What causes a high birth rate

Birth turnaround in Germany - what is it and what are the causes?

A few months ago, the news caused a sensation in Germany that more old age diapers were sold than baby diapers in 2015. This news put it in a nutshell: In the reflection of its public opinion, Germany sees itself as a country with steadily declining births and progressive aging. Frequent searches on Google are “Are the Germans dying out?” “Are our pensions safe?” Or “Refugees and pension fund”. Statistics to confirm these fears are easy to find. In an international and intra-European comparison, Germany is one of the countries with the lowest birth rate and the highest average age. On the other hand, there are increasing signs that at least in parts of Germany a trend reversal has taken place in births1 and that this is mainly affecting urban regions.2 In some places the new urban baby boom is already part of local identity. The births e.g. in Leipzig alias "Hypezig" 3 have been rushing from record to record for years. Modernity, cosmopolitanism and children are part of the identity of the young urban society there.

Birth development in the federal states

The birth rate in the Federal Republic has been declining for decades. As Figure 1 shows, the post-war baby boom was reversed from the mid-1960s. Since then, there has been a trend towards decreasing births. After the fall of the Wall, there were expectations that the slightly higher fertility rates in the GDR would lead to a trend reversal for all of Germany. But although births peaked in the year of reunification in 1990, they fell again immediately afterwards. In the following years the decline was even stronger than before. The sober time series display, however, hides the dramatic regional shifts within Germany. As is well known, the decline in the overall German birth rate in the decade after the turn of the century is due to the slump in the birth rate in the new federal states. Figure 2 illustrates this through the use of indices in which the number of births in each federal state in 1990 is standardized to the value 100. The graphic shows the relative birth development since the fall of the Wall. The east-west divide in the birth rate is obvious. While the live births in the new federal states halved in the three years after the reunification, the old federal states were initially able to maintain their birth rate and only then fell into a slight downward trend. In line with this, the birth trend in Berlin shows itself to be an east-west mix, in that it is almost exactly in the middle between the old and the new federal states.

illustration 1
Birth development in Germany

Source: Federal Statistical Office, Wiesbaden 2016.

Figure 2
Birth development after German unification
Live births, index (1990 = 100)

Source: Destatis, accessed March 2016, own calculations.

On the right-hand edge of Figure 2 it becomes clear that there are signs of an upswing in births in many federal states. In order to investigate the question of whether and to what extent a trend reversal (birth reversal) is actually taking place here, we shall exclude the 1990s in the further course of our argument. The decade after reunification is dominated too much by the very specific problems of economic transformation; the east-west divide is too clear, which obscures current developments across Germany. We are therefore now shifting the starting point of the considerations to the year 2000. From this year onwards, the special postural trend in the birth rate in the new federal states normalizes.

Table 1 shows the birth development between 2000 and 2014, the last year for which current birth data are available. The clear east-west differences have now disappeared. The two large cities of Hamburg and Berlin show the strongest positive dynamics in the birth rate, followed at a considerable distance by Saxony, Brandenburg and Bremen. The “baby boom” of recent years is therefore not only an East German phenomenon, but also an urban one. The birth rate in the federal states is also influenced by the migration of the population. The relative birth development is shown in the right column, according to which the federal states are arranged in descending order. Saxony-Anhalt and Baden-Württemberg show almost the same percentage decline in live births (8.9% and 9.9% over the entire period), but in Saxony-Anhalt this is accompanied by a shrinking population due to emigration (-14, 5% in contrast to a slight population increase in Baden-Württemberg). The birth trend in comparison to the population is therefore very different in Saxony-Anhalt than in Baden-Württemberg. In Saxony-Anhalt, births are increasing significantly compared to the population; in Baden-Württemberg, on the other hand, births are falling even more significantly than the total number of births compared to the population.

Table 1
Birth and population development in the federal states, 2000 to 2014
federal stateBirthspopulationBirths / population
Mecklenburg-Western Pomerania-3,7-9,97,0
North Rhine-Westphalia-11,4-2,1-9,6
Lower Saxony-16,4-1,3-15,3

Source: Destatis, accessed March 2016, own calculations.

