Towards a ‘baby recession’ in Europe? : differential fertility trends during the economic crisis.
Date: 2013-05-07
Institutions: Eurostat
Subjects: EU Member State, EU statistics, economic recession, fertility, population statistics, social impact

Population and social conditions 

Author:  Giampaolo LANZIERI 

S t a t i s t i c s   i n   f o c u s  
13/2013 

Towards a ‘baby recession’ in Europe? 
Differential fertility trends during the economic crisis 

The relationship between the economy and 
population dynamics has long been discussed, 
but is still controversial. Fertility is commonly 
assumed to follow the economic cycle, falling in 
periods of recession and vice-versa, though 
scientific evidence is still not unanimous on this. 
This report looks at fertility trends in 31 
European countries against selected indicators 
of economic recession. Fertility rates are also 
computed for women differentiated by parity, 
employment status, educational attainment and 
migrant status, highlighting the impact that the 
economic crisis may have on specific population 
groups.  

In 2008, several European countries entered a 
period of economic crisis, usually featuring a fall in 

gross domestic product (GDP). From the start of 
the recession, the total fertility rate (TFR, see 
methodological notes) started to decline across 
Europe. 

Figure 1 shows that in 31 European countries, the 
economic crisis spread in 2009, while decreases in 
fertility became a common feature in Europe with a 
time lag. The peak of the crisis (in terms of 
geographic reach) in 2009 was accompanied by 
stagnation of the TFR in several countries, 
followed by a distinct fall. In 2008, there were no 
falls in the rate compared to the previous year, but 
by 2011, the TFR had declined in 24 countries. 
With some exceptions, these trends in fertility rates 
mirrored the changes that occurred in the number 
of live births. 

Figure 1: Number of countries by year-on-year change of GDP and TFR 

35

30

25

20

15

10

5

0

GDP

GDP

GDP

GDP

TFR

TFR

TFR

TFR

2007 - 2008

2008 - 2009

2009 - 2010

2010 - 2011

2007 - 2008

2008 - 2009

2009 - 2010

2010 - 2011

Negative change

No change

Positive change

Notes: changes in GDP lower in absolute value than 0.1% and changes in TFR lower in absolute value than 0.01 live births per 
women are classified as 'No change'. GDP in millions of euro, chain-linked volumes, reference year 2000 (at 2000 exchange rates). 

Source: computation of the author on Eurostat data (online data codes: nama_gdp_k, demo_find). 

 
 
 
 
 
 
 
 
 
Fewer births were due more to fewer would-be mothers than to lower fertility 

From the beginning of the crisis, the total number 
of live births in Europe reversed the previous 
upward trend (see Figure 2). Between 2008 and 
2011, the total number of live births fell by 3.5 %, 
from 5.6 to 5.4 million, and the number of 
countries which recorded a fall compared to the 
previous year grew from 1 to 26 out of 31. 

Figure 2: Number of live births in Europe 

s
n
o

i
l
l
i

M

5.7

5.6

5.5

5.4

5.3

5.2

5.1

5.0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Source: computation of the author on Eurostat data (online data 
code: demo_gind). 

The number of live births can be broken down into 
the product of the age-specific fertility rates by the 
respective number of women of childbearing age 
(WCA) — the ‘would-be mothers’. The overall 
size of this population group has been slowly 
decreasing over recent years and, by 2011, it was 
shrinking in about two-thirds of European countries 
(post-census revisions of the population size in 
various countries may affect the current estimates 
— see methodological notes). 

Although the year-on-year change in relative terms 
of the total number of women of childbearing age 
is much lower than the corresponding relative 
changes of the TFR (which is the sum of the age-
specific fertility rates), its impact can be more 
significant. Table 1 reports the total number of live 
births, which would have occurred under different 
hypotheses. 

Table 1: Simulated number of live births in 2009-2011 
according to various scenarios 

TFR and WCA as 
in 2008

TFR as in 2008 
and actual WCA 

Actual TFR and 
actual WCA

Number of live births in 
Europe (in million)

Relative difference from 
benchmark 2008

16.844

16.655

16.539

---

-1.1%

-1.8%

Source: computation of the author on Eurostat data (online data 
codes: demo_find, demo_pjan). 

Considering that 2008 was the peak year in the 
number of live births, taking this year as a 
benchmark and keeping constant its conditions 
(summarised by the WCA and TFR) over the next 
three years gives the hypothetical number of live 
births which would have occurred during 2009-
2011 if no change had taken place in both the 
number of would-be mothers and in age-specific 
fertility rates. Allowing only the WCA to decrease 
as actually occurred gives the number of live births 
resulting from a shrinking number of women of 
childbearing age who keep their fertility behaviour 
constant (i.e., the TFR). This hypothetical scenario 
enables us to roughly estimate the impact of 
changes in the WCA, all other things being equal. 
Finally, allowing both WCA and TFR to change 
leads to what was actually recorded over the period 
2009-2011. 

Table 1 shows that the change in WCA alone is 
responsible for about 62 % of the decrease in the 
number of live births. If fertility had not decreased 
since 2008, about 189 000 live births would have 
been ‘lost’ anyway, due to fewer would-be 
mothers. The decline of the TFR that occurred after 
2008 has in fact amplified this effect. This 
downturn is of most interest because, unlike the 
changes in WCA, largely determined by past 
fertility conditions and thus mainly driven by 
inertia, changes in TFR are supposedly more 
reactive to current factors. 

Fertility rates returned to ‘lowest-low‘ levels in some Eastern European countries 

There has been a general recovery of fertility over 
the past decade (see Table 2), though with some 
exceptions (such as Luxembourg and Portugal). 
The average across countries has risen by about 
0.15 live births per woman between 2002 and 
2008-09. Such an increase in fertility rates is 
usually explained by scholars as due to 
recuperation after the postponement of 
childbearing. Therefore, it would not be an 

effective increase of the quantum of fertility, but 
simply a tempo effect. In other words, taking a 
longitudinal perspective, by the end of their 
childbearing years, successive cohorts of women 
would have accomplished about the same level of 
completed fertility. Decreases recorded by a period 
indicator such the TFR would be due mainly to 
temporary postponements of childbearing.  

2 

13/2013 — Statistics in focus  

 
 
 
 
 
In 2008, no country had a TFR below 1.3, 
considered by some scholars as marking a level of 
‘lowest-low’ fertility. This recuperation process 
seems to have stopped around 2009 and, by 2011, 
the TFR in a few countries (Hungary, Poland and 
Romania) had perhaps unexpectedly fallen again, 
below the 1.3 live births per woman. 

