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This study takes a 'country-of-origin' or dissimilation perspective to compare the timing of births and completed fertility of international migrants and of those who stay at origin. In order to disentangle selection effects determining differential fertility behaviour of migrants, other mechanisms explaining migrant fertility (disruption, interrelation of events) are also examined. Furthermore, we take into consideration the prevalence of polygamy in Senegal to enhance our knowledge of migrant fertility in this specific context. For the empirical analysis, we use longitudinal data collected in the framework of the MAFE-Senegal project (Migrations between Africa and Europe), which includes retrospective life histories of non-migrants in Senegal and migrants in France, Italy and Spain. We estimate discrete time hazard models and Poisson regressions for male and female respondents separately to analyse the timing of first and higher-order births as well as completed fertility. The results show a strong disruptive effect of migration on childbearing probabilities for men and women, clearly related to the geographic separation of partners due to the out-migration of the man. Increased birth risks in the first year upon arrival could be observed for migrant women following their husbands to Europe, suggesting an interrelation of migration and fertility events. Regarding completed fertility, migrants have significantly fewer children by the age of 40 compared to their non-migrant counterparts, which among men is largely driven by a strong negative effect of polygamous migrants.
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Fertility Differences Between Migrants and Stayers
in a Polygamous Context: Evidence from Senegal
Elisabeth K. Kraus
1
&Amparo González-Ferrer
2
Accepted: 26 December 2020/
#The Author(s) 2021
Abstract
This study takes a country-of-originor dissimilation perspective to compare the
timing of births and completed fertility of international migrants and of those who stay
at origin. In order to disentangle selection effects determining differential fertility
behaviour of migrants, other mechanisms explaining migrant fertility (disruption,
interrelation of events) are also examined. Furthermore, we take into consideration
the prevalence of polygamy in Senegal to enhance our knowledge of migrant fertility in
this specific context. For the empirical analysis, we use longitudinal data collected in
the framework of the MAFE-Senegal project (Migrations between Africa and Europe),
which includes retrospective life histories of non-migrants in Senegal and migrants in
France, Italy and Spain. We estimate discrete time hazard models and Poisson regres-
sions for male and female respondents separately to analyse the timing of first and
higher-order births as well as completed fertility. The results show a strong disruptive
effect of migration on childbearing probabilities for men and women, clearly related to
the geographic separation of partners due to the out-migration of the man. Increased
birth risks in the first year upon arrival could be observed for migrant women following
their husbands to Europe, suggesting an interrelation of migration and fertility events.
Regarding completed fertility, migrants have significantly fewer children by the age of
40 compared to their non-migrant counterparts, which among men is largely driven by
a strong negative effect of polygamous migrants.
Keywords Migration .Fertility .Polygamy .Sub-Saharan Africa .MAFE
Journal of International Migration and Integration
https://doi.org/10.1007/s12134-020-00802-0
*Elisabeth K. Kraus
elisabeth.kraus@bib.bund.de
Amparo González-Ferrer
amparo.gonzalez@cchs.csic.es
1
Federal Institute for Population Research, Wiesbaden, Germany
2
Spanish National Research Council (CSIC), Madrid, Spain
Introduction
In 2013, about 540,400 Senegalese lived abroad, which corresponds to almost 4% of
the Senegalese population. In the same year, the top five destination countries of
Senegalese migrants were France, the Gambia, Italy, Spain and Mauritania (World
Bank 2016). With a total fertility rate of 5.1 children per woman (ANSD 2014), fertility
is high, placing the country at the intermediate stage of the fertility transition
(Schoumaker 2019). Furthermore, almost one-quarter of married men in Senegal live
in polygamous marriages, and nearly one-half of all married women have at least one
co-wife (ANSD 2014). High rates of out-migration, high fertility levels and a relatively
high prevalence of polygamy make Senegal an interesting case for studying the fertility
behaviour of migrants: The separation of partners due to intercontinental long-distance
migration to Europe is likely to have a major impact on the timing of births and
completed fertility of men and women.
Research on international migration and fertility of sub-Saharan African migrants to
Europe is scarce. The few studies that examine the fertility of African migrants in
European destination areas do not take into consideration the fertility behaviour at origin
but rather compare migrantsfertility to that of natives at destination (Devolder and Bueno
García 2011; Toulemon 2004) or only look at migrants (Kraus 2019). One noteworthy
exception is the article by Wolf and Mulder (2018), which analyses the reproductive
behaviour of Ghanaian migrants in the Netherlands and the UK compared to stayers in
Ghana. Furthermore, only few studies on migration and fertility deal with the issue of
polygamy (Bledsoe 2004; Bledsoe et al. 2007; Bledsoe and Sow 2008). In other migration
settings, scholarship on migrant fertility also mostly compares the fertility behaviour of
migrants with that of natives at destination (González-Ferrer et al. 2017; Krapf and Wolf
2015;Kulu2005;Milewski2007). Few studies analyse the fertility of migrants compared
to that of stayers at origin, taking a context-of-originor dissimilation perspective
(FitzGerald 2012;Guvelietal.2017;Guvelietal.2016). This has been done for
Mexico-US migration (Choi 2014; Frank and Heuveline 2005; Lindstrom and Giorguli-
Saucedo 2002,2007; Massey and Mullan 1984;Parrado2011) and Turkey-Germany
migration (Baykara-Krumme and Milewski 2017;Guvelietal.2016), for both of which
bi- or multinational data from origin and destination areas are available.
Various mechanisms or hypotheses have been developed to describe and explain the
link between migration and fertility (Andersson 2004;Kulu2005; Kulu and González-
Ferrer 2014; Milewski 2007; Milewski and Mussino 2018). Theoretically and methodo-
logically, these explanations build on the assumption of monogamous partnerships, while
polygamous unions are not considered. To fill this gap in current research on migrant
fertility, we aim at answering the following research questions: What are the differences in
fertility timing and quantum between international migrants and stayers at origin? How is
the migration experience of male and female partners related to their fertility outcomes?
And, finally, how is migrantsfertility shaped in a polygamous context of origin? We
answer these questions by focusing on Senegalese migrants in Europe and their non-
migrant
1
counterparts at origin. We utilize data from the MAFE-Senegal project
1
The terms non-migrantand stayerare used interchangeably throughout the article, both referring to
individuals who remain in their country-of-origin, i.e. who did not migrate (yet).
Kraus E.K., González-Ferrer A.
(Migrations between Africa and Europe), which collected longitudinal retrospective life
histories in Senegal and in the major European destination countries: France, Italy and
Spain.
The contributions of this study are twofold. First, most studies on migrant fertility
concentrate on women only, neglecting entirely the location of the male partner. Few
other studies include migrant mens migration trajectories or their socioeconomic
characteristics and the impact on fertility (Guetto and Panichella 2013;Kraus2019;
Milewski 2007; Wolf 2016; Wolf and Mulder 2018). However, male and female
migration and fertility trajectories tend to be coordinated and interdependentand part
of a joint household strategy (Lindstrom and Giorguli-Saucedo 2007, p. 827). Thus,
besides the migration moves of the respondent, this article also pays attention to the
whereabouts of the partner (or partners in polygamous unions). Second, the aspect of
polygamy will be added to the standard explanations for migrant fertility.
Background
Marriage, Polygamy and Fertility in Senegal
In Senegal, the extended family is the basic social unit (Baizán et al. 2014). On average,
a household consists of eight individuals (ANSD 2014), one of the largest household
sizes in West Africa. This size is a result of both the extended multigenerational family
structure forming the household, as well as the polygamous regime. As in many
polygynous societies, marriage in Senegal is almost universal (Lardoux and Van de
Walle 2003) and staying unmarried is seen as a secondary choice(Antoine and
Nanitelamio 1996, p. 130) and few Senegalese stay unmarried. In 2013, the mean
age at first marriage was 22.4 for women (rural: 19.4, urban: 25.5) and 29.9 for men
(rural: 27.7, urban: 31.9), indicating a significant age difference between spouses
(ANSD 2014). A total of 23.1% of married men live in polygamous marriages, and
44.0% of all married women have at least one co-wife. On average, polygamous men
have 2.6 wives. Polygamy is more widespread in rural areas (39.8%) than in urban
areas (29.1%) and decreases with educational attainment, ranging from 24.1% for men
and 47.1% for women among those with no formal education to 13.9% for men and
24.1% for women among those with superior educational attainment (ANSD 2014).
Polygamy is only possible due to the significant age differences between spouses,
especially between men and their second or higher-rank wives (Antoine 2006). Over
time, the prevalence of polygamy seems to have declined with education and urban-
ization(Bledsoe et al. 2007, p. 388). Divorce rates in Senegal are relatively high,
especially in urban areas (Antoine and Nanitelamio 1996), but due to rapid remarriage
and high levels of polygamy among the men, only 0.7 and 2.1% of the men and
women, respectively, were divorced and single in 2013 (ANSD 2014).