Table 1 shows the need for a more in-depth analysis. First of all, the East-West divide that was so prominent after the fall of the century has receded into the background since the turn of the millennium and should therefore be supplemented by other criteria when analyzing the birth rate. The distinction between urban and non-urban areas is particularly instructive. Second, the regional delimitation according to federal states is hardly conducive to a deeper understanding of the birth trend for various reasons. It is a political demarcation that conveys little meaningful information due to the different sizes and internal heterogeneity of the federal states. In the following section, we will therefore move on to the much finer NUTS 3 breakdown, which then allows the differentiation of regions according to their degree of urbanization and at the same time opens up the perspective for comparative European studies.

Birth dynamics in German NUTS 3 regions

NUTS data from Eurostat are based on a uniform system of territorial units for statistics for the entire territory of the EU and some neighboring countries.4 After the first beginnings in the 1990s, the NUTS statistics have been based on a regulation of the European Commission since 2003. The territorial division at that time is now known as NUTS 2003. Since then there have been three revisions that have led to the NUTS territorial divisions in 2006, 2010 and 2013. The latter is the currently valid one, but it is not fully implemented in the available data. The profile of the NUTS statistics is not only the broad geographical coverage of EU and neighboring countries, but also their systematic division into three levels. In the following, we will use the third level (NUTS-3), which in Germany essentially covers the cities and districts, but not in all cases.

Due to the history of its development with several revisions, the NUTS statistics show inaccuracies as well as gaps in time and space. The data problems also result from changes in the territorial delimitation, e.g. if rural districts are redefined, merged or divided as part of a territorial reform. In Germany, this affects part of the NUTS 3 data in Mecklenburg-Western Pomerania and all Saxon NUTS 3 data except for the cities of Chemnitz, Dresden and Leipzig. The complete data for these regions are not available, so they have to be excluded.

From the NUTS 3 statistics, we use the number of births and the population per region. Some of them are available broken down by gender and age group. However, gaps in the age cohorts mean that we can only use data on the total population (broken down by gender if necessary). For the population, it should be noted that the results of the 2011 census are currently only included in 2014. The revision of the data for 2012 and 2013 is planned, but has not yet taken place.5 We supplement these data with a classification of the NUTS 3 regions into the three categories predominantly urban, predominantly rural and intermediate. We supplement the NUTS 3 data from Eurostat by classifying the regions according to their affiliation to the old or new federal states. In the end, 373 NUTS 3 regions remain for which the data and classifications mentioned for 2000 to 2014 are completely available. This is the database for the following study. 6

The central study variable is the annual crude fertility rate, which is defined as the number of births per 1,000 members of the population. The raw fertility rate must not be confused with the total fertility rate, which is the most frequently used indicator at Destatis to characterize the current birth rate.7 The detailed data on the age of the women giving birth, which are necessary for its calculation, are in NUTS-3 -Statistics not available. Figure 3 gives a first impression of the data in the form of a "league table" (top 3, bottom 3). The first three regions have the highest fertility rate in the 2014 database, the remaining three have the lowest fertility rate this year.8 The black line in the middle shows the annual median of all 373 fertility rates. Each year, 186 NUTS 3 regions have fertility rates that are above or below this line. The figure shows the enormous ranges of fertility development in Germany. While the six designated regions began at roughly the same level in 2000, a gap has opened up between them at the current edge. The east-west difference in the birth rate takes a back seat, because four of the six regions are in the old federal states and the top 3 show an almost complete convergence between Dresden and the two major cities in western Germany. The contrast between urban and rural regions, on the other hand, is prominent.

Figure 3
Birth rates in NUTS 3 regions (top-bottom league table)
crude birth rate (number of births per 1000 inhabitants)

Source: Eurostat, accessed March 2016, own calculations.

Figure 4 takes up this problem by contrasting the pair of opposites “old federal states versus new federal states” with the pair of opposites “urban versus rural”. The majority of the available NUTS 3 regions appear twice in the figure: on the one hand as a region in the old or the new federal states, on the other hand as an urban or rural region.9 The respective regional type is compared with the overall German development. The horizontal axis shows the development of the population of the respective regional type compared to the overall German development from the base year 2000. The vertical axis shows the corresponding for the birth rate. The time series run from the inside out. Mind you: The four lines were not deliberately arranged in a star shape, this constellation results from the data. The line in the northwest quadrant shows that the new federal states lost around 6% of their population between 2000 and 2014 compared to the total German population, but were able to increase their birth rate by almost 30% compared to the overall German average. The other lines are to be understood accordingly. In summary, the following picture emerges:

  • The new federal states are losing population due to emigration, but increasing their birth rate. The old federal states are increasing their population, but their fertility rates are falling.
  • The rural regions are losing their population due to emigration and at the same time experience a decline in their birth rate, while the urban regions are increasing their population and the birth rate.

