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 Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: حبيب نورة)
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حبيبنا العوض المسلمي ..
عيد سعيد لك ولكل الرائعين ..
قائمة بروز دي انا فهمتها تاني باعتبار اغلب قاطينها يقضوا عيدهم خارجها
فمن وين بيجيب بتاع البقالة والجزارة والمشترين لبضاعتو - دا اذا ما قام هو نفسه سافر ليقضي العيد خارج الخرطوم - والعجب كمان ناس ام درمان ديلك 0 وش غامز جهة وليد المبارك )
لك كل الود والتحايا ولبورداب الخرطوم الرائعين
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 Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: HAIDER ALZAIN)
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حبيبنا حيدر الزين كل عام وانت الذين تعزهم وتعرفهم بالف خير ,
وكل عيد وانت في زيادة للخير وتوفيق من الله ,,
وزي ما قلت ان سكان الخرطوم مؤقتون يخلون بيوتهم في الاعياد الي الولايات او اطراف الخرطوم "كحالتي مثلا"
ولكن عندما يعودون ثاني ايام العيد او ثالث ايام العيد يجدون الكل مقفل ليس من عدم المشترين بل لانهم في الغالب
من سكان ولاية النيل الابيض او الجزيره ,,ويقضون العيد مع اهليهم .
وناس امدرمانخليهم براهم اولاد قلبا , انا اقصد في الغالب اولاد بحري والخرطوم ,.
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: العوض المسلمي)
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وبداية ان الخرطوم تصبح مدينه بلا فعاليه هو انني ذهبت اليوم لشراء الصحف فوجدت
ان صحف التيار للاستاذ عثمان ميرغني وصحيفة فون وصحيفة حكايات وكثير من الصحف لم تصدر هذا
اليوم . مع توقع توقف باقي الصحف غدا كما تعودنا في اعياد سابقه باستثناء اخبار اليوم والدار ,
اها يا اشباب بلد تؤجز صحفها ماذا ننظر منها ؟؟!
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: العوض المسلمي)
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سلامات يا اخونا العوض
Quote: هو انني ذهبت اليوم لشراء الصحف فوجدت
ان صحف التيار للاستاذ عثمان ميرغني وصحيفة فون وصحيفة حكايات وكثير من الصحف لم تصدر هذا
اليوم |
اذا انا فهمت صح من كلامك الفوق دا
فبتكون الجريدة خلصت بدري من المكتبة المشيت ليها
لانو انا الان معاي عدد التيار اليوم
وابرز مانشيت فيه الميرغني بعد عشرين عاما يصلي في مسجد والده
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: يسرى معتصم)
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طالما انه بتاع البقالة وبتاع الجزارة وبتاع الفحم وبتاع المساويك وبتاع النظافه وبتاعين العربات المالين الشوارع ويسبو في نهار رمضان جرستا وعطشا
طالما ديل كللللللللللللهم من بره خرطوم السجم دي فما كان الاولي يقعدوا في محل ما هم معيدين
علي الاقل يبقو قريبين من اهلهم بدل المساسقه الما عندها طعم ديي ؟
زحمة في الفاضي
عليك الله ياالعوض شوف الخرطوم دي ايام العيد رايقه كيف؟
بي وسخه ده بس اليختوها لينا ناس التتار وهولاكو ديل
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: عبدالوهاب علي الحاج)
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أخونا العوض : كل سنه وانت طيب وامانيك محققه باذن الله.
أعجبني طرحك خاصة مسالة النفايات : شي مخجل للغايع ززز الخرطوم معيده ومليانه قاذورات في اطراف الشوارع ودا كان الابشع وفي الشوارع الداخليه كان منظر مؤلم وخاصه والدنيا عيد زى ما قلت.
تخيل بالاضافه لجيوش الباعوض التي أقلقت منامن ...أضف اليها جحافل الذباب ....حاجه مؤسفه للغايه.
أما الهدوء الذى عماها فهذه هي المحمده الوحيده ز..انشاء الله ما نصنف ((أقصائيين))
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: عبدالوهاب علي الحاج)
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Quote: نفهم من كدا يافيصل الرشيد
انك اقصائي |
لووووووووووووووووووول يا وهبه .... انا قايل الالفه غايب اتاريك قاعد
القصد ليس هو الاقصائية وانما انا ضد الهجرة من الريف الي المدن بهذه الصورة الهمجيه
يعني تلقي واحد جايي من سقط لقط احدي الولايات المشهورة بأنه البجو منها كلهم بشتغلو في اللقيمات والطعمية
اها زي ده كان قعد وخته صاجه ده قبله هناك ورمي طعميته وبلاويهو دي قبلو ما كان اخير؟
بدل يجي يعمل ليه زحمه ما عندها معني وقدر البدخلو يصرفو مواصلات وايجار
وفي واحدين فاهمين انه القروش في الخرطوم بلموها من الشارع
اها الواحد من ديل بجي دافر ويخلي حواشته زراعته ويجي يتحاوم هنا يترقد من ضل لي ضل وتمر سنه ورا سنه بدون فايده واخرته الانحراف
ياخ نقول شنو والا شنو
طبعا في ناس حيجو ناطين يقولو ليك ناس الانقاذ هم الهمشو الناس ديل وخلوهم يفكو درب الله ويجو الخرطوم ينشلو ويقيفو في الاستوبات
وفي واحدين طبعا بعرضو خارج الداره وما عارفين انه برغم الظروف الاقتصادية الحاصله لكن الناس دي زي الارانب المره تتم الاربعين تلقاها شحنت التاني
يعني تدخل البيت تلقاهو زي الروضه ما تفرز اعمارهم كم وولدوهم متين وتلقي الراجل طبعا زي ما بقولوا همو في حاجتين يملا بطنوا ويفضيها
وديل ياهم العملو ليك الثورات لحدي الدشليون بي سبب عمايلم دي
باختصار انعدام للاستراتيجية في بناء وتكوين الاسرة
وتسال الواحد يقول ليك الرزق علي الله .. ونعم بالله وما عندنا شك في انه ربنا مقسم الارزاق حتي للنمل لكن ربنا ادانا عقل عشان نفكر بيه
بدل ما كل واحد جايب 9 اطفال وما قادر علي مصارف المدارس والاكل والشراب والعلاج والطهورة والسجم والرماد
يجيبهم اتنين او تلاته علي الاقل يحاول يعمل ليهم حاجه تضمن انهم يطلعوا ناس نافعين لمجتمعاتهم ويقدروا يشيلو نفسهم بعدين
بدل يفقس ويطلق في الشارع ساكت
وهبه
الاسرة السودانية فاقدة لبوصلة الادارة ماشين بدون اي حساب لاي حاجه يعني بسياسة اليحصل يحصل عشان كده لاحظ حجم الفاقد التربوي في المجتمع
الكلام والمغسه علي هذا المواطن كبيرة عشان كده نسال الله صلاح الحال (وش متهرب من المسؤلية)
اما الحكومة فهي اخر من يعلم
ــــــــــــــــــــــــــــــ
ياخ كل سنة وانت بألف خير
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: Faisal Elrasheed)
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Quote:
القصد ليس هو الاقصائية وانما انا ضد الهجرة من الريف الي المدن بهذه الصورة الهمجيه
يعني تلقي واحد جايي من سقط لقط احدي الولايات المشهورة بأنه البجو منها كلهم بشتغلو في اللقيمات والطعمية
اها زي ده كان قعد وخته صاجه ده قبله هناك ورمي طعميته وبلاويهو دي قبلو ما كان اخير؟
بدل يجي يعمل ليه زحمه ما عندها معني وقدر البدخلو يصرفو مواصلات وايجار
وفي واحدين فاهمين انه القروش في الخرطوم بلموها من الشارع
اها الواحد من ديل بجي دافر ويخلي حواشته زراعته ويجي يتحاوم هنا يترقد من ضل لي ضل وتمر سنه ورا سنه بدون فايده واخرته الانحراف
ياخ نقول شنو والا شنو
طبعا في ناس حيجو ناطين يقولو ليك ناس الانقاذ هم الهمشو الناس ديل وخلوهم يفكو درب الله ويجو الخرطوم ينشلو ويقيفو في الاستوبات
وفي واحدين طبعا بعرضو خارج الداره وما عارفين انه برغم الظروف الاقتصادية الحاصله لكن الناس دي زي الارانب المره تتم الاربعين تلقاها شحنت التاني
يعني تدخل البيت تلقاهو زي الروضه ما تفرز اعمارهم كم وولدوهم متين وتلقي الراجل طبعا زي ما بقولوا همو في حاجتين يملا بطنوا ويفضيها
وديل ياهم العملو ليك الثورات لحدي الدشليون بي سبب عمايلم دي
باختصار انعدام للاستراتيجية في بناء وتكوين الاسرة
وتسال الواحد يقول ليك الرزق علي الله .. ونعم بالله وما عندنا شك في انه ربنا مقسم الارزاق حتي للنمل لكن ربنا ادانا عقل عشان نفكر بيه
بدل ما كل واحد جايب 9 اطفال وما قادر علي مصارف المدارس والاكل والشراب والعلاج والطهورة والسجم والرماد
يجيبهم اتنين او تلاته علي الاقل يحاول يعمل ليهم حاجه تضمن انهم يطلعوا ناس نافعين لمجتمعاتهم ويقدروا يشيلو نفسهم بعدين
بدل يفقس ويطلق في الشارع ساكت
وهبه
الاسرة السودانية فاقدة لبوصلة الادارة ماشين بدون اي حساب لاي حاجه يعني بسياسة اليحصل يحصل عشان كده لاحظ حجم الفاقد التربوي في المجتمع
الكلام والمغسه علي هذا المواطن كبيرة عشان كده نسال الله صلاح الحال (وش متهرب من المسؤلية)
اما الحكومة فهي اخر من يعلم
|
حقو واحد يديك بونيه في كوعك يطلع طايق مخك
كايس لي شكله مع اي واحد منكم
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: محمد زكريا)
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brother,Faisal
EID Mubaraak
وتسال الواحد يقول ليك الرزق علي الله .. ونعم بالله وما عندنا شك في انه ربنا مقسم الارزاق حتي للنمل لكن ربنا ادانا عقل عشان نفكر بيه
بدل ما كل واحد جايب 9 اطفال وما قادر علي مصارف المدارس والاكل والشراب والعلاج والطهورة والسجم والرماد
يجيبهم اتنين او تلاته علي الاقل يحاول يعمل ليهم حاجه تضمن انهم يطلعوا ناس نافعين لمجتمعاتهم ويقدروا يشيلو نفسهم بعدين
بدل يفقس ويطلق في الشارع ساكت
it is sound and wise judgement,
بدل يفقس ويطلق في الشارع ساكت
Most of European Countries are looking for IMMAGRANTS, I think the best solution to send them there
Late studies shows the DECLINE of the Birth Fertiltay Among the EUROPEANS,, By 2050 they NEEDS for at least
four hundred MILLOONS of Immagrants to cover their shortages
In my opnion the goverment has to do more to answer the chronicle problem of the inflation of the growing population, with strategic and long lasting response, in various front
If u do Mental Maping u will see the changeability in Sudan
El hadi
Note: for more read the underneath reserach
Low Fertility in Europe: Causes, Implications and Policy
Options
Hans-Peter Kohler Francesco C. Billari José Antonio Ortega
February 15, 2006
Note: This paper has been published as: Hans-Peter Kohler, Francesco C. Billari and José A. Ortega (2006).
“Low Fertility in Europe: Causes, Implications and Policy Options.” In F. R. Harris (Ed.), The Baby Bust:
Who will do the Work? Who Will Pay the Taxes? Lanham, MD: Rowman & Littlefield Publishers, 48-109.
1 Introduction
The global population is at a turning point. At the end of 2004, the majority of the world’s population is
believed to live in countries or regions below-replacement fertility, and the earlier distinct fertility regimes,
‘developed’ and ‘developing’, are increasingly disappearing in global comparisons of fertility levels (Wilson
2001, 2004). Several aspects of this convergence towards low fertility are particularly striking. First, the
spread of below-replacement fertility to formerly high fertility countries has occurred at a remarkably rapid
pace and implied a global convergence of fertility indicators that has been quicker than the convergence of
many other socioeconomic characteristics. Second, earlier notions that fertility levels may naturally stabilize
close to replacement level—that is fertility levels with slightly more than two children per women—have
been shattered. Sustained below-replacement fertility has become commonplace, and Europe has been
a leader in the trend towards low and very low fertility. Europe also witnessed in the last 15 years the
emergence of unprecedented low fertility levels with a total fertility rate (TFR) at or below 1.3 children per
woman. Kohler et al. (2002) have labeled these patterns as lowest-low fertility to emphasize the dramatic
implications of these unprecedentedly low levels of fertility: for instance, if they persist over a long time in
a contemporary low-mortality context, TFR levels at or below 1.3 imply a reduction of the annual number
of births by 50% and a halving of the population size in less than 45 years. There have been no cases of
sustained lowest-low fertility prior to 1990 (Figure 1). In the early 1990s, Italy and Spain were the first
countries to attain and sustain lowest-low fertility levels, and in 2002 there were 17 lowest-low fertility
countries in Southern, Central and Eastern Europe with a total population of over 278 million persons. As
a matter of fact, the median total fertility rate, i.e., the TFR level below which 50% of the populations in
Europe live, is currently with 1.31 only slightly above lowest-low fertility. Third, recent fertility trends have
been accompanied by a remarkable divergence of European countries in terms of their fertility levels and
Kohler is Associate Professor of Sociology, 3718 Locust Walk, University of Pennsylvania, Philadelphia, PA 19104-
6299, USA; Email: [email protected], Homepage: http://www.ssc.upenn.edu/hpkohler. Billari is Associate Professor
of Demography, Institute of Quantitative Methods, Bocconi University, viale Isonzo 25, 20135 Milano, Italy, email:
[email protected]. Ortega is Associate Professor of Economics, Departamento de Economía e Historia Económica,
University of Salmanca, 37007-Salamanca, Spain; email: [email protected]. This paper is in part based on our earlier work; in
particular, Section 2 is based on Billari and Kohler (2004) and Section 3 is based on Kohler, Billari, and Ortega (2002).
1
1993
1999
Prior to 1990:
no cases of
sustained
TFR 1.3
Southern Europe
Greece
Italy
Spain
Central and Eastern Europe
Bosnia and Herzegovina
Bulgaria
Czech Republic
Hungary
Latvia
Lithuania
Poland
Romania
Slovak Republic
Slovenia
Former Soviet Republics
Armenia
Belarus
Moldova
Ukraine
South/East Asia
Japan
Korea
2002
?
Figure 1: The emergence and spread of lowest-low fertility in Europe during 1990–2002
future population trends, with current patterns ranging from countries that stabilized at moderately belowreplacement
fertility levels to lowest-low fertility countries with TFR declines below 1.3 (Figure 2). For
instance, several European countries that were among the first to experience sustained below-replacement
fertility in the late 1960s and early 1970s, including Denmark, France, the Netherlands and the United
Kingdom, exhibit relatively high fertility in 2002. Moreover, the Dutch, Danish and French TFRs have
increased during the last decade to levels of 1.72 (The Netherlands), 1.77 (Denmark), and 1.89 (France)
(Council of Europe 2003), and several other European countries exhibit even higher TFRs. These trends
are in sharp contrast to the pervasive TFR declines in Southern, Central and Eastern Europe to levels below
1.3, leading to pronounced differences across European countries in their future demographic trajectories.