Generally, marriages are arranged within the extended family and are often
formed between cousins (Vives and Vazquez Silva 2016). After marriage, the first
and potential other wives usually move in with their family-in-law to care for the
elders, especially the mother-in-law (González-Ferrer et al. 2012). This does not
necessarily mean, however, that the wife (wives) cohabits under the same roof with
their husband, as it is not unusual that partners live in different places (Beauchemin
Fertility Differences Between Migrants and Stayers in a Polygamous...
et al. 2013; Lardoux and Van de Walle 2003), for example due to internal or
international migration of the man. Separate residence, arranged marriages, polyg-
amy and relatively large age differences between spouses are all factors that add up
to a certain social distance between partners (González-Ferrer et al. 2012; Vives and
Vazquez Silva 2016).
Fertility in Senegal is high, with 5.1 children per woman in 2013, with an important
urban-rural divide (rural: 6.2, urban: 4.1; ANSD 2014). The high fertility levels are
likely to be the result of the cultural desire for large families, the high infant mortality
rate and the low use of modern contraceptive methods(Bass and Sow 2006,p.95).
Womens fertility decreases with the number of co-wives, which is mainly the result of
lowered frequency of intercourse and increased age of the husband when higher-rank
wives enter the polygamous union (Lardoux and Van de Walle 2003). As in other sub-
Saharan African countries, Senegalese fertility declines over time at a relatively slow
pace, compared to other developing countries (Bongaarts 2016).
Senegalese Migration to Europe: History and Family Migration Strategies
Senegalese migration to France, as the former colonial power, essentially began in
the early 1960s (Beauchemin et al. 2013). Early Senegalese migrants were recruited
tojointheFrencharmy,andlater,manyofthemstayedtoworkintheautomobile
industry. In the 1970s and 1980s, economic migration to France became more
difficult due to stricter immigration policies, and, consequently, migratory flows
diversified and migrants also chose other European destinations. In the 1990s, Italy
became the most important destination within Europe. From the end of the 1990s
onwards, Spain also became an important receiving country for Senegalese migrants
(Beauchemin et al. 2014).
Migration strategies of sub-Saharan African migrants in Europe changed over
time. In the 1960s, Senegalese migrants to France were mainly young, male and
single (Barou 2001). After spending several years at the destination and accumulat-
ing sufficient economic resources, migrant men started forming families in Senegal
with one or several wives and children during regular visits at home. Once the
migrants returned for good, they were in the advantaged position of being the head of
a family with various polygamous unions and several children (Barou 2001). This
migration practice of male migrants became more difficult when immigration pol-
icies at destination restricted and impeded these circular migration strategies. The
possibility of reuniting with the wife/wives (and children) at the destination ap-
peared as a new option in the late 1970s (Beauchemin et al. 2013). However,
reunification at the destination was a sub-optimal choice(Baizán et al. 2014)for
several reasons.
First, Senegalese elders often opposed the practice of reunification at destination
since they would lose a large part of the remittances sent by their sons from Europe, as
well as the household help of their daughters-in-law (Baizán et al. 2014;González-
Ferrer et al. 2012). Second, large and often polygamous Senegalese families encoun-
tered problems in Europe related to social integration and housing. Moreover, restric-
tive immigration policies prohibited the reunification of polygamous families (Baizán
et al. 2014;Beaucheminetal.2013) and polygamous men could lose their work and
residence permits for having more than one wife. This led to a possible marginalization
Kraus E.K., González-Ferrer A.
of additional wives and their children by divorcing her, whether in name or in fact, or
sending her back home, even though she may have originally come quite lawfully
under a French regime that allowed polygamy(Bledsoe 2004,p.103).Theresultwasa
circulation of young women, aslotdynamic[]:atendencytorotatemultipleholders
through a single position, resulting in high fertility rates during short time periods, as
has been found for Gambians in Spain (Bledsoe and Sow 2008,pp.1112). Other
studies using the same dataset as our study found that partners living in polygamous
unions have significantly lower odds of reunifying with their partner at the destination
(Baizán et al. 2014; Beauchemin et al. 2015). Thirdly, the normality of social distance
and of spatial separation among couples prevalent in Senegalese society contributed to
long-lasting transnational family arrangements (Vives and Vazquez Silva 2016), which
are more prevalent than reunification at destination (Baizán et al. 2014). The migrants
who, from the 1990s onwards, chose Italy and Spain as preferred European destina-
tions, faced similar problems with regard to their family arrangements. Finally, the
independent migration of Senegalese women to European destinations is an emerging,
but still rather scarce, phenomenon (Toma and Vause 2013).
Another peculiarity of Senegalese couples in the context of international migration is
that a relatively high share of unions is formed at a distance, meaning that the partners
do not reside in the same country at the moment of union formation. These marriages
are sealed rapidly during migrantsvisits to Senegal and are negotiated between the two
families or within the extended family (Mondain et al. 2009). According to Baizán et al.
(2014), one-half of all Senegalese transnational partnerships were formed while the
man already had migrated to Europe.
Migration and Fertility: Theoretical Framework, Previous Empirical
Evidence and Hypotheses
Most studies on migration and fertility build on different hypotheses or explanations
that describe and examine differences in fertility timing and quantum between migrants
and the native population at the destinationsuch as adaptation, convergence or
assimilation. In this study, however, we take a context-of-originor dissimilation
perspective (FitzGerald 2012;Guvelietal.2017;Guvelietal.2016)bycomparing
the fertility behaviour of migrants with that of the non-mobile population at origin
(stayers). This approach allows to disentangle dissimilation effectsi.e. how mi-
grants dissimilate (become different from those whom they leave behind)(FitzGerald
2012,p.1726),alsocalledhomeland dissimilation(FitzGerald 2012). The dissimila-
tion perspective covers selection effectsi.e. that migrants are a (self-) selected group
with characteristics associated with differential fertility behaviour compared to the
overall origin populationas well as issues related to the migration process itself,
namely fertility disruption due to migration and interrelation of several
life course events.
Selection
The selection hypothesis argues that the fertility behaviour (timing and quantum)
of migrants differs from that of non-migrants at origin due to the fact that migrants
Fertility Differences Between Migrants and Stayers in a Polygamous...
are not randomly selected from their population of origin. Migrants may be
selected (or self-select) on observable characteristics, such as education and other
socioeconomic factors (Adserà and Ferrer 2014), as well as on unobservable
characteristics such as social mobility aspirations (Milewski 2010a), openness to
innovation (Lindstrom and Giorguli-Saucedo 2002), high aspirations for children
or family proneness (Kulu and González-Ferrer 2014; Lindstrom and Giorguli-
Saucedo 2007). Most previous studies on international migration and the fertility
selection hypothesis cover Mexican migration to the USA (Lindstrom and
Giorguli-Saucedo 2002,2007), Turkish migration to Germany (Baykara-Krumme
and Milewski 2017;Guvelietal.2016) or one article on Ghanaian migration in
Western Europe (Wolf and Mulder 2018), for which bi-national surveys sampling
migrants and non-migrants at origin were conducted. A recent article compares
Albanian, Moroccan and Ukrainian migrant women in Italy, Italian native women
in Italy as well as non-migrant women at the respective countries of origin,
merging different data sources (Impicciatore et al. 2020). Although researchers
arrive at different conclusions, they agree that migrants are selected on observable
and unobservable characteristics that influence their fertility behaviour, but the
degree and the type of selection are ambiguous.
Intercontinental migration from sub-Saharan Africa to Europe involves overcom-
ing long geographic distances, implying a relatively high amount of financial
resources and knowledge. Thus, the poorest ones are not those who manage migrat-
ing from Senegal to Europe but rather those with a certain educational and financial
level (Shaw 2007; van Dalen et al. 2005). Using the same dataset as this paper,
González-Ferrer et al. (2014) have shown that Senegalese migrants in Europe are a
positively selected group of their population of origin in terms of socioeconomic
status (González-Ferrer et al. 2014) and Toma and Vause (2013) have found that
migrant women are more highly educated than their non-migrant counterparts and
that this positive selectivity holds true for both independent female migrants as well
as partner-related migration. Furthermore, in patriarchal societies such as Senegal,
where women face social control by their extended family, highly educated women
are more likely to reunify with their partners in European destination countries,
while less educated women more often stay behind in the country-of-origin (Baizán
et al. 2014;Beaucheminetal.2015).Highlyeducatedmenaremorelikelytoreunify
with their wives in Europe than in Senegal (Baizán et al. 2014). Hence, men and
women who live with their partner in Europe tend to be more highly educated
compared to men and women who are separated from their partner due to migration,
as well as stayers at origin.