Figure 3 shows the geographic pattern of the TFR 
over time. At the start of the previous decade, the 
average TFR was at its lowest over the 12 years 
considered. In several countries in Northern and 
Western Europe, its level was above 1.7, while in 
Eastern and Southern Europe, low fertility was 
widespread. The next three years see a clear divide 

between Northern and Western Europe, with a 
relatively high level of fertility, Eastern Europe, 
with ‘lowest-low’ fertility, and Central and 
Southern Europe, with slightly higher fertility, but 
still below 1.5 live births per woman. Between 
2006 and 2008, fertility in Eastern Europe 
continued to recover, leaving behind only Slovakia: 
in this period, fertility in Europe is essentially 
divided by a diagonal running from North-East to 
South-West. Finally, during the last three years, the 
average TFR grew further in some countries, but 
fell back in others, blurring the geographical 
pattern of low fertility in Eastern Europe. 

Figure 3: Average total fertility rate by 3-year periods, 2000-2011 

Note: for LV and HR the average 2000-2002 is based only on the 2002 year. 
Source: computation of the author on Eurostat data (online data code: demo_find). 

  Statistics in focus — 13/2013 

3 

 
 
 
4

1
3
/
2
0
1
3
—
S
t
a
t
i
s
t
i
c
s

i

n

f

o
c
u
s

Table 2: Total fertility rate in European countries, 2000-2011 

BE
BG
CZ
DK
DE
EE
IE
EL
ES
FR
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
RO
SI
SK
FI
SE
UK
IS
NO
CH
HR
Average

2000
1.67
1.26
1.14
1.77
1.38
1.38
1.89
1.26
1.23
1.89
1.26
1.64
:
1.39
1.76
1.32
1.70
1.72
1.36
1.37
1.55
1.31
1.26
1.30
1.73
1.54
1.64
2.08
1.85
1.50
:
1.52

2001
1.67
1.21
1.14
1.74
1.35
1.34
1.94
1.25
1.24
1.90
1.25
1.57
:
1.30
1.66
1.31
1.48
1.71
1.33
1.31
1.45
1.27
1.21
1.20
1.73
1.57
1.63
1.95
1.78
1.38
:
1.48

2002
1.65
1.21
1.17
1.72
1.34
1.37
1.97
1.27
1.26
1.88
1.27
1.49
1.23
1.24
1.63
1.30
1.45
1.73
1.39
1.25
1.47
1.25
1.21
1.19
1.72
1.65
1.64
1.93
1.75
1.39
1.34
1.46

2003
1.66
1.23
1.18
1.76
1.34
1.37
1.96
1.28
1.31
1.89
1.29
1.50
1.29
1.26
1.62
1.27
1.48
1.75
1.38
1.22
1.44
1.27
1.20
1.20
1.76
1.71
1.71
1.99
1.80
1.39
1.32
1.48

2004
1.72
1.29
1.23
1.78
1.36
1.47
1.93
1.30
1.32
1.92
1.33
1.49
1.24
1.26
1.66
1.28
1.40
1.72
1.42
1.23
1.40
1.29
1.25
1.24
1.80
1.75
1.77
2.04
1.83
1.42
1.34
1.50

2005
1.76
1.32
1.28
1.80
1.34
1.50
1.86
1.33
1.34
1.94
1.32
1.42
1.31
1.27
1.63
1.31
1.38
1.71
1.41
1.24
1.40
1.32
1.26
1.25
1.80
1.77
1.78
2.05
1.84
1.42
1.41
1.51

2006
1.80
1.38
1.33
1.85
1.33
1.55
1.92
1.40
1.37
2.00
1.35
1.45
1.35
1.31
1.65
1.34
1.39
1.72
1.41
1.27
1.36
1.32
1.31
1.24
1.84
1.85
1.84
2.08
1.90
1.44
1.38
1.54

2007
1.82
1.42
1.44
1.84
1.37
1.63
2.01
1.41
1.39
1.98
1.37
1.39
1.41
1.35
1.61
1.32
1.37
1.72
1.38
1.31
1.33
1.30
1.38
1.25
1.83
1.88
1.90
2.09
1.90
1.46
1.40
1.56

2008
1.85
1.48
1.50
1.89
1.38
1.65
2.10
1.51
1.46
2.01
1.42
1.46
1.44
1.47
1.61
1.35
1.44
1.77
1.41
1.39
1.37
1.35
1.53
1.32
1.85
1.91
1.96
2.15
1.96
1.48
1.46
1.61

2009
1.84
1.57
1.49
1.84
1.36
1.62
2.10
1.52
1.39
2.00
1.41
1.51
1.31
1.55
1.59
1.32
1.43
1.79
1.39
1.40
1.32
1.38
1.53
1.41
1.86
1.94
1.94
2.23
1.98
1.50
1.49
1.61

2010
1.86
1.49
1.49
1.87
1.39
1.63
2.07
1.51
1.38
2.03
1.41
1.44
1.17
1.55
1.63
1.25
1.38
1.79
1.44
1.38
1.36
1.33
1.57
1.40
1.87
1.98
1.98
2.20
1.95
1.52
1.46
1.61

2011
1.81
1.51
1.43
1.75
1.36
1.52
2.05
1.42
1.36
2.01
1.40
1.35
1.34
1.76
1.52
1.23
1.49
1.76
1.42
1.30
1.35
1.25
1.56
1.45
1.83
1.90
1.96
2.02
1.88
1.52
1.40
1.58

Notes:’:’ =not available; average for 2000 and 2001 without LV and HR, thus likely overestimated. In bold, maximum value across years for the specific country. 

Source: Eurostat (online data code: demo_find). 

 
 
 
 
 
 
 
 
 
 
 
Changes in fertility partially follow changes in the economy, with an average lag 
of less than two years  

It may be difficult to disentangle what could be a 
‘natural’ decrease in the number of live births, due 
to the shrinking number of women of childbearing 
age and/or to the continuing decline in their fertility 
rates, from the impact of an occasional shock, such 
as an economic crisis. A recession can influence 
fertility in various ways, although its effect may be 
softened by government interventions. Apart from 
the direct impact of the crisis at individual level, 
the economic uncertainty that can spread in periods 
of hardship may influence fertility. From this point 
of view, the duration of a crisis may play an 
important role and, in some countries, the duration 
and the depth of the current recession are 
unprecedented. 