Fourth, as a consequence of below-replacement fertility that has prevailed for several decades starting since
the 1960s and 1970s, low birthrates in Europe have begun to generate negative population momentum, that
is, a new force for population shrinkage over the coming decades due to the fact that past below-replacement
fertility will soon result in declining numbers of potential parents (Lutz et al. 2003). A continuation of this
trend could substantially exacerbate the future aging of the population, reinforce a future decline in the
population size and constrain the effectiveness of policy interventions aimed at increasing the number of
births.
In this paper we investigate the emergence and persistence of low and particularly lowest-low fertility
in Europe, analyze its demographic patterns and socioeconomic determinants, and address the factors that
underlie the divergence of fertility levels in Europe and developed countries more generally. The central
thrust of our argument is that the emergence of lowest-low fertility in Europe is due to the combination of
four distinct demographic and behavioral factors. First, economic and social changes have made the postponement
of fertility a rational response for individuals. Second, social interaction processes affecting the
timing of fertility have rendered the population response to these new socioeconomic conditions substantially
larger than the direct individual responses. As a consequence, modest socioeconomic changes can
explain the rapid and persistent postponement transitions from early to late age-patterns of fertility that have
been associated with recent trends towards low and lowest-low fertility. Third, demographic distortions
2
Total fertility rate 1975
Total fertility rate 2001/02
1.6 2 2.5 3.2 4
1.1 1.3 1.6 2
Lowest−low fertility
countries in 2001/02
Ireland
Iceland
Macedonia
Spain
Italy
Russian Federation
Germany
Ukraine
United Kingdom
France
Netherlands
Azerbaijan
Denmark
Median TFR in 1975
Figure 2: Comparison of the total fertility rate in Europe in 1975 and 2002
The ‘×’ mark gives the exact position of a country, while the area of circle is proportional to the country’s population
size in 1990. Source for data: Council of Europe (2003); see Table A.1 for list of countries and data.
of period fertility measures, caused by the postponement of fertility and changes in the parity-composition
of the population, have reduced the level of period fertility indicators below the associated level of cohort
fertility (for discussion of this technical aspect, see Bongaarts and Feeney 1998; Kohler and Ortega 2002).
Fourth, institutional settings in Southern, Central and Eastern European countries have favored an overall
low quantum of fertility. Moreover, this institutional setting has caused particularly large reductions in
completed fertility in lowest-low fertility countries due to the delay of childbearing.
2 Patterns of low and lowest-low fertility in Europe
Against the background of these recent changes in the demographic landscape in Europe and other developed
countries, there is little doubt that the emergence and persistence of lowest-low fertility entails profound
consequences for virtually all aspects of society. Some of these implications of Europe’s low and lowestlow
fertility pattern on the population size and structure are illustrated in Figure 3 using the UN medium
population forecasts for Europe, Bulgaria, Denmark, France, Germany, Italy and the Russian Federation
(see http://www.un.org/esa/population/unpop.htm. The different countries included in these analyses are
representative for the major fertility patterns and welfare regimes in contemporary Europe. The United
States is also included in these analyses for comparison. Figure 3 shows that, while the U.S. and a small
number of European countries are projected to grow in the next decades, Europe as a whole is projected to
decline. Some countries such as Bulgaria, Russia and Italy are likely to experience a substantial declines
in their population size. This different trends in population size in Europe are mostly due to fertility trends
3
that differ drastically across European countries. France and Denmark, for instance, are expected to have
moderately high fertility with TFRs above 1.7 children per woman, continuing their most recent experiences.
Most other European countries are projected to have lower—and often much lower—fertility in the next
decades, and Europe as a whole is projected to experience a TFR of below 1.5 until about 2020. These
fertility trends in combination with increases in longevity imply that population aging—as measured for
instance by the increase in the median age of the population and the old-age dependency ratio—will occur
across Europe. Europe’s median age, for instance, is projected to increase from 37.7 years in 2000 to 47.9
in 2040. The old-age dependency ratio is projected to increase from 22 persons aged 65 years and older per
100 persons aged 15–64 (2000) to 44 persons aged 65+ per 100 persons aged 15–64 (2040). However, there
is likely to be considerable heterogeneity in this population aging across Europe. The median age in 2040
in Figure 3 ranges from 44.4 years (France) to 52.7 years (Italy), and the old-age dependency ratio ranges
from 37 (Russia) to 63 (Italy). Demographically speaking, therefore, European countries are pulled apart by
a differential extent of population aging. In addition, the above trends in Europe are in striking contrast to
those in the United States. While the U.S. population is also aging in the next decades, this process occurs
in the context of a growing population, a relatively high level of fertility and substantial immigration. In
comparison with Europe, therefore, the increases in the median age or the old-age dependency ratio during
the next decades are rather modest.
The implications of population aging, and the societal changes associated with this trend, are going to
be most pronounced in countries with very low fertility. These countries are likely to experience a dramatic
transformation of their age pyramids (Figures 4–5), and the social and economic organization of individuals
and families in these highly-aged societies is an unchartered territory in demographic history. The implications
of this changes will reach across all aspects of society and individual lives. Lowest-low fertility, for
instance, is going to substantially alter the structure and age-composition of the labor force as well as of the
young and old population, and female—and probably also male—labor supply patterns will change due to
the combination of low and late fertility. Lowest-low fertility will also transform a wide range of social relations,
which are frequently taken for granted, due to the fact that low fertility, fewer siblings and increases
in childlessness diminish the potential of family networks to provide social, psychological and economic
support. The increased diversity in living arrangements and the changes in the timing of fertility have also
important consequences for the income distribution, the well-fare of small children, and the life-chances
across individuals and households.
Despite this ample need for information and evaluation of these developments, the demography of
lowest-low fertility is still in its infancy. The emergence of sustained lowest-low fertility first occurs in
Southern, Central and Eastern European countries. Based on Council of Europe (2003), seventeen countries
attained lowest-low fertility levels by 2002 (Table 1): three in Southern Europe (Greece, Italy and Spain),
ten in Central and Eastern Europe (Bosnia and Herzegovina, Bulgaria, Czech Republic, Hungary, Latvia,
Lithuania, Poland, Romania, Slovak Republic, Slovenia) and four in the former Soviet Union (Armenia,
Belarus, Moldova, Ukraine). The first countries to reach lowest-low fertility levels were Spain and Italy in
1993. They were then joined by Bulgaria, the Czech Republic, Latvia and Slovenia in 1995, and by the remaining
lowest-low fertility countries between 1996 and 2002. In addition, several other countries in Central
and Eastern Europe and the Balkans have very low TFR levels, and Croatia (1.34), Estonia (1.37), Russia
(1.32) will possibly join—or re-join, such as Russia—the group of lowest-low fertility countries. More-
4
1980 2000 2020 2040
70 80 90 100 110 120 130
year
population size (2000 == 100)
(a) Population Size (2000 == 100)
BG
DK
EUR
F
GER
IT
RU
USA
1980 2000 2020 2040
−0.5 0.0 0.5 1.0
year
annual population growth rate (%)
(b) Population growth rate (%)
BG
DK
EUR
F
GER
IT
RU
USA
1980 2000 2020 2040
1.2 1.4 1.6 1.8 2.0 2.2
year
Total fertility rate (children per woman)
(c) Total fertility rate (children per woman)
BG
DK
EUR
F
GER
IT
RU
USA
replacement fertility
1980 2000 2020 2040
72 74 76 78 80 82 84 86
year
Life expectancy at birth, females (years)
(d) Life Expectancy at Birth, Females
BG
DK
EUR
F
GER
IT
RU
USA
1980 2000 2020 2040
30 35 40 45 50
year
median age (years)
(e) Median age
BG
DK
EUR
F
GER
IT
RU
USA
1980 2000 2020 2040
10 20 30 40 50 60
year
old age dependency ratio
(f) Old Age Dependency Ratio
BG
DK
EUR
F
GER
IT
RU
USA
Figure 3: UN projections (medium variant) for Europe, USA, Bulgaria, Denmark, France, Germany, Italy
and the Russian Federation
Notes: The different demographic measures are defined as follows: Population size: De facto population in a country,
area or region as of 1 July of the year indicated. Population growth rate: annual average exponential rate of growth
of the population. Total fertility rate (TFR): The average number of children a hypothetical cohort of women would
have at the end of their reproductive period if they were subject during their whole lives to the fertility rates of a given
period and if they were not subject to mortality. It is expressed as children per woman. Life expectancy: The average
number of years of life expected by a hypothetical cohort of individuals who would be subject during all their lives to
the mortality rates of a given period. It is expressed as years. Median age: Age that divides the population in two parts
of equal size, that is, there are as many persons with ages above the median are there are with ages below the median.
Old age dependency ratio: the ratio of the population aged 65 years or over to the population aged 15–64.
5
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Europe 2000
Females Males
0.04 0.02 0 0.02 0.04
Europe 2040
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
United States 2000
Females Males
0.04 0.02 0 0.02 0.04
United States 2040
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Bulgaria 2000
Females Males
0.04 0.02 0 0.02 0.04
Bulgaria 2040
proportion of population in age group
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Denmark 2000
proportion of population in age group
Females Males
0.04 0.02 0 0.02 0.04
Denmark 2040
Figure 4: Population age pyramids based on the UN medium projections: Europe, United States, Bulgaria
and Denmark
6
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
France 2000
Females Males
0.04 0.02 0 0.02 0.04
France 2040
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Germany 2000
Females Males
0.04 0.02 0 0.02 0.04
Germany 2040
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Italy 2000
Females Males
0.04 0.02 0 0.02 0.04
Italy 2040
proportion of population in age group
Females Males
0.04 0.02 0 0.02 0.04
0 − 5
5 − 10
10 − 15
15 − 20
20 − 25
25 − 30
30 − 35
35 − 40
40 − 45
45 − 50
50 − 55
55 − 60
60 − 65
65 − 70
70 − 75
75 − 80
80 − 85
85 − 90
90 − 95
95 − 100
100+
Russia 2000
proportion of population in age group
Females Males
0.04 0.02 0 0.02 0.04
Russia 2040
Figure 5: Population age pyramids based on the UN medium projections: France, Germany, Italy and Russia
7
over, other European countries with traditionally low fertility, such as Austria (1.34), Switzerland (1.4), and
Germany (1.31), are candidates that may soon join the group of lowest-low fertility countries.
Despite these very low levels of fertility, demographic analyses suggest that the decline in the desire
to have at least one child has not been a primary driving force in the emergence of lowest-low fertility in
the Southern, Central and Eastern European countries (Kohler et al. 2002). While childlessness is likely to
rise, it is projected to remain at relatively modest levels. Calculations by Kohler et al. (2002), for instance,
suggest that a cohort experiencing the fertility pattern observed during the mid/late 1990s attains a childlessness
of 16–19% in Italy and Spain and of 13–19% in Bulgaria, Czech Republic and Hungary (for related
calculations, see also Sobotka 2004a,b). These levels of childlessness are comparable to the corresponding
estimates for Sweden and the Netherlands in the late 1990s, and these levels quite are modest in a historical
20th-century perspective or when compared to the childlessness observed in some other countries, as for instance
Germany, where more than quarter of the women in the 1965 cohort are estimated to have remained
childless (Sobotka 2004b).
These findings on childlessness therefore suggest that even in lowest-low fertility contexts, the biological,
social and economic incentives for children are sufficiently strong that most women (or couples) desire
to have at least one child (e.g., Foster 2000; Kohler and Behrman 2003; Morgan and King 2001). Nevertheless,
while first births are not necessarily foregone in lowest-low fertility countries, they are delayed to an
increasingly late age. For instance, the mean age at first birth in all lowest-low fertility countries is higher
in 2000-02 than in 1990 (Table 2). In the Southern European countries, postponement has been very intense
with annual increases in the mean age exceeding 0.2 per year. Combined with a relatively high initial mean
age, this postponement has lead to some of the highest mean ages at first birth worldwide. In the Central
and Eastern European (CEE) countries, the patterns are not so uniform. Extremely fast postponement has
occurred in Slovenia, the Czech Republic and Hungary. Other countries, like Bulgaria, Estonia, Latvia and
Romania, have experienced moderate postponement with increases in the mean age at first birth around 0.1
per year, and these countries continue to have a very young mean age. Similar patterns also prevail in other
countries of the former Soviet Union like Russia, Belarus and Armenia.
2.1 Fertility-Related Patterns of Household and Union Dynamics
The trend toward delayed childbearing—especially for first births—has occurred not only in lowest-low
fertility countries, but in almost all countries across Europe. This almost universal transition towards a
late pattern of childbearing, however, implies that the extent to which specific socioeconomic and institutional
contexts in different European countries accommodate late childbearing has become an essential
determinant of cross-country variation in fertility levels. To better understand this interrelation between
institutional contexts and patterns of childbearing, we begin our analyses in this paper with a series of descriptive
aggregate analyses to revisit the relation between low and lowest-low period fertility on the one,
and key fertility-related behaviors—such as leaving the parental home, marriage and women’s labor force
participation—on the other side. These analyses can improve our understanding of the demographic, socioeconomic
and institutional context that is associated with the emergence—or non-emergence—of lowest-low
fertility in European countries, and it characterizes the basic demographic and socioeconomic patterns that
are associated with low and lowest-low fertility in contemporary Europe.
8
Table 1: Total fertility rate (TFR) in lowest-low fertility countries, candidate countries, and selected other
countries
Most recent
TFR year TFR fell
1980 1990 2000 2002 2 1.3
Lowest-low fertility countries
Southern Europe
Greece 2.23 1.39 1.29 1.25a 1983 1998
Italy 1.64 1.33 1.24 1.27 1977 1993
Spain 2.20 1.36 1.24 1.25 1982 1993
Central and Eastern Europe
Bosnia and Herzegovina 1.93 1.71 1.34 1.23 1984 2002
Bulgaria 2.05 1.82 1.30 1.21 1987 2001
Czech Republic 2.10 1.90 1.14 1.17 1983 1995
Hungary 1.91 1.87 1.32 1.30 1980 1999
Latvia 1.90 2.01 1.24 1.24 1991 1995
Lithuania 1.99 2.03 1.39 1.24 1992 2001
Poland 2.26 2.05 1.34 1.24 1992 2001
Romania 2.43 1.84 1.31 1.26 1990 2001
Slovak Republic 2.31 2.09 1.30 1.19 1992 2000
Slovenia 2.10 1.46 1.26 1.21 1981 1995
Former Soviet Republics
Armenia 2.33 2.63 1.11 1.21 1993 1999
Belarus 2.04 1.90 1.31 1.22 1990 2001
Moldova 2.41 2.39 1.30 1.21 1994 2000
Ukraine 1.95 1.89 1.09 1.10 1989 1997
South/East Asia
Japan 1.29b 1975 2003
Korea 2.83 1.59 1.47 1.19b 1984 2001
Lowest-low fertility candidates in Europe
Andorra – – 1.32 1.36 – –
Austria 1.65 1.46 1.36 1.40 1973 –
Croatia 1.92 1.67 1.40 1.34 1968 –
Estonia 2.02 2.04 1.34 1.37 1991 1997‡
Germany 1.56 1.45 1.38 1.31 1971 1992‡
Russian Federation 1.86 1.90 1.21 1.32 1990 1996‡
Switzerland 1.55 1.58 1.50 1.40 1972 –
Selected other countries
Denmark 1.55 1.67 1.77 1.72 1973 –
France 1.95 1.78 1.88 1.89 1975 –
Netherlands 1.60 1.62 1.72 1.73 1973 –
United Kingdom 1.89 1.83 1.64 1.64 1974 –
United States 1.81 2.08 2.06 2.01 1995† –
Notes: a = 2001, b = 2003; †= fertility has increased to levels above 2.0 by 2002; ‡= fertility has
increased to levels above 1.3 by 2002; Sources: Council of Europe (2003); Martin et al. (2003);
Mathews and Hamilton (2002).