Educational selectivity might explainat least partlythe differential fertility
behaviour of migrants compared to stayers. In most developing countries, poorer,
less educated and rural women have higher and earlier fertility patterns than their
wealthier, more educated and urban counterparts (Bongaarts 2003; Castro-Martín
and Juarez 1995;Schoumaker2004; Weinberger 1987). For Senegal, Marchetta
andSahn(2015) found a strong delaying effect of womenseducationontheage
at first child, operating mainly through a later entry into marriage (Marchetta and
Sahn 2015). Within partnerships, the effect of the wifeseducationismore
influential for couplesfertility behaviour (timing and quantum) than the influ-
ence of the husbands educational level (Jejeebhoy 1995). Therefore, as migrants
Kraus E.K., González-Ferrer A.
to Europe tend to be positively selected in terms of their socioeconomic status, we
expect that, controlling for individual socioeconomic characteristics, fertility
differentials (timing and quantum) between migrant and non-migrant men and
women should diminish (H1: Selection and fertility timing and completed
fertility).
Fertility Disruption
Other explanations that disentangle differences in fertility between migrants and
non-migrants describe diverging fertility patterns of migrants linked to the migra-
tion process itself. The disruption hypothesis states that birth timing and birth
spacing of migrants may be disrupted or delayed during the time shortly before
and after the migration move due to disruptive factors inherent to the migration
process, such as economic and psychological stress or the spatial separation of
spouses (Kulu 2005). Especially, the geographic separation of partners due to
migration is likely to have a temporary disruptive effect on men and womens
fertility calendar due to reduced exposure to conception, which might be partic-
ularly important in origin countries with relatively high fertility rates, such as
Senegal, and long-distance migration flows, where mutual visits are difficult. A
short-term disruptive effect of couple separations on birth probabilities has been
found for Mexican migrants to the USA (Lindstrom and Giorguli-Saucedo 2002,
2007; Massey and Mullan 1984), as well as in the context of sub-Saharan African
migration, e.g. intercontinental and internal migration in Mozambique
(Agadjanian et al. 2011), or internal migration in Ghana (Chattopadhyay et al.
2006). To sum up, long-lasting transnational family arrangements are often the
preferred option of Senegalese families due to strict visa requirements and restric-
tive immigration policies in European destination countries as well as the culture-
related preferences pointed out above. Furthermore, long geographic distances
associated with high travel expenses (González-Ferrer et al. 2014) make circular
migration strategies difficult. For all these reasons, Senegalese partners experience
prolonged separations from each other. Therefore, our expectation regarding
fertility disruption is that women and men who are spatially separated from their
partneror partners in the case of polygamous mendue to out-migration
experience a disruption in childbearing and, accordingly, have lower birth prob-
abilities compared to non-migrant women and men at origin (H2: Disruption and
fertility timing).
Fertility disruption due to the separation of partners primarily influences birth
timing; however, in the long run, completed fertility may also be affected, if
partners are not able to make up for the lost reproductive time caused by their
spatial separation. If migration episodes are short or if they coincide with non-
fecund periods, couples are likely to catch up with their non-migrant counterparts
in terms of the number of children, as has been found for the case of Mexican
migration to the USA (Lindstrom and Giorguli-Saucedo 2002). In Senegal, how-
ever, separations related to the migration to Europe of one partner are longer-term
arrangements and thus, fertility recovery might be more difficult compared to
migration settings where spousal separation is rather short-term. Baizán et al.
(2014) found that 10 years after migration-related separation, only approximately
Fertility Differences Between Migrants and Stayers in a Polygamous...
40% of the migrants had (re)unified with their partner either at destination or at
origin. This means that the conception of more children is restricted to visits of the
migrant partner at origin or the non-migrant partner at the destination. Hence,
concerning disruption and completed fertility, we hypothesize that women and
men who are either themselves a migrant and/or have a migrant partner show
lower completed fertility compared to non-migrant men and women at origin (H3:
Disruption and completed fertility).
Finally, research dealing systematically with the impact of international migra-
tion processes on fertility behaviour in polygamous unions is scarce (exceptions
include Bledsoe 2004; Bledsoe et al. 2007; Bledsoe and Sow 2008; Sargent and
Cordell 2003). Migrant men with multiple wives at the same time may be spatially
separated from them at the same time; thus, the disruptive effect of migration on
fertility should be stronger. We thus expect that for polygamous men the depres-
sive effect of migration on fertility timing and completed fertility should be
stronger compared to monogamous migrant men (H4: Disruption and polygamy).
Interrelation of Migration, Union Formation and Fertility
The interrelation of events hypothesis argues that higher-birth risks immediately
after migration can be seen as the coincidence of several life eventsmigration
and marriagetaking place at the same time (Mulder and Wagner 1993)and
thereby temporarily resulting in higher first-birth probabilities compared to natives
at destination and non-migrants at origin (Andersson 2004; Lindstrom and
Giorguli-Saucedo 2007;Milewski2007). In the case of marriage migration, most
studies agree on the fact that marriage and migration are interrelated events and
that (mostly female) marriage migrants have an accelerated transition to a first
child upon arrival at destination (Andersson 2004;Milewski2007; Nedoluzhko
and Agadjanian 2010; Nedoluzhko and Andersson 2007). While this refers mostly
to first-birth probabilities, the timing of second and higher-order births may also
be affected after the reunification of partners. The migration of the second spouse
(usually the woman) to join the partner at destination may be interpreted as a re-
formation of an old household under new circumstances(Milewski 2010b,p.
303) and thus result in higher higher-order birth probabilities compared to natives
at destination or stayers at origin, also called arrival effect(Milewski 2010b). It
has also been observed that disrupted fertility behaviour before the migration
move was recovered by higher childbearing rates shortly after the move, known
as catching-up behaviour(Goldstein and Goldstein 1981;Milewski2007). Using
thesamedataasthisstudydoes,Kraus(2019) graphically shows that female
Senegalese migrants experience one or several first or higher-order births in the
years following their migration to Europe, also indicating an arrival effect. Sim-
ilarly, after a marriage formed at a distance, the woman may follow her husband to
the destination country immediately or after some time and, once at the destina-
tion, experience a quick transition to a first or subsequent child. We expect that
Senegalese women have higher birth probabilities in the years immediately after
arrivingattheirdestinationcomparedtonon-migrantwomenatorigin(H5:
Interrelation of events and fertility timing).
Kraus E.K., González-Ferrer A.
Data and Methods
Data: The MAFE-Senegal Survey
Properly analysing whether migrants and non-migrants differ in their fertility be-
haviour has several data requirements. First, a dataset including information on
migrants as well as on stayers at origin is needed. Therefore, a transnational sample
is required that covers data both on individuals that migrated as well as individuals
that never left the country of origin. Second, since we focus on men and women, the
data should provide information on migration and fertility histories of both sexes.
Third, we are interested in the temporal ordering of migration and childbearing
events. Hence, a longitudinal time-varying dataset is required. Fourth, we are not
only interested in the time-varying migration status of the respondents but also of
their partners.
The MAFE survey (Migrations between Africa and Europe
2
) is one of the few
datasets that fulfils all four criteria. In the framework of this project, longitudinal
life-history data were collected in sub-Saharan African origin countries and in major
European destination countries. For the Senegalese part of the project, about 200
current Senegalese migrants were interviewed in three European destination coun-
triesFrance, Italy and Spainthroughout 2008. Furthermore, some 1000 individ-
uals (non-migrants, returnees and migrantsspouses) were interviewed in Senegal.
In Spain, a second round of the survey was conducted in 2011 (Migraciones entre
Senegal y España (MESE)), adding 405 individuals to the original sample of
Senegalese migrants in Spain.
3
In total, the dataset contains life histories of 2073
men and women.
In each country, a different sampling strategy was applied to select the respon-
dents. In Spain, the municipal population register (Padrón) served as a national
sampling frame for drawing a random sample of undocumented and documented
Senegalese migrants. Since in France and Italy no such sampling frame exists, a non-
probabilistic quota sampling technique was used. In Senegal, a stratified random
sample was drawn from households and individuals living in the region of the capital
city Dakar. The fact that non-migrants were sampled only in Dakar might bias the
results, insofar as the migrants interviewed in Europe originate from all over
Senegal. The capital region is different from more rural Senegalese areas in socio-
economic and demographic terms, as well as in its gender norms, resulting in
differential fertility behaviour (TFR in urban areas 4.1 and in rural areas 6.2
2
The MAFE project is coordinated by INED (C. Beauchemin) in partnership with the Université catholique
de Louvain (B. Schoumaker), Maastricht University (V. Mazzucato), the Université Cheikh Anta Diop (P.
