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Migration from new-accession countries and duration expectancy in the EU-15: 2002-2008
Jack DeWaard1
Jasmine Trang Ha2
James Raymer3
Arkadiusz Wiśniowski4
Abstract
European Union (EU) enlargements in 2004 and 2007 were accompanied by increased migration from new-accession to established-member (EU-15) countries. The impacts of these flows depend, in part, on the amount of time that persons from the former countries live in the latter over the life course. In this paper, we develop period estimates of duration expectancy in EU-15 countries among persons from new-accession countries. Using a newly developed set of harmonised Bayesian estimates of migration flows each year from 2002 to 2008 from the Integrated Modelling of European Migration (IMEM) Project, we exploit period age patterns of country-to-country migration and mortality to summarize the average number of years that persons from new-accession countries could be expected to live in EU-15 countries over the life course. In general, the results show that the amount of time that persons from new-accession countries could be expected to live in the EU-15 nearly doubled after 2004.
Keywords
European Union; Migration; Duration of Residence; Completed Stays; Life Course; Duration Expectancy; Multiregional; Multistate
1 Department of Sociology, Minnesota Population Center, University of Minnesota. 909 Social Sciences, 267 19th Ave. South, Minneapolis, MN, 55455, USA. E: jdewaard@umn.edu, P: (612) 624-9522, F: (612) 624-7020.2 Department of Sociology, Minnesota Population Center, University of Minnesota.3 Australian Demographic and Social Research Institute, Australian National University, Canberra, AUS.4 School of Social Statistics, University of Manchester, Manchester, UK.
Acknowledgements
This research is supported by center grant #R24 HD041023 awarded to the Minnesota Population Center at the University of Minnesota by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and by research funds awarded to DeWaard by the Life Course Center at the University of Minnesota. The age-specific migration data used in this paper were estimated as part of the Integrated Modelling of European Migration (IMEM) Project, www.imem.cpc.ac.uk, funded by the New Opportunities for Research Funding Agency Co-operation in Europe (NORFACE), 2009-2012. The authors wish to thank the Editor and two anonymous reviewers for their helpful comments.
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Abstract
European Union (EU) enlargements in 2004 and 2007 were accompanied by increased
migration from new-accession to established-member (EU-15) countries. The impacts of
these flows depend, in part, on the amount of time that persons from the former countries
live in the latter over the life course. In this paper, we develop period estimates of duration
expectancy in EU-15 countries among persons from new-accession countries. Using a
newly developed set of harmonised Bayesian estimates of migration flows each year from
2002 to 2008 from the Integrated Modelling of European Migration (IMEM) Project, we
exploit period age patterns of country-to-country migration and mortality to summarize the
average number of years that persons from new-accession countries could be expected to
live in EU-15 countries over the life course. In general, the results show that the amount of
time that persons from new-accession countries could be expected to live in the EU-15
nearly doubled after 2004.
Keywords
European Union; Migration; Duration of Residence; Completed Stays; Life Course;
Duration Expectancy; Multiregional; Multistate
2
1. Introduction
Efforts to assess the economic and social impacts of enlargements of the European
Union (EU) in 2004 and 2007 are limited by “uncertainty about the duration of stay”
among persons from new-accession countries in established-member (EU-15) countries
(Sumption and Somerville 2010:17).5 Research suggests that many persons from new-
accession countries have no intention of staying permanently in EU-15 countries, with
upwards of 50 percent leaving within the first five years after arrival in some cases
(Blanchflower and Lawton 2008; Dustmann and Weiss 2007; Green et al. 2007). These
figures, however, reflect “current stays,” or the duration of a single migration trip, and not
“completed stays,” or accumulated lived experience in EU-15 countries over the life course
(Green et al. 2007:73). The duration of completed stays is particularly important in this
context given the highly temporary, circular, and repeated nature of migration (Dustmann
and Weiss 2007; Quinn 2011; Sumption and Somerville 2010; White 2011; Zaiceva and
Zimmermann 2012). Of course, there are significant obstacles to estimating the duration of
completed stays, including (i) the fairly short amount of time that has elapsed since EU
enlargements in 2004 and 2007, (ii) that migrants from new-accession countries are very
young, with many years ahead of them to accrue time in EU-15 countries (Brücker and
Damelang 2009), and (iii) over the life course, non-migrants in new-accession countries
might eventually select into migration.
5 Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland,
Slovakia, and Slovenia joined the EU in 2004. Bulgaria and Romania joined the EU in
2007. Although the focus of this paper is with EU expansions in 2004 and 2007, Croatia
joined the EU in 2013, bringing the total number of new-accession countries to 13.
3
Given these issues, in this paper, we develop period estimates of duration
expectancy in EU-15 countries among persons from new-accession countries. Taking a
multiregional (or multistate) approach (Rogers 1975, 1995; Schoen 1975, 1988), we exploit
period age patterns of country-to-country migration and mortality to generate conditional
life expectancies at birth. Our estimates summarize the average number of years that
persons from new-accession country i could be expected to live in EU-15 country j over the
course of their lives if, at each age, they were exposed to the prevailing risks of country-to-
country migration and mortality in period t. Estimates are developed for each pair of new-
accession and EU-15 countries each year from 2002 to 2008. Given well-documented
problems with how countries differentially collect, process, and report migration statistics
(Kahanec et al. 2010; Kupiszewska and Nowok 2008; Massey et al. 1998; Nowok et al.