9
Table 2: Mean age at first birth (MAFB) in lowest-low fertility countries, candidate countries, and selected
other countries
Annual
increase in
Mean age at first birth (MAFB) MAFB
1980 1990 2000 2002 1980 1990– Year of
1990 2000 onset
Lowest-low fertility countries
Southern Europe
Greece 24.1 25.5 27.3c – 0.14 0.20 1983
Italy 25.0 26.9 28.7b – 0.19 0.26 1978
Spain 25.0 26.8 29.1 – 0.18 0.23 1979
Central and Eastern Europe
Bosnia and Herzegovina 23.3 23.6 – – 0.03 – –
Bulgaria 21.9 22.2 23.5 23.9 0.03 0.13 1992
Czech Republic 22.4 22.5 25.0 25.6 0.01 0.25 1991
Hungary 22.4 23.1 25.1 25.6 0.07 0.20 1980
Latvia 22.9 23.0 24.4 24.9 0.01 0.14 1992
Lithuania 23.8 23.2 23.9 24.3 -0.06 0.07 1994
Poland 23.4 23.3 24.5 25.0 -0.01 0.12 1991
Romania 22.5 22.7 23.6 24.1 0.02 0.09 1991
Slovak Republic 22.7 22.6 24.2 24.7 -0.01 0.16 1991
Slovenia 22.9 23.7 26.5 27.2 0.08 0.28 1985
Former Soviet Republics
Armenia 22.1 22.8 23.0 – 0.07 0.02 1994
Belarus – 22.9 23.4 23.5 – 0.05 1997
Moldova – – – 23.0 – – –
Ukraine – – – – – – –
South/East Asia
Japan 26.4 27.0 28.0 28.3 0.06 0.1
Korea – – – – – – –
Lowest-low fertility candidates in Europe
Andorra – – – – – – –
Austria – 25.0 26.4 26.7 – 0.14 1984
Croatia 23.4 24.1 25.5 25.9 0.07 0.14 1978
Estonia 23.2 22.9 24.0 24.6 -0.03 0.11 1991
Germany† 25.0 26.6 28.2 28.4d 0.16 0.16 1972
Russian Federation 23.0 22.6 23.0b – -0.04 0.06 1994
Switzerland† 26.3 27.6 28.7 28.9 0.13 0.11 1971
Selected other countries
Denmark 24.6 26.4 27.5a – 0.18 0.18 1967
France 25.0 27.0 27.9 28.0d 0.20 0.09 1973
Netherlands 25.7 27.6 28.6 28.7 0.19 0.10 1972
United Kingdom† – 27.3 29.1 – – 0.18 –
United States 22.7 24.2 24.9 – 0.15 0.07 1974
Notes: a = 1996, b = 1997, c = 1999, d = 2001; †= birth-order within current marriage; Sources: Council of
Europe (2003); Martin et al. (2003); Mathews and Hamilton (2002).
10
2.1.1 Leaving the Parental Home
Leaving the parental home is one of the crucial nodes of the life-course and a central event in early adulthood.
First, it generally implies the formation of a new household and greater autonomy for young people in all
aspects of social life and personal decision-making, including also many fertility-related decisions. Second,
and most important for our context, childbearing in developed countries almost invariably takes place after
young adults have left their parental home, and home-leaving constitutes a central correlate of fertility and
union formation in Europe and other industrialized countries.
In a pioneering study, Kiernan (1986) investigates home-leaving in six Western European countries
in 1982. The study identifies Denmark as the country with the earliest home-leaving, followed by West
Germany, France, the Netherlands, Ireland and the UK. In a follow-up investigation, Fernández Cordón
(1997) examined the living arrangements of young adults over time in Spain, Greece, Italy, France, Germany
and the UK between 1986 and 1994. These longitudinal analyses revealed that Italy had the highest share
of young people co-residing with their parents during early adulthood, while the UK had the smallest share.
Moreover, Corijn (1999) found that cohorts in most European countries born around 1950 and 1960 were
postponing the transition out of the parental home. This common trend towards delayed home-leaving,
however, co-exists with substantial variation in the timing of this event across countries: Italy and Spain
are among the countries with a late separation from the parental home, while Austria, the Netherlands and
Sweden were among the countries with an early pattern.
Despite this overall heterogeneity in patterns of home-leaving, however, there is an important regularity
with respect to the relation of home-leaving and lowest-low fertility. In particular, retrospective survey
data—which are the only available data source for this purpose—reveal that the timing of home-leaving
is quite homogeneously concentrated at relatively late ages among lowest-low fertility countries. In an
international comparison of the timing of home-leaving for cohorts born around 1960, for instance, Italy,
which is the first country experiencing lowest-low fertility in the early nineties, has the highest age both
for men and for women with 26.7 years and 23.6 years respectively. Some Central and Eastern European
countries, including those with lowest-low fertility, are not distant from the latest-late pattern of Southern
European countries. On the other hand, Sweden represents the opposite side of the ranking with 20.2 years
for men and 18.6 for women, resulting in a difference of more than 6.5 years (males) and 5 years (females)
in the timing of home-leaving across European countries (see Billari et al. 2001).
2.1.2 Fertility and Marriage: A Shifting Relationship?
In a well-known study, Hajnal (1965) traces an East-West divide in historical family systems in Europe, the
so-called Hajnal line, that connects the cities of Trieste in North-Eastern Italy and St. Petersburg in Western
Russia. To the West of this line, the family formation pattern is dominated by a neo-local nuclear family
with relatively late marriage and a significant proportion of individuals who never marry. To the east of
Hajnal’s line, marriage has been early and universal, and the family is often extended. This divergence
of marriage pattern along Hajnal’s like also prevails after WWII and persists until the present time. It is
particularly pronounced between Central and Eastern Europe on the one and Southern Europe on the other
side (Monnier and Rychtarikova 1992). Countries to the west of Hajnal’s line reveal greater heterogeneity
and diversity in contemporary marriage behaviors that do not easily cluster into a single pattern (Reher
1998).
11
Even if historical patterns are an important aspect shaping present marriage behaviors and family organizations,
the emergence of lowest-low fertility is associated with an important shift of the relationship
between marriage and fertility between the mid 1970s and the beginning of this decade. In particular, it has
traditionally been argued that cumulated fertility is inversely related to age at marriage, and variations in
the age at marriage have often been an important explanatory factor of aggregate fertility differences across
countries. For instance, a linear relationship between total fertility and the age at first marriage has been
shown to be a surprisingly good approximation, and Billari et al. (2000) estimate that a one-year increase
in the age at marriage would bring down the number of female children ever born by about 0.08 in Italian
cohorts born around 1950.
In contrast to this positive association between marriage and fertility, the recent emergence of lowestlow
fertility, especially in Southern Europe, is associated with a situation in which long-term partnership
commitments—symbolized by a high prevalence of legal marriage and low prevalence of divorce—
apparently represent an obstacle for the progression to (relatively) high fertility levels. To illustrate this
association, we compare on the left-hand side of Figure 6 the level of period total fertility with the period
total first marriage rate (TFMR) (see Appendix Table A.1 for the list of included countries and the underlying
data). In order to indicate the relevance of individual countries for the relationships in Figure 6, the
data points are surrounded by circles that have an area proportional to a country’s population size. In 1975,
Figure 6a shows that marriage and fertility were still closely intertwined and there has been a positive correlation
between the total fertility and the total first marriage rate. The correlation radically changes at the end
of the 1990s. In particularly, after lowest-low fertility has emerged, the positive correlation between the total
fertility and the TFMR is has vanished, and countries with high fertility levels no longer exhibit high marriage
propensities (Figure 6b). A similarly shifting relation occurs also with respect to fertility and divorce
(Figures 6c,d). In 1975, a higher level of divorce in European countries was associated with lower levels of
fertility in cross-sectional comparisons, and the period total divorce rate (TDR) exhibits a negative correlation
with the level of total fertility (Figure 6c). This correlation reverses in 2001–02: countries with high
TDR levels exhibit higher fertility levels than countries with a low total divorce rate (Figure 6d). In Figure
7 we additionally illustrate that the relationship between the extent of out-of-wedlock childbearing and the
level of fertility has reversed along with the shifting centrality of marriage. In particular, a cross-sectional
comparison on European countries in 1975 reveals a negative correlation between the level of extra-marital
fertility and total fertility. In 2001–02, this correlation has become positive, and along with this reversal,
the Southern European countries, Italy and Spain, stand out as combining both lowest-low fertility and the
lowest prevalence of non-marital fertility.
In summary, the above analyses reinforce the argument that the emergence of lowest-low fertility during
the 1990s has been associated with fundamental shifts in the relationships between fertility and marriage.
In particular, there has been an increasing disconnection between marriage patterns and fertility levels after
the emergence of lowest-low fertility in the 1990s in cross-sectional analyses of European countries,
and marriage formation and dissolution are no longer important predictors of national fertility levels in
cross-sectional analyses of European countries during the late 1990s (see also Heuveline et al. 2003). Moreover,
the above analyses show that the aggregate cross-country relationship between partnership formation/
dissolution and levels of fertility has become quite indeterminate in the late 1990s, which is strikingly
different from the strong relations between fertility and union formation and dissolution that prevailed 20
12
0.6 0.8 1.0 1.2 1.4
Total first marriage ratio (TFMR), 1975
Total fertility, 1975
(a) Total fertility and first marriage: 1975
1.6 2 3 4
Correlation coefficient = +0.50
0.4 0.5 0.6 0.7
Total first marriage ratio (TFMR), 2001/02
Total fertility, 2001/02
(b) Total fertility and first marriage: 2001/02
1.1 1.3 1.6 2
Correlation coefficient = −0.02
Lowest−low fertility
0.0 0.1 0.2 0.3 0.4 0.5
Total divorce ratio (TDR), 1975
Total fertility, 1975
(c) Total fertility and divorce: 1975
1.6 2 3 4
Correlation coefficient = −0.48
0.1 0.2 0.3 0.4 0.5
Total divorce ratio (TDR), 2001/02
Total fertility, 2001/02
(d) Total fertility and divorce: 2001/02
1.1 1.3 1.6 2
Correlation coefficient = 0.27
Lowest−low fertility
Figure 6: Relationship between total fertility, marriage and divorce in 1975 and 2001/02
Notes: See Table A.1 for the data and list of countries. The ‘×’ mark gives the exact position of a country, while
the area of circle is proportional to the country’s population size in 1975 or 2002. The regression line included in the
figures is obtained from a weighted regression with weights equal to the population size. Source for data: Council of
Europe (2003).
13
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Proportion of extra−marital births, 1975
Total fertility, 1975
(a) Total fertility and extra−marital births: 1975
1.6 2 3 4
Correlation coefficient = −0.41
0.0 0.1 0.2 0.3 0.4 0.5 0.6
Proportion of extra−marital births, 2001/02
Total fertility, 2001/02
(b) Total fertility and extra−marital births: 2001/02
1.1 1.3 1.6 2
Correlation coefficient = +0.61
Lowest−low fertility
Figure 7: Relationship between the proportion of extra-marital births and total fertility in 1975 and 2001/02
See Notes to Figure 6. Source for data: Council of Europe (2003).
years earlier. In addition, further analyses—not reported here in detail—reveal important differences in
home-leaving, union formation and dissolution between lowest-low fertility countries (see also Billari et al.
2001). On the one hand, the Southern European pattern is characterized by late separation from the parental
household, a low prevalence of cohabitation and extra-marital fertility, and a high centrality of marriage
with long-term commitments and low rates of divorce. On the other hand, the Central and Eastern European
pattern is more diverse and characterized earlier home-leaving, lower rates of marriage and higher rates of
divorce and extra-marital fertility than the Southern European pattern.
2.2 Fertility-related Patterns of Labor Force Participation
In addition to witnessing a changing relation between fertility and marriage or divorce, the 1990s have also
challenged the conventional wisdom about the aggregate-level relation between total fertility and women’s
labor force participation. In particular, conventional economic theory predicts that increases in the wage rate
of women lead to increases in women’s labor force participation on the one side, and decreases of fertility
on the other side due to increased opportunity costs of children in combination with a low income elasticity
of the number of children (Becker 1981; Cigno 1991;Willis 1973). At the macro level, this relation has been
14
Female labour force participation ratio, 1975
Total fertility, 1975
0.3 0.4 0.5 0.6
(a) Total fertility and labour force participation: 1975
1.6 2 3
corr = -0.61
Spain
Italy
West-Germany
France
Netherlands
Denmark
Sweden
Female labour force participation ratio, 1996
Total fertility, 1996
0.5 0.6 0.7
(b) Total fertility and labour force participation: 1996
1.3 1.6
corr = +0.81
Lowest-low fertility
Spain
Italy
West-Germany
France
Netherlands
Denmark
Sweden
Figure 8: Relationship between the labor force participation of women and total fertility in 1975 and 1996
See Notes to Figure 6. Source for data: Kögel (2004).
translated into the hypothesis that total fertility and female labor force participation rate (FLFPR) should be
inversely related in cross-country studies.
In this section we investigate the empirical evidence for this hypothesis as part of our overall attempt in
this paper to portrait the socioeconomic context of lowest-low fertility trends. In particular, several recent
studies have documented that the cross-country correlation between the total fertility level and women’s
labor force participation (FLFPR) has changed its sign in OECD countries during the mid 1980s and early
1990s (Ahn and Mira 2002; Engelhardt et al. 2004; Kögel 2004; Rindfuss et al. 2003). This finding is
also confirmed in regression-based analyses (Brewster and Rindfuss 2000; Esping-Andersen 1999), where
the labor force participation of women has a positive (and significant) influence on the total fertility in
cross-sectional analyses of OECD countries in the 1990s, while comparable analyses for the 1970s reveal a
negative influence.
This reversal is depicted in Figure 8 that plots total fertility levels against female labor force participation
rate (FLFPR) for 1975 and 1996. We focus in Figure 8 on Western Europe, where the labor force
participation of women has traditionally been very different between countries (the countries included in
Figure 8 include Austria, Belgium, Denmark, Finland, France, West-Germany, Ireland, Italy, Luxembourg,
Netherlands, Norway, Sweden, Switzerland, United Kingdom, Greece and Spain). In 1975, countries with a
15
high FLFPR, such as Sweden or Denmark, exhibited low fertility in a European comparison, while countries
with low FLFPR, such as Italy or Spain, had relatively high fertility. In 1996, high FLFPR is associated with
high fertility, such as in Denmark and Sweden, while lowest-low fertility countries such as Italy and Spain
are characterized by a quite modest participation of women in the labor market. It is also important to note
that changes in fertility levels—rather than changes in the labor force participation of women—have been
more prevalent in the countries in Figure 8, and the relative country positions with respect to female labor
force participation rates have been remarkably constant during the period 1975–96 (e.g., see the labeled
points in the figure).
The above findings about the changing association between total fertility levels and women’s labor force
participation has spurred several additional analyses that investigate this issue further. Ahn and Mira (2002),
for instance, emphasize the relevance ofMediterranean countries in the above pattern because the emergence
of lowest-low fertility is an important factor contributing to the reversal of the correlation. Brewster and
Rindfuss (2000) also emphasize the role of institutional arrangements, e.g., different family policies, childcare
systems or welfare state typologies, and they stress the altered social norms regarding the combination
between childrearing and labor force participation of women. Specifically, lowest-low fertility in Southern
Europe has occurred in a context with a very low compatibility of childbearing with woman’s labor market
participation, which is due to the difficulties in entering and re-entering the labor market and the limited
flexibility of working hours (Bettio and Villa 1998; Del Boca 2002).