Table 3 reports the correlations between the time 
series of the changes in the TFR and in selected 
indicators of economic crisis for each European 
country. In fact, the interest here is in looking at the 
potential link between changes in economic 
conditions and changes in fertility behaviour. These 
correlations have been computed taking into 
account a lag in the TFR from 0 to 3 years: hence, 
four correlations were computed for each country 
and indicator. Table 3 only shows the highest 
values of the correlations (with the expected sign), 
together with the lag at which they were found. To 
focus on the effect of the economic crisis, the 
correlations were computed using annual data from 
2000 to 2011, which makes the number of available 
cases rather limited, especially for correlations 
between time series shifted by 3 years. Results also 
depend on the quality of the demographic data, 
which may be affected by various issues (see 
methodological notes).  

The usual indicator of economic growth is based on 
the GDP. The expected relationship is that negative 
changes in GDP correspond to negative changes in 
the TFR, possibly with some delay, thus showing a 
high positive correlation at particular lags. The 
correlation with the TFR is relevant in Spain and 
Latvia without any lag; in Bulgaria, Poland and 
Romania with one year of lag; and in the Czech 
Republic, Denmark, Estonia, Greece, the 
Netherlands, Finland, Sweden, Iceland, Norway 
and Croatia with two years of lag. Taking the 
overall average across countries, a change in GDP 
is mostly positively correlated with a change in the 
TFR within about 19 months. 

It must be noted that in some countries, there may 
also be negative correlations at some lags, thus 
supporting the hypothesis of TFR changes counter-

cyclical to the economic trends, but usually their 
intensity is lower than the positive correlations at 
different lags. Exceptions in this regard are Latvia, 
Lithuania, Malta, Austria and Romania. For Malta, 
Austria and Romania, these negative correlations 
do not seem to be relevant once the number of 
available cases is taken into account, whereas they 
are noticeable for Lithuania at lag 2 and for Latvia 
at lag 3. In these two countries, the evidence would 
suggest changes in TFR negatively correlated with 
changes in GDP. 

Another indicator selected for this study is Actual 
Individual Consumption (AIC), which is 
considered to provide a better measure of the 
material welfare condition of households, because 
it refers to goods and services actually consumed 
by individuals, irrespective of whether these goods 
and services are purchased and paid for by 
households, by government, or by non-profit 
organisations. By looking at the correlation of the 
changes in AIC with changes in TFR, the intention 
is to analyse the impact of the changing material 
situation of households, rather than the country’s 
living standards (as measured by the GDP), on 
fertility behaviour. Likewise for GDP, the expected 
relationship between changes in AIC and TFR is 
positive. 

Most relevant positive correlations between AIC 
and lagged TFR are found for Belgium, Denmark, 
Malta and Poland at lag zero; for Bulgaria, Greece, 
Latvia and Romania with a lag of one year; for 
Estonia, the Netherlands and Norway with a lag of 
two years; and for Hungary, Sweden, the United 
Kingdom and Switzerland with a lag of three years. 
The average lag (without Spain and Iceland) for a 
change in TFR is thus again of about 19 months. 
However, in Germany, Cyprus, Luxembourg and 
Austria, there is a negative correlation higher in 
absolute values than the positive one, but still at 
negligible levels, whereas in Latvia and Lithuania, 
this negative correlation is rather noticeable. 

The next indicator is the annual unemployment rate 
for the age group 15-49 (UNE). The expected 
relationship here is with negative sign, meaning 
that a positive change of the UNE should be 
correlated with a negative change of the (lagged) 
TFR. This is particularly the case for Greece and 
Latvia without lag; for Poland with one year of lag; 
for Denmark, Estonia, Cyprus, the Netherlands and 
Iceland with two years of lag; and for the United 
Kingdom with three years of lag. The country 
where there is a positive correlation higher than the 

  Statistics in focus — 13/2013 

5 

 
 
negative are Belgium, the Czech Republic, France, 
Lithuania, Portugal and Slovenia, but none 
relevant. On average, changes in the 
unemployment rate would then be negatively 
correlated with changes in TFR lagged by about 
19 months, as in the case of GDP and AIC. 

The last indicator used for Table 3 is the annual 
average of the consumers’ confidence index (CCI), 
meant to measure the sentiment of economic 
uncertainty. As for GDP and AIC, the correlation 
between changes in the CCI and lagged changes in 
the TFR is expected to be positive. The values are 
particularly relevant only for Latvia and Romania, 
with one year of lag, and for Poland with two years 
of lag. However, several countries have negative 

correlations higher in absolute value than the 
highest positive: Belgium, Austria, Slovakia, 
Finland, Sweden, and particularly Spain, Lithuania 
and Luxembourg. Privileging the pro-cyclical 
relationship between CCI and TFR, on average, a 
change in consumers’ confidence would be 
correlated with a change in the TFR, delayed by 
about 22 months. 

In general, the correlations of economic indicators 
with the lagged TFR have the expected sign in 
most countries, though not particularly significant. 
However, in a few cases, it cannot be excluded that 
the economic crisis may actually open a ‘window 
of opportunity’ for childbearing, especially for 
specific population groups. 

Table 3: Highest correlations and corresponding lags of the TFR with various indicators of economic 
recession by country, 2000-2011 

GDP
highest
positive
correlation
0.613
0.913
0.776
0.734
0.422
0.707
0.421
0.902
0.618
0.435
0.659
0.624
0.729
0.156
0.578
0.620
0.592
0.832
0.204
0.657
0.290
0.687
0.474
0.528
0.737
0.753
0.670
0.786
0.894
0.529
0.693
0.620

GDP
corresponding
correlation
lag (in years)
2
1
2
2
0
2
1
2
0
2
2
2
0
1
3
1
1
2
0
1
3
1
2
1
2
2
3
2
2
2
2
1.6

AIC
highest
positive
correlation
0.794
0.788
0.563
0.626
0.100
0.678
0.601
0.820
:
0.539
0.651
0.617
0.684
0.147
0.411
0.835
0.839
0.887
0.180
0.858
0.582
0.639
0.574
0.331
0.648
0.756
0.721
:
0.814
0.973
0.573
0.629

AIC
corresponding
correlation
lag (in years)
0
1
1
0
2
2
1
1
:
3
3
1
1
0
2
3
0
2
0
0
3
1
1
3
2
3
3
:
2
3
2
1.6

UNE
highest
negative
correlation
-0.055
-0.561
-0.438
-0.790
-0.245
-0.823
-0.384
-0.745
-0.542
-0.170
-0.584
-0.737
-0.679
none
-0.638
-0.418
-0.487
-0.731
-0.418
-0.892
-0.134
-0.460
-0.396
-0.286
-0.390
-0.524
-0.778
-0.866
-0.454
-0.432
-0.710
-0.526