2006; Poulain et al. 2006), a key innovation of this paper is our use of harmonised estimates
of country-to-country migration flows developed by Integration Modelling of European
Migration (IMEM) Project (Raymer et al. 2013), which permit bounding our estimates of
duration expectancy by corresponding measures of uncertainty.
2. EU Enlargements, Migration, and Impacts
EU enlargements in 2004 and 2007 resulted in increased migration from new-
accession to EU-15 countries (Brücker and Damelang 2009; Kahanec et al. 2010). This is
not surprising since migration flows are often responsive to wage and employment
differentials favoring receiving (versus sending) countries (Greenwood 1997; Massey et al.
1998), not to mention reduced barriers to intra-EU mobility afforded by EU membership.
Nonetheless, it was concerning at the time because, relative to EU-15 countries, with the
4
exception of Cyprus and Malta, new-accession countries were former Eastern Bloc
countries with lower national incomes, younger populations, and more recent transitions to
a market-based economy (Kahanec et al. 2010).
Bracketing well-documented problems with the availability, quality, and cross-
national comparability of migration data (Kahanec et al. 2010; Kupiszewska and Nowok
2008; Massey et al. 1998; Nowok et al. 2006; Poulain et al. 2006), issues to which we will
later return, the 2004 enlargement of the EU was accompanied by a pronounced increase in
the number of foreign-born residents living in EU-15 countries. Excluding Cyprus and
Malta, between 2000 and 2004, the average annual change in the number of foreign-born
residents from new-accession countries living in the EU-15 was +61,000 persons (Brücker
and Damelang 2009; Kahanec et al. 2010). Between 2004 and 2005, this figure increased to
+250,000 persons, and climbed upwards thereafter, with the United Kingdom and Ireland
absorbing the bulk of these gains. Similar changes in the number of foreign-born residents
from Bulgaria and Romania living in EU-15 countries were recorded after these countries
accessed to the EU in 2007, with most of these gains concentrated in Italy and Spain.
Although the magnitudes of these changes also capture processes other than migration, they
provide reasonable estimates of the overall trend of migration from new-accession to EU-
15 countries following EU enlargements in 2004 and 2007.
With respect to economic and social impacts, many countries in the EU-15 did not
immediately open their labour markets to persons from new-accession countries in order to
buffer the potential effects (Boeri and Brücker 2001; Kahanec et al. 2010). Indeed, the
reason that the United Kingdom and Ireland absorbed such a large share of new-accession
migrants after the 2004 enlargement of the EU is because they immediately opened their
5
labour markets (Barrett 2010; Blanchflower and Lawton 2008; Green et al. 2007; Sumption
and Somerville 2010). Other countries in the EU-15 gradually opened their labour markets
to persons from new-accession countries, with Austria and Germany being the last to do so.
Barrell et al. (2010) showed that labour force increases on account of migration from new-
accession countries following EU enlargements were associated with short-term increases
in GDP per capita, unemployment, and inflation in EU-15 countries. Long-term gains in
productivity and GDP were also reported, as well as eventual declines in unemployment
and inflation. However, as they point out, their results are sensitive to factors that vary
across EU-15 countries, including social welfare policies, infrastructure, and housing (for
detailed assessments for selected EU-15 countries, see Kahanec and Zimmermann 2010).
3. Duration of Residence in the EU-15 among New-Accession Migrants
An important consideration in efforts to assess the economic and social impacts of
migration from new-accession to EU-15 countries is the amount of time that persons from
the former live in the latter (Sumption and Somerville 2010). Duration of residence is a
well-documented indicator of migrants’ economic and social integration in receiving
countries (Geddes et al. 2005; Huddleston et al. 2011; Niessen et al. 2007). In the context of
receiving countries in Europe, duration of residence has been linked to outcomes including
migrants’ educational, occupational and earnings trajectories (De Valk et al. 2011; Le
Grand and Szulkin 2002; Van Tubergen 2004); residential integration (Vono-de-Vilhena
and Bayona-Carrasco 2012); civic participation (Aleksynska 2011; Wright and Bloemraad
2012); and health and mortality assimilation (Malmusi et al. 2010; Mladovsky 2009). As
noted by Geddes et al. (2005:15) in their discussion of the European Civic Citizenship and
6
Inclusion Index, now called the Migrant Integration Policy Index (Huddleston et al. 2011;
Niessen et al. 2007), long-term residence, in particular, affords migrants the ability to
“contribute to society whilst maintaining their links with their country of origin and move
freely within the EU.” This is also a key consideration of supra-national governing bodies,
e.g., the European Commission, in setting immigration and integration policy priorities.
While duration of residence is typically estimated using retrospective survey
questions or migration life histories, there is substantial “uncertainty about the duration of
stay” among persons from new-accession countries in EU-15 countries for several data-
related reasons (Sumption and Somerville 2010:17). First, estimates of duration of
residence in EU-15 countries by country of origin are often unavailable, generated from
data sources of varying quality, or not cross-nationally comparable (Organisation for
Economic Cooperation and Development 2008; Zaiceva and Zimmermann 2012). Second,
existing estimates require grouping into coarse duration intervals to facilitate cross-national
comparisons (Van Tubergen 2004:155; note, this is also an issue with estimates provided
by the Organisation for Economic Cooperation and Development 2008). Finally, even the
best estimates using complete life histories of migrants are limited to only a handful of
sending and receiving countries (Goldstein 1964; Toma and Castagnone 2014; see also Paul
2011), if they are collected or publicly available at all, making comprehensive cross-
national comparisons virtually impossible.