3 Explaining the emergence of lowest-low fertility: Incentives, social interactions
and institutional factors
After characterizing the basic patterns of European low fertility and their relation to marriage, divorce and
labor force participation, we explore in this section the socioeconomic conditions and individual-level determinants
that underlie this transformation of the demographic landscape in Europe. We initially focus on
the delay of childbearing that we have emphasized in our earlier analyses as one of the central demographic
aspects in understanding lowest-low fertility. The basic starting point of our discussion is the observation
that fertility is a dynamic process over the life-course. When individuals progress through their life-course
and make plans for the future, they can decide—possibly sequentially—how many children they have in
total, which is denoted as the quantum of fertility, and they can also decide when they have these children,
which is denoted as the timing or tempo of fertility. Individuals have considerable control over the timing
of fertility. Specifically, due to the widespread availability of reliable contraception in most lowest-low fertility
countries, we can assume that births are looked for, or at least, not intentionally avoided. In such a
context, there are different reasons why individuals may not have an extra child for the moment: one may
plan to have a child at a later time, or one may plan not to have a child at all, or one might not have a
clear idea about these future plans. It is important that this decision to postpone childbearing can be revised
afterwards. There is no irreversible commitment associated with plans to delay fertility, at least within the
biological and medical limits that determine the ages of childbearing. This flexibility is in sharp contrast to
the transition into parenthood, which is generally irreversible once a child is born. This asymmetry between
the irreversibility of childbirth and the reversibility of future plans about the timing of fertility provides an
incentive to postpone the decision of having children. A postponement can reduce the uncertainty about
16
Table 3: Economic indicators and gross university enrollment ratios for lowest-low fertility countries
Country Economic Indicators Gross University Enrollmentc
GNI GDP GDP Average Women Men
per average growthb inflation
capitaa growthb 1989 1999– 1989 1999–
1999 1990–99 1999 1990–99 2000 2000
Greece 12.1 2.2 3.4 6.2 25.3 56.2 24.4 53.2
Italy 20.2 1.4 1.4 3.4 29.1 52.8 30.3 40.7
Spain 14.8 2.2 3.7 3.1 33.8 62.3 36.3 53.0
Bulgaria 1.4 -2.7 2.4 116.5 28.2 50.1 24.4 35.7
Czech R. 5.0 0.8 -0.2 7.7 13.9 29.1 17.7 28.2
Estonia 3.4 -1.3 -1.1 15.5 26.5 62.6 25.7 43.3
Hungary 4.6 1.0 4.5 17.4 14.9 40.5 13.7 33.1
Latvia 2.4 -4.8 0.1 9.2 29.0 62.4‡ 20.4 37.9‡
Romania 1.5 -0.8 -3.2 61.4 8.4 24.3† 8.6 20.8†
Slovenia 10.0 2.4 4.9 9.9 27.8 61.3‡ 22.3 45.7‡
Armenia 0.5 -3.2 3.3 32.5 23.8d 14.0† 23.8d 10.5†
Belarus 2.6 -3.0 3.4 169.6 50.3 56.2 45.5 43.7
Russia 2.3 -6.1 3.2 52.0 58.9 73.0 48.4 57.4
Ukraine 0.8 -10.7 -0.4 69.8 45.8d 46.0‡ 45.8d 40.4‡
Notes: (a) GNI per capita = gross national income per capita in thousand US$; (b) GDP = gross national
product; (c) gross university enrollment ratio is the total enrollment in university education, regardless
of age, divided by the population of the age group which officially corresponds to university education;
(d) enrollment ratio pertains to males and females combined. Calendar year: (†) 1996; (‡) 1998–99.
Sources: The World Bank, Data & Statistics (available at http://www.worldbank.org; UNESCO, Institute
for Statistics (online available at http://www.unesco.org)
the costs and benefits of children, and also the uncertainty associated with the economic situation and the
stability of partnerships in early adulthood.
3.1 The socioeconomic background of delayed childbearing in lowest-low fertility countries
The socioeconomic context of decisions about timing of parenthood varies substantially across lowest-low
fertility countries, and there is a striking difference between Southern European and Central/Eastern European
(CEE) countries. In Southern European countries, per capita income levels are at medium to high
levels with steady growth, and these countries have also experienced low inflation (Table 3). At the same
time, the entry into the labor market for young adults is extremely difficult (Table 4). The three lowest-low
fertility countries in Southern Europe have the highest youth unemployment rates in the European Union in
1999, and this situation has been essentially unchanged since 1989. Unemployment rates are also higher for
females than for males, in contrast to Northern European countries. The link between unemployment and
low fertility is also supported by the observation that the only Southern European country with relatively
high fertility is Portugal, with considerably lower unemployment rates than its Mediterranean counterparts.
The chronic high unemployment situation in Southern Europe has discouraged young adults from entering
the labor market and made higher education more attractive, and it has deteriorated working conditions
17
Table 4: Youth unemployment rates (under 25) in Southern Europe
Country Women 1989 Women 1999 Men 1989 Men 1999
Italy 38.5 38.3 25.9 28.6
Greece 34 39.3 17 21.4
Spain 42.6 37.3 24.4 21.7
Portugal 15.8 11.1 8.3 7.5
EU (15) 19.6 19.2 14.4 16.7
Source: OECD, Employment Statistics (available at http://www.oecd.org)
to sometimes precarious situations with mostly low-paid temporary jobs. In addition, there is a crowdingout
process in which more educated young people are displacing less educated people from their traditional
positions (e.g., Dolado et al. 2000). The labor market uncertainty and poor economic prospects in early
adulthood also facilitate the commonly observed behavior of prolonging the stay in the parents’ household
until relatively late ages. In both Italy and Spain, for instance, the successful entry into the labor force tends
to accelerate household and union formation (Billari et al. 2002).
There is also considerable heterogeneity in the determinants of low fertility and postponement among
Eastern Europe countries and former Soviet Republics. While all of these countries share the common experience
of the transition from a planned to a market economy, the success of this transition and the economic
hardship during the transformation have varied considerably. Some of these tremendous differences in income
levels and economic outcome during the transition period are documented in Table 3. Most of the CEE
countries with lowest-low fertility, and in particular those in the former Soviet Union, have experienced a
decline in output over the transition period. Many countries have also experienced a substantial surge in
inflationary pressures during the economic crisis. This is especially the case in the former Soviet Union, and
countries such as Bulgaria or Romania. In addition, income levels have been very volatile in all transition
countries in Table 3, and the median income fluctuated from year to year by as much as 25 per cent (Forster
and Toth 1997; Lokshin and Ravallion 2000). Similarly, labor turnover has been very frequent and lead
to common spells of unemployment. For instance, 57 per cent of Russian women during 1994–1998 were
very concerned about the possibility of not being able to provide themselves with the bare essentials in the
following year (Kohlmann and Zuev 2001; see also Kohler and Kohler 2002).
The structure of wages and employment has also been transformed in Central and Eastern European
transition countries. The returns to human capital have considerably increased as compared to the pretransition
period, and young cohorts can expect reward levels for skills that approach—or are comparable
to—the returns in western European countries (e.g., Munich et al. 1999; Newell and Reilly 2000; Orazem
and Vodopivec 1995; Rutkowski 1996). In contrast, there has been a decline in the returns to experience for
low educated people. As a result, poverty is particularly common among the low educated and those having
more than two children (Grootaert and Braithwaite 1998; Milanovic 1998).
18
3.2 Postponement as a rational response to socioeconomic incentives
Based on the above sketch of the socioeconomic background, we can investigate the individual-level determinants
of delayed childbearing in lowest-low fertility countries. In particular, an important commonality of
the socioeconomic context in lowest-low fertility countries is a high level of economic uncertainty in early
adulthood. This uncertainty provides an incentive to delay decisions that imply long-term commitments,
such as the decision to have children, and it provides an incentive to invest in education and human capital.
In the Southern European countries, the uncertainty is basically due to youth unemployment and/or job
instability. High unemployment risks simultaneously lower the opportunity costs of pursuing higher education
and create incentives for education due to the increased employment opportunities. Higher education
has thus become the primary pathway for individuals to increase their chances of finding a stable job with
a sufficient wage (Lassibille et al. 2001; Sá and Portela 1999). In the CEE countries, the uncertainty is due
to the overall economic insecurity and hardship caused by the transition. Moreover, the economic transition
has increased the returns to education. The combination of these factors has rendered human capital
investments very attractive since these investments provide insurance against poverty and enable access to
more stable employment with relatively high salaries. The main problem in attaining education faced by
individuals in Eastern Europe is that the opportunity costs may be too high in some of the poorest countries.
Parents may have problems financing higher education of their children since they are also affected by the
transition, and credit constraints may preclude access to loans in order to cover tuition and consumption
during studies.
The university enrollment ratios in Table 3 reflect the drastic increase in higher education in Southern
European countries where half of the women pursue university studies in the late 1990s. Central and Eastern
European countries share this general trend towards increased enrollment ratios, particularly for women.
Estonia, Slovenia, Latvia and Bulgaria, have strongly increased their enrollment ratios to levels comparable
to western countries. The levels in the Czech Republic, Hungary and Romania have also increased, but since
these countries started at much lower levels they are still lagging behind. The only deviations from the trend
towards increased higher education are among the former Soviet Republics.
The comparison of the evolution of university enrollment with the mean age at childbearing is very illuminating.
The countries with marked increases in higher education tend to be identical to the countries with
the most pronounced delays in the mean age at first birth. This association between delays in childbearing
and increases in individuals’ human capital investments is consistent with our hypothesis: increasing returns
to education induce young adults—and particularly young women—to study for a longer time in the expectation
that this improves their ability to cope with the economic uncertainty and to take advantage of the
new opportunities created during the transition period. Exceptions to this general pattern seem to be concentrated
among countries where the economic situation is worst, and where the coping strategy of higher
education and human capital investments is not accessible for important fractions of the population. In addition
to the human capital motive for delaying childbirth, the very unstable standards of living in Eastern
Europe also lead to a strategic postponement in which children—and similar decisions implying long-term
commitments—are deferred in the expectation that the uncertainty about future prospects is reduced over
time.
Changes in social policy are an important additional factor in the former socialist countries. In the
socialist period many countries had developed a system of incentives that rewarded early childbearing, for
19
instance via easier access to housing and paid maternity leave. These incentives resulted in a reduced age
at motherhood, especially during the 1980s (Frejka 1980; Zakharov and Ivanova 1996). During the 1990s
many of these benefit structures have ended, or eroded due to inflation, or were modified, and this fact has
also contributed to the postponement of motherhood in the last decade.
A further determinant of the postponement–low-fertility nexus is the delay of childbearing in association
with investments in housing and durables. This is especially relevant in Italy and Spain, where the interference
of childbearing with educational investments has been much reduced due to the delay of parenthood
to very late ages. In these countries, the preponderance of own property in the housing market and the restricted
rental market induces young people to stay at home with their parents until their financial resources
are adequate for paying the mortgage (Duce Tello 1995). Since this can take several years after entry in the
labor market, this process can lead to delays of childbearing substantially beyond the completion of higher
education.
3.3 Social feedback effects on the timing of fertility
The previous section has primarily focused on individuals’ incentives that render delayed childbearing more
advantageous. The discussion of these individual-level determinants of timing decisions, however, is not
sufficient to understand the fertility change in contemporary Europe and other developed countries. In
particular, we believe that important social feedback mechanisms reinforce individuals’ behavior changes
to socioeconomic conditions, particularly with respect to changes in the timing of fertility. Social feedback
exert important influences on the dynamics of the fertility postponement for at least three reasons (Kohler
et al. 2000; Montgomery and Casterline 1996):
Social learning about the optimal timing of fertility: The optimal timing of fertility is a highly complicated
problem for women or couples, especially in the context of uncertainty and changing socioeconomic
environments. Social learning provides a possibility to simplify and augment decision-making in this context.
Childbearing and career experiences of friends are therefore likely to influence women’s and couples’
decisions about the timing of fertility. For instance, the interaction with others can provide information
about questions like “How did classmates, who had their first child relatively early, fare in terms of career
and partnership?” and “What is the divergence in social and economic attainment between those who had
their children early as compared to those who had them later?” In addition to this possibility to learn from
others, social learning also implies an aggregate-level feedback mechanism. In particular, in a population
that delays childbearing, social learning from others implies that the experience of friends having children
is revealed at an increasingly later age. A woman at some given age, say age 25, therefore faces more uncertainty
about the advantages and disadvantages of childbearing in a population that exhibits a late pattern of
childbearing as compared to an identical woman in a population with early childbearing. Higher uncertainty
in turn implies a further incentive to delay childbearing. Social learning therefore implies a multiplier effect
that reinforces the impact of socioeconomic changes that lead to delayed patterns of childbearing.
Social feedbacks mediated through the marriage market: In many lowest-low fertility countries, partnership
formation and marriage are inherently connected with the transition into parenthood. This is particularly
the case in Italy and Spain, where out-of-wedlock childbearing is still relatively rare, pre-marital
cohabitation is not wide-spread, and the trend towards late childbearing is associated with late home-leaving
and late union-formation (De Sandre 2000; Delgado and Castro Martín 1998). An important demographic
20
implication of this trend towards late union-formation is the induced shift in the composition of potential
mates in the marriage market. While the traditional literature on marriage squeezes emphasizes the effect
of differential cohort sizes (e.g., Goldman et al. 1984; Grossbard-Shechtman 1985), similar implications
are caused by changes in the age-distribution of union formation. In particular, a general delay of partnership
formation in the population reduces the marriage market ‘costs’ encountered by individuals who delay
marriage/cohabitation: first, it increases the probability of finding a partner at later ages, for instance after
finishing more extended education, and second, it increases the expected ‘quality’ of marriageable partners
at older ages because the marriage market will be ‘thicker’ and contain more potential mates at any given
age. Socioeconomic changes that provide incentives for delayed childbearing, for instance higher returns
to female education or technological innovations facilitating fertility control, therefore affect the timing of
marriage in a twofold manner: on the one hand, via a direct effect on individual’s incentives to delay, and
on the other hand, via an indirect effect through the reduction in the costs of delaying marriage/cohabitation
for individuals. The latter aspect gives again rise to a social multiplier effect (for a formal analysis and
application to the U.S., see Goldin and Katz 2002).
Social feedbacks through competition in the labor market: A further potentially relevant mechanism of
social interaction is competition in the labor market that is caused by the presence of high unemployment.
In this situation, the labor market can give rise to a social multiplier effect, quite similar to the mechanism
operating through the marriage market above (for a related formal model, see Kohler 2001, Chapter 6).
In particular, social interaction reinforces the effect of unemployment and economic uncertainty towards
delayed childbearing. This social multiplier effect arises because women with children tend to have lower
labor supply than women without children, especially in those low and lowest-low fertility countries with
inflexible labor markets and insufficient supply of day-care. In this situation, a delay of childbearing in
the population increases the level of childlessness among women at the primary ages of entering the labor
market. This increased childlessness leads to an increased female labor supply, which in turn increases
the competition and unemployment risks during early adulthood. The postponement of fertility caused by
unemployment during early adulthood is therefore exacerbated through a feedback process that increases
the overall female labor supply in the age groups that are most affected by economic stress.
We argue in this section that, as a result of these social feedback mechanisms, the delay of childbearing
follows a postponement transition that shares many characteristics of the fertility transition in Europe or
contemporary developing countries (e.g., see Bongaarts and Watkins 1996). This notion of a postponement
transition is substantiated in Figure 9. In this figure we define the year of onset of the postponement transition
as the first in a group of three years during which the mean age at first birth increases by more than .3
years. Within lowest-low fertility countries, this year of onset ranges from 1978 (Italy) to 1994 (Lithuania,
Armenia) and 1997 (Belarus) (Table 2). The horizontal axis in Figure 9 plots the years since the onset of
the postponement transition, and the vertical axis depicts the change in the mean age at first birth since
this onset. In order to avoid a cluttering of the graph, we display some CEE countries with a very recent
onset in a sub-graph. In addition we include several other European countries for comparison. Particularly
interesting in this context are the Netherlands that are representative for a Western European country with
an early onset of the postponement transition (1972) and a moderately high total fertility rate (1.73 in 2002).