Sakho), the Université de Kinshasa (J. Mangalu), the University of Ghana (P. Quartey), the Universitat
Pompeu Fabra (P. Baizán), the Consejo Superior de Investigaciones Científicas (A. González-Ferrer), the
Forum Internazionale ed. Europeo di Ricerche sullImmigrazione (E. Castagnone) and the University of
Sussex (R. Black). The MAFE project has received funding from the European CommunitysSeventh
Framework Programme under grant agreement 217206. The MAFE-Senegal survey was conducted with the
financial support of INED, the Agence Nationale de la Recherche (France), the Région Ile de France and the
FSP programme International Migrations, territorial reorganizations and development of the countries of the
South. For more information, see https://mafeproject.site.ined.fr/en/.
3
Additional analyses showed that the results across the two Spanish samples, apart from some minor
differences, were substantively the same.
Fertility Differences Between Migrants and Stayers in a Polygamous...
children per woman; ANSD 2014). Since fertility is lower in Dakar than in other
areas, this inconsistency should not be problematic for the analyses but rather
strengthen the findings. The samples across all countries were stratified by age
and sex; men and women each represented 50% of all surveyed individuals in each
country, and half of the individuals of both genders were aged between 25 and 40,
the other half between 41 and 75 (Beauchemin and González-Ferrer 2011).
Our descriptive results are weighted to account for the different sampling procedures
employed across different countries (for a detailed description of the weighting
strategies, see Schoumaker and Mezger 2013).
The dataset includes time-varying residential and migration histories as well as
information on childbearing and union formation of the interviewee. Moreover, the
respondent also provided information on their past and current partners (educational
attainment, socioeconomic and civil status at the time of the survey, country of birth,
nationality and migrations) and complete histories could be reconstructed including
exact information on the children born and the migratory movements of both partners.
Analytical Approach
The empirical section is divided into two parts; the first covers the timing of childbear-
ing and how migration contributes to short-term fertility differentials between migrant
and non-migrant men and women and the second examines completed fertility and the
long-term differences between these groups.
From the initial MAFE-Senegal sample (N= 2,073), 4 women were dropped
because they indicated having two partners simultaneously. For the first part of the
empirical analysis on fertility timing, the data were arranged as a person-year
dataset. The annual histories begin at the age of 15 and end at the age of 45 for
women and 60 for men or the year of the survey in 2008. The second data
collection round in Spain was also limited to 2008; thus, observations for 2009
2011 were dropped. We opted for different age thresholds for men and women
since men are able to have children up to higher ages and age differences between
partners are relatively high in Senegal (ANSD 2014; Antoine and Nanitelamio
1996; Marchetta and Sahn 2015). Furthermore, only person-years spent within a
union are included in the analysis, as childbearing out of the union is relatively rare
in Senegal (first births out of union: women N=40,menN= 47). Marriages as well
as consensual unions are considered, although most unions are marriages. The final
dataset consists of 11,750 person-years for women and 9,212 person-years for men
(3,852 and 3,648 person-years for first-birth analyses), corresponding to 920
womenand778men.
We employ discrete time hazard models with repeated events to predict the instan-
taneous hazard that an event (birth) will occur during a person-year (Box-Steffensmeier
and Zorn 2002). For the analysis of first-birth risks, individuals leave the risk set once
the event has occurred. The dependent variable is coded 0 when no birth occurs during
a person-year and is coded 1 if a child is born. Standard errors are clustered on the
individual level.
Table 5(women) and Table 6(men) in the appendix provide the descriptive sample
characteristics used for the analyses of fertility timing by type of time-varying migra-
tion status of the respondent. The main independent variable is the time-varying
Kraus E.K., González-Ferrer A.
residence of the partners.
4
This categorical variable covers all migration stays of the
respondent and his/her partner(s) of at least 1 year in duration and has four possible
outcomes: both (all) partners in Senegal;
5
(at least one) woman in Senegal, man in
France, Italy or Spain;both (all) partners in France, Italy or Spainand other,which
covers person-years in which one or both partners were in another country (i.e. none of
the four survey countries, including mainly stays in neighbouring African countries).
6
The category for partners being together in Senegal includes respondents and partners
that never migrated as well as migrants beforeor after, for return migrantstheir
migration. Since the survey only provides information on a yearly basis, we opted for
lagging this variable by 1 year (t-1) in order to ensure the temporal ordering of
migration and childbearing events. Assuming that pregnancy takes 9 months, a 1-
year lag seems an appropriate time interval. Another migration-related variable ac-
counts for the duration of stay in France,Italy or Spain of the respondent (arrival
year,+ 1 year,+ 2 years,+ 3 years,4+ years/non-migrant), which is also lagged
one year.
To account for the sociodemographic selection of migrants, a variable of the
combined education of the partners is included. This variable has four possible
outcomes: both (all) primary,(at least one) woman secondary/man primary,(at
least one) woman primary/man secondary or both (all) secondary.Wealsoaccount
for whether the respondent was economically active in the previous year as well as for
the lagged financial situation of the household regarding the purchase of basic goods,
covering the categories less than sufficientand sufficient or better.
Furthermore, we include several dichotomous partnership-related covariates: Co-
wife in union, in the models for women, indicating whether the woman has at least one
co-wife within the current partnership (versus not having a co-wife), and polygamous
union, in the models for men, indicating whether the man has several wives simulta-
neously (versus only one wife). Fertility-related variables are the time since union
formation/last birth, also serving as process time for the event history analyses.
Moreover, in the models on higher-order births, we control for parity, which accounts
for the birth number, ranging from parity 1to parity 6+. Furthermore, several
demographic control variables were included in the models: Urban, to control for
rural-urban differences in fertility and migration patterns, and measuring whether the
respondent was born in one of the ten largest cities of Senegal. Religious affiliation is
controlled for, distinguishing between the major Muslim brotherhoods, Tidianeand
Mourideand other Muslimbranches, as well as the category other, which includes
Christians and other religious affiliations. Furthermore, we control for birth cohort
(before 1965,1965 and after)andage in age groups (women: 1524,2534,
3545; men: 1524,2534,3544, 4560).
4
For male respondents, the MAFE data provide information on his past and current partners of all
(simultaneous) partnerships. For female respondents, the data also give information on all her past and current
partners and on whether or not there was a co-wife in the partnership. About these co-wives, however, no
demographic or socioeconomic characteristics were collected.
5
Terms in brackets refer to men in polygamous unions.
6
Unfortunately, the number of person-years with the woman residing in Europe and the man residing in
Senegal was too small for a separate category. This constellation was added to the othercategory.
Fertility Differences Between Migrants and Stayers in a Polygamous...
Completed fertility of women and men was predicted using a reduced sample,
including only respondents aged 40 and older
7
at the survey and who ever had been
in a partnership up to this age. The resulting sample covers 426 women and 450 men.
The dependent variable is a measure for the number of children born up to this age and
ranges from 0 to 14, with a weighted mean of 5.1 for women and 4.1 for men. As this
variable is count data, Poisson regression with robust standard errors to control for mild
violations of the equidispersion assumption is used (Cameron and Trivedi 2009). The
main independent variable accounts for the migration experience of the respondent and
their partner(s) up to the age of 40 and has four possible outcomes for women: both
(all) non-migrants,woman ever migrant in France, Italy or Spain, man non-migrant,
woman non-migrant, man ever migrant in France, Italy or Spainand both (all)
ever migrants in France, Italy or Spain. For men, only three categories were distin-
guished since the category woman migrant, man non-migrantwas not observed in the
data on male respondents. Other covariates are co-wife in union (in the models for
women), polygamous union (in the models for men), education of the partners,birth
cohort,urban and religious affiliation, with the same categories as in the models for
fertility timing.
Results
Multivariate Results on Fertility Timing
Models W1W6 in Table 1(women) and models M1M6 in Table 2(men) present the
estimates for the discrete time hazard models of the transition to a (first) child according
to the time-varying residence of the respondent and their partner(s), controlling for a
range of other covariates. Regarding the socioeconomic selectivity of migrants, we
expected that fertility differentials between migrant and non-migrant men and women
would diminish once socioeconomic characteristics were controlled for (H1: Selection
and fertility timing and completed fertility). In order to test this, we applied a stepwise
approach; in models W2 and W4 for women and models M2 and M4 for men, several
socioeconomic measures were added. However, the differences between current non-
migrants at origin and current migrants to France, Italy or Spain remain when adding
the lagged educational attainment of the partners, labour force status of the respondent
and the financial situation of the household. This holds for women and men as well as
for first and higher-order birth transitions. Nevertheless, education is an important
predictor of birth probabilities; women and men with secondary education have lower
odds of a birth compared to their less-educated counterparts, which is in line with
previous findings. Furthermore, men who were economically active in the previous
year have a significantly higher probability of a first or higher-order birth in the
following year compared to men who were not working. Women, on the contrary, have
a lower probability of a higher-order birth if they worked in the previous year. Finally,
having sufficient financial resources to purchase basic goods is positively associated
with increased higher-birth probabilities, while this relationship is the opposite for first
births. Stable economic conditions seem crucial to afford larger families.