UNE
corresponding
correlation
lag (in years)
2
0
0
2
0
2
1
0
1
3
2
2
0
none
3
1
0
2
3
1
2
1
1
3
2
2
3
2
2
2
2
1.6

CCI
highest
positive
correlation
0.219
0.570
0.444
0.541
0.512
0.531
0.705
0.467
0.317
0.240
0.458
0.481
0.912
0.290
0.526
0.363
0.581
0.573
0.243
0.882
0.429
0.711
0.396
0.072
0.234
0.434
0.610
:
:
:
:
0.472

CCI
corresponding
correlation
lag (in years)
0
1
2
3
0
3
3
1
1
2
3
1
1
1
3
3
1
3
0
2
1
1
2
2
3
3
3
:
:
:
:
1.8

BE
BG
CZ
DK
DE
EE
IE
EL
ES
FR
IT
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
RO
SI
SK
FI
SE
UK
IS
NO
CH
HR
Average

Notes: ‘:‘ = data not available; none = no correlation of the selected sign. TFR = year-on-year change of the total fertility rate; GDP = 
year-on-year change of the gross domestic product at market prices in euros per capita, chain-linked volumes, reference year 2000 
(at 2000 exchange rates); AIC = year-on-year change of the actual individual consumption in euros per capita, chain-linked volumes, 
reference year 2000 (at 2000 exchange rates); UNE = year-on-year change of the unemployment rates from 15 to 49 years; CCI = 
year-on-year change of the consumer confidence indicator, annual average. Annual TFR data not available for LV (2000, 2001) and 
HR (2000, 2001); annual AIC data not available for FI, CH (2011) and HR (2010, 2011); annual UNE data not available for HR (2000, 
2001); annual CCI data not available for BG (2000), CY (2000), LT (2000), LU (2000, 2001), MT (2000, 2001), PL (2000) and RO 
(2000). 

Source: computation of the author on Eurostat data (online data codes: demo_find, demo_gind, nama_gdp_k, nama_fcs_k, 
lfsa_urgan) and on data from the Business and Consumer Surveys of the Directorate General for Economic and Financial Affairs of 
the European Commission (http://ec.europa.eu/economy_finance/db_indicators/surveys/index_en.htm). 

6 

13/2013— Statistics in focus  

 
 
 
 
 
Slight tendency to wider decreases in first births than in subsequent births 

An economic crisis may prompt would-be parents 
to postpone childbearing, especially if they are 
childless. Table 4 shows the quota of the TFR 
attributable to live births from (previously) 
childless women (TFR 1) and that for women who 
already had at least one child (TFR 2+). Due to 
data unavailability, these indicators could not be 
computed making reference to the population 
composition by parity (the number of live births a 
woman had in the past). Thus the female 
population ‘exposed’ to childbearing is the total 
number of women of childbearing age, regardless 
of any previous live birth they may have delivered. 
By multiplying the percentages in Table 4 with the 
corresponding TFR value in Table 2, the values of 
TFR 1 and TFR 2+ (not shown here) can be 
obtained. 

In general, the decrease from the respective peak 
value over 2007-2011 was slightly more relevant 
for the first-order TFR. However, on the whole, the 
two rates mostly moved together, so by 2011, the 
difference between them did not increase much. A 

particular case is Greece, where the TFR of order 
two and higher has plummeted over recent years, 
falling below the TFR of first order, which rose 
slightly.  

In proportion to the overall TFR, in Bulgaria, 
Estonia, Spain, Latvia and Lithuania, the decrease 
in the TFR 1 from the peak value over the four 
years to 2011 is higher than 3 percentage points 
(p.p.), and in Ireland and in the Nordic countries 
the decrease is between 1 and 3 p.p.  

A few countries saw the proportion of TFR 
attributable to childless women rise, as in Greece 
and Slovakia. On average across all countries, there 
was a slight reduction over time of the proportion 
of TFR attributable to first-order live births. This 
means that the changes in TFR 1 were either 
somewhat less positive or more negative than those 
of TFR 2, or even trended in the opposite 
(negative) direction.  

Table 4: Percentage of TFR attributable to live births of first order (TFR 1) and to live births of order two and 
over (TFR 2+), 2007-2011 

BE
BG
CZ
DE
EE
IE
EL
ES
CY
LV
LT
LU
HU
MT
NL
AT
PL
PT
RO
SI
SK
FI
SE
UK
IS
NO
CH
HR
Average

2007
46.1
57.8
48.3
:
46.5
41.8
48.4
58.6
45.2
50.9
51.6
51.7
47.0
50.8
46.5
47.3
49.5
54.9
52.8
49.1
47.1
41.9
45.5
43.4
39.8
43.5
50.4
47.4
48.6

2008
45.6
57.9
49.1
:
46.4
41.9
48.6
54.7
45.2
50.1
51.0
50.7
47.4
51.9
46.2
47.7
49.9
54.9
54.0
50.1
48.7
41.7
45.7
42.4
39.3
44.6
49.8
47.7
48.7

TFR 1
2009
48.3
55.4
49.1
50.3
44.9
42.8
48.3
55.0
45.7
48.4
49.5
51.7
47.8
52.9
46.9
47.8
50.4
55.5
54.0
49.9
48.4
41.9
45.5
43.0
39.2
44.2
49.8
47.8
48.5

2010
:
54.4
48.3
49.9
41.6
42.4
49.6
54.2
46.6
47.5
47.1
52.8
48.6
51.5
46.8
47.9
50.0
54.7
53.6
50.1
49.4
41.8
44.6
41.8
38.3
44.2
50.1
47.6
48.2

2011
:
53.7
49.0
50.0
40.0
40.4
51.8
54.2
46.7
47.0
47.5
52.9
47.9
52.4
46.7
48.4
49.5
55.3
53.3
49.7
50.6
40.9
43.9
:
37.5
43.0
49.7
:
48.0

2007
53.9
42.2
51.7
:
53.5
58.2
51.6
41.4
54.8
49.1
48.4
48.3
53.0
49.2
53.5
52.7
50.5
45.1
47.2
50.9
52.9
58.1
54.5
56.6
60.2
56.5
49.6
52.6
51.4

2008
54.4
42.1
50.9
:
53.6
58.1
51.4
45.3
54.8
49.9
49.0
49.3
52.6
48.1
53.8
52.3
50.1
45.1
46.0
49.9
51.3
58.3
54.3
57.6
60.7
55.4
50.2
52.3
51.3