The figure reflects the substantial increases in the mean age at first birth in lowest-low fertility countries
that we have emphasized throughout this paper. More importantly, the standardization of the time-scale in
21
−10 0 10 20 30
0 1 2 3 4 5
Years since onset of transition
Cumulative increase in mafc
Aus 84
Bul 92
Cro 78
Cze 91
Dk 67
Fra 73
Ger 72
Gr 83
Hun 80
It 78
Lit 94
NL 72
Sp 79
Swi 71
Lat 92
Sn 85
NL 72
Further
countries:
Arm 94
Rus 94
Bel 97
Further
countries:
Est 91
Pol 91
Ro 91
Sk 91
Figure 9: Onset and pace of the postponement transition in European countries
Note: Graph includes all European countries in Tables 1–2, with exception of Andorra, Bosnia and Herzegovina,
Moldova, Ukraine, and United Kingdom for which adequate data are missing. For country codes, see Table A.1.
Source for data: Council of Europe (2003).
22
this figure reveals several key characteristics that seem to be inherent to the postponement of fertility: (a) the
onset of delayed childbearing in low and lowest-low fertility countries is a break with an earlier regime that
is characterized by a relative stability in first-birth timing; (b) once initiated, the postponement transitions
tend to be persistent and irreversible, leading to large changes in the mean age at first birth; (c) the broad
characteristics of the postponement transition are similar across a wide range of socioeconomic conditions:
for instance, the paths for all countries with an onset of the transition up to 1991—that is, Austria, Croatia,
the Czech Republic, Denmark, Estonia, France, Germany, Greece, Hungary, Italy, the Netherlands, Poland,
Romania, Slovenia, Slowak Republic, Spain and Switzerland—trace each other closely. This similarity
occurs despite the fact that these countries represent very different socioeconomic conditions in Europe,
including also very different patterns of post-1990 economic crises in Eastern Europe and very different
levels in the mean age at first birth prior to the postponement transition. For countries with an onset of the
transition after 1993 it is still very early to make inferences about the path of the postponement transitions,
but it seems very likely that they will follow the other lowest-low fertility countries.
The above postponement transition towards late childbearing regimes, which is in our opinion likely
to occur in many European and other developed countries, can therefore be been seen as a further step in
a long-term transformation of fertility and related behaviors. In particular, the above discussion suggests
that the long-term trend towards low and lowest-low fertility in Europe is related to three distinct transition
processes: the (first) demographic transition leading to parity-specific stopping behavior within marriage,
the second demographic transition resulting in ideational changes and in the rise of non-marital family forms,
and most recently, the postponement transition that shifts the timing of fertility towards a late childbearing
regime. The postponement transition is therefore a third step that follows the control of marital fertility and
the transformation of partnership behaviors, and it implies a delay of parenthood towards later age as the
combined result of individual incentives for late childbearing and social interaction effects that reinforce this
trend.
It is also clear that the upper age-limit to childbearing prevents substantial future postponement without
changing the age-pattern of parity-specific fertility rates. Yet, in many CEE countries with still relatively
early childbearing the postponement of birth, even at relatively rapid annual rates such as an annual increase
in the mean age at first birth by .2, can continue for at least two to three decades until they reach the late agepatterns
of fertility currently observed among Northern and Southern European countries. In Western and
Southern European countries with an already very late age-pattern of childbearing, a differential postponement
of fertility across age-groups can continue for a considerable time. For instance, borrowing a popular
idea on human longevity, one may foresee a rectangularization of fertility patterns. This rectangularization,
which needs not be only a feature of lowest-low countries but of all below-replacement fertility countries,
is characterized by a concentration of childbearing in an increasingly narrow age-interval. In this scenario,
few women will have children prior to, say, age 28 or 29, and childbearing at parity one and two will be
concentrated when women are in their thirties. There will be very few higher parity births, especially among
women with a late onset of childbearing.
3.4 Determinants of the quantum in lowest-low fertility countries
There is quite widespread agreement in the literature that lowest-low fertility countries share an institutional
setting that implicitly favors a relatively low quantum of fertility. For instance, the lowest-low fertility coun-
23
tries in Southern Europe, Italy and Spain, provide highly insufficient child-care support (Esping-Andersen
1999). In the 1980s, for instance, the share of children below age 3 with day-care coverage in Southern
Europe was 4.7%, with respect to 9.2% in Continental Europe (Austria, Belgium, France, Germany and
the Netherlands) and 31.0% in the Nordic countries (Denmark, Finland, Norway and Sweden) (Esping-
Andersen 1999). The labor market is also relatively inflexible in terms of possibilities for part-time work
or re-entering the labor force after an absence due to child-birth (Del Boca 2002; González et al. 2000;
Stier et al. 2001). This hinders the combination of female labor force participation and childbearing. In
comparison with other Western European countries, Italy and Spain also have among the lowest levels of
state support for families with children in terms of tax allowances or direct transfers (Esping-Andersen
1999). While this deficit is partially compensated through strong family networks, as for instance through
the provision of child-care or economic resources by grandparents (Reher 1997), this substitution of family
support for public support is likely to be insufficient in contemporary industrialized countries. Moreover,
the high integration of young adults in their parents’ home and extended family may even discourage union
formation and fertility (Dalla Zuanna 2001).
Family roles in the Southern European lowest-low fertility countries have also been slow in adapting to
the new role of women (Chesnais 1996). Italy and Spain have a highly asymmetric labor divisions within
households, which becomes even more asymmetric after the birth of the first child (Palomba and Sabbadini
1993). The countries therefore conform with McDonald’s (2000a) argument about gender equity: fertility
falls to very low levels when gender equity rises in individual-oriented institutions, like the labor market,
while it remains low in family-oriented institutions.
The moderate and very low quantum in Eastern Europe is in part determined by similar institutional
factors hindering high parity progression probabilities. In addition, many of the pronatalist—or at least
family friendly—policies in CEE countries have discontinued after 1990 (Macura 2000), and the economic
crisis has deteriorated particularly the high integration of women in the labor market. Furthermore, Eastern
Europe is characterized by a persistence of economic insecurity throughout the life-course. This is in contrast
to Southern Europe, where unemployment and economic stress are concentrated during early adulthood
years. In Eastern Europe, the uncertain long-term outlook regarding unemployment, the housing situation
and economic recovery implies that uncertainty affects not only the timing of the first birth but also the
transition to the second child and higher-parity children.
While the above institutional context—at least in Southern Europe—has been relatively constant in
recent decades, its effect on the quantum of fertility has not. In particular, the effect of this institutional
context needs to be investigated with an explicit attention to the rapid postponement that has transformed the
age-pattern of entering parenthood in lowest-low fertility countries. Specifically, the delay of childbearing
has been associated with substantially increased investments in higher education for females (Table 3).
Similarly, labor market experience prior to marriage and parenthood are likely to be higher for women with
late childbearing than for women with early fertility. A direct consequence of these increased levels of
female human-capital and labor market experience at the time of childbirth is an increase in the opportunity
costs of childbearing in terms of foregone wages.
This relation between the timing of fertility and the wage-level (measured around first childbirth) is
depicted by the broken line in Figure 10(a). The wage-level has been standardized so that it equals one for
women with an early onset of parenthood. It increases with a later age at first birth because the delay in
24
childbearing is generally associated with higher levels of human capital and labor-market experience that
are rewarded in the labor market. This rise in wages increases the opportunity costs of time spent outside
the labor-market, and it increases the costs of time-intensive ‘goods’ such as children. The opportunity cost,
however, is not as high as the wage level since there can be some labor force participation. In particular,
women with late childbearing can substitute away from ‘own’ child-care and into ‘purchased’ child-care
(kindergarten, household help, etc.). This implies that the opportunity costs of children increase less steeply
with delayed childbearing than the index of wages (for the moment we ignore other costs of children that
may potentially depend on the age at first birth, such as for instance health costs during pregnancy).
The extent of this difference between wages and opportunity costs of children, however, depends on the
compatibility of childbearing with female labor force participation. In a country with a low compatibility,
the ability to arrange a flexible part-time work, or the ability to find a position that can be combined with
institutional day-care, is limited. Hence, the scope for the above substitution from time-at-home to timein-
the-labor-market is restricted. The postponement-induced increase in wages therefore translates into
substantial increases in the opportunity costs of children, including also the opportunity costs of additional
children after the first child (see line AB in Figure 10a). These higher child-costs will tend to reduce the
quantum of fertility and the parity progression probabilities after the first birth.
If there is a high compatibility of childbearing and female labor force participation, wage increases
associated with late childbearing lead to more modest increases in the opportunity costs of children (see line
AC in Figure 10a). In particular, women will be able to shift relatively flexibly their time allocation from
time-at-home to time-in-the-labor-market, and this substitution diminishes the effects of increased wages
on child-costs. In addition, with high levels of female labor force participation there can also be a positive
income effect on the demand for children.
These differences between countries with high and low compatibility of work and children have important
implications for the causal effects of delayed childbearing on the quantum of fertility. In particular,
the higher human-capital associated with delayed childbearing translates directly into increased opportunity
costs of children. This effect is especially relevant when it is combined with the large delays in childbearing
that occur during the postponement transition. In this case, the postponement-induced increases in childcosts
are likely to imply substantial declines in individual’s demand for children of birth-order two and
higher.
Socioeconomic conditions that provide incentives for individuals to delay childbearing, such as uncertainty
in early adulthood, therefore indirectly increase the costs of children and have an indirect negative
impact on the desired number of children. This effect is particularly strong in the context of inflexible labor
markets and insufficient availability of day-care that characterizes Southern European lowest-low fertility
countries. Moreover, this effect is likely to constitute one of the key reasons why postponement effects,
which measure the reduction in completed fertility due to an additional year of delay in parenthood, are
particularly strong in Southern Europe (Kohler et al. 2002), and it explains the “falling behind” of cumulated
cohort fertility at higher ages in Italy and Spain as compared to countries such as the Netherlands or
Denmark that have combined late childbearing without important reductions in cohort and period fertility
(Billari and Kohler 2004).
In summary, the above discussion suggests that the postponement of fertility is not neutral with respect
to the quantum of fertility. Quite to the contrary, there is a negative association, and the magnitude of this
25
Postponement
effect
Postponement effect as a function of
compatibility of fertility and FLFP
low
compatibility
high
compatibility
Postponement effect = (relative) decline in completed
fertility associated with an additional
delay of childbearing by one year
Age at first
birth (AFB)
Wages =opportunity costs of time
not in labor market
Index of opportunity costs of
children with low compatibility
of children with labor-force
participation
early
AFB
late
AFB
1
Index of wages
and child-costs
b) Postponement effect and compatibility of fertility and
female labor force participation
a) Wages, child-costs, and compatibility of fertility and
female labor force participation
Compatibility of
fertility and female
labor force participation
(FLFP)
Index of opportunity costs of
children with high compatibility
of children with labor-force
participation
A
B
C
·
·e.g., Southern European
lowest-low fertility countries
e.g., Denmark or
Sweden
Figure 10: Postponement of fertility, wages and child-costs
26
negative effect of delayed parenthood on the quantum of fertility depends mainly on the compatibility of
work and children (Figure 10b). On the one hand, countries with low compatibility between female labor
force participation and childbearing, such as Italy and Spain, are subject to large postponement effects.
These countries therefore experience substantial reductions in completed fertility that are causally related to
delayed childbearing. On the other hand, in countries with a high compatibility of work and children, as for
instance Denmark or Sweden, the increased costs of time-at-home associated with delayed parenthood can
be partially accommodated by increasing the labor force participation. These countries are therefore likely
to have a smaller postponement effect, and late childbearing in itself does not imply strong reductions in the
quantum of fertility. The above analyses also suggest that differential postponement effects—as depicted in
Figure 10b—constitute an important determinant of the differential reductions in second and higher order
fertility in European countries as a result of delayed childbearing. Differences in these postponementquantum
interactions are therefore likely to be an important factor underlying the divergence of fertility
levels between low and lowest-low fertility countries in Europe that we have emphasized in our introductory
section.
3.5 The future of lowest-low fertility—some speculations
Three questions seem to be of central importance in assessing the future of lowest-low fertility. First, is
lowest-low fertility a permanent, long-term phenomenon or is it merely a transient phenomenon that will
disappear from the demographic landscape in the near future? Second, has lowest-low fertility already
reached its lowest levels, or are future declines in fertility likely? Third, is the emergence of lowest-low
fertility likely to be a wide-spread phenomenon, or will it remain restricted to regions such as Southern,
Central and Eastern Europe, where this pattern is currently concentrated? Our evaluation of the future of
lowest-low fertility indicates that this pattern is unlikely to be a short-term phenomenon that will quickly
disappear from the demographic landscape. In our opinion, lowest-low fertility is likely to be a persistent
pattern, at least for several decades. We expect that it prevails for a considerable period in the CEE countries
with a TFR below 1.3. In addition, we believe that lowest-low fertility is likely to spread in the near future
to several other countries that currently experience a TFR between 1.3 and 1.4 (see Tables 1–2). These
European ‘lowest-low fertility candidates’, for instance, include Austria, Germany, Switzerland, and several
Central/Eastern European countries like Poland, Lithuania, Slovakia, Russia and Croatia, comprising overall
a population of 248 million people. It is also likely that fertility declines further in some countries that have
already very low levels of fertility. In particular, several Eastern European countries and former Soviet
Republics—have experienced TFR levels below 1.3 without a pronounced postponement of fertility (Figure
9). Once the pace of fertility postponement in these countries increases, it is likely to depress fertility levels
further, perhaps even to TFR levels below 1.0. At the same time, the periods with the most rapid pace
of postponement may have already passed in Southern European lowest-low fertility countries. Annual
increases of the mean age at first birth may thus start to decline in the next years, resulting in a possible
reversal of fertility trends in Italy and Spain. Some first signs of this pattern are already visible. In the
last few years, the Italian and Spanish TFRs have recovered from their troughs of 1.20 (Italy, 1995–96)
and 1.17 (Spain, 1996), and the total fertility rate in both countries TFR increased to 1.3 by 2003. This
recovery has been associated with a decline in the pace of fertility postponement during the late 1990s
(Figure 11). A similar reduction occurred in Western and Northern European countries with very advanced
27
-0,40
-0,20
0,00
0,20
0,40
0,60
0,80
1,00
1,20
1,40
Western & Northern
Europe
Southern Europe Central Europe & Baltic
countries
Absolute increase in MAFB
1970-75 1975-80 1980-85
1985-90 1990-95 1995-2000
Figure 11: The increase in the mean age at first birth in European regions since 1975
Source: Sobotka (2004b)
ages of childbearing, while Central European and Baltic countries took the lead in the pace of postponement
towards the late 1990s—albeit at a younger mean age at first birth than theirWestern, Northern and Southern
European counterparts (Sobotka 2004b; see also Table 2).
In a global perspective it is in our opinion unlikely that lowest-low fertility remains restricted to Europe.
Particularly South-East Asian countries might cross the lowest-low barrier. Two important countries, Japan
and Korea, have joined the group of lowest-low fertility countries during 2000–03 (Tables 1–2; Suzuki
2003), and regions of Hong-Kong and Macao already experienced lowest-low fertility levels during the
1990s. These countries are potentially forerunners in a spread of very low fertility levels to South-East Asia.