7
A higher age limit for men would have resulted in a sample too small for the regressions models.
Kraus E.K., González-Ferrer A.
Table 1 Women: Discrete-time hazard models predicting a first/higher-order birth in given year (odds ratios)
1st birth
(W1)
1st birth
(W2)
1st birth
(W3)
2+ births
(W4)
2+ births
(W5)
2+ births
(W6)
Time since union
formation/last
birth
0.90*** (0.01) 0.91*** (0.01) 0.91*** (0.01) 0.96*** (0.01) 0.96*** (0.01) 0.96*** (0.01)
Parity 1 Ref. Ref. Ref.
2 0.88+ (0.06) 0.86* (0.06) 0.86* (0.06)
3 0.85* (0.06) 0.81** (0.06) 0.81** (0.06)
4 0.75** (0.07) 0.70*** (0.06) 0.70*** (0.06)
5 0.94 (0.10 ) 0.86 (0.09) 0.86 (0.09)
6+ 0.95 (0.09) 0.84+ (0.08) 0.84+ (0.08)
Urban No Ref. Ref. Ref. Ref. Ref. Ref.
Yes 1.09 (0.10) 1.10 (0.10) 1.10 (0.10) 0.85** (0.04) 0.91+ (0.05) 0.91+ (0.05)
Religious
affiliation
Tidiane Ref. Ref. Ref. Ref. Ref. Ref.
Mouride 0.71*** (0.07) 0.70*** (0.07) 0.71*** (0.07) 0.90+ (0.05) 0.91 (0.05) 0.91+ (0.05)
Other Muslim 0.89 (0.12) 0.91 (0.12) 0.90 (0.12) 1.07 (0.09) 1.10 (0.09) 1.10 (0.09)
Other 0.63* (0.12) 0.63* (0.12) 0.65* (0.12) 0.77* (0.08) 0.80* (0.08) 0.79* (0.08)
Birth cohort Before 1965 Ref. Ref. Ref. Ref. Ref. Ref.
1965 and after 0.96 (0.09) 0.98 (0.10) 0.97 (0.10) 0.79*** (0.04) 0.79***(0.04) 0.79*** (0.04)
Age 1524 Ref. Ref. Ref. Ref. Ref. Ref.
2534 0.97 (0.10) 1.02 (0.10) 1.03 (0.10) 0.87* (0.05) 0.93 (0.05) 0.93 (0.05)
3545 0.57* (0.15) 0.61+ (0.17) 0.62+ (0.17) 0.40***(0.04) 0.45*** (0.04) 0.46*** (0.04)
Residence of
partners,
combined
Both SN Ref. Ref. Ref. Ref. Ref. Ref.
Woman SN,
man FIS
0.62*** (0.09) 0.60*** (0.09) 0.60*** (0.09) 0.62*** (0.05) 0.61*** (0.05) 0.61*** (0.05)
Both FIS 1.45* (0.23) 1.50** (0.23) 1.34 (0.27) 0.75*** (0.05) 0.75*** (0.05) 0.71*** (0.06)
Other 0.34*** (0.04) 0.33*** (0.04) 0.33*** (0.04) 0.70*** (0.06) 0.69*** (0.06) 0.68*** (0.06)
Co-wife in union No Ref. Ref. Ref. Ref. Ref. Ref.
Yes 1.16 ( 0.12) 1.13 ( 0.12) 1.12 ( 0.12) 1.05 (0.06) 1.0 0 (0.05) 1.00 ( 0.05)
Education
partners,
combined
Both primary Ref. Ref. Ref. Ref.
Woman
secondary,
man
primary
0.83 (0.12) 0.83 (0.12) 0.69*** (0.06) 0.69*** (0.06)
Woman
primary,
man
secondary
0.94 (0.11) 0.95 (0.11) 0.92 (0.06) 0.91 (0.06)
Both secondary 0.76* (0.08) 0.76* (0.08) 0.73*** (0.05) 0.73*** (0.05)
Economically
active
No Ref. Ref. Ref. Ref.
Yes 1.00 (0.09) 1.03 (0.09) 0.87* (0.05) 0.87* (0. 05)
Financial
situation
household
Less than
sufficient
Ref. Ref. Ref. Ref.
Sufficient
or better
0.89 (0.09) 0.90 (0.09) 1.12* (0.06) 1.12* (0.06)
Duration in FIS 4+ years /
non-migrant
Ref. Ref.
Arrival year 2.07** (0.51) 1.72** (0.32 )
+1 year 1.00 (0.34) 1.03 (0.20)
+2 years 0.47+ (0.19) 1.11 (0.21)
+3 years 0.76 (0.31) 0 .83 (0.18)
N (person-years) 3852 3852 3852 11,750 11,750 11,750
Data: MAFE-MESE Biographic Survey (2008/2011), unweighted
+p<0.1,*p< 0.05, ** p< 0.01, *** p< 0.001; exponentiated c oefficients; standard errors in parentheses; missing v alues in the
independent variables are included in the models but results are not displayed; SN=Senegal, FIS=France, Italy or Spain
Fertility Differences Between Migrants and Stayers in a Polygamous...
Table 2 Men: Discrete-time hazard models predicting a first/higher-order birth in given year (odds ratios)
1st birth
(M1)
1st birth
(M2)
1st birth
(M3)
2+ births
(M4)
2+ births
(M5)
2+ births
(M6)
Time since union
formation/last
birth Parity
0.92***(0.01) 0.92*** (0.01) 0.92*** (0.01) 0.91*** (0.01) 0.91*** (0.01) 0.91***(0.01)
1Ref. Ref. Ref.
2 0.82** (0.06) 0.81** (0.06) 0.81** (0.06)
3 0.73*** (0.07) 0.72*** (0.07) 0.72*** (0.07)
4 0.78** (0.07) 0.76** (0.07) 0.76** (0.07)
5 0.79* (0.09) 0.78* (0.09) 0.78* (0.09)
6+ 0.71**(0.08) 0.69*** (0.08) 0.70*** (0.08)
Urban No Ref. Ref. Ref. Ref. Ref. Ref.
Yes 0 .75** (0.07) 0.7 6** (0.08) 0.76 ** (0.08) 0.93 (0.0 6) 0.95 (0.06) 0.95 (0.06)
Religious
affiliation
Tidiane Ref. Ref. Ref. Ref. Ref. Ref.
Mouride 0.99 (0.10) 0.94 (0.10) 0.94 (0.10) 0 .86* (0.06) 0.84 * (0.06) 0.84** (0.06 )
Other Musli m 0.94 (0.12) 0.94 (0.13) 0 .93 (0.13) 0.98 ( 0.08) 1.03 (0.09) 1.03 (0.09)
Other 0.87 (0.17) 0.98 (0.20) 0.98 (0.20) 0 .89 (0.12) 0.98 (0.1 3) 0.99 (0.13)
Birth cohort Before 1965 Ref. Ref. Ref. Ref. Ref. Ref.
1965 and after 0.63*** (0.06) 0.64*** (0.06) 0.65*** (0.06) 0.73*** (0.05) 0.75*** (0.05) 0.75*** (0.05)
Age 1524 Ref. Ref. Ref. Ref. Ref. Ref.
2534 2.22*** (0.24) 1.97*** (0.23) 1.99*** (0.23) 1.14 (0.16) 1.06 (0.16) 1.06 (0.16)
3544 2.80*** (0.46) 2.39*** (0.40) 2.24*** (0.38) 1.11 (0.16) 1.03 (0.16) 1.01 (0.16)
4560 3.13**(1.29) 3.16**(1.27) 3.32**(1.40) 0.63** (0.11) 0.59** (0.11) 0.58** (0.10)
Residence of
partners,
combined
All SN Ref. Ref. Ref. Ref. Ref. Ref.
Woman
(women)
SN,
man FIS
0.66** (0.09) 0.64** (0.09) 0.85 (0.14) 0.52*** (0.04) 0.50*** (0.04) 0.55*** (0.05)
All FIS 1.09 (0.21) 1.19 (0.24) 1.41+ (0.29) 0.59*** (0.05) 0.60***(0.05) 0.61*** (0.05)
Other 0.37***(0.05) 0.36*** (0.05) 0.38*** (0.05) 0.92 (0.10) 0.90 (0.09) 0.91 (0.10)
Polygamo us
union
No Ref. Ref. Ref. Ref. Ref. Ref.