Data limitations aside, there is an important set of substantive issues that is perhaps
the greatest source of uncertainty with respect to duration of residence. While migration
from new-accession to EU-15 countries is not exactly permanent (Blanchflower and
Lawton 2008; Dustmann and Weiss 2007; Green et al. 2007), neither is it a one-time event.
7
Instead, it is often a circular or repeated process (Dustmann and Weiss 2007; Quinn 2011;
Sumption and Somerville 2010; White 2011; Zaiceva and Zimmermann 2012). Prior
research has detailed several arrangements that generate circular migration, including, for
example, seasonal household employment, e.g., as an au pair, and agricultural work
(DeWaard 2013; Green et al. 2007; Sumption and Somerville 2010). While many persons
from new-accession countries return home to their countries of origin, many cycle back to
EU-15 countries at multiple points over the life course. Consequently, the duration of
“current stays” in EU-15 countries does not capture the lived experience of persons from
new-accession countries that results from a series of “completed stays” (Green et al.
2007:73).
While the distinction between the duration of current and completed residence is
helpful, in the context of migration from new-accession to EU-15 countries, estimating the
duration of completed residence is problematic for at least three reasons. First, since only
about ten years have passed since EU enlargements in 2004 and 2007, it is an open question
whether this is a sufficient amount of time to glimpse the totality or even a significant
portion of circular or repeat migration. Second, persons from new-accession countries are
disproportionately young; about two-thirds of persons from new-accession countries living
in the EU-15 are between the ages of 15 and 34, compared to about one-third of natives
(Brücker and Damelang 2009). Importantly, many of these individuals are just entering the
labour force, and, thus, have many years ahead of them to accrue time in EU-15 countries
over the remainder of their lives. Finally, in shifting to a life course perspective, one must
account for the fact that non-migrants living in new-accession countries might, at various
8
points in the life course, eventually select into migration to EU-15 countries, and will
thereby accrue time in these destinations.
To address the issues above, we develop estimates of duration expectancy in EU-15
countries among persons from new-accession countries. Our work builds on previous
research by DeWaard and Raymer (2012) and DeWaard (2013), but with a different and
substantially improved set of harmonised age-specific migration flow estimates obtained
from the IMEM project, which incorporated a data measurement model, information from
experts, and measures of uncertainty (Raymer et al. 2013; Wiśniowski et al. forthcoming).
In what follows, we detail our approach to estimating duration expectancy in EU-15
countries among persons from new-accession countries, including summary measures and
the data and model used.
4. Summary Measures of Duration Expectancy
The key quantities of interest in this paper are conditional life expectancies at birth
in each new-accession country. These life expectancies are calculated separately for each of
seven periods (t = 2002, 2003,…, 2008) in our data.6 They describe the experiences of
synthetic cohorts and their implied hypothetical stationary populations.
Life expectancy at birth in each new-accession country i, e0i (i ∈ new-accession
countries) can be partitioned into two components, each of which is a conditional life
expectancy at birth. The first component, in-country life expectancy, e0i ,i, expresses the
average number of years that persons from new-accession country i could be expected to
live in i over the course of their lives given prevailing age patterns of country-to-country 6 t sub-/super-scripts are omitted from the notation below, but are nonetheless implied.
9
migration and mortality in period t. The second component, out-of-country life expectancy,
e0i , i, expresses the average number of years that these persons could be expected to live
outside of i (denoted by “~i”) over their lives. These two quantities are additive, and sum to
life expectancy at birth, e0i , in new-accession country i (Rogers 1975, 1995).
Out-of-country life expectancy can be partitioned across any number of defined
receiving countries j (j = 1, 2,..., K, for i≠j), such that e0i , j expresses the average number of
years that persons from new-accession country i could be expected to live in receiving
country j based on period migration and mortality schedules. These quantities are additive,
such that ∑j
e0i , j=¿ e0
i , i ¿ (for i≠j). While country j can be any receiving country, if we
restrict the set of receiving countries to those in the EU-15, then e0i , j (j ∈ EU-15 countries,
for i≠j) is the duration expectancy in EU-15 country j among persons from new-accession
country i. Further summing these quantities across receiving countries in the EU-15, ∑j
e0i , j
can be interpreted as the duration expectancy in the EU-15 as a whole among persons from
new-accession country i. These quantities, e0i , j and ∑
je0
i , j, are the quantities of interest in
the current paper, and, as expectations, can be interpreted as averages that capture different
types of migration, e.g., primary, return, and repeat.
5. Data and Methods
Data for this paper come from several sources. Data on migration come from the
IMEM project (Raymer et al. 2013; Wiśniowski et al. forthcoming), and include age-
specific distributions of counts of country-to-country migration for each pair of countries in
10
the EU and European Free Trade Association (EFTA), as well as a residual “rest of world”
category, each year from 2002 to 2008. Age-specific death counts for EU/EFTA countries
are taken from Eurostat, and, for the rest of the world, are derived from estimates provided
by the United Nations (UN) by subtracting deaths in EU/EFTA countries from world totals.
Because the model, described below, requires inputs in the form of age-specific
probabilities of country-to-country migration and death, age-specific population data for
EU/EFTA countries are taken from Eurostat, and, for the rest of the world, are taken from
the UN.
