respondents. Our
results imply that for second births, women with low and medium levels of education
show similar annual birth probabilities. By contrast, highly educated mothers have
signicantly higher annual birth probabilities compared to those with medium educa-
tion (AME = 0.042). In order to identify whether this pattern is different for respon-
dents with Turkish origin and non-migrant Germans, we specify an interaction effect
(Model 5), which is graphically displayed in Fig. 4 (numbers are shown in Table 9
in the appendix). Again, second generation migrants mark the reference group. The
graph indicates that the positive effect of high education is found only for Germans,
whose annual probability of having a second child is signicantly higher compared
to second generation migrants with high education. One caveat of our analysis is that,
although we were using the largest survey dataset available in Germany, we still ran
into sample size problems. These sample size restrictions limit our ability to analyze
interaction effects in greater detail. This is also the reason why we have refrained
from running the three-way-interaction models for second births.
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Persisting Differences or Adaptation to German Fertility Patterns? 155
1 3
6 Discussion
Germany has been one of the major receiving countries for migrants in Europe. The
labour migrants who arrived in the 1960s and early 1970s partially remained in Ger-
many, formed their families and had children. Therefore, the study of integration
processes is increasingly reaching a stage where also the behaviour of 1.5 and second
generation migrants can be analysed. Focusing on descendants of Turkish migrants,
who are the largest migrant group from a single country of origin in Germany, we
were interested if differences persist or fertility patterns adapt. This is an interesting
endeavour because social integration of migrants is a topic of public interest. Beyond
that, the socialization and adaptation processes allow us to learn something about the
interplay of normative and institutional determinants of social change (Kalter 2003).
Based on data of the German Mikrozensus, this study focused on fertility patterns
of the 1.5 and second generation Turkish migrants compared to non-migrant western
Germans. Our results show that the 1.5 generation, who migrated as children, have
the highest annual probability of having a rst child; Germans have the lowest prob-
ability, while the second generation lie in between these two groups.
The comparison of the second and 1.5 generations allows us to disentangle adapta-
tion and socialization effects. According to adaptation theory, the destination coun-
try’s childbearing values and its opportunity structure inuence migrants’ fertility
behaviour. Because both groups, the 1.5 generation as well as the second generation,
have spent their entire adult life in Germany, they should adapt to the low fertility
patterns of non-migrant Germans to the same extent. Alternatively, socialization the-
ory expects that the migrant generations differ because the generation 1.5 had been
partly socialized in Turkey, while the second generation spent its entire childhood in
Germany. Our analyses show that 1.5 generation migrants differ markedly from the
German pattern, while the fertility behaviour of the second generation is more similar
to that of non-migrants. This is in line with the socialization hypothesis. The fertility
Fig. 4 Interaction model of migration background and education. Transition to second birth. Average
marginal effects (Model 5). (Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations.
Notes: Controlled for duration since rst birth, mother’s age at rst birth, mother’s birth cohort)
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156 S. Krapf, K. Wolf
1 3
differentials between the two migrant generations indicate that family values learnt
through childhood socialisation are of great importance and play a role in later fertil-
ity behaviour of migrants’ descendants. This nding does not necessarily contradict
adaptation arguments, but it seems that socialization effects are more relevant here.
We nd adaptation tendencies of fertility particularly among highly educated
women. For those with lower education, the annual probability of having a rst birth
varies strongly between non-migrants, 1.5 and second generation migrants, while
the difference diminished slightly for those with medium education. Among highly
educated women, annual rst birth probabilities do not differ across the three migrant
status groups. It seems that differences between German non-migrants and Turkish
descendants of the 1.5 and second generation are partly caused by women’s educa-
tional background. Our ndings indicate that high education has an equalizing effect,
i.e. that the effect of a migrant background vanishes for women with high education.
Other studies have shown that the transition to rst birth differs by educational level
(Tesching 2012). In order to compare such differences across migrant background,
we did three way interactions for migrant status, education and age. However, the
second generation is still quite young and so far only a small share of women with
Turkish roots have both attained high education and reached ages above 30 years.
Thus, the single categories in our analysis were very small and we refrain from draw-
ing strong conclusions. Future studies about similarities and differences between age
patterns of migrants’ descendants and non-migrants should be done as soon as data
on at least 40 year old second generation migrants is available.