Yes 0 .69 (0.17) 0.68 ( 0.17) 0.67 (0.17) 2.25*** (0.17) 2.27* ** (0.17) 2. 25*** (0.17)
Education
partners,
combined
All primary Ref. Ref. Ref. Ref.
Man secondary,
woman
(women)
primary
1.38* (0.18) 1.37* (0.18) 0.90 (0.06) 0.90 (0.06)
Man primary,
at least 1
woman
secondary
0.79 (0.12) 0.78 (0.12) 0.90 (0.09) 0.90 (0.09)
All secondary 0.89 (0.11) 0.90 (0.11) 0.73***(0.05) 0.73*** (0.05)
Economically
active
No Ref. Ref. Ref. Ref.
Yes 2.08***(0.32) 2.02*** (0.31) 1.57** (0.25) 1.55** (0.25)
Financial
situation
household
Less than
sufficient
Ref. Ref. Ref. Ref.
Sufficient or
better
0.83+ (0.08) 0.81* (0.08) 1.11+ (0.07) 1.10+ (0.06)
Duration in FIS 4+ years /
non-migrant
Ref. Ref. Ref.
Arrival year 0.74 (0.25) 0.51* (0.14)
+1 year 0.33** (0.14) 0.90 (0.21)
+2 years 0.53+ (0.18) 0.57* (0.16)
+3 years 0.30** (0.13) 0.98 (0.23)
N (person-years) 3648 3648 3648 9212 9212 9212
Data: MAFE-MESE Biographic Survey (2008/2011), unweighted
+p<0.1,*p< 0.05, ** p< 0.01, *** p< 0.001; exponentiated c oefficients; standard errors in parentheses; missing v alues in the
independent variables are included in the models but results are not displayed; SN=Senegal, FIS=France, Italy or Spain
Kraus E.K., González-Ferrer A.
The second hypothesis postulates that women and men who are spatially
separated from their partner (or partners for polygamous men) due to out-
migration experience a disruption in childbearing and, accordingly, have lower
birth probabilities compared to non-migrants at origin (H2: Disruption and fertility
timing). The geographic separation of couplesi.e.meninEuropeandwomen
staying in Senegalduring the preceding year results in significantly lower birth
probabilities in the following year. This holds for first as well as higher-order
births and in both the female and male models (W2, W5, M2, M5). Menssolo
migration leads to significantly lower odds of having a child in a given year, thus
confirming our second hypothesis.
The type of partnership is also related to the timing of births. The results indicate that
birth transitions of women living with a co-wife in their current partnership are not
significantly different from women in a monogamous union. Men in polygamous
unions, however, have a more than the twofold probability of having a second or
higher-order birth compared to monogamous men in a given year. An interaction effect
combining the residence of the partners and the type of union (monogamous vs.
polygamous) shows that this difference is largest in years when men are with their wife
(wives) in Senegal and is smallest when men reside alone in Europe leaving their wife
(wives) behind in Senegal (Fig. 1). This partially supports hypothesis 4 (H4: Disruption
and polygamy), in which we expected that the depressive effect of migration on birth
timing is strongest for polygamous migrant men compared to monogamous migrants.
The exponentiated coefficients for women and men also show that respondents
residing with their partner(s) together in Europe have significantly lower odds of birth
compared to women and men who stay with their partners at origin. This is true,
however, only for second or higher-order births. On the contrary, for women who are in
Europe with their husbands, significantly higher first-birth probabilities can be
Fig. 1 Men: Fertility timing: Interaction of residence of partners and polygamous union. Predicted probabil-
ities, 95% confidence intervals. Data: MAFE-MESE Biographic Survey (2008/2011), unweighted dependent
variable: transition to any birth; independent variables are the same as in model M6, Table 2, adding an
interaction effect for residence of partners and polygamous union; SN=Senegal, FIS=France, Italy or Spain
Fertility Differences Between Migrants and Stayers in a Polygamous...
observed in the year of their arrival, compared to women who are together with their
husbands at origin (W3). Similarly, higher-order birth risksalthough low overall
when both partners are together at destinationincrease in the year when women
arrive at destination to join their husband (W6). This leads us to confirm hypothesis 5
(H5: Interrelation of events and fertility timing), stating that Senegalese migrant women
have high birth probabilities in the years immediately after arriving at their destination
compared to non-migrant women. Independent of parity, migrant women experience a
strong interrelation of the timing of their migration move and the ensuing fertility. Men,
in contrast, have very low first and higher-order birth risks in the years of and following
their arrival (M3, M6), as for them migration and arriving at destination
basically means separation from their wife (wives).
The fertility-related control variables show significant results and point in the
same direction for women and men. The more time passes after a birth (or since
union formation for first births), the lower the probability of having a child. More-
over, the probabilities of a birth decrease with parity. Furthermore, the demographic
covariates show that individuals with an urban background have lower birth prob-
abilities. Members of the Mouride brotherhood have lower birth risks than those
affiliated with the Tidiane brotherhood. With regard to the birth cohort, birth
transitions slowed down for persons born in more recent years, indicating a slow
declineinfertilityratesinlinewiththefertilitytransitionunderwayinmanysub-
Saharan African countries.
Multivariate Results on Completed Fertility
Table 3(women) and Table 4(men) present the incidence rate ratios for completed
fertility at age 40. Regarding the positive socioeconomic selectivity of migrants,
hypothesis 1 postulated that fertility differentials between migrant and non-migrant
men and women should diminish when controlling for their socioeconomic character-
istics (H1: Selection and fertility timing and completed fertility). However, there is no
support for this in the data. For both women and men, the effect of migration
experience on the number of children remains essentially the same after adding the
covariate for the partnerscombined educational attainment. This is in line with the
results on fertility timing presented in the previous section, where we also included
other dimensions of socioeconomic status (labour force status and financial situation) to
capture migrant selectivity.
Regarding fertility disruption, we expected that women and men who are either
themselves a migrant and/or have a migrant partner show lower completed fertility
compared to non-migrant men and women (H3: Disruption and completed fertility).
The results for women clearly show that being a migrant is associated with a lower
number of births compared to their non-migrant counterparts, and thus, hypothesis 3
could be confirmed. Non-migrant women with a migrant partner have also fewer
children than those with a non-migrant husband, but this becomes insignificant (p<
0.11) after adding the measure for education (model W8, Table 3). Changing the
reference category in the female models, the results show that migrant women with a
non-migrant partner have a significantly lower completed fertility (p< 0.05) compared
to migrant women with a migrant partner, indicating that these female solo migrants are
highly selective with low fertility levels. For men, however, there is no significant
Kraus E.K., González-Ferrer A.
difference in the number of children between being a migrant with a non-migrant wife
(wives) or with a migrant wife (wives).
Finally, regarding hypothesis 4 (H4: Disruption and polygamy), we anticipated that
for polygamous men the depressing effect of migration on completed fertility should be
stronger than for monogamous men. Table 4shows that men who have several
simultaneous unions have significantly higher completed fertility. The graphic presen-
tation of the interaction effect of migration experience at age 40 and the type of union
(Fig. 2) displays that this effect is mainly driven by the polygamous: while for
monogamous men, there is no significant negative effect of being a migrant on the
number of children born, for polygamous men, this negative effect is large and highly
significant. Thus, H4 could be confirmed. As men often become polygamous at higher
ages, and here we only account for polygamy and fertility up to the age of 40, the effect
of having two or more simultaneous unions on the completed fertility of migrants might
even be underestimated. For women, the incidence rate ratios indicate that living with
one or several co-wives does not affect the number of children they have up to age 40,
which is not in line with previous research that showed that women in polygamous
unions compared to women in monogamous unions had lower fertility (Lardoux and
Van de Walle 2003).
Table 3 Women: Completed fertility: Poisson regression models predicting total number of births at age 40
(incidence rate ratio)
completed (W7) completed (W8)
Urban No Ref. Ref.
Yes 0.93 (0.05) 1.00 (0.05)
Religious affiliation Tidiane Ref. Ref.
Mouride 0.94 (0.06) 0.93 (0.05)
Other Muslim 0.92 (0.09) 0.98 (0.08)
Other 0.90 (0.12) 0.91 (0.11)
Birth cohort Before 1965 Ref. Ref.
196574 0.87* (0.05) 0.88* (0.05)
Co-wife in union No Ref. Ref.
Yes 1.08 (0.06) 1.05 (0.05)
Migration experience
partners, combined
Both non-migrants Ref. Ref.
Woman ever FIS, man non-migrant 0.60*** (0.07) 0.63*** (0.07)
Woman non-migrant, man ever FIS 0.86+ (0.08) 0.87 (0.07)
Both ever FIS 0.73*** (0.05) 0.75*** (0.05)
Education partners,
combined
Both primary Ref.