Figure 4 contains an invitation to rethink. The demographic debate in the Federal Republic is currently strongly fixated on the East-West contrast, which, as the figure shows, is actually serious. The population decline due to emigration is perceived as a problem that threatens the very existence of the new federal states. In return, the birth boom is celebrated as evidence that a younger generation is growing up and that hopes for the future are not lost. However, the east-west contrast, which is reflected in the northwest and southeast quadrants, embodies more of the past. The contrast between urban and rural regions is likely to be even more important for the demographic dynamics of the coming years. Migration movements and a new “baby boom” present the cities with new challenges that are acutely exacerbated by the influx of refugees.

Figure 4
Population and birth dynamics by regional type, 2000 to 2014
Changes in%, base year 2000 = 0

Source: Eurostat, accessed March 2016, own calculations.

Birth turnaround: when and where?

Has there actually been a change in the birth rate in the Federal Republic of Germany? In order to be able to answer this question with sufficient certainty, we have to systematically use the term birth turnaround. We explain our approach using the example of three NUTS 3 regions: Freudenstadt (NUTS label DE12C), Leipzig (DED51) and Passau (DE222). The solid lines in Figure 5 show the fertility rates in the three cities.

Figure 5
Selected annual fertility rates and quadratic trends
crude birth rate (number of births per 1000 inhabitants)

Note: dashed lines = estimated trends.

Source: Eurostat, accessed March 2016, own calculations.

A first approach to dating the birth rate of a region could be to identify the birth rate in the year in which the birth rate has the lowest value. Since the fertility rates are higher before and after, it tends to go down before and afterwards it tends to go up. The year of change dated in this way is 2001 in Leipzig, 2004 in Passau and 2012 in Freudenstadt. A disadvantage of this method is that it is prone to random fluctuations, data errors or outliers. In Passau this concerns the years 2003 and 2004, in which the available NUTS 3 data for births show considerable inaccuracies, which leads to fluctuations in the reported birth rate. In addition, with this method of dating the birth rate, the problem arises that even if the regional fertility rates were purely random over time, minimum fertility rates would occur in an (also random) number of NUTS 3 regions, which would then be incorrectly referred to as the birth rate.

In order to reduce the random dependency when dating the turn of the birth, an approach based on the method of latent growth curves is used.10 The time series of the fertility rates of each region is smoothed by a quadratic trend:

xit = ai + bi t + ci t 2 + uit

Xit denotes the logarithm of the fertility rate in region i in year t, with i = 1, ..., 373 as the index of the NUTS 3 regions and t = 1, ..., 15 as the index for the years 2000 to 2014. The Residuals uit capture the deviations from the quadratic trends. The coefficients ai, bi and ci are determined for each region by a least squares estimate. In Figure 5, the estimated trends are shown by the dashed lines.

The latent growth curve model for dating the turn of the birth not only has the advantage that the significance of the results achieved can be tested more easily, it also provides a concentration of the information on the essentials. The course of the fertility rate in each region is reduced to two relevant parameter values ​​(bi and ci). This means that three stylized growth curves can be distinguished for the birth trends, depending on whether the minimum of the birth trend is on the left, in the middle or on the right of the year 2000 to 2014:

  1. If the minimum of the trend line is in the year 2000 (e.g. for Leipzig), then the fertility rate of the region concerned is on the upswing over the entire period. The turn of the birth is then either in the year 2000 or before.
  2. If the minimum of the trend line is in one of the years from 2001 to 2013 (e.g. for Passau), then this is referred to as the year of the birth of the new year in the region.
  3. If the minimum of the trend line is in 2014 (e.g. Freudenstadt), then the fertility rate shows a downward trend over the entire period and the region has not (yet) experienced a birth turnaround.