A recent study on low fertility in urban China (Zhao 2001) has also shown that the one-child policy reduced
the total fertility rate of urban China to a level of 1.15 starting in 1980, and the Chinese urban population
may already constitute one of the largest lowest-low fertility populations worldwide.
4 U.S. versus European fertility: what explains the difference?
In striking contrast to the projected population shrinkage due to low fertility and negative population momentum
in Europe, the U.S. population continues to be characterized by rapid growth (Figure 3). Almost 33
million people were added to the U.S. population between 1990–2000, corresponding to a growth of 13%
during the 1990s, making it the greatest absolute 10-year population increase in U.S. history. The majority
of this growth in recent years is attributed to natural increase—that is, an excess of birth over deaths—
while net immigration accounted for about 40% (Kent and Mather 2002). Moreover, population growth
was concentrated in the South and West of the United States. Slow population growth on the state-level is
primarily concentrated in the northern and eastern parts of the United States, and population decline during
1990–2000—mostly as a result of migration losses—occurred almost exclusively in some rural counties
28
Table 5: Projected Population of the United States, by Race and Hispanic Origin: 2000 to 2050
Population and race or Hispanic
origin
2000 2010 2020 2030 2040 2050
TOTAL 282,125 308,936 335,805 363,584 391,946 419,854
White alone 228,548 244,995 260,629 275,731 289,690 302,626
Black alone 35,818 40,454 45,365 50,442 55,876 61,361
Asian Alone 10,684 14,241 17,988 22,580 27,992 33,430
All other racesa 7,075 9,246 11,822 14,831 18,388 22,437
Hispanic (of any race) 35,622 47,756 59,756 73,055 87,585 102,560
White alone, not Hispanic 195,729 201,112 205,936 209,176 210,331 210,283
Notes: (a) Includes American Indian and Alaska Native alone, Native Hawaiian and Other Pacific Islander alone, and
Two or More Races. Source: U.S. Census Bureau, 2004, “U.S. Interim Projections by Age, Sex, Race, and Hispanic
Origin,” , Internet Release Date: March 18, 2004
stretching across the Great Plains states from the Mexican border to the Canadian border (U.S. Census Bureau
2001). The U.S. population is also projected to grow by almost 50% in the coming decades (Table 5),
including a 7% growth of the white non-Hispanic population, a 188% increase in the Hispanic population
and a 213% increase in the Asian population until 2050.
While the divergence of fertility trends between the U.S. and Europe is well-known, resulting also in
predictions about a growing “demographic marginalization” of Europe within the global population (e.g.,
Demeny 2003; The Economist 2002a,b), it is somewhat surprising that the U.S. high level of current and
projected fertility is not shared with Canada. Although the U.S. and its northern neighbor share a long
border, overlapping cultures and similar socioeconomic contexts, Canada’s total fertility rate was just 1.5
children per woman in 2000, compared with the United States’ rate of 2.1. Canada’s fertility is more in
line with that of Europe, Japan, and Australia than that of the United States. The most recent divergence in
fertility rates between the U.S. and its northern neighbor originates in the mid-1970s, when fertility in both
countries declined to about 1.8. In contrast to the U.S., where the total fertility rate edged back up to 2.1,
however, the Canadian rate never recovered from the 1970 baby bust. Moreover, while minority populations
in the United States—especially Hispanic immigrants—have higher fertility rates than many of the minority
groups in Canada, the higher fertility rates of blacks and Hispanics by itself explains only about 40 percent
of the differences in total fertility rates (Belanger and Ouellet 2002; Kent and Mather 2002).
A frequently cited explanation for higher American fertility is that the United States is more racially and
ethnically diverse than other more developed countries. The largest U.S. minority groups tend to have higher
fertility than the white non-Hispanic majority, and foreign-born women tend to have higher fertility than
U.S.-born women. Because minorities and immigrants make up an increasing share of the U.S. population,
these racial and ethnic differences may keep fertility at the same relatively high level for decades to come.
While correct, the racial and ethnic diversity of the U.S. explains just part of the fertility gap between the
United States and other more developed countries. The TFR for non-Hispanic whites was about 1.8 for most
of the 1990s, and inched up to 1.87 in 2000—lower than the TFR for Hispanics and blacks, but still higher
29
than in other more developed countries.
The key to understanding the relatively high U.S. fertility seems to lie in the relatively young age pattern
of fertility, the only modest pace of fertility postponement and in the relatively high compatibility of childrearing
and labor force participation (Morgan 2003; see also Tables 1–2). In terms of day care for children,
the United States provides an example of business and volunteer organizations increasing the availability of
child care, and with federal and state government playing a relatively minor role in the provision of child care
services (Rindfuss et al. 2003). The use of child care is also viewed positively. Within the United States, for
example, the proportion agreeing that “a preschool child suffered if the mother works” declined from 68%
in 1977 to 48% in 1991 for the adult population, and declined from 73% in 1970 to 34% in 1991 for married
women of childbearing age (Rindfuss et al. 1996). In West Germany in 1996, 76% of the adult population
think small children suffer if their mother goes to work (European Commission 1998). The nature of the job
market is also an important consideration. One strategy available to parents is to stagger their working hours
so that at any given time only one parent is working. In the United States, among dual earner couples with
children under 14, in 1997, 31% had at least one parent who worked some schedule other than a fixed daytime,
Monday through Friday, schedule (Presser 1999). Related to working hours is the time when grocery
and other stores are open. In many countries, there has been a shift towards stores staying open longer hours,
thus making it easier for working parents to shop for the necessities of everyday life. In addition, based on a
review of available time-use data for developed countries, Joshi (1998) reports that additional hours in paid
work for women are counterbalanced by fewer hours spent on home production and, to a lesser extent, by
declines in leisure and sleep. This pattern is particularly pronounced for the Nordic countries, the U.K., and
the U.S. As a result of this high flexibility of the U.S. labor market, American women exit the labor market
after the birth of the first child for much shorter periods than do German women or women in other low
fertility countries (Diprete et al. 2003; see also Adsera 2004). Government transfers in countries such as
Germany often make up for a substantial part of this difference, but the net costs of children remain tend to
remain smaller for American women due to their exists from the labor market. Indeed, the greater cost and
longer exits from the labor force are associated with lower rates of first birth in West Germany than in the
United States. High unemployment and market rigidities also make the re-entry into the labor market after a
maternity leave more difficult in Germany (or Europe) as compared to the U.S., and career-oriented women
who are aware about these difficulties may chose not to have children—or have fewer children—rather than
risking their careers through child-related disruptions in their labor market participation.
In summary, therefore, why is America different? The United States has a much higher total fertility
rate than other developed countries. Recently, the United States has also experienced stronger productivity
growth, much higher levels of immigration but lower life-expectancy than European countries. Other important
differences are that Americans work more hours per week, take shorter vacations, tend to retire at
older ages, and experience a much lower incidence of long-term unemployment. One might argue that the
U.S. fertility trends simply trails behind Europe and Japan, and that the TFR in the U.S. will fall to historically
low levels in future years, as occurred for so many wealthy countries in recent decades. However, the
situation of the U.S. compared to most other high-income countries differs in at least two respects (Technical
Panel on Assumptions and Methods 2003). First, population composition favors a higher fertility level,
since some of the largest immigrant and minority groups within the U.S. have fertility levels that lie above
than the national average. For example, the TFR among Hispanics in the U.S. was 2.75 in 2001, 35 percent
30
higher than the national average of 2.03. The TFR of 2.10 for non-Hispanic Blacks in the same year was
slightly above the national value, while non-Hispanic Whites, Asians/Pacific Islanders, and American Indians
had below-average fertility levels. Since Hispanics and non-Hispanic Blacks together comprise roughly
a quarter of the U.S. population, their higher fertility levels are an important source of the nation’s relatively
high TFR. Second, fertility in the U.S. is relatively high for the population as a whole. Notably, the TFR
of non-Hispanic White women, falling in a range from 1.77 to 1.87 during 1990–2001, exceeds the national
average for most other high-income countries. While the heterogeneity of the U.S. population is therefore
one factor that contributes to the relatively high level of fertility in the United States, it does not constitute
the primary explanation. Instead, it appears that an overriding factor is their greater ability to combine work
and childbearing, thanks to a variety of institutional factors. In general, women (and couples) are deterred
from having children when the economic cost—in the form of lower lifetime wages—is too high. Compared
to other high-income countries, this cost is diminished by an American labor market that allows more
flexible work hours and makes it easier to leave and then re-enter the labor force. The importance of this
situation is reflected in the positive relationship between measures of women’s labor force activities and
levels of fertility across wealthy countries in recent years (Figure 8). As a result, despite a lack of public
financial support for families with children, it appears that the flexibility offered to individuals through the
market in the U.S. facilitates integration of work and traditional family life.
5 Homeostatic responses to low fertility
In light of the striking contrast between European and U.S. fertility trends it is essential to ask which
processes or policy interventions can revert Europe’s low fertility. While policies targeted at increases
the number of children born to women and couples are clearly a possibility, and these options are discussed
in the next section, we first consider demographic mechanism that implies homeostatic forces and could
potentially lead to increased quantum of fertility in the future. That is, is it possible that low fertility reverts
itself without policy intervention? The leading economic model suggesting this possibility is the Easterlin
hypothesis (Easterlin 1980) that predicts an inverse relation between cohort sizes and fertility level. In particular,
the theory predicts that—under conditions of restrictive immigration—declining cohort sizes result
in higher levels of fertility because young adults in small cohorts experience easier transitions into the labor
market due to less competition. This aspect is potentially relevant for the European low fertility context
since persistent lowest-low fertility leads not only to a rapid aging of the population with its well-known
problems for social security and related transfer programs, but it also leads to substantially reduced relative
cohort sizes. For instance, the first lowest-low fertility cohorts born early in the 1990s in Italy and Spain are
about 41% smaller than the cohorts born 25 years earlier. In the next 10–20 years, when these small cohorts
begin higher education, or begin to enter the labor and housing markets, they are likely to face substantially
more favorable conditions than their 25-year older predecessors, who have contributed importantly to the
emergence of lowest-low fertility in the 1990s. This positive effect of cohort size, first proposed by Easterlin
in the context of the U.S. baby boom (for a summary of these arguments, see Easterlin 1980), seems
particularly likely given the limited international migration into lowest-low fertility countries. These positive
experiences in the labor and housing market during early adulthood may contribute to an increase in
both period and cohort total fertility rates. Despite its speculative character, this effect may nevertheless be
31
important since it is likely to be one of the few demographic factors with homeostatic implications that can
lead to a reversal of lowest-low fertility.
6 Policy responses to low and lowest-low fertility
Government policies are a possible alternative to the—somewhat speculative—self-correcting mechanisms
discussed in the previous section. Various terms are used to describe governments’ attempts to influence
demographic developments such as population aging. Most commonly, these government interventions are
referred to as “population policy”. Such policy can include measures that are designed to have an impact on
the population structure, of which birth rate or fertility rate is the most prominent indicator. Many authors
also employ the term “family policy” to emphasize that government policies often do not aim at specific
goals in terms of the population size and structure, but are concerned with family well-being and resultant
activities that are directed towards families with children. Although the policy objective of both terms seem
to differ considerably—family on the one hand and population on the other—the actual definitions of family
policy and population policy do not make clear distinctions. Since family policies are an integral part of
welfare-state policies, it is also useful to draw on the literature on European welfare-state regimes in reviewing
and classifying family-policy set-ups in Europe. According to Esping-Andersen (1999), European
countries can be grouped into four distinct welfare-state regimes according to the intentions of their social
policies and the principles on which they are based universalistic welfare states (the Nordic countries),
conservative welfare states (continental European countries), liberal welfare states (Anglosaxon countries),
and—somewhat contested—Southern-European welfare states (Mediterranean countries). Universalistic
welfare states are characterized by welfare-state policies that are targeted at individual independence and
social equality between individuals (not families). Conservative welfare states direct their welfare-state
policies towards status maintenance and the preservation of traditional family forms, and they often rely
heavily on familialism, that is on the family as a provider of welfare. Liberal welfare states encourage
market-based individualism through minimal social benefits and though subsidizing private and marketized
welfare schemes, and social benefits are usually means-tested and poverty-related. The Southern European
welfare states are often considered part of the conservative welfare-state regimes; but their stronger
familialism merits that they are viewed as a separate welfare-state regime (Neyer 2003).
While different welfare regimes embrace very different philosophies and fertility-related welfare policies,
the different regimes are only weakly associated with differential fertility levels in Europe: the Nordic
countries with their universalistic welfare regimes tend to have relatively high fertility in Europe, and the
Southern European welfare regime is associated with lowest-low fertility. The Anglosaxon welfare regime is
associated with moderately high fertility, while the conservative welfare regimes comprise a wide spectrum
of fertility levels including ranging from Germany (TFR = 1.31 in 2001) to France (TFR = 1.89 in 2002).
The largest pressures to respond with policy changes to low and lowest-low fertility currently exist in
the conservative and Southern European welfare regimes. The specific population or family policies that
have been proposed in this context can be classified as follows (Grant et al. 2004): (a) preventive policies,
aimed at affecting the demographic behaviors that are believed to lead to adverse outcomes; these preventive
policies can be indirect, such as economic policies, gender policies and education policies, or direct, such
as migration policy, family support, reproductive health policy and family-friendly employment policies;
32
and (b) ameliorative policies aimed at accommodating or ameliorating the consequences of low fertility,
population decline and population aging, including for instance social security reform, labor force policy,
health care policy or policies towards the elderly.
Various preventive and ameliorative policy responses to low and lowest-low fertility have been widely
discussed and are often subject to a heated debate. A detailed discussion of these policies is beyond the
scope of this paper. Instead, we focus our discussion on two specific subsets of the overall policy responses
to population aging in Europe: immigration and policies directed towards increasing the level of fertility.
6.1 Immigration
European countries have depended on immigrants to supply labor in times of economic prosperity for a
long time. In recent years while removing restrictions to mobility within the European Union, however,
European governments have tightened controls over immigration from outside the EU. This has lead to
various complex and often uncoordinated systems of incentives and disincentives to influence international
flows of population. Contemporary immigration policy in Europe is thus aimed at restricting the number of
new immigrations and limiting the perceived “social discohesion” that is thought to come with them; such
policies usually have no direct population objectives (Grant et al. 2004). The impact of these policies on
population dynamics, nonetheless, is relevant and significant and have resulted in quite distinct international
migration patterns across European countries.
International migration policies and international migration patterns are almost certain to change in response
to population aging and population decline in Europe. At the same time, does increased immigration
constitute a policy response that ameliorates the consequences of very low fertility with respect to (1) population
growth, (2) working-age population growth and (3) changes in the support ratio? The United Nations
in their (2000) report on replacement migration concluded that the potential of immigration to substitute for
domestic births is rather limited. Replacement migration refers to the international migration that would be
needed to offset declines in the size of population, the declines in the population of working age, as well as
to offset the overall aging of a population. A key finding of the UN report is that if retirement ages remain
essentially where they are today, increasing the size of the working-age population through international
migration is the only short- to medium-term option to reduce declines in the support ratio. However, such a
policy would not reverse the process of aging.