Woman secondary, man primary 0.65*** (0.06)
Woman primary, man secondary 0.89+ (0.06)
Both secondary 0.73*** (0.05)
N426 426
Data: MAFE-MESE Biographic Survey (2008/2011), unweighted
+p<0.1,*p< 0.05, ** p< 0.01, *** p< 0.001; exponentiated coefficients; standard errors in parentheses;
missing values in the independent variables are included in the models but results are not displayed;
FIS=France, Italy, Spain
Fertility Differences Between Migrants and Stayers in a Polygamous...
Regarding the demographic control variables, the results show that the number of
children decreases for the younger birth cohort, both for women and men, and that
religious affiliation and urban background have no significant effect.
Conclusion
The aim of this article was to compare the fertility behaviour of migrants and those who
stay at origin by taking a country-of-originor dissimilation perspective and consider-
ing the polygamous setting in Senegal. In order to disentangle selection effects deter-
mining the fertility behaviour of migrants, other mechanisms explaining migrant fertility
were also examined (disruption, interrelation of events), as several may be at work either
simultaneously or sequentially. Overall, we found evidence for both differences in
fertility timing and completed fertility between migrants and stayers at origin. A strong
disruptive effect of migration on childbearing could be observed, clearly related to the
Table 4 Men: Completed fertility: Poisson regression models predicting total number of births at age 40
(incidence rate ratios)
completed (M7) completed (M8)
Urban No Ref. Ref.
Yes 0.93 (0.06) 0.93 (0.06)
Religious affiliation Tidiane Ref. Ref.
Mouride 0.91 (0.06) 0.90 (0.06)
Other Muslim 0.89 (0.09) 0.89 (0.09)
Other 0.83 (0.11) 0.83 (0.11)
Birth cohort Before 1965 Ref. Ref.
196574 0.81** (0.06) 0.80** (0.05)
Polygamous union No Ref. Ref.
Yes 1.84*** (0.13) 1.83*** (0.13)
Migration experience
partners, combined
All non-migrants Ref. Ref.
Man ever FIS, woman
(women) non-migrant
0.76*** (0.05) 0.76*** (0.05)
Man ever FIS, at least 1
woman ever FIS
0.73*** (0.07) 0.75** (0.07)
Education partners,
combined
All primary Ref.
Man secondary, woman
(women) primary
1.10 (0.09)
Man primary, at least 1
woman secondary
0.98 (0.10)
Man secondary, at least 1
woman secondary
0.94 (0.08)
N450 450
Data: MAFE-MESE Biographic Survey (2008/2011), unweighted
+p<0.1,*p< 0.05, ** p< 0.01, *** p< 0.001; exponentiated coefficients; standard errors in parentheses;
missing values in the independent variables are included in the models but results are not displayed;
FIS=France, Italy, Spain
Kraus E.K., González-Ferrer A.
geographic separation of couples due to the out-migration of the man. Women were less
likely to experience a birth in a given year when their partner was in Europe in the prior
year. This is true for first births as well as higher-order births. Combining data on the
migration status of the respondent and their partner(s) analytically enabled linking
disrupted fertility to the separation of partners, which could not have been done without
the information on partners migratory movements. Concerning completed fertility,
migrant womenand men have significantly fewer children throughout their reproductive
life course compared to their non-migrant counterparts. Part of this difference can surely
be explained by the prolonged separation of partners, making fertility recovery difficult
or impossible. Yet, our results suggest that the major reason why Senegalese migrant
men have fewer children than their non-migrant counterparts is related to polygamy,
as polygamous migrants apparently do not recover their fertility, and their completed
fertility by the age of 40 remains lower than that of non-migrant polygamous men.
On the contrary, for female fertility outcomes, our data do not show any effect of
living in a polygamous union with another wife in this context.
Against our expectations, selectivity on observable characteristics such as educa-
tional attainment and economic performance and resources could not explain the
fertility differences between migrants and stayers. It can be assumed, however, that,
at least part of the differences in fertility between migrants and non-migrants are the
result of selectivity on unobservable characteristics. Some authors argue that migrants
have intrinsic preferences or personality traits that are difficult or impossible to measure
that shape their fertility outcomes, such as social mobility aspirations (Milewski 2007),
openness to innovation (Lindstrom and Giorguli-Saucedo 2002), high aspirations for
children and family proneness (Baykara-Krumme and Milewski 2017; Kulu and
González-Ferrer 2014; Lindstrom and Giorguli-Saucedo 2007). Unfortunately, the
MAFE survey does not provide this information. Another partial explanation for the
Fig. 2 Men: Completed fertility: Interaction of migration experience and polygamous union. Predicted
number of births, 95% confidence intervals. Data: MAFE-MESE Biographic Survey, unweighted. dependent
variable: number of births; independent variables are the same as in model M8, Table 4, adding an interaction
effect for migration experience of partners and polygamous union; FIS=France, Italy or Spain
Fertility Differences Between Migrants and Stayers in a Polygamous...
lower fertility of migrants might be adaptation or convergence processes towards lower
fertility levels and higher costs of childbearing and childrearing in European destination
countries. Low second and higher-order birth probabilities of migrant women and men
residing together at the destination might be an indication for this.
Another issue covered to a lesser extent in the standard explanations for migrants
fertility behaviour and previous research, and providing another perspective to the
results presented here, is that having children under specific circumstances may also
entail benefits or advantages, in particular for women, going beyond the argumenta-
tion of childbearing being the result of differential costs and opportunities. For
instance, in many sub-Saharan African societies, young women see their children as
the key to security in her husbands home and a bulwark against competition from
present or future co-wives(Bledsoe et al. 2007, p. 388). Giving birth to many
children may be seen as a strategy of a woman to strengthen her position within
the extended (polygamous) family. For migrant women, in contrast, having a fast
transition to a (first) child shortly upon arrival in the destination country has been
interpreted as a legal strategy to get the citizenship of the respective country for that
child and sometimes the parents themselves (Lindstrom and Giorguli-Saucedo 2007;
Milewski 2007). Although this does not apply to the countries under study, other
advantages may emerge in European destination countries, such as social security and
health care benefits, or the childrens right to education (Bledsoe et al. 2007; Bledsoe
and Sow 2008).
While the current study contributes to the existing research on migrant fertility,
several limitations should be mentioned. First, the formulated hypotheses and the
analytical approach are based on the assumption that migration shapes fertility behav-
iour; however, fertility may also influence migration decisions, as has been shown in
several studies (Lindstrom and Giorguli-Saucedo 2007; Ribe and Schultz 1980). Births
are not only postponed as a consequence of couple separation, but migration may also
be initiated or delayed as a result of a birth. Second, another issue that could not be
addressed in this study is that fertility differences between migrants and stayers may
operate through differential selection processes into partnerships, as has been found for
Senegal (Marchetta and Sahn 2015). For instance, women marrying a migrant, and
especially marriage migrants, probably are selected on socioeconomic factors, as well
as on their aspirations for marrying a migrant and eventually following him to Europe
and having a child there. Moreover, both men and women entering a polygamous union
are selected on socioeconomic characteristics, which ultimately also determine their
migration behaviour as well as their fertility desires and outcomes. Third, the models do
not account for the specific destination country (France, Italy, Spain), although fertility
levels, socioeconomic conditions and the social and economic integration of migrants
may vary across destinations and Senegalese migration to France has a much more
established colonial and migratory history than migration to the other two countries.
Investigating the effect that different receiving contexts may have on the fertility
behaviour of the same migrant group is a relevant issue for further research, which
goes beyond the country-of-origin-perspective of this study. Notwithstanding these
limitations, the current research provides some new perspectives as well as innovative
theoretical and empirical insights to existing theories on the family formation of
migrant populations and especially for migration flows from sub-Saharan Africa and
other polygamous settings.
Kraus E.K., González-Ferrer A.