With this method, the birth turnaround in Leipzig is dated to 2000 and in Passau to 2007. Compared to the method described first, there is a slight shift in the birth turnaround for Leipzig and a significant shift in Passau. According to this procedure, Freudenstadt did not have a birth rate in 2012 because its birth rate is in a permanent downward trend in the available period.

The upper part of Figure 6 shows how the trend reversal in fertility rates has spread over time. The columns indicate the number of regions which, according to the procedure described, are going through their birth turnaround in the respective year.This also means that these regions will show an increasing birth trend from then on. The column for 2000 indicates that 29 regions have increasing fertility rates over the entire period, 23 of them from the new federal states, 6 from the old ones.11 In the following years, the spread of the birth rate is initially static, only assuming between 2004 and 2008 Drive up. Then the real boom years of the birth turn follow. In 2009, 2010 and 2011 a total of 200 regions experienced a trend reversal, all in the old federal states. The momentum then slows down again, and in the end only 18 regions remain with falling fertility rates over the entire period. The lower part of the figure shows that the birth turnaround starts in regions with an above-average population. After picking up speed from the middle of the decade, increasingly smaller regions are being recorded. The proportion of urban regions is above average over the entire period. In the boom years of the turnaround, the proportion of urbanity rises steeply, only to decrease again afterwards. In concrete terms, this means that in the boom years from 2009 to 2011, increasingly smaller urban regions in the old federal states will be affected by the birth upturn, and later suburban and rural regions as well.

Figure 6
Number and profile of the regions with the turn of the birth

Source: Eurostat, accessed March 2016, own calculations.

connects the regional birth turnaround with the birth trend in Germany. The solid black line in Figure 7 represents the number of births; the bars show the number of births in those NUTS 3 regions that are on the rise from the relevant year at the latest, differentiated according to urban, suburban and rural regions.12 The dashed line shows the total number of births in the regions up to have not yet seen the birth rate in the relevant year. The figure shows that the ups and downs of the total German birth rate are based on a deep structure of regional change. At the beginning of the new millennium, the upswing in the birth rate in the new federal states and in the big cities is more than offset by the downswing in other regions; the overall German birth rate is therefore downwards. The more regions change over the years to the camp of the upswing, this downward movement comes to a standstill. From 2011 at the latest, the majority of the regions will be on the upswing, with the result that all German births will then increase. If the regional change described is permanent, then one can expect that the German birth upturn will continue for even longer.

Figure 7
Total births and births in regions where the birth rate began

Source: Eurostat, accessed March 2016, own calculations.

The turn of the birth: facts, questions, consequences

In many regions of Germany there has actually been a trend reversal in the fertility rate. It begins in the new federal states, where it initially presents itself as a correction of the massive drop in the birth rate after reunification. From 2000, the metropolitan regions in the old federal states (Hamburg, Munich) and Berlin are experiencing an upswing in the birth rate. From the middle of the decade, the trend reversal spread to increasingly smaller western German urban regions, and later also to suburban and rural regions, which, however, lag behind overall. The overall German birth trend reflects the shift in the balance between regions with a shrinking and booming birth rate. At the beginning of the 2000s, only a few regions were experiencing an upswing in the birth rate, which is why the overall German birth rate is falling. Ten years later, the trend reversal has spread to the majority of the regions, which is why the nationwide birth rate is beginning to rise. In the years in between (around 2005 to 2010), the upswing and downswing in the birth rate are roughly balanced, so that the nationwide birth rate stagnates. A kind of “relay race” can be observed in the east-west proportion of the birth rate. While the birth upswing begins mostly in the new federal states, in 2005 it spread to the old federal states, the proportion of which will exceed that of the new federal states from 2008 onwards. In view of the size differences between the new and the old federal states in terms of the number of regions and the population, a noticeable all-German birth boom can only occur if it also includes the old federal states. This will be the case from 2006 onwards.

What are the reasons for the trend reversal towards more children that is spreading before our eyes in Germany? In the public debate - if it has already identified the topic - there are often explanatory models that emphasize the change in values:

  • New generations, especially the so-called millennials, are increasingly turning to traditional values: community, family, children.
  • The crisis of the neoliberal value system that has prevailed for decades is changing the way people plan their lives. The goal of happiness in life through economic success becomes doubtful, people orientate themselves towards the community and the family. This also includes children again.
  • New urbanity is developing into a holistic way of life, in which not only the better range of cultural and educational institutions in the cities is important, but also the better ability to combine work, family and children. The supply of the appropriate infrastructure and support through a targeted social and family policy play an important role.