TFR 2+
2009
51.7
44.6
50.9
49.7
55.1
57.2
51.7
45.0
54.3
51.6
50.5
48.3
52.2
47.1
53.1
52.2
49.6
44.5
46.0
50.1
51.6
58.1
54.5
57.0
60.8
55.8
50.2
52.2
51.5

2010
:
45.6
51.7
50.1
58.4
57.6
50.4
45.8
53.4
52.5
52.9
47.2
51.4
48.5
53.2
52.1
50.0
45.3
46.4
49.9
50.6
58.2
55.4
58.2
61.7
55.8
49.9
52.4
51.8

2011
:
46.3
51.0
50.0
60.0
59.6
48.2
45.8
53.3
53.0
52.5
47.1
52.1
47.6
53.3
51.6
50.5
44.7
46.7
50.3
49.4
59.1
56.1
:
62.5
57.0
50.3
:
52.0

Notes: ‘:‘= not available. Data for missing countries (DK, FR and IT) not available. Average computed on the 24 countries for which 
all 5 years of data are available, thus excluding BE, DE, UK and HR. Live birth order for UK refers only to births within marriage. In 
bold, maximum value across years for the specific country and live birth order. 

Source: computation of the author on Eurostat data (online data codes: demo_fordagec, demo_pjan). 

  Statistics in focus — 13/2013 

7 

 
 
 
 
Mixed fertility behaviour across countries for employed and non-employed 
women 

Because the economic crisis may have differing 
effects on the fertility behaviour of different 
categories of women, it is interesting to look at 
values for the specific fertility indicator for selected 
population breakdowns.  

Table 5 shows the specific TFR for employed and 
non-employed women, the latter comprising 
unemployed and inactive women. Across countries, 
the differential fertility according to employment 
status is not consistently positive or negative 
between 2007 and 2011. In Belgium, Germany, 
Austria, Romania, Finland and Norway, non-
employed women have higher fertility than those 
employed; the opposite applies for the other 
countries for which data are available, except for 
Greece, Luxembourg and Malta, where the group 
with higher fertility changes over time. 

Differentials in fertility by employment status can 
reach remarkable values in both directions: in 
Germany, in 2011, employed women have 1.8 live 
births fewer than non-employed women, about the 
same value as in Croatia, where the differential is 
reversed. 

The tendency of fertility in the two groups over 
recent years is not consistent across Europe. In 
some countries, the differentials have further 
increased; in other countries, specific TFR have 
been converging, sometimes even reversing the 
sign of the differential. 

For instance, in Germany, the fertility of non-
employed women has increased and that of 

employed women decreased, while in Spain, the 
opposite occurred; in Greece, the TFR of non-
employed women fell below that of employed 
women, changing from a positive differential of 
about 0.2 average live births for non-employed 
women to a similar value for employed women; in 
Norway, the two groups converged.  

It is thus difficult to detect a common pattern 
across Europe, taking into account that fertility 
behaviour in population groups defined according 
to their relationship to the labour market may be 
influenced by national policies to combine work 
and family life. 

As total TFR also depends also on the composition 
of the population (see methodological notes), an 
increase or decrease in a specific TFR does not 
necessarily impact much on the overall TFR. 

For instance, in Germany, the proportion of women 
of childbearing age classified as non-employed is 
slightly above one third. Hence, the relatively high 
fertility of this population group influences the 
overall TFR much less than that of employed 
women of childbearing age, whose fertility is even 
below one live birth per (employed) woman. In 
fact, the increase of 0.46 live births per non-
employed woman over the five years examined has 
produced little effect on the total TFR, which has 
continued to be around 1.37 live births per woman 
(see Table 2), due to the corresponding fall of 
about 0.10 live births in the TFR of employed 
women. 

Fertility of women with medium education has decreased more visibly than of 
those with low or high education 

The level of educational attainment is often 
considered to be a proxy of the socio-economic 
status of a person. To improve comparability across 
countries, the national level of educational 
attainment is converted according to an 
international standard classification of education 
(ISCED) with seven degrees from 0 to 6. The level 
zero indicates no formal education and the level 6 
corresponds to the highest achievable level of 
education (such as a PhD). 

Table 6 shows the specific TFR of women with 
different levels of educational attainment, grouped 
in ‘low’ (ISCED from level 0 to level 2), ‘medium’ 
(ISCED 3-4) and ‘high’ (ISCED 5-6). 

Apart from Nordic countries (Denmark, Finland 
and Norway), Portugal and Malta, in general, 
women with low education had a higher TFR 
between 2007 and 2011. Differentials reached a 
level as high as 2.2 live births per woman 
(Slovakia, 2009). 

Comparing 2011 to the peak year of fertility (in 
bold in Table 6), on average across countries, the 
fertility of women with a medium level of 
education dropped by about 9 %, while the 
decrease for women with high or low education 
was less significant. However, the pattern at 
national level is quite diversified, and the same 
applies within countries. Fertility may have 
different patterns in different population groups. 

8 

13/2013 — Statistics in focus  

 
 
 
Changes in the specific TFR of population 
subgroups affect the overall TFR to the extent of 
their relative weight in the population. So, in 
general, the same change would have less effect if 

it were to occur in the fertility of women with high 
education, given that their share in the total number 
of women in childbearing ages is about one fifth 
(on average across countries). 

In most countries, immigrants’ fertility decreased more than that of natives 

Citizenship and country of birth are two different 
ways of looking at migrant status. In general, a 
foreign-born person has migrated at least once in 
their lifetime, while a person with foreign 
citizenship has not necessarily done so, but has a 
foreign background. 

These characteristics may influence the 
demographic behaviour in terms of fertility, though 
in neither case is there a direct indication of the 
duration of the residence of the person in the host 
country. 

A foreign-born woman could actually have arrived 
in a country long ago, or even have grown up there, 
hence being largely influenced by the local culture. 
A woman with foreign citizenship may acquire the 
citizenship of the host country — the longer her 
residence in the host country, the higher the 
probability that she would change her citizenship, 
thus possibly leaving the group of women with 
foreign citizenship (with differences depending on 
the policies of naturalisation of the country). 

Table 7 shows the specific TFR of women who 
hold foreign citizenship or were born abroad. In all 
countries but the Czech Republic, Denmark, 
Estonia, Latvia and Iceland, these population 
groups have higher fertility than national or native-
born women. In Cyprus and Hungary, the TFR of 
foreign women falls below the level of that for 
national citizens during those three years. 