Table 5 Women: Descriptive statistics of variables. Percentages of person-years at risk and number of birth
events by time-varying migrant status of respondent
Respondents residence during person-year (t-1) in
SN FIS Other
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Parity (tv) 0 19.8 640 19.8 122 26.4 16
1 13.9 522 22.0 114 24.5 19
2 13.6 398 19.7 81 23.7 15
3 14.0 309 15.2 53 11.2 9
4 10.9 196 9.6 35 5.1 7
5 9.0 155 3.9 23 3.8 5
6+ 18.9 287 9.9 24 5.3 7
Urban (tc) No 67.2 1575 50.7 198 80.2 52
Yes 27.0 822 43.3 211 13.7 26
missing 5.9 110 6.0 43 6.1 0
Religious
affiliation
(tc)
Tidiane 56.5 1332 35.7 182 61.9 49
Mouride 31.6 778 22.3 127 29.0 15
Other Muslim 7.9 261 21.3 100 8.8 8
Other 3.2 104 8.8 27 0.1 4
missing 0.8 32 12.0 16 0.2 2
Birth cohort
(tc)
Before 1965 60.0 1315 43.8 111 55.3 47
1965 and after 40.0 1192 56.2 341 44.7 31
Age (tv) 15-24 31.1 1021 10.5 99 36.3 30
25-34 41.7 1157 47.9 239 49.4 40
35-45 27.3 329 41.7 114 14.3 8
Co-wife in
union (tv)
No 54.6 1509 85.4 360 77.2 45
Yes 44.6 977 13.9 87 20.7 31
missing 0.8 21 0.8 5 2.1 2
Residence of
partner (tv,
t-1)
SN 78.6 1900 5.7 29 33.4 9
FIS 5.6 309 85.4 417 9.9 10
Elsewhere 15.9 298 8.9 6 56.7 59
Education
partners,
combined
(tc)
Both primary 57.3 1249 23.6 185 28.2 38
Woman secondary,
man primary prim.
5.8 171 17.1 80 8.5 11
Woman primary,
man secondary
21.9 530 13.8 54 28.7 12
Both secondary 11.4 451 41.7 122 29.8 15
missing 3.7 106 3.9 11 4.9 2
Appendix
Fertility Differences Between Migrants and Stayers in a Polygamous...
Table 5 (c ontinued)
Respondents residence during person-year (t-1) in
SN FIS Other
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Economically
active (tv,
t-1)
No 64.7 1634 43.3 245 53.3 47
Yes 35.3 873 56.7 207 46.7 31
Financial
situation
household
(tv, t-1)
Less than sufficient 42.0 831 26.1 131 18.0 20
Sufficient or better 57.7 1672 73.8 321 82.0 58
missing 0.3 4 0.1 0 0.0 0
Duration in
FIS
(tv, t-1)
4+ years /
non-migrant
64.9 220
Arrival year 9.6 93
+1 year 9.6 55
+2 years 8.3 47
+3 years 7.7 37
Total 94.4 2507 4.1 452 1.5 78
Data: MAFE-MESE Biographic Survey (2008/2011), weighted percentages.
percentages may not total 100% due to rounding; tv=time-varying, tc=time-constant; SN=Senegal,
FIS=France, Italy, Spain
Kraus E.K., González-Ferrer A.
Table 6 Men: Descriptive statistics of variables. Percentages of person-years at risk and number of birth
events by time-varying migrant status of respondent
Respondents residence during person-year (t-1) in
SN FIS Other
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Parity (tv) 0 25.7 417 23.7 142 22.1 27
1 13.2 340 21.4 128 15.0 18
2 12.9 242 20.0 112 9.5 13
3 11.8 169 14.0 75 4.9 13
4 5.6 126 8.2 57 15.9 15
5 6.6 116 5.2 36 8.2 10
6+ 24.2 336 7.4 60 24.4 25
Urban (tc) No 66.0 1160 52.8 353 68.6 90
Yes 29.5 531 45.2 241 30.4 28
missing 4.5 55 2.0 16 1.1 3
Religious
affiliation (tc)
Tidiane 40.3 716 29.7 218 41.2 48
Mouride 36.5 602 40.0 240 43.5 47
Other Muslim 16.6 318 15.5 95 9.0 14
Other 6.3 94 6.6 26 2.1 11
missing 0.4 16 8.2 31 4.2 1
Birth cohort (tc) Before 1965 62.0 1190 63.4 381 80.0 97
1965 and after 38.1 556 36.6 229 20.0 24
Age (tv) 1524 11.9 168 2.6 19 8.7 10
2534 39.7 796 35.0 206 31.4 47
3544 27.9 556 40.2 297 42.2 44
4560 20.6 226 22.2 88 17.7 20
Polygamous
union (tv)
No 83.5 1373 83.7 469 80.4 93
Yes 16.5 373 16.3 141 19.6 28
Residence of
partner(s) (tv,
t-1)
SN 90.2 1600 57.3 356 69.1 79
FIS 0.9 18 36.7 225 1.7 2
Elsewhere 1.4 47 1.4 11 23.0 36
missing 7.6 81 4.6 18 6.3 4
Education
partners,
combined
(tc)
All primary 52.9 888 37.7 259 48.3 71
Man
secondary,
woman
primary
19.3 356 18.4 119 16.5 18
Man primary,
woman
secondary
7.2 113 7.8 73 10.0 6
All secondary 19.6 373 35.1 152 25.2 26
missing 1.1 16 1.0 7
No 13.5 123 6.3 20 8.1 5
Fertility Differences Between Migrants and Stayers in a Polygamous...
Acknowledgements The research leading to these results has received funding from the European
Communitys Seventh Framework Programme (grant 217206) and the Spanish Ministry of Science
and Technology (grant CSO2009-12816). We are very grateful for the comments and support
provided by Alícia Adserà and Nadja Milewski and for the useful suggestions of two anonymous
reviewers.
Funding Open Access funding enabled and organized by Projekt DEAL.
Declarations
Conflict of Interest The authors declare that they have no conflict of interest.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence,and
indicate if changes were made. The images or other third party material in this article are included in the
article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not
included in the article's Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Table 6 (c ontinued)
Respondents residence during person-year (t-1) in
SN FIS Other
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Exposure
(person-
years, %)
Number
of births
Economically
active
(tv, t-1)
Yes 86.5 1623 93.7 590 1.9 116
missing 0
Financial
situation
household
(tv, t-1)
Less than
sufficient
33.3 626 26.5 195 14.8 26
Sufficient or
better
63.2 1104 73.2 413 84.6 95
missing 3.5 16 0.4 2 0.6 0
Duration in FIS
(tv, t-1)
4+ years /
non-migrant
78.2 496
Arrival year 5.5 29
+1 year 5.5 32
+2 years 5.5 25
+3 years 5.4 28
Total 81.2 1746 15.9 610 2.9 121
Data: MAFE-MESE Biographic Survey (2008/2011), weighted percentages.
percentages may not total 100% due to rounding; tv=time-varying, tc=time-constant; SN=Senegal,
FIS=France, Italy, Spain
Kraus E.K., González-Ferrer A.
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Kraus E.K., González-Ferrer A.
... For example, the majority of the studies either compared fertility of the migrants either with that of the native populations at the destination (Alderotti et al., 2019;Devolder & Bueno, 2011;Saikia et al., 2019;Stonawski et al., 2016) or have compared the fertility behaviour of different migrant groups living in the same destination (Kraus, 2019;Milewski & Mussino, 2018). But taking into consideration the fertility behaviour of the migrants with respect to their original population is sparse (Kraus & Gonz alez-Ferrer, 2021;Mussino & Cantalini, 2022;Wolf & Mulder, 2019); especially in the Indian context (Ghosh & Chakraborty, 1997). Barring a few (Balbo et al., 2013), none of the studies has made any attempt to examine the complex pathways through which the determinants, including socio-cultural norms of a community delineate the fertility behaviour of migrants and sedentes belonging to the same ethnic origin. ...
... These pathways substantially support the 'adaptation' and 'disruption' hypotheses and trail the validation that variation in fertility between sedentes and migrants with no correlated genetic differences from their origin, resulted from the varying socio-ecological context, constrain, and the strategic adjustment of the reproductive behaviour (Guetto, 2018;Reyneri & Fullin, 2011). However, studies undertaken to examine the fertility differentials between sedentes and migrants did not provide a universal trend (Baiz an et al., 2014;Chattopadhyay et al., 2006;Kraus & Gonz alez-Ferrer, 2021). For example, Abbasi-Shavazi et al. (2015) attributed fertility decline among Afghan immigrants in Iran owing to their migration from a high fertility regime to a low fertility regime and adaptation to the host society. ...
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... However, recent literature argues that solely comparing the group means of fertility behaviors between migration groups and the destination natives is insufficient to distinguish whether the distinct fertility patterns of migration groups are 'imported attitudes and behaviors' from the origin countries or linked to the destination contexts and specific migration situations (Baykara-Krumme & Milewski, 2017;Impicciatore et al., 2020). Therefore, to understand whether the fertility patterns of migration groups are linked to the fertility context of their origin country, recent studies have developed a dissimilation perspective to investigate the fertility behaviors' difference (or similarity) between immigrants and the 'stayers' in their origin country (Baykara-Krumme & Milewski, 2017;Glick, 2010;Impicciatore et al., 2020;Kraus & González-Ferrer, 2021;Milewski & Baykara-Krumme, 2021;Puur et al., 2017). ...
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