Obviously, these explanatory models are not sharply delimited from one another. Scientifically sound approaches to understanding the boom in the birth rate cannot ignore such explanatory patterns, but should be based on clear and, if possible, quantifiable facts. The change in values ​​cannot be ignored, but it takes place in a concrete socio-economic framework. The years 2009 to 2011 were identified as a particularly dynamic phase (boom years) in the turn of the German birth rate. In these years, two major upheavals are paralleled, which have concrete measurable effects on the economic situation of the people.

  • Global financial and economic crises: The Lehman crisis in 2008, followed by the great global economic recession in 2009 and 2010 by the sometimes ongoing euro crisis. For the population in the crisis countries, it brought about a considerable deterioration in the economic situation, which not least affected young sections of the population.
  • Turnaround in family policy in Germany: after a long history, it was decided in 2007 to replace childcare allowance with parental allowance, followed by the Child Promotion Act 2008, with the legal right of every child to attend a day care center from the age of one. An investment program to expand care facilities helped to give legal entitlement a real basis. These resolutions are recognized as the most important reorientation of German family policy for decades. 13

It is well known that the financial and economic crises in southern and northern Europe in recent years had completely different demographic effects. Especially young labor market migrants from the south made their way to the north. What is less well known is that the birth rate was also asymmetrical. Figure 8 shows that the fertility rates in the crisis countries Greece, Italy, Portugal and Spain plummet from the crisis year 2008 and in some cases fall below the German fertility rate by 2014, which survives the crisis unchanged and even increases in the end. In Great Britain, too, which was not directly affected by the euro crisis, the birth rate remained almost unchanged during this period. Millennials or the change in values ​​caused by the crisis cannot explain these north-south differences, because these factors should have the same effect in all countries. The reasons for the differences will have to be sought in the asymmetries of economic development. In the south, these include the dramatic rise in unemployment and, in particular, youth unemployment, the crisis in the real estate sector and, above all, the massive government spending cuts under the primacy of budget restructuring. All of them have a direct impact on the prospects of the younger generations and thus also on their family planning.

In Germany, the effects of the crisis can hardly be separated from those of the turnaround in family policy that took place at the same time. The decisive political decisions were made in 2007 and 2008, but some of the measures only came into effect with a delay (the legal right to childcare e.g. from mid-2013). The investment program to expand care facilities also took time. If these delays are taken into account, the effects of the turnaround in family policy are likely to fall precisely in the period of the boom years of the birth turnaround. A causal connection between family policy and the birth turnaround has not yet been proven, but it is a possibility that should be examined in more detail in further studies. Above all, the intra-European comparison and the strong, sometimes crisis-related movements in the relevant data offer the opportunity for new insights into the possibilities and limits of family policy.

Will the birth boom continue? It is well known that predictions are difficult when they concern the future. In view of the fact that in many of the NUTS 3 regions examined only a few years ago the birth rate began, it is still too early to predict a reliable upward trend in the fertility rate. We therefore urge you to rethink: Instead of vertical it is advisable to think horizontally; Instead of exclusively discussing the ups and downs of births, we should ask which factors have driven the regional spread of a more child-oriented model of society in Germany and could further drive it forward. The interplay between urban and rural regions is likely to play an important role. A look beyond the borders can help. A comparison of Figure 3 and Figure 8 shows that the front runners among German cities have achieved fertility rates that roughly correspond to the national fertility rate in Great Britain. Great Britain has long been much more urbanized than Germany. The country has already seen the recovery in birth rates that Germany is currently experiencing. For the German fertility development, a look at Great Britain could therefore be a look into the future.

Figure 8
Crisis and fertility in a European comparison
crude birth rate (number of births per 1000 inhabitants)

Source: Eurostat, accessed May 2016, own calculations.

We would like to thank Jan Engelhardt and Dr. Jana Windwehr, both Martin Luther University Halle-Wittenberg.

  • 1Demographie - Babyboom in Deutschland, in: Handelsblatt from December 16, 2015, www.handelsblatt.com/politik/deutschland/demografie-babyboom-in-deutschland/12730