In fact, in almost all countries where the fertility of 
women with foreign citizenship decreased between 
2009 and 2011, the decline was higher than among 
women with national citizenship, either in absolute 
or in relative terms. In only two years, in Bulgaria, 
Greece, Cyprus and Hungary, the TFR decrease for 
foreigners was more than one fifth of the initial 
value; on the other hand, strong TFR increases 
were recorded in Lithuania, Malta and Slovenia, 
though for Slovenia, the evidence for foreign-born 
women trends in the opposite direction. 

As for the native women, their TFR is more stable, 
even in countries where the economic crisis has hit 
hardest, such as Italy, Cyprus, Spain and Portugal, 
while in Bulgaria, Greece and Hungary, the TFR 
decrease has been much lower than for foreigners. 
Luxembourg is a peculiar case in which the fertility 
of native women has fallen sharply. There have 
also been quite significant decreases in some 
Nordic countries, where the level of TFR of native 
women is relatively high.  

As there is no country in which a majority of the 
population is composed of immigrants, any change 
in their specific TFR is less relevant (for the overall 
fertility) than a change in the specific TFR of the 
native population. However, an increase in the 
proportion of migrants in countries where their 
specific fertility is higher than that of natives would 
increase the overall TFR, even with unchanged 
specific fertility rates. 

  Statistics in focus — 13/2013 

9 

 
 
 
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Table 5: Specific total fertility rates by employment status, 2007-2011 

BE
DK
DE
EE
EL
ES
LU
HU
MT
AT
PL
PT
RO
SI
FI
NO
HR
Average

2007
1.76
:
0.96
2.08
1.32
1.50
1.70
2.15
1.51
1.33
:
1.48
1.35
1.45
:
:
2.23
1.60

Employed women
2009
1.81
1.90
0.87
2.21
1.47
1.82
1.48
2.14
1.56
1.31
1.81
1.45
1.37
1.61
1.67
1.84
2.52
1.66

2010
:
:
0.90
1.95
1.53
1.87
1.73
1.78
1.39
1.40
1.80
1.48
1.30
1.64
1.69
1.85
2.51
1.62

2008
1.80
1.93
0.98
2.14
1.43
1.69
1.85
2.18
1.53
1.34
1.70
1.50
1.39
1.53
:
1.78
2.44
1.68

2011
:
1.78
0.88
1.96
1.52
1.91
1.72
1.79
1.27
1.41
1.78
1.44
1.14
:
:
1.80
2.44
1.59

2007
2.03
:
2.20
1.04
1.50
1.23
2.20
0.85
1.32
1.53
:
1.20
1.44
1.20
:
:
0.75
1.39

Non-employed women
2009
2.05
1.56
2.48
1.02
1.56
0.95
2.07
0.83
1.21
1.63
1.04
1.19
1.52
1.28
2.30
2.54
0.69
1.38

2010
:
:
2.58
1.25
1.44
0.90
1.80
0.82
1.29
1.58
1.00
1.27
1.45
1.32
2.21
2.30
0.68
1.37

2008
2.11
1.65
2.22
1.04
1.57
1.20
1.77
0.84
1.36
1.63
1.13
1.27
1.55
1.50
:
2.70
0.65
1.37

2011
:
1.60
2.66
1.04
1.32
0.80
1.61
0.82
1.75
1.52
0.92
1.30
1.43
:
:
2.16
0.63
1.35

Notes: population by employment status estimated from LFS data. Data for missing countries (BG, CZ, IE, FR, IT, CY, LV, LT, NL, SK, SE, UK, IS and CH) not available (‘:‘). Average computed on the 11 
countries for which all 5 years of data are available, thus excluding BE, DK, PL, SI, FI and NO. In bold, maximum value across years for the specific country and population group. 

Source: computation of the author on Eurostat data (see methodological notes). 

 
 
 
 
 
 
 
 
 
 
 
 
 
Table 6: Specific total fertility rates by educational attainment, 2007-2011 

BE
CZ
DK
EE
EL
ES
HU
MT
AT
PL
PT
RO
SI
SK
FI
SE
NO
HR
Average

2007
1.67
1.98
1.48
2.36
2.05
1.78
1.54
1.40
1.53
:
1.29
2.03
1.48
2.64
1.81
2.00
:
1.60
1.82

Women with education ISCED 0-2
2010
2009
2008
:
1.82
1.87
1.98
1.99
2.11
1.56
1.54
1.57
2.21
2.00
1.86
2.07
2.07
2.10
1.76
1.74
1.89
1.47
1.54
1.59
1.47
1.46
1.45
1.63
1.59
1.63
1.49
1.46
1.51
1.31
1.24
1.34
1.79
2.00
2.07
2.14
1.60
2.18
3.13
3.07
3.41
1.80
1.79
1.81
2.06
2.10
2.13
1.73
1.70
1.75
1.63
1.54
1.64
1.86
1.86
1.86

2011
:
2.10
1.44
1.77
2.03
1.69
1.49
1.66
1.56
1.35
1.38
1.98
:
3.20
1.77
2.04
1.72
1.31
1.82

2007
1.78
1.42
1.61
1.57
1.37
1.57
1.13
1.32
1.38
:
1.43
0.95
1.30
1.09
1.58
1.69
:
1.41
1.40

Women with education ISCED 3-4
2010
2009
2008
:
1.74
1.82
1.46
1.48
1.50
1.63
1.61
1.64
1.56
1.62
1.68
1.53
1.50
1.54
1.52
1.53
1.61
1.01
1.11
1.14
1.62
1.71
1.76
1.39
1.39
1.43
1.32
1.36
1.36
1.40
1.42
1.50
0.84
0.90
0.98
1.33
1.33
1.36
1.20
1.20
1.14
1.62
1.60
1.64
1.70
1.68
1.74
1.65
1.71
1.73
1.52
1.49
1.54
1.44
1.46
1.47

2011
:
1.38
1.53
1.31
1.44
1.46
1.02
1.39
1.41
1.23
1.35
0.74
:
1.22
1.61
1.67
1.58
1.42
1.35

2007
1.80
1.49
2.17
1.37
1.23
0.95
1.52
1.65
1.21
:
1.52
1.43
1.72
1.38
2.03
1.99
:
1.43
1.53

Women with education ISCED 5-6
2010
2009
2008
:
1.76
1.82
1.47
1.48
1.53
2.04
1.99
2.18
1.48
1.42
1.52
1.34
1.32
1.36
0.99
0.99
1.00
1.47
1.50
1.52
1.21
1.34
1.31
1.26
1.18
1.24
1.46
1.47
1.50
1.46
1.49
1.49
1.66
1.89
2.02
1.85
1.78
1.87
1.45
1.59
1.49
2.01
2.03
2.05
2.07
2.02
2.10
2.08
2.08
2.13
1.52
1.56
1.53
1.56
1.55
1.58

2011
:
1.38
1.90
1.59
1.24
1.01
1.34
1.41
1.30
1.38
1.47
1.66
:
1.60
1.94
2.00
2.01
1.57
1.53

Notes: population by educational attainment estimated from LFS data for BE, CZ, EE, EL, ES, HU, AT, PL, PT, RO, SI, SK and HR. Average computed on the 14 countries for which all 5 years of data are 
available, thus excluding BE, PL, SI and NO. In bold, maximum value across years for the specific country and population group. ‘:‘=not available 

Source: computation of the author on Eurostat data (see methodological notes) (online data codes: demo_faeduc, demo_pjanedu). 