We estimate duration expectancy in EU-15 countries among persons from new-
accession countries using a multiregional (or multistate) population model (Rogers 1975,
1995; Schoen 1975, 1988). First, we consider a birth cohort in new-accession country i,
e.g., Bulgaria. Between the ages of zero and four, members of this cohort can remain in
country i, migrate to another country in the EU/EFTA or the rest of the world, or die
according to the age-specific probabilities of country-to-country migration and death in our
data. In the next age interval, five to nine years, members of this birth cohort, who now
reside not only in country i, but also in other countries in the EU/EFTA and the rest of the
world, migrate and die according to the observed age-specific probabilities of country-to-
country migration and death. We then repeat this process sequentially for each and every
age interval until this cohort has died out. Along the way, we record the number of person-
years lived by this cohort in each EU/EFTA country and the rest of world. In conjunction
with information on the size of the initial birth cohort in new-accession country i, duration
expectancy is estimated as follows:
11
e0i , j=
T0i , j
l0i (1)
In (1), T 0i , j is the total number of person-years lived in receiving country j beyond
age zero (i.e., birth) by members of, in our case, a synthetic cohort born in country i; and l0i
refers to the size of the birth cohort in i. Because summary estimates of duration expectancy
are generated separately for each new-accession country i one at a time, the size of l0i is
arbitrary, and is set to 100,000 in the current paper (Palloni 2001).
The process described above follows a first-order Markov process (Rogers 1975,
1995; Schoen 1988):
l (x+n )=l (x ) P(x), (2)
where l (x ) is a population row vector at exact age x with K = 33 elements, one for each
EU/EFTA country, the rest of the world, and death. Each element corresponds to the
number of persons from our synthetic birth cohort in new-accession country i living in each
EU/EFTA country and the rest of the world at age x, as well as the number of persons who
have died by age x. At exact age zero, because persons from new-accession country i have
yet to migrate or die, each element in the l (0 ) vector is set to zero, excluding the element for
i, which is set to 100,000.
The P ( x ) matrix is a K by K matrix containing age-specific probabilities of country-
to-country migration and death between ages x and x+n. These probabilities are calculated
from our data. Because the migration data used in the current paper cover a span of one
year and the width of the age intervals is five years, following DeWaard and Raymer
12
(2012:550), we transform each of the age-specific probabilities in the P ( x ) matrix in (2) so
that these reflect the probability of migrating over five years:
pxij
5❑ =1−[1−( M x
ij5
❑
1+0.5 M xij
5❑ )]
5
(3)
In (3), M xij
5❑ is the rate of migration from sending country i to receiving country j between
the ages of x and x+5 in our data for period t (t = 2002, 2003,…, 2008), M x
ij5❑
1+0.5 M xij
5❑ is the
corresponding probability of migrating over one year, and pxij
5❑ is the resulting probability of
migrating over five years.
The l (x+n ) vector is an updated population row vector that contains counts of the
number of persons from our synthetic birth cohort in new-accession country i living in each
EU/EFTA country and the rest of the world at age x+n, as well as counts of the number of
persons who have died by age x+n.
Total person-years in (1) are calculated using the information contained in the
population vectors in (2) at each age. Person-years lived in country j in the age-interval x to
x+n by members of a birth cohort from country i are calculated by averaging the number of
persons lived in j at consecutive ages, lxj and lx +n
j , multiplied by one-half of the width of the
age interval (Palloni 2001; Rogers 1975, 1995; Schoen 1988), which, as noted above, is
five years. These quantities are summed across all age intervals to arrive at total person-
years lived in country j by members of a birth cohort from new-accession country i, and
subsequently divided through by the size of the birth cohort in i to arrive at an estimate of
duration expectancy. Estimates of duration expectancy are generated separately for each
13
birth cohort (i.e., for each new-accession country i) and for each of the seven periods
(2002-2008) in our data.
With respect to the migration data used in this paper, observed age-specific country-
to-country migration counts are publicly available data from Eurostat, the statistical agency
for the European Union. However, these estimates contain inconsistencies due to
measurement differences across countries. These inconsistencies are well-documented
elsewhere (Kupiszewska and Nowok 2008; Nowok et al. 2006; Poulain et al. 2006; Raymer
et al. 2013), and are a result of different definitions and timing criteria used to determine
whether a migration has officially occurred. Differences in coverage and undercount are
also problematic. Some publicly available data, e.g., those reported by Nordic countries, are
considered more accurate than those reported by countries with weak population registers,
e.g., Poland, or those that rely on surveys as a means for official statistics, e.g., United
Kingdom. Finally, in many cases, migration data are simply not reported or even collected.
As part of the IMEM project, Raymer et al. (2013) developed an integrated
approach to harmonise country-to-country migration flow data using a Bayesian model that
quantifies uncertainty in the process. A measurement model was developed to account for
the different criteria used by countries to qualify migrants, undercounts of emigration and
immigration, coverage of migration types, and accuracies of the data collection
mechanisms. Expert information was also obtained to inform model parameters, including,
for example, the magnitude of undercount, which cannot be estimated using migration data
alone (Wiśniowski et al. 2013). A spatial interaction model (see Kim and Cohen 2010; Abel
2010) with economic, demographic and geographic covariates was then used to estimate
missing flows. Age and sex distributions of origin-destination flows were obtained through
14
a Bayesian multilevel multinomial model, which reconciled the data in terms of different
reports of age and sex compositions of migration, but assumed that measurement effects
were the same across age groups and sexes (Wiśniowski et al. forthcoming). Estimated age
and sex compositions were then combined with the estimated origin-destination flows to
provide full posterior distributions of migration counts each year from 2002 to 2008.