The first column in Table 6 shows the numbers of migrants assumed in the UN medium variant population
projection (see also Figures 3–5). For example, the total number of migrants for the United States
for the fifty-year period is 38 million; and the average annual number is 760 thousand. For Europe, the
total immigration is 18.8 millions, or 376 thousand annually. Except for the United States, the numbers of
migrants needed to maintain the size of the total population (second column in Table 6) are considerably
larger than those assumed in the medium variant of the UN projections. In Italy, for example, the total
number of migrants is 12.6 million (or 251 thousand per year) versus 0.3 million (or 6 thousand per year) in
the medium variant. For the European Union, the respective numbers are 47 million versus 13 million (or
949 thousand per year versus 270 thousand per year). In order to keep the working-age population (15 to
64 years) at a constant size, the numbers of migrants are even larger (third column in Table 6). In Germany,
for instance, the total number of migrants is 24 million (or 487 thousand per year) in in order to maintain a
constant working age population versus 17 million (or 344 thousand per year) that are necessary for main-
33
Table 6: Replacement migration in Europe: total immigrants for period 2000–2050 and average annual
number of immigrants (in 1,000) for different replacement goals
Scenario 1 2 3 4
Constant ratio
of 15–64 to
Constant Constant 65 years or
Medium total age group older
variant population 15–64 persons
A. Total number, in 1,000, for period 2000–2050
France 325 1,473 5,459 89,584
Germany 10,200 17,187 24,330 181,508
Italy 310 12,569 18,596 113,381
Russian Federation 5,448 24,896 35,756 253,379
United Kingdom 1,000 2,634 6,247 59,722
United States 38,000 6,384 17,967 592,572
Europe 18,779 95,869 161,346 1,356,932
European Union 13,489 47,456 79,375 673,999
B. Average annual number, in 1,000, for period 2000–2050
France 7 29 109 1,792
Germany 204 344 487 3,630
Italy 6 251 372 2,268
Russian Federation 109 498 715 5,068
United Kingdom 20 53 125 1,194
United States 760 128 359 11,851
Europe 376 1,917 3,227 27,139
European Union 270 949 1,588 13,480
Source: United Nations (2000)
34
taining a constant population size. Expressed in terms of migrants per million inhabitants in 2000, Italy
requires the highest number of immigrants, with 6,500 annual immigrants per million inhabitants, in order
to maintain its working-age population, followed by Germany, with 6,000 annual immigrants per million
inhabitants; the United States would require the smallest number of immigrants, approximately 1,300 per
million inhabitants. Finally, the number of immigrants that are necessary to keep the ratio of of 15–64 to 65
years or older persons (= support ratio) constant are extraordinarily large (fourth column in Table 6). For
the European Union, the total number of migrants in this scenario is 674 million (or 13 million per year),
and for Italy it is 113 million (or 2.3 million per year).
Most analysts consider the levels of immigration that are required to keep the population-size, the size
of the labor force or the support ratio at its constant level as unrealistic for Europe. In summary, therefore,
immigration to Europe—even if its level increases in future decades—is unlikely to prevent the population
decline and rapid population aging. The aging of the total population, and decreases in the number of people
of working age, thus cannot be stopped through immigration, particularly in European countries with very
low fertility levels. At the same time, it seems likely that increases in immigration levels—even if they do
not prevent population aging and decline—are likely to be a widespread response of European countries
to low fertility, combined with other measures to increase the level of fertility (see below). Furthermore,
internal migration within an enlarging European Union is likely to become more important in this context; in
particular, internal EU migration is likely to contribute to population aging and decline in sending countries,
as well as ameliorate population aging and decline in receiving countries. While the most important sending
countries of migrants within the European Union also experience declines in the population size and are
unlikely to be long-term sources of migrants, the potential future joining of Turkey to the European Union
is likely to substantially affect these migration streams due to Turkey’s relatively young age structure and
the substantial projected population growth.
6.2 Policies to influence fertility
The only viable long-term strategy to limit the extent of population aging and the decline of the population
size will be an increase in the level of fertility. Several such policies are already in place—although not
always with an explicit goal to increase fertility (Grant et al. 2004). In particular, especially in Western
Europe, governmental efforts to affect fertility have been generally implicit policy measures to steer family
formation decisions with financial incentives (e.g., tax exemptions), or family-friendly facilities (e.g.,
childcare facilities). Explicit population policies directed at increasing fertility, also called pronatalist policies,
are less common in European countries. In the past they were widely implemented as part of a strict
procreative policy in the former socialist regimes of Eastern European countries; currently, explicit policies
intended to boost fertility (or at least to prevent it from falling) are pursued in some countries such as France.
Despite the small number of countries that pursue explicit pronatalist policies, a growing number of
countries in Europe view their low birth rates with the resulting population decline and aging to be a serious
crisis, jeopardizing the basic foundations of the nation and threatening its survival (Chamie 2004; Stark
and Kohler 2002, 2004). In attempting to raise birth rates, governments are thus increasingly seeking to
address the underlying causes of low fertility and adopt polices, programs and incentives to encourage
couples, in particular women, to increase their child bearing. Maternity and paternity leave, childcare, after
school programs, part-time employment, job security, cash allowances and other financial incentives are
35
Table 7: Government views on the level of fertility and policies on fertility level
number of Percentage
countries Too low Satisfactory Too high Total
Government views on the level of fertility
1976 29 24 76 0 100
1986 29 31 69 0 100
1996 43 42 56 2 100
2003 43 63 37 0 100
Policies on the level of fertility
Raise Maintain Lower No intervention
1976 29 24 24 0 52
1986 29 28 21 0 52
1996 43 37 9 2 51
2003 43 47 9 0 44
Source: United Nations (2004)
among the measures adopted or being carefully reviewed by governments. These concerns are illustrated by
several magazine and newspaper articles quoting leading national politicians (all quotes are cited in Chamie
2004): (a) France offers C800 reward for each new baby: “The French PrimeMinister, Jean-Pierre Raffarin,
announced last week that a bonus of C800 (£560, $895) will be awarded mothers for each baby born after
1 January 2004. The bonus is part of a series of measures to encourage families to have more children.”
(British Medical Journal 10 May, 2003). (b) Italy offers cash to boost its birth rate: “The 2004 budget
package includes a one-time 1,000 euros ($1,200) payment to Italians on the birth of their second child, a
measure set to run from December 1 until the end of 2004. . . .Mayor Rocco Falivena (of Laviano) digging
deep into town coffers is offering couples 10,000 euros ($11,900) for every newborn baby.” (Reuters 7
December 2003). (c) In address to Estonians’, President calls on citizens to make more babies: “Worried
about a declining population, Estonia’s president has urged the country’s 1.4 million residents to make more
babies. ‘Let us remember that in just a couple of decades the number of Estonians seeing the New Year will
be one-fifth less than today,’ President Arnold Ruutel said in a speech broadcast live on national television
Wednesday.” (New York Times 2 January 2003).
A more detailed look at the perception of national fertility levels is provided in Table 7. Between 1976
and 2003 the proportion of European countries that view their level of fertility as too low has increased
from 24% to 63%, reflecting a shift from a satisfactory assessment of fertility patterns. The proportion of
countries that have a policy to raise fertility levels increased from 21% to 44%. The countries that report
having a policy of “no intervention” include Germany, Italy, Norway, Portugal, Spain and Switzerland; these
countries, however, do have family or social policies that may lead to higher fertility, although they are not
labeled pronatalist. The remaining countries have implemented a broad range of policies and measures to
raise fertility levels.
Looking forward, McDonald (2000b) has proposed the following comprehensive “toolbox” of public
36
policies to impact low and lowest-low fertility:
• Financial incentives
– Periodic cash payments, usually in the form of regular payments to parents for each child.
– Lump sum payments or loans, including payments at the time of birth of a baby (baby bonus,
maternity benefit), at the time a child starts school or at some other age.
– Tax rebates, credits or deductions based on the presence of a child.
– Free or subsidized services or goods, including education at all levels, medical and dental services,
public transport, and recreation services such as sporting, entertainment, leisure or artistic
activities.
– Housing subsidies, including periodic cash payments such as housing benefits, lump sum cash
payments as first-time home-buyer grants or mortgage reductions at the birth of each child, tax
rebates or deductions for housing costs, or subsidies to housing-related services.
• Work and family initiatives
– Maternity and paternity leave, including the right of return to a position following leave related
to the birth of a child.
– Child care, including the provision of free or subsidized child care as part of the family-friendly
employment policies, including for those who are not employed.
– Flexible working hours and short-term leave for family-related purposes.
– Anti-discrimination legislation and gender equity in employment practices.
• Broad social change supportive of children and parenting
– Employment initiatives that improve the job prospects of young men and women, especially also
in the part-time sector.
– Child-friendly environments, including traffic calming, safe neighborhood policies, public recreational
facilities such as playgrounds, provision for children in places of entertainment and in
shopping centers in order to build a child-friendly environment.
– Gender equity, including non-gender specific workplace policies, gender-neutral tax-transfer
policies in social insurance, support of workers with family responsibilities irrespective of gender,
removal of institutional remnants of the male breadwinner model of the family, acceptance
of fathers as parents by service providers and more general recognition and support to fathers as
parents.
– Marriage and relationship supports, including the provision of greater encouragement in the formation
of relationships, relationship education, relationship counseling, and possibly economic
incentives to marry (e.g., through housing assistance).
– Development of positive social attitudes towards children and parenting, including a clear and
simple message that people desiring children will be supported by society without creating inequities
to the childless, voluntary or involuntary.
In addition to these policies, there are many alternative policy suggestions aimed at increasing fertility
levels. Policy proposals are abundant, albeit not always realistic in the face of limited government resources.
Recent examples that expand beyond the above “toolbox”, for instance, include tempo policies that aim at
reducing the pace of fertility postponement, or perhaps even reversing the trend (Lutz et al. 2003; Lutz and
Skirbekk 2004), a proposal to restructure the Italian system of transfers so that each newborn child becomes
37
1980 2000 2020 2040
60 80 100 120
year
# of women aged 20−35 (2000 = 100)
EUR
USA
BG
DK
F
GER
IT
trends almost completely determined RU
by current age structure
Figure 12: Number of women in primary ages of childbearing (ages 20–35) for Europe, USA, Bulgaria,
Denmark, France, Germany, Italy and the Russian Federation (year 2000 = 100, based on UN
medium projection)
an “account holder” that receives and gives transfers throughout life (Livi-Bacci 2004), and linking fertility
and economic security at old age (Demeny 1987).
The above policy proposals to impact fertility are comprehensive, ambitious and potentially also controversial
in terms of a country’s welfare state philosophy. Elements of these proposals, however, will almost
certainly be implemented, or, if already implemented, extended in European low fertility countries. Nevertheless,
when assessing the impact on future trends of population aging and decline, it is important to keep
an essential caveat of these policies in mind: even if some of the above policies are effective in terms of
increasing individual’s and couple’s fertility, however, it is important to recognize that future declines in the
number of women (and couples) in childbearing ages limit the impact of these population policies on the
number of births and population aging (see also Demeny 2003). Figure 12, for instance, shows the number
of women in primary ages of childbearing (ages 20–35) for Europe, USA, Bulgaria, Denmark, France,
Germany, Italy and the Russian Federation (based on UN medium projection, year 2000 = 100). In Europe,
and in all European countries included in Figure 12, the number of women in primary childbearing ages is
projected to decline between 2000 and 2040. This decline is close to 35% for Europe, and it exceeds 50% in
Italy and Bulgaria. Moreover, the decline until about 2025 is almost completely determined by the current
age structure of the population (except for migration). The substantial declines in the number of women in
childbearing ages in Europe and in lowest-low fertility countries implies that the annual number of births
would continue to decline even if fertility policies resulted in a large increases in the number of children
born per women. The negative population momentum (Lutz et al. 2003) occurs because low fertility levels
result in successively smaller birth cohorts, and past periods of low and lowest-low fertility are already man-
38
Table 8: Qualitative findings from empirical studies on the impact of policies on fertility
Total fertility Timing of Specific birth Age of Other
rates births order mothers individual
characteristics
Family cash Small positive Contradictory Small positive Some evidence
benefits effects in most results on effects, or that effects of
countries whether effects of contradictory policies differ
policies are larger results, on the among ethnic
Tax policies Positive effects in for first or effects of welfare groups
the US and Larger effects of subsequent births benefits on
Canada policies on the teenage births
timing of births Small or no effect (but evidence
Family-friendly Positive effect of than on on probability of limited to few
policies part-time and completed fertility having a first countries)
flex-time work child
Weak or
contradictory
effects of
maternity leave
Child care Positive effect, Some evidence
availability weak in some that effects of
countries child-care
availability and
costs differ
according to the
employment
status of mothers
Source: Sleebos (2003)
ifested in the population age structure in 2000 (see Figures 4–5). Girls that were not born during a period
of low fertility in the past will not become mothers 20–35 years later—the negative population momentum
thus reinforces the effect of low fertility. As a result of this negative momentum that is already built into
the current population age structure, fertility policies—even if effective on the individual level—potentially
have only a limited effect on slowing population aging or on reversing the decline of the population size.
6.3 Evaluation of current population policies
Several evaluations of the effect of family and population policies on the level of fertility have been conducted
in recent years (e.g., Gauthier 1996, 2002; Gauthier and Hatzius 1997; Grant et al. 2004; Pampel
2001; Sleebos 2003), although virtually all of these studies fall short of a sophisticated policy evaluation
based on experimental studies. Keeping this important limitation in mind, there seems to be a consensus
among studies that policies have only a moderate and long-term effect. For instance, Sleebos (2003) concludes:
(a) The impact of any specific policies on women’s or couple’s reproductive decisions depends on
a broad range of factors, and detailed studies are necessary to evaluate these policies. A qualitative assessment,
based on the currently available empirical evidence, of the effectiveness of various policies for
changing fertility behavior in OECD countries is given in Table 8. (b) Some studies have documented that
the impact of family policies is more significant on the timing of fertility rather than on the total number of
children achieved over a full reproductive cycle (Barmby and Cigno 1990; Ermisch 1988). (c) Several of
the studies reviewed in Sleebos (2003) investigated the effect of of family cash benefits on the total fertility
39
rates, suggesting a weak but positive relation. The estimated estimated impact of policies, however, is small.
Gauthier and Hatzius (1997), for instance, estimate that a 25% increase in family allowances would increase
fertility rate by about 0.6% in the short-run, and by about 0.4% in the long-run—that is, an increase of the
total fertility rate of 0.07 children per woman. (d) Several studies for Austria, Canada, Hungary, Italy, the
Netherlands, Norway, Swedish and the United States all conclude that work/family reconciliation measures,
such as maternity or parental leave and childcare subsidies, have a positive impact on fertility. The estimated
effect is however also small. Hyatt and Milne (1991), for instance, estimated that 1% increase in the real
value of maternity benefit would increase total fertility rate in Canada between 0.09 and 0.26%. In contrast,
Gauthier and Hatzius (1997), report that neither the duration nor the benefits provided by maternity leave
explain much of the variation in total fertility rates across OECD countries. Availability of jobs suited to
the needs of mothers also favors fertility. Castles (2003) reports a positive link between the percentage of
employees working flexi-time and total fertility rates across OECD countries. Del Boca (2002) also finds
a positive relationship between availability of part-time jobs and fertility rates in Italy, and Adsera (2004)
finds that a large share of public employment, by providing employment stability, and generous maternity
benefits linked to previous employment, such as those in Scandinavia, boost fertility of the 25–34 year old
women. (e) Results on the impact of child care on total fertility rates also vary, partly depending on the
form of child care. Some studies have documented a strong positive relationship between total fertility rates
and formal childcare availability (e.g., Castles 2003; Rindfuss et al. 2004), in particularly for children below
the age of three, while other analyses have found no effect of childcare availability on the decision to
have a first child (Andersson et al. 2004; Hank and Kreyenfeld 2003). These inconsistent findings about the
availability of childcare may in part be due to a lack of control in existing studies for the determinants of
childcare provision. In an important recent study that addresses this limitation, Rindfuss et al. (2004) use
fixed-effect analyses of child care availability data from 1973 to 1997 for Norway’s 435 municipalities, and
show a strong, statistically significant, positive effects of child care availability on the transition to motherhood.