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Table 7: Specific total fertility rates by citizenship (left panels) and by country of birth (right panels), 2009-2011 

BE
BG
CZ
DK
DE
EE
IE
EL
ES
IT
CY
LV
LT
LU
HU
MT
NL
AT
PT
SI
FI
SE
UK
IS
NO
CH
Average

Women with national citizenship
2011
2010
2009
1.72
1.76
1.74
1.51
1.49
1.57
1.48
1.55
1.55
1.77
1.89
1.86
1.33
1.36
1.32
1.56
1.69
1.66
:
:
:
1.32
1.38
1.38
1.33
1.33
1.34
1.31
1.32
1.31
1.44
1.46
1.46
1.36
1.20
1.34
1.74
1.54
1.54
1.29
1.31
1.70
1.24
1.26
1.33
1.36
1.29
1.37
1.74
1.77
1.76
1.32
1.32
1.28
1.31
1.31
1.27
1.48
1.55
1.51
1.82
1.86
1.85
1.85
1.93
1.89
:
:
:
2.06
2.24
2.26
1.83
1.89
1.92
1.42
1.42
1.40
1.52
1.55
1.57

Women with foreign citizenship
2011
2010
2009
2.42
2.53
2.54
2.48
2.79
3.25
0.71
0.71
0.76
1.66
1.78
1.75
1.59
1.62
1.58
1.31
1.33
1.46
:
:
:
2.26
2.58
2.87
1.56
1.66
1.69
2.04
2.13
2.24
1.37
1.58
1.82
1.29
1.02
1.20
4.70
3.64
3.18
1.79
1.97
1.55
1.15
1.20
1.44
3.87
3.31
2.90
2.05
2.09
2.18
2.02
2.08
2.03
2.01
2.11
2.05
3.81
2.49
2.73
2.13
2.20
2.16
2.44
2.53
2.47
:
:
:
1.82
2.02
2.13
2.30
2.42
2.50
1.85
1.86
1.82
2.11
2.07
2.10

Native-born women
2010
:
:
:
1.91
:
1.66
:
:
1.33
:
:
:
1.55
1.09
:
1.42
1.79
1.32
1.27
1.56
1.85
1.93
1.86
2.27
1.93
:
1.74

2011
:
:
:
1.79
:
1.55
2.07
:
1.33
:
:
:
1.73
1.16
:
:
1.75
1.31
1.27
1.61
1.82
1.85
:
2.05
1.86
:
1.70

2009
1.56
:
:
1.88
:
1.65
:
:
1.34
:
:
:
1.54
:
:
1.51
1.79
1.27
:
1.53
1.85
1.88
1.82
2.28
1.93
:
1.72

Foreign-born women
2010
:
:
:
1.68
:
1.31
:
:
1.63
:
:
:
1.69
2.33
:
1.15
1.86
1.95
2.08
1.96
2.10
2.26
2.49
1.92
2.08
:
1.86

2011
:
:
:
1.59
:
1.20
1.97
:
1.53
:
:
:
3.19
1.96
:
:
1.83
1.90
1.98
1.35
2.03
2.18
:
1.90
2.01
:
1.88

2009
3.10
:
:
1.66
:
1.34
:
:
1.67
:
:
:
1.65
:
:
0.86
1.85
1.91
:
1.86
2.03
2.22
2.50
2.08
2.26
:
1.87

Notes: average of specific TFR by citizenship computed on the 24 countries for which all 3 years of data are available, thus excluding IE and UK. Average of specific TFR by country of birth computed on the 
11 countries for which all 3 years of data are available, thus excluding BE, BG, CZ, DE, IE, EL, IT, CY, LV, LU, HU, MT, PT, UK and CH. Data for FR, RO, PL, SK and HR are missing for both 
characteristics. In bold, maximum value across years for the specific country and population group. (‘:‘= not available) 

Source: computation of the author on Eurostat data (see methodological notes) (online data codes for population: migr_pop2ctz, migr_pop4ctb). 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Latest monthly data point to fewer countries with decreasing number of live births 

There is still little empirical evidence about the path 
fertility is taking lately. The most up-to-date 
information is shown in Figure 4, based on the data 
available for 2012 on live births by month. 

Each box shows the relative change, all within the 
same range ±20 %, from the corresponding month of 
2011 of the cumulated number of monthly live births. 
The horizontal dotted grey line is set to zero, meaning 
that the cumulated number of live births is 
progressing to match what happened the previous 
year. 

Lines in the upper part of the boxes mean that the 
cumulated number of live births is higher in 2012 
than in the same month of 2011, and vice versa. The 
latest available monthly observations define the 
length of the line, which can range from a semester 
up to the entire year, the latter corresponding to the 
full length of the horizontal axis.  

Besides the provisional data, a country may have also 
provided a forecast for live births for the following 
months, indicated by a dashed line. 

For instance, during the first months of 2012, 
Lithuania had far fewer live births than in the same 
period of 2011, but it later recovered, and by the end 
of the year the (forecasted) cumulated number of live 
births almost matched the total for the previous year. 
Greece, Malta and Croatia provided no data for 2012 
and thus are not shown in Figure 4.

Table 8: Countries by change from previous year of 
the number of live births in 2011 (full year) and 2012 
(up to the available monthly data) 

Increase in 
the first 
months of 
2012

Decrease in 
the first 
months of 
2012

BE*, IE, UK

SK, CH

Increase in 
2011

Decrease in 
2011

DE*, CY*, LV, 
LU, HU*, PL*, 
RO*, SE, NO

Count

12

BG*, CZ, DK, 
EE, ES*, FR, 
IT, LT*, NL, 
AT, PT*, SI, 
FI, IS
16

Count

5

23

28

Notes: (*) including forecasted values. Values for 2012 refer to 
the provisional cumulated data covering only part of the year, 
variable across countries. EL, MT and HR missing. 