To carry the above efforts—particularly, their attention to measurement and
uncertainty—forward, in the current paper, we implemented the following procedure to
generate a corresponding measure of uncertainty to accompany our estimates of duration
expectancy. First, for each age-specific country-to-country migration count in each year, we
took a random draw from the full posterior distribution, referenced above (Wiśniowski et
al. forthcoming). Second, using age-specific data on population counts, detailed at the
beginning of this section, we calculated the probabilities contained in the P ( x ) matrices in
(2), and made the adjustment detailed in (3). Third, we then ran through the multiregional
model and calculated the quantities in (1) for each pair of new-accession and EU-15
countries in each year. Fourth, to provide an external point of reference for our estimates,
we rescaled the quantities in (1) so that our estimates of life expectancy at birth, e0i , in each
new-accession country i in each year matched corresponding estimates provided by the
World Bank.7 Finally, we repeated the previous steps 100 times to generate distributions of
duration expectancy in EU-15 countries among persons from new-accession countries. In
7 The correlation between our estimates of life expectancy at birth and those provided by
the World Bank is 0.93.
15
the next section, we summarize the means of these distributions and corresponding standard
errors.8
6. Results: Duration Expectancy in the EU-15
In Figure 1, we display mean estimates (across the 100 runs, detailed above) for
each period of total life expectancy at birth in each new accession country i, e0i , and in-
country life expectancy at birth, e0i ,i, which summarize the average number of years that
persons from i could be expected to live in i over the course of their lives.
---FIGURE 1 ABOUT HERE---
Total life expectancy increased in each new-accession country over the 2002-2008
period, with gains ranging from +0.05 years in Lithuania to +2.87 years in Estonia. In
contrast, in-country life expectancy decreased, with magnitudes ranging from -1.17 years in
Slovenia to -12.09 years in Lithuania. As we noted earlier, declines in in-country life
expectancy translate into gains in out-of-country life expectancy because these quantities
sum to total life expectancy. To see this, in Figure 2, we display estimates of out-of-country
life expectancy at birth, e0i , i, or the average number of years that persons from new-
accession country i could expect to live outside of i over the course of their lives. These
8 An alternative approach might be to summarize medians and quartiles. We summarize
means and standard errors because the distributions of the quantities in (1) are not badly
skewed and the tails are not especially heavy. Readers can verify this for any/all
distributions of interest, as the full set of estimates for each pair of new-accession and EU-
15 countries each year from 2002 to 2008 is provided in the online appendix.
16
estimates are displayed alongside estimates of duration expectancy in the EU-15 among
persons from new-accession countries, which are derived by restricting the set of receiving
countries to those in the EU-15.
---FIGURE 2 ABOUT HERE---
As should be the case, changes in out-of-country life expectancy mirror changes in
in-country life expectancy, with the smallest gain recorded for Slovenia and the largest gain
recorded for Lithuania. With respect to the aims of this paper, the pertinent question is
whether and the extent to which changes in out-of-country life expectancy are mirrored by
changes duration expectancy in the EU-15. As is evident, in Figure 2, with exception of a
few new-accession countries, e.g., the Czech Republic and Slovakia that exchange
substantial migration flows with each other and/or with countries outside of the EU-15,
there is a fairly strong correlation (r = 0.63, p < 0.001) between out-of-country life
expectancy and duration expectancy in the EU-15.
To walk through how to interpret the estimates in Figure 2, in 2002, persons from
Poland, for example, could be expected to live an average of 11.71 years (15.47 percent of
total life beyond age zero) outside of Poland over the course of their lives. By 2004, this
figure was 18.60 years (24.85 percent). And, by 2008, this figure was 23.44 years (31.02
percent). The largest year-to-year change in out-of-country life expectancy at birth was
+7.05 years between 2003 and 2004, the year Poland joined the EU. It is therefore not
surprising that that largest year-to-year change in duration expectancy, +6.18 years, in the
EU-15 among persons from Poland also occurred between 2003 and 2004. Estimates for
other countries follow a similar pattern. For example, for Romania, which accessed to the
17
EU in 2007, there is a pronounced increase in out-of-country life expectancy (+8.46 years)
and duration expectancy in the EU-15 (+7.36 years) between 2006 and 2007.
In interpreting the estimates in Figure 2 and in subsequent tables and figures, it is
important to keep in mind that our efforts in this paper are effectively an exercise in
demographic translation. Because our estimates are derived from period data on age-
specific country-to-country migration (and mortality), the trends displayed in Figure 2 are
similar to what one would see if they plotted migration counts or rates from new-accession
countries to the EU-15 over time. Our contribution is therefore to translate this information
into a set of summary measures of duration expectancy in the EU-15 among persons from
new-accession countries, recognizing, as we noted earlier, that these measures describe the
experiences of synthetic cohorts and their implied hypothetical stationary populations.
In Figure 3, we go one step further. Rather than summarize duration expectancy in
the EU-15 as a whole, as we did in Figure 2, we do so for each EU-15 country. Due to
issues of space, we present estimates for each pair of new-accession and EU-15 countries in
2002 and 2008.9
---FIGURE 3 ABOUT HERE---
While persons from new-accession countries could be expected to live an increasing
portion of their lives outside of their new-accession country of origin, with a considerable
share of these years accrued in the EU-15 (see Figure 2), there is substantial heterogeneity
with respect to in which countries in the EU-15 new-accession migrants could be expected
to accumulate time. For example, of the 7.05 years that persons from Estonia could be
9 The full set of estimates for each pair of new-accession and EU-15 countries each year
from 2002 to 2008 is provided in the online appendix.