In addition, utilizing a “natural experiment” provided by the introduction of a policy in Spain that
provides working mothers with a monthly childcare benefit amounting to one hundred Euros for each small
child, Sánchez-Mangas and Sánchez-Marcos (2004) show that the introduction of this policy resulted in an
increase in the labor participation of mothers with small children. For low and medium educated women, for
which the policy seems to be most effective, more than 40% of the 3.5 percentage point increase in female
labor force participation during 2002–03 can be attributed to the policy change.
In summary, the studies reviewed in Sleebos (2003) provide mixed conclusions as to the effects of
various policies on fertility behavior. Similar conclusions were obtained also in other evaluations of family/
population policy effectiveness (Gauthier 1996; Grant et al. 2004). On balance, Sleebos (2003) concludes
that the evidence supports a weak positive relation between reproductive behavior and a variety of policies.
Moreover, an important conclusion from the study is that policy measures which may potentially affect reproductive
behavior will manifest their influence only in the long-term. Thus, a consistent application of
different measures over time is likely to be more important than abrupt introduction of large pro-natalist
measures, which could be reversed at some later stage. Moreover, policies targeted at an increased compatibility
between childbearing and labor force participation, as well as policies aimed at reducing uncertainty in
early adulthood due to high unemployment and related factors, are most promising in our opinion based on
the theoretical framework and empirical evidence provided in this paper (Sections 3 and 6.2–6.3). Finally,
40
consistent also with our assessment of policy effectiveness and the existence of a negative population momentum,
Sleebos (2003) concludes that policy-makers should not expect too much from pronatalist policies,
and knowledge about the effects of policies and their complementarities in many areas is still too limited to
guide the design of cost-effective interventions.
7 Conclusions
Low and lowest-low fertility is likely to be a considerable challenge for many developed countries in the
next decades. The analyses in this paper allow us to draw some first conclusions about the causes and
implications of, and potential policy responses to, low and lowest-low fertility in Europe. First, our portrait
of contemporary European fertility patterns identifies a systematic pattern of lowest-low fertility that is
characterized by a rapid delay of childbearing, a low progression probability after the first child (but not
particularly low levels of first-birth childbearing), a “falling behind” in cohort fertility at relatively late ages
(in Southern Europe) and a reversal in the relative ranking of lowest-low fertility countries in a European
comparison of total fertility levels (Billari and Kohler 2004). At the end of the 1990s, therefore, there
emerges a clear clustering of European nations separating them into countries with low fertility levels and
countries with lowest-low fertility, and this clustering is mirrored in many fertility-related behaviors such as
women’s labor force participation, the diffusion of cohabitation or out-of-wedlock childbearing and other
dimensions.
Second, lowest-low fertility countries are themselves heterogeneous and cluster into two distinct patterns.
On the one hand, Southern European lowest-low fertility countries, including foremost Italy and
Spain, exhibit also latest-late home-leaving behavior, a limited spread of non-marital cohabitation, a low
share of extramarital births, a limited diffusion of divorce, and a relatively low share of women participating
in the labor force. They also exhibit a more marked postponement of first births and a lower recuperation
of fertility at higher ages. On the other hand, Central and Eastern European countries exhibit relatively earlier
household independence, union formation. They also they have higher non-marital fertility and divorce
rates, and first births take place earlier than in Southern European lowest-low fertility countries.
Third, we have argued in the previous sections that lowest-low fertility, defined as a period TFR below
1.3, is caused by a combination of the following demographic and socioeconomic factors: (a) Socioeconomic
incentives to delay childbearing that make postponed fertility a rational response to high economic
uncertainty in early adulthood, increased returns to education, shortages in the labor market and similar
factors. (b) Social feedback effects on the timing of fertility that reinforce the adjustment of individual’s desired
fertility to socioeconomic changes. In particular, social feedback effects can give rise to postponement
transitions that lead to rapid, persistent and generally irreversible delays in childbearing across a wide range
of socioeconomic conditions. (c) Institutional settings, characterized by labor market rigidities, insufficient
child-care support and a prevalence of relatively traditional gender roles, favor an overall low quantum of
fertility and lead to reductions in completed fertility that are causally related to the delay in childbearing.
The postponement of fertility therefore does not only lead to a delayed pattern of childbearing. It also
implies important negative effects on the quantum of fertility and on completed fertility, and this effect is
particularly strong in the institutional context that is characteristic of lowest-low fertility countries. While
the above factors are not necessarily unique to lowest-low fertility countries, we believe that lowest-low fer-
41
tility countries are characterized by a combination of all four factors in a particularly pronounced fashion.
Lowest-low fertility is therefore the outcome of an interaction of demographic and behavioral factors that
each in itself would lead to lower fertility. In combination and interaction, however, these factors reinforce
each other and lead to lowest-low fertility. It is also noteworthy that substantial childlessness has not been a
driving force leading to reduced fertility in the group of countries currently classified as lowest-low fertility
countries.
Fourth, the emergence of lowest-low fertility during the 1990s has been accompanied by a disruption
or even a reversal of many well-known patterns that have been used to explain cross-country differences in
fertility patterns. For instance, the cross-sectional correlations European countries between the total fertility
level on the one side, and the total first marriage ratio, the proportion of extramarital births and the female
labor force participation ratio on the other side have reversed during the period from 1975 to 2001/02. In
2002, there is also no longer evidence that divorce levels are negatively associated with fertility levels.
Hence, there are crucial changes in the relationship between traditional determinants of fertility—such as
marriage, divorce, home-leaving and women’s labor force participation—and fertility before and after the
emergence of lowest-low fertility, and perhaps most importantly, there is a clear indication that a high
prevalence of marriage and institutionalized long-term partnership commitments are no longer associated
with higher fertility in cross-sectional comparisons. While the detailed analysis of the determinants of this
reversal is beyond the scope of the present paper, one fundamental cause can probably not be disputed: The
reversal in cross-sectional associations between fertility and related behaviors is in part due to the different
demographic factors driving fertility change. Initially, the decline towards low fertility has been importantly
related to stopping behavior, that is, a reduction of higher parity births. More recently, the postponement of
fertility—particularly for first births—has emerged as a crucial determinant of differences in fertility levels
among developed countries.
Fifth, the United States with its relatively high fertility near replacement levels, its high levels of immigration
and its substantial projected population growth. While the high U.S. fertility is commonly attributed
to the high fertility of Hispanic and African American sub-populations, these factors can not provide an
explanation for the “curiously high” fertility of the U.S. Instead, the key to understanding the relatively high
U.S. fertility therefore lies in the relatively young age pattern of fertility and the only modest pace of fertility
postponement as well as a relatively high compatibility between childrearing and labor force participation or
other opportunities/constraints on fertility. This high compatibility is not achieved through an extensive welfare
state targeted at the family and children, but through a market-based system combining a very flexible
labor market, flexible work schedules, privately supplied day-care and high female labor force participation.
Sixth, the policy options available to European low and lowest low fertility countries are limited. The
existing empirical evidence provides mixed conclusions as to the effects of various policies on fertility
behavior. On balance, that the evidence supports a weak positive relation between reproductive behavior and
a variety of policies, but policy measures which may potentially affect reproductive behavior will manifest
their influence only in the long-term. Policy measures that aim to make women’s participation in the formal
labor force compatible with childrearing are in our opinion among the most promising alternatives. The
effectiveness of such measures, however, is likely to be limited due to a negative population momentum
that results from decades of below-replacement fertility in many parts of Europe since the 1960s and 1970s.
Even if policies are effective in raising women’s or couple’s fertility, and even if levels of immigration into
42
Europe increase, a loss of demographic weight within the global population, a decline in the population
size during the coming decades and a substantial aging of the population are therefore safe predictions
for the Europe of the twenty-first century (Demeny 2003). It is clear that current social and economic
institutions are not sustainable in light of these trends, and individual’s life-courses already have been—and
will continue to be—transformed in response to reductions in fertility and increases in longevity. Adjusting
to the demographic reality of the 21st century will therefore constitute a major challenge for policy makers
and companies on the one, and for individuals and families on the other side. Whether the adjustment
to these trends can be successful, and whether these trends lead to a reduced well-being of individuals if
appropriate policies are implemented, is still an open question.
43
Table A.1: Total fertility, total first marriage ratio (TFMR), total divorce ratio (TDR) and proportion of
extra-marital births in Europe
Total Total first Total Proportion of
fertility marriage ratio divorce ratio extra-marital births
1975 2002 1975 2002 1975 2002 1975 2002
Andorra (And) – 1.36 – – – – – –
Armenia (Arm) 2.79 1.21 – 0.37i 0.15 0.06 2.80 13.20
Austria (Aus) 1.83 1.40 0.75 0.50 0.20 0.45 13.50 33.80
Azerbaijan (Az) 3.92 1.58 0.83 0.57 – 0.11 5.20 7.60
Belarus (Bel) 2.20 1.22 – 0.68 – 0.50i 7.40 21.40
Belgium (Bel) 1.74 1.62 0.89 0.46 0.16 0.54 3.10 0.21e
Bosnia and Herzegovina (Bos/Herz) 2.38 1.23 0.69b – – – 5.60 10.60
Bulgaria (Bul) 2.22 1.21 1.00 0.47 0.15 0.21 9.30 42.80
Croatia (Cro) 1.92 1.34 0.82 0.69 0.13 0.16 4.90 9.60
Czech Republic (Cze) 2.40 1.17 0.99 0.48 0.30 0.46 4.50 25.30
Denmark (Dk) 1.92 1.72 0.67 0.73 0.36 0.47 21.70 44.60
Estonia (Est) 2.04 1.37 0.94 0.42 0.50b 0.48 15.70 56.30
Finland (Fi) 1.68 1.72 0.70 0.64 0.26 0.50 10.10 39.90
France (Fra) 1.93 1.89 0.86 0.59 0.17 0.38i 8.50 43.70i
Georgia (Geo) 2.52 1.42 0.99b 0.32i – 0.08 0.20 45.90
Germany (Ger) 1.48 1.31 0.81 0.54 0.25 0.42i 8.50 25.00i
Greece (Gr) 2.32 1.25i 1.16 0.52h 0.05 0.16g 1.20 4.30i
Hungary (Hun) 2.35 1.30 1.00 0.47 0.24 0.42 5.60 31.40
Iceland (Ice) 2.65 1.93 0.79 0.58i 0.26 0.40h 33.00 62.30
Ireland (Ire) 3.43 2.00 0.94 0.59f – – 3.70 31.10
Italy (It) 2.21 1.27 0.95 0.62 0.03 0.12i 2.60 9.70h
Latvia (Lat) 1.97 1.24 1.01 0.44 0.52 0.37 11.70 43.10
Lithuania (Lit) 2.18 1.24 1.01 0.54 0.42a 0.41i 6.20 27.90
Luxembourg (Lux) 1.55 1.63 0.80 0.50 0.10 0.51 4.20 23.20
Macedonia (Mac) 2.71 1.77 0.86 0.77i 0.09 0.09 6.60 10.70
Malta (Mal) 2.17 1.46 – 0.73i – – 1.10b 15.00
Moldova (Mol) 2.52 1.21 1.11b 0.58 – 0.39 8.00 20.50h
Netherlands (NL) 1.66 1.73 0.83 0.59 0.19 0.37 2.10 29.10
Norway (Nor) 1.98 1.75 0.80 0.47 0.21 0.46 10.30 50.30
Poland (Pol) 2.26 1.24 0.93 0.57 0.15 0.18 4.70 14.40
Portugal (Por) 2.75 1.47 1.39 0.66 0.02 0.39 7.20 25.50
Romania (Ro) 2.60 1.26 0.97 0.66 0.20 0.20 3.50 26.70
Russian Federation (Rus) 1.97 1.32 1.03 0.60d 0.38 0.43d 10.70 29.50
Serbia and Montenegro (Serb/Mont) 2.33 1.71i 0.81 0.66i 0.12 0.14i 9.90 20.20i
Slovak Republic (Sk) 2.53 1.19 0.94 0.50 0.18 0.33 5.20 21.60
Slovenia (Sn) 2.17 1.21 0.99 0.43 0.15 0.25 9.90 40.20
Spain (Sp) 2.80 1.25 1.05 0.59i 0.04c 0.15e 2.00 17.70h
Sweden (Swe) 1.77 1.65 0.63 0.49 0.50 0.55 32.80 56.00
Switzerland (Swi) 1.61 1.40 0.65 0.65 0.21 0.40 3.70 11.70
Ukraine (Ukr) 2.02 1.10 – – 0.34 0.38 8.80 19.00
United Kingdom (UK) 1.81 1.64 0.87 0.54h 0.30 0.43f 9.00 40.60
Notes: a = 1970, b = 1980, c = 1981, d = 1996, e = 1997, f = 1998, g = 1999, h = 2000, i = 2001. Source: Council of
Europe (2003).
44
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: El hadi A.bashir)
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يا ود الرشيد كل عام وأنت بخير
دعوتك لكل قرد أن يطلع جبلوا هي دعوة لإزالةالعاصمة تماما
وتفريغها من ساكنيهاالذين تنحدر أغلبيتهم الساحقة من الريف
وهي دعوة صريحة لقلب الحكومة لأن ساكن القصر الجمهوري حييقطع تذكرة
سفر one way لحوش بانقا.( شايف الفوضى كيف؟ ).
فانظر أخي الكريم من أي الجبال إنحدرت ؟ وإن لم تجد بغيتك يوم الوقفة في بص الدويم, الأبيض
الفاشر, الجنينة, جوبا, واو, سنار, الدمازين, ملكال, القضارف, كسلا, بورتسودان, دنقلا, مروي ,
كريمة, مدني , فالذنب ليس على الكمسنجي بل علي محمد علي باشا والدفتردار وكتشنر.
والعفش داخل البص على مسؤولية صاحبه.
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 Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: معاوية الأرباب)
|
يا مسلمى .... الدعوات الطيبات بدوام النعم
وكل عام والشباب وامهم بالف خير
(( يا اخوى انت من زمن ناس ( العرشكول ) بيقفلو فى العيد وجاك زول يا بحر ابيض ))
والله بيــه حليفتها اصبحت مناوبــة العيد فى (( الدكاكين / الكناتين )) بالشــى الفلانـــى
_________
التحايا لاهل العرشكول لكم كانت لهم علينا (ايادى بيضاء )
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Re: علشان تعرف الخرطوم قائمة بروز؟؟ زورنا في العيد (Re: Faisal Elrasheed)
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العوض ... كل سنة وإنت طيب.
| Quote: والقاذورات والاوساخ تصبح امام كل بيت , |
طيب القاذورات والأوساخ دي جات من وين؟ قايمة بروز برضو؟
عارف. عندنا جماعة من أهلنا دايماً في العيد أكتر حاجة بيكونوا مبسوطين ليها إنو الموية بتكون متوفرة، ودايماً تعليقهم (نستمتع بي حمام بالدش قبل ما أهل العوض يجوا).
التوقيع:
محمد أبوالعزائم
عن/ مواطني منطقة البراري
عن/ أهالي العاصمة
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العوض المسلمي
حبيب نورة
HAIDER ALZAIN
عواطف ادريس اسماعيل
mayada kamal
يسرى معتصم
Faisal Elrasheed
عبدالوهاب علي الحاج
محمد زكريا
El hadi A.bashir
معاوية الأرباب
بدر الدين اسحاق احمد
محمد أبوالعزائم أبوالريش
فيس بوك
تويتر
انستقرام
يوتيوب
بنتيريست