Source: computation of the author on Eurostat data (online data 
code: demo_fmonth) 

Table 8 summarises changes in the number of live 
births, showing that nine countries are expected to 
invert the negative change observed in 2011, but this 
will not be the case for half the countries shown. 

For instance, Germany had about 15 000 fewer live 
births in 2011 compared to 2010, while the value 
forecast by the national statistical office for 2012 was 
about 7 000 live births more than in 2011. 

The continuation or reversal of past trends in 2012 
may be due either to changes in the number of women 
of childbearing age and/or in fertility rates, but the 
data necessary for such disaggregation are not yet 
available for all countries. 

  Statistics in focus — 13/2013 

13 

 
 
 
 
Figure 4: Cumulative monthly live births in 2012 (provisional data in percentage change from corresponding 
month of previous year) 

Notes: solid line = provisional data; dashed line = values forecast by the national statistical office. EL, MT and HR missing. 

Source: computation of the author on Eurostat data (online data code: demo_fmonth). 

14 

13/2013— Statistics in focus  

 
 
 
 
METHODOLOGICAL NOTES 

Geographical coverage 

The term ‘Europe’ is used for the sake of simplicity to designate the area covered by the following 31 countries, listed 
according to the EU protocol order (between brackets their code): Belgium (BE), Bulgaria (BG), the Czech Republic (CZ), 
Denmark (DK), Germany (DE), Estonia (EE), Ireland (IE), Greece (EL), Spain (ES), France (FR), Italy (IT), Cyprus (CY), 
Latvia (LV), Lithuania (LT), Luxembourg (LU), Hungary (HU), Malta (MT), the Netherlands (NL), Austria (AT), Poland 
(PL), Portugal (PT), Romania (RO), Slovenia (SI), Slovakia (SK), Finland (FI), Sweden (SE), the United Kingdom (UK), 
Iceland (IS), Norway (NO), Switzerland (CH) and Croatia (HR). 

Data sources 

Most of the statistics presented in this report are experimental and are not part of the regular production of Eurostat. All 
input Eurostat data are provided by the national statistical offices. Population by employment status and by educational 
attainment are estimated from Labour Force Survey data. 

Post-census revisions 

For most of the countries, population data for 2011 take into account the results of the latest population census (held in 
2011); the time series between the census rounds 2001 and 2011 have not yet been revised. The revision of population data 
for previous years may lead to changes in the demographic indicators presented in this report. Further, the comparison of 
these indicators referring to pre-census and post-census years may result in differences which could be at least partially 
explained with the lack of revision of past population data. Hence, care should be taken when comparing the results for 
2011 with previous years. 

Demographic indicators 

The total fertility rate (TFR) is the most common period indicator of fertility, measuring the average number of live births a 
woman would deliver if she were to experience the fertility rates of a given period (usually a year). It is computed as the 
sum over childbearing age of age-specific fertility rates, in their turn computed as the ratio of the number of live births 
from women of a given age to the number of women of the same age exposed to the risk of childbearing (usually estimated 
as the average number of women in that year). 

The employment-specific TFR, as well as the education-specific TFR and the migration-specific TFR, are computed from 
age-specific fertility rates of the first type, which relate the number of events specific to a characteristic (live births by 
employment status, or by educational attainment, or by citizenship, or by country of birth in this report) to the number of 
women who are at risk of that specific event. For instance, the TFR of employed women is the sum of the age-specific 
fertility rates computed as the ratio between the live births to employed women at a selected age and the average number of 
employed women of the same age. 

A birth-order specific TFR would then require the number of women by age and parity, but the latter information is not 
available. Hence, the TFR by birth order presented in this report is a rate of the second kind, i.e. for each childbearing age, 
it relates live births by birth order to the total number of women, regardless of the number of live births they delivered 
before. 

For each childbearing age, the sum of the age- and characteristic-specific fertility rates weighted with the corresponding 
share of their population at risk in the total number of women in childbearing age is equal to the total age-specific fertility 
rate. Therefore, changes in the total TFR could simply reflect changes in the composition of the population at risk by the 
selected characteristic with unchanged characteristic-specific fertility rates. 

The characteristic-specific TFRs are computed by grouping the events and the population at risk by 5-year age group 
because the computation by single age, though possible, may be too sensitive to small numbers and/or to the sampling size 
of the population at risk. Where the latter approach is used, the values of the indicators may differ by several percentage 
points. 

Further data quality issues 

Where the population breakdown is estimated by Labour Force Survey data, its total population is recalibrated to match the 
latest revisions available in the demographic data. In some countries, the youngest age classes relevant for employment 
(e.g., from 15 to 19 years old) may be under-represented in the sample, which would lead to an overestimate of the 
corresponding age- and characteristic-specific fertility rate, and thus to an over-estimate of the specific TFR. 

Misclassification of live births by educational attainment of the mother at younger ages may be particularly influential on 
the overall total fertility rate. In order to remove such an impact, live births occurring to women aged 18 years and under 
have all been classified in ISCED 0-2, and those to women aged from 19 to 21 years with ISCED 5-6 reclassified as 
occurring to women with ISCED 3-4. Hence, age-specific fertility rates are set to zero up to age 18 for women with ISCED 
3-4, and up to age 21 for women with ISCED 5-6. 

  Statistics in focus — 13/2013 

15 

 
 
 
Further information 

Eurostat website: http://ec.europa.eu/eurostat 

Data on ’Population statistics’ 
http://epp.eurostat.ec.europa.eu/portal/page/portal/population/data/database 

Further information about ‘Population statistics’ 
http://epp.eurostat.ec.europa.eu/portal/page/portal/population/introduction 

Journalists can contact the media support service: 

Bech Building, Office A4/125, L-2920 Luxembourg 
Tel.: (352) 4301 33408  
Fax: (352) 4301 35349 
E-mail: eurostat-mediasupport@ec.europa.eu 

European Statistical Data Support: 

With the members of the ‘European statistical system’, Eurostat has set up a network of 
support centres in nearly every Member State and in some EFTA countries. 

Their role is to provide help and guidance to Internet users of European statistics. 

Contact details for this support network can be found on the Eurostat website at: 
http://ec.europa.eu/eurostat/. 

All Eurostat publications can be ordered via the ‘EU Bookshop’: 
http://bookshop.europa.eu/. 

Manuscript completed on: 07.05.2013 
Data extracted on: 22.03.2013 
ISSN 1977-0316 
Catalogue number: KS-SF-13-013-EN-N 
© European Union, 2013