18
expected to live in the EU-15 based on prevailing age patterns of country-to-country
migration and mortality in 2002, nearly one-half of this time (3.46 years, or 49.08 percent)
could be expected to be lived in Finland. By 2008, persons from Estonia could expect to
live 7.57 years in Finland out of a total of 15.52 years in the EU-15 based on prevailing age
patterns migration and mortality during this year.
Across all pairs of new-accession and EU-15 countries, duration expectancy
increased over the 2002-2008 period, with magnitudes ranging from <+0.01 years in the
case of persons from the Czech Republic in Luxembourg to +6.14 years for persons from
Malta in the United Kingdom. To further organize this information, in Table 1, for each
new-accession country, we summarize duration expectancy in the top three EU-15
countries as of 2008. Mean estimates are provided, along with corresponding standard
errors.
---TABLE 1 ABOUT HERE---
In 2008, the United Kingdom (7.22 years), Greece (5.44 years), and Germany (0.91
years) were the top destinations in the EU-15 for persons from Cyprus. Across all new-
accession countries, the United Kingdom and Germany clearly stand out as top destinations
for persons from new-accession countries. While previous research has documented this
much with respect to the size of migration flows (Kahanec et al. 2010), as we discussed
earlier, our efforts do so with respect to the implications of these flows for duration
expectancy. In addition to the United Kingdom and Germany, a handful of other EU-15
countries are important destinations for persons from new-accession countries, e.g., Spain
for persons from Bulgaria and Romania, both of which accessed the EU in 2007.
19
While the full set of estimates is available in the online appendix, in the next few
figures, we walk through how these estimates were constructed, using as a case study
duration expectancy in Germany and the United Kingdom among persons from Poland. We
selected these countries because migration from Poland to Germany and the United
Kingdom was substantial after the 2004 enlargement of the EU, drawing significant
attention from scholars, policy-makers, and the media (Kahanec et al. 2010). We begin, in
Figure 4, by displaying distributions of age-specific counts of migration from Poland to
Germany and the United Kingdom in 2002 and 2008, taken from the IMEM Project
(Raymer et al. 2013; Wiśniowski et al. forthcoming).
---FIGURE 4 ABOUT HERE---
The reason that duration expectancy increased in both Germany and the United
Kingdom between 2002 and 2008 (see Figure 3 and Table 1) is due to the fact that,
excluding the very old ages, the intensity of migration increased at each age between 2002
and 2008.10 Another important feature of the migration counts displayed in Figure 4 is the
fact that we are working with distributions (versus point estimates) of country-to-country
flows at each age in each year, which capture inherent uncertainty in the migration inputs
used in the multiregional models.11 As we discussed earlier, the inputs for the multiregional
models combine random draws of age-specific country-to-country migration counts with
10 This is also reflected in the age-specific transition probabilities (not shown).
11 As a quality check, we increased the number of random draws to 1,000 to ensure that our
100 random draws of age-specific country-to-country migration counts for each year
capture the range of the full posterior distributions. The resulting distributions are virtually
identical.
20
corresponding population-level denominator data. In assembling this information, running
through the multiregional model, and subsequently repeating this process 100 times, we
thereby generate a corresponding distribution (versus point estimate) of duration
expectancy. These distributions are shown in Figure 5 for persons from Poland in Germany
and the United Kingdom for 2002 and 2008.
---FIGURE 5 ABOUT HERE---
In Figure 5, relative to in 2002, greater uncertainty in the IMEM estimates of age-
specific country-to-country migration is reflected in a wider distribution of duration
expectancy in 2008. For example, whereas based on prevailing age patterns of country-to-
country migration and morality in 2002, our estimates of duration expectancy among
persons from Poland in the United Kingdom ranged from 0.36 years to 1.42 years, the
range was 7.60 years in 2008. Combining our mean estimates in Figure 5 with mean
estimates for each of the intervening five years between 2002 and 2008, we plot these
estimates in Figure 6. Mean estimates (across each of the 100 runs, discussed earlier) are
displayed with 95 percent confidence intervals. Minimum and maximum values are also
displayed to show the range of our estimates.
---FIGURE 6 ABOUT HERE---
Judged by the 95 percent confidence intervals, although our estimates are fairly
precise, they are less precise over time, reflecting greater uncertainty in the IMEM
migration counts at each age across years. This is especially the case for our estimates of
duration expectancy in the United Kingdom among persons from Poland, which, as shown
earlier in Figure 4, reflect greater uncertainty in migration counts at virtually all ages,
21
especially peak working ages.12 In this way, and in contrast to previous research (DeWaard
2013; DeWaard and Raymer 2012), not only do our estimates of duration expectancy
reflect age patterns of country-to-country migration and mortality, but also inherent
uncertainty, as quantified in the IMEM estimates.
We conclude by providing estimates of duration expectancy in the EU-15 among
persons from all new-accession countries, versus from each new-accession country
individually. These estimates, shown in Figure 7, are subdivided into two groups of new-
accession countries, those that accessed to the EU in 2004 and those that did so in 2007.
Methodologically, generating these estimates requires a slight modification to the
multiregional model described earlier. Because we simultaneously consider multiple birth
cohorts, one from each new accession country, in a single model, the size of each birth
cohort, l0i , must be proportional to the observed distribution of the population at age zero
across new-accession countries in each period.13 The estimates in Figure 7 are consistent
12 We constructed similar figures to those shown in Figure 6 for each pair of new-accession
and EU-15 countries. Generally, the degree of uncertainty in our estimates of duration
expectancy is relatively more pronounced for country-pairs wherein the destination country
is the United Kingdom, which, ultimately, reflects greater uncertainty in counts of age-
specific migration to the United Kingdom in the IMEM estimates.
13 Recall from our earlier discussion that when the model is run for a single birth cohort
(i.e., a birth cohort in a single new-accession country), the size of the birth cohort is
arbitrary. However, when multiple birth cohorts are simultaneously considered in the same
model, it is necessary to adjust model inputs so that the size of each birth cohort is
proportional to the observed distribution across countries.
22
with the estimates presented in previous figures and tables; however, they provide a
glimpse of duration expectancy beyond specific pairs of new-accession and EU-15
countries. In this way, we provide a closing portrait of duration expectancy in the EU-15 as
a whole among persons from new-accession countries as a whole.
---FIGURE 7 ABOUT HERE---
Based on prevailing age patterns of country-to-country migration and mortality in
2002, persons from new-accession countries could be expected to live an average of 8.67
years in the EU-15. The same figure, based on age patterns of migration and mortality in
2008, was 16.56 years. Given that ten countries accessed to the EU in 2004 and two
countries in 2007, these estimates are more heavily weighted toward the former group of
countries. Among persons living in countries that accessed to the EU in 2004, an additional
7.53 years could be expected to be lived in the EU-15 between 2002 and 2008, with the
largest increase, +4.81 years, coming between 2003 and 2004. Similarly, among persons
living in countries that accessed to the EU in 2007, an additional 8.81 years could be
expected to be lived in the EU-15 between 2002 and 2008, with the largest increase, +7.72
years, coming between 2006 and 2007.
As we show in Table 2, the majority of this time could be expected to be accrued in
Germany (4.20 years), the United Kingdom (3.08 years), and Italy (2.76 years) for persons
from new-accession countries as a whole. Among persons living in countries that accessed
to the EU in 2004, France is likewise a key destination, as are Italy and Spain for persons
living in countries that accessed to the EU in 2007.
---TABLE 2 ABOUT HERE---
23
7. Discussion
In this paper, motivated by the issue of “uncertainty about the duration of stay”
among persons from new-accession countries in EU-15 countries after EU enlargements in
2004 and 2007 (Sumption and Somerville 2010:17; see also Organisation for Economic
Cooperation and Development 2008; Van Tubergen 2004; Zaiceva and Zimmermann
2012), we began by drawing a distinction between the duration of current and completed
residence. The latter captures the circular or repeated nature of migration over the life
course, but remains problematic given the recency of the EU enlargements, the age
structure of persons from new-accession countries, and the potential for future selection
into migration to the EU-15. Using a new set of harmonised Bayesian estimates of country-
to-country migration flows and multiregional life tables, we therefore provided a
descriptive portrait of duration expectancy in EU-15 countries among persons from new-
accession countries each year from 2002 to 2008.
Our efforts are not without their limitations. First, like any period measure, our
estimates describe the experiences of synthetic cohorts and their implied hypothetical
stationary populations. A well-known assumption of multiregional models of the sort used
in this paper is the underlying Markov assumption, which dictates that migration and
mortality transitions at each age are governed solely by the prevailing set of age-specific
transition probabilities in our data. While this assumption is not inherently problematic, it is
limiting because the age-specific probabilities of migration and mortality are not allowed to
change over time (i.e., periods). As such, our estimates of duration expectancy describe
what would happen to a birth cohort, and ultimately in a population, exposed to a set of
period migration and mortality schedules that persisted (i.e., did not change) over time.
24
Second, with respect to return migration (i.e., those from new-accession country i, who
after some amount of time in EU-15 country j, return to i), prior research shows that the
risk of migration is much higher among persons returning to their place of birth (Rogers
1995). Country of citizenship is also an important source of heterogeneity (DeWaard and
Raymer 2012). Unfortunately, the IMEM data only capture migration by previous or next
country of residence, and were not developed (separately or cross-classified) by country of
birth or citizenship. Third, the multiregional model used in this paper assumes that, upon
arrival in a new country, migrants are instantaneously subject to the prevailing age-specific
mortality schedule therein. Future research might consider loosening this restriction by, for
example, allowing for a gradual transition from one set of age-specific mortality rates to
another. Finally, the IMEM estimates, and consequently our estimates, stop in 2008 during
the global economic recession. Given that our estimates reflect period migration and
mortality trends, it is conceivable that they would change, perhaps even substantially, in the
years after 2008.
These limitations aside, our efforts provide a new vantage point for thinking about
duration expectancy in EU-15 countries. Our efforts can be improved as new data come
online for translating information on country-to-country migration flows into temporal
metrics, and can be used to inform research on duration of residence in the EU-15 and
elsewhere. They can likewise be extended. For example, recalling Rogers’ (1975, 1995)
pioneering work on internal migration within the United States, Kupiszewska and
Kupiszewski (2005) detail a multiregional model that simultaneously includes international
and internal migration, in addition to mortality. With sufficient data, estimates of duration
expectancy could be derived for places within EU-15 countries, as well as for other
25
countries and places therein outside of Europe. With respect to policy and related
implications, following previous work by DeWaard (2013, 2015), estimates of duration
expectancy can potentially be used to assess countries’ long-term residence policies, e.g., as
scored in the Migrant Integration Policy Index (Geddes et al. 2005; Huddleston et al. 2011;
Niessen et al. 2007), and as predictors in explanatory models of anti-immigrant sentiment
and other outcomes.
Just as life expectancy is an indicator of human development, our hope is that
duration expectancy will gradually be incorporated into the toolbox of summary measures
—primarily, migration rates (in, out, and net) and foreign-born population stocks, e.g.,
percent foreign born—typically used to describe aggregate migration patterns. Not only do
our estimates of duration expectancy capture the relational character of country-to-country
migration flow data, they also provide a parsimonious way to summarize age patterns of
country-to-country migration in a single estimate with uncertainty.
26
Disclosure of Potential Conflicts of Interest
Conflict of Interest: The authors declare that they have no conflict of interest.
27
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Figure 1. Total and In-Country Life Expectancy: New-Accession Countries, 2002-2008
35
Figure 2. Out-of-Country Life Expectancy and Duration Expectancy in the EU-15: New-Accession Countries, 2002-2008
36
Figure 3. Duration Expectancy in EU-15 Countries: New-Accession Countries, 2002 and 2008
37
Figure 4. Migration Counts by Age Group: Poland to Germany and the United Kingdom, 2002 and 2008
38
Figure 5. Distributions of Duration Expectancy in Germany and the United Kingdom: Poland, 2002 and 2008
39
Figure 6. Duration Expectancy in Germany and the United Kingdom: Poland, 2002-2008
Figure 7. Duration Expectancy in the EU-15: All New-Accession Countries by Accession
Date to the EU, 2002-2008
Table 1. Duration Expectancy in Top 3 EU-15 Countries: New-Accession Countries, 2002
and 2008.
Cyprus2008 7.22 (0.21) 5.44 (0.21) 0.91 (0.01)2002 3.89 (0.12) 2.39 (0.09) 0.48 (<0.01)
Czech Republic2008 1.77 (0.02) 1.70 (0.05) 0.66 (0.02)2002 1.31 (0.02) 0.23 (0.01) 0.28 (<0.01)
Estonia2008 7.57 (0.12) 2.36 (0.07) 1.38 (0.02)2002 3.46 (0.05) 0.97 (0.01) 0.78 (0.01)
Hungary2008 4.23 (0.07) 2.34 (0.08) 1.20 (0.11)2002 2.77 (0.04) 0.35 (0.01) 0.52 (0.05)
Latvia2008 1.94 (0.03) 1.61 (0.05) 1.22 (0.05)2002 1.44 (0.02) 0.24 (<0.01) 0.14 (<0.01)
Lithuania2008 3.84 (0.11) 2.76 (0.1) 2.37 (0.03)2002 0.53 (0.02) 0.36 (0.01) 1.84 (0.03)
Malta2008 11.40 (0.4) 2.28 (0.18) 1.75 (0.05)2002 5.26 (0.19) 0.92 (0.07) 0.77 (0.02)
Poland2008 6.14 (0.09) 5.46 (0.16) 1.27 (0.03)2002 4.65 (0.06) 0.76 (0.02) 0.57 (0.01)
Slovakia2008 3.25 (0.04) 2.40 (0.07) 1.56 (0.03)2002 2.74 (0.04) 0.31 (0.01) 0.93 (0.02)
Slovenia2008 1.69 (0.02) 1.10 (0.03) 0.88 (0.01)2002 1.42 (0.02) 0.49 (0.01) 0.48 (<0.01)
Bulgaria2008 5.04 (0.08) 4.61 (0.07) 3.43 (0.19)2002 4.06 (0.06) 2.72 (0.04) 1.73 (0.01)
Romania2008 8.62 (0.23) 7.38 (0.13) 3.25 (0.04)2002 5.31 (0.13) 5.00 (0.08) 1.92 (0.03)
Germany
Germany
Finland
Germany
United Kingdom
New-Accession Origin
Spain
United Kingdom
Germany
Germany
Germany
Spain
Italy
France
United Kingdom
Italy
United Kingdom
Germany
United Kingdom
United Kingdom
United Kingdom
Ireland
United Kingdom
France
Germany
Greece
Austria
Austria
Italy
Italy
Ireland
Germany
France
Sweden
United Kingdom Germany
EU-15 Destination by Rank1 2 3
Greece
Note: Standard errors in parentheses
Table 2. Duration Expectancy in Top 3 EU-15 Countries: All New-Accession Countries by
Accession Date to the EU, 2002 and 2008
All New-Accession Countries United Kingdom2008 4.20 (0.04) 3.08 (0.06) 2.76 (0.05)2002 3.06 (0.03) 0.59 (0.01) 1.61 (0.03)
2004 Accession Countries United Kingdom2008 4.41 (0.05) 3.90 (0.09) 0.97 (0.02)2002 3.40 (0.04) 0.62 (0.01) 0.41 (0.01)
2007 Accession Countries2008 7.35 (0.18) 7.01 (0.11) 3.66 (0.04)2002 4.60 (0.11) 4.97 (0.07) 2.18 (0.02)
EU-15 Destination by Rank3
France
Germany
New-Accession Origin GroupItaly
1
Italy
Germany
Germany
Spain
2
Note: Standard errors in parentheses
top related