Our study adds to the literature on the fertility behaviour of migrants in advanced
societies. First, in line with ndings for other countries (Blau et al. 2008 for the US;
Garssen and Nicolaas 2008 for the Netherlands; Parrado and Morgan 2008 for the US;
Scott and Stanfors 2011 for Sweden), we were able to show a process of convergence
across migrant generations in Germany. However, the second generation Turkish still
differs markedly from non-migrant Germans, thus fertility adaptation seems to be
less developed than for example in the Netherlands (Garssen and Nicolaas 2008). In
addition, we illustrated that a distinction between the 1.5 and second generation is
appropriate and necessary. From a theoretical point of view, both groups should differ
in their fertility behaviour due to varying socialization experiences during childhood.
In line with several migrant groups in Sweden (Scott and Stanfors 2011), our results
conrm this theoretical relationship for the case of Turkish migrants in Germany. So
far, only differences between 1.5 and second generation Turkish migrants concerning
completed fertility have been shown (Stichnoth and Yeter 2013). We extended this
to parity-specic evidence. Both the transitions to rst and second childbirth have
been found to differ between the two migrant generations. Furthermore, our results
indicate a potential for fertility convergence in future if descendants of Turkish
migrants increase their average educational attainment. Those of Turkish origin still
have lower levels of education on average today, compared to non-migrant Germans.
As especially the highly educated second generation has similar fertility patterns to
non-migrants, the aggregated fertility of Turkish migrants should decline given an
increase in educational attainment in the years to come.
For future research, in order to complete our picture of the fertility of migrants’
descendants, we should study the transition to third birth. This is of specic interest,
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Persisting Differences or Adaptation to German Fertility Patterns? 157
1 3
as there might be a large difference between women in western Germany, who follow
the so-called “two child norm”, and women of Turkish origin, who experience a tran-
sition to a third child more often (Milewski 2010b). In this paper, we have refrained
from analysing third births which was related to the age structure of second (and
partly 1.5) generation Turkish migrants in Germany who are only now reaching ages
above 35 years and the number of women who are at risk of having a third birth has
been still small (see Table 5 in the appendix for the number of exposures and occur-
rences). This will change as second generation migrants grow older. The Mikrozen-
sus 2013 again includes the survey items on parents’ migrant status which offers the
opportunity to investigate the fertility behaviour of the descendants of migrants in
Germany further.
Acknowledgements The research leading to these results received funding from the European Union’s
Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 320116 for the research
project Families And Societies.
Open Access This article is distributed under the terms of the Creative Commons Attribution License
which permits any use, distribution, and reproduction in any medium, provided the original author(s)
and the source are credited.
Appendix
Table 3 Number of rst birth events. Non-migrant Germans, 1.5 and second generation migrants. (Source:
Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
German 1.5 generation 2nd generation
Share (per-
son years)
Number of
events
Share (person
years)
Number of
events
Share (person
years)
Number of
events
Education
Low 18.8 % 9345 59.7 % 573 41.1 % 422
Medium 36.4 % 13,729 22.6 % 153 28.6 % 207
High 44.3 % 8775 17.7 % 50 29.6 % 73
Missing 0.5 % 153 0.5 % 40.7 % 3
Age
18–24 11.8 % 1607 10.3 % 49 22.9 % 68
25–29 19.4 % 4682 15.6 % 119 34.5 % 253
30–34 27.5 % 9647 30.7 % 248 31.6 % 289
35–40 41.4 % 16066 43.4 % 364 11.0 % 95
Cohort
1965–1972 51.0 % 19718 53.9 % 451 13.9 % 131
1973–1979 31.1 % 9391 32.1 % 253 51.3 % 416
1980–1991 17.8 % 2893 14.0 % 76 34.9 % 158
Total 100.0 % 32002 100.0 % 780 100.0 % 705
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158 S. Krapf, K. Wolf
1 3
Table 4 Number of second birth events. Non-migrant Germans, 1.5 and second generation migrants.
(Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
German 1.5 generation 2nd generation
Share (per-
son years)
Number
of events
Share (person
years)
Number of
events
Share (person
years)
Number
of events
Education
Low 34.8 % 5505 76.0 % 467 64.7 % 269
Medium 44.3 % 7302 17.4 % 114 25.9 % 99
High 20.3 % 4427 6.1 % 28 9.1 % 27
Missing 0.6 % 96 0.5 % 40.3 % 3
Age
18–24 1.9 % 363 2.2 % 18 4.0 % 15
25–29 8.9 % 1848 9.8 % 80 24.7 % 116
30–34 25.6 % 5184 31.0 % 210 49.0 % 197
35–40 63.6 % 9935 57.0 % 305 22.3 % 70
Cohort
1965–1972 74.0 % 11,953 67.1 % 385 30.1 % 99
1973–1979 21.7 % 4519 29.5 % 200 57.6 % 246
1980–1991 4.3 % 858 3.4 % 28 12.3 % 53
Total 100.0 % 17330 100.0 % 613 100.0 % 398
Table 5 Number of third birth events. Non-migrant Germans, 1.5 and second generation migrants.
(Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
German 1.5 generation 2nd generation
Share (per-
son years)
Number of
events
Share (person
years)
Number of
events
Share (person
years)
Number
of events
Education
Low 37.0 % 1390 76.7 % 215 74.0 % 79
Medium 44.5 % 1417 19.0 % 32 21.6 % 12
High 18.5 % 805 4.3 % 44.4 % 3
Age
18–24 0.3 % 45 0.8 % 31.0 % 3
25–29 4.0 % 328 7.6 % 24 18.1 % 21
30–34 21.9 % 1039 30.1 % 79 53.9 % 48
35–40 73.8 % 2212 61.4 % 147 26.9 % 23
Cohort
1965–1972 80.4 % 2701 74.1 % 178 35.5 % 31
1973–1979 17.7 % 937 24.3 % 68 58.8 % 57
1980–1991 1.8 % 147 1.6 % 75.7 % 7
Total 100.0 % 3600 100.0 % 247 100.0 % 91
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Persisting Differences or Adaptation to German Fertility Patterns? 159
1 3
Table 6 Interaction migration background and education. Transition to rst birth. Discrete-time haz-
ard model (Model 2). Average marginal effects. Reference group: Second generation Turkish migrants.
(Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
2nd generation German 1.5 generation
Low education Ref. − 0.046*** 0.029***
Medium education Ref. − 0.034*** 0.021**
High education Ref. − 0.000 0.011*
Controlled for mother’s age, cohort
*p < = 0.10 ; * *p < = 0. 05 ; * * * p < = 0.01
Table 7 Descriptive statistics. Number of rst birth events by migration status, education and age.
(Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
Age Education
Low Medium High
Share (person
years)
Number of
events
Share (per-
son years)
Number of
events
Share (per-
son years)
Number of
events
German
18–25 71.19 % 5876 70.25 % 5985 68.35 % 1915
26–32 22.86 % 2840 24.34 % 6124 26.21 % 4895
33–40 5.94 % 346 5.41 % 843 5.44 % 1374
1.5 migrant generation
18–25 82.78 % 450 81.07 % 104 66.47 % 24
26–32 14.08 % 76 16.18 % 32 26.05 % 19
33–40 3.14 % 72.75 % 67.47 % 5
2nd migrant generation
18–25 85.29 % 322 85.76 % 123 77.15 % 36
26–32 13.56 % 68 13.61 % 59 20.67 % 33
33–40 1.16 % 60.62 % 42.18 % 2
Table 8 Three-way interaction of migration status, education and age. Transition to rst birth. Discrete-
time hazard model. Average marginal effects. Reference group: Second generation Turkish migrants.
(Source: Mikrozensus 2005 and 2009, unweighted. Authors’ own calculations)
Age Education
Low Medium High
German
18–25 0.060 0.034 0.010
26–32 0.083 0.089 0.056
33–40 0.036 0.050 0.068
1.5 generation Turkish
18–25 0.127 0.086 0.030
26–32 0.118 0.120 0.054
33–40 0.046 0.118 0.047
2nd generation Turkish
18–25 0.094 0.057 0.017
26–32 0.108 0.141 0.049
33–40 0.093 0.171 0.024
*p < = 0.10 ; * *p < = 0. 05 ; * * * p < = 0.01
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160 S. Krapf, K. Wolf
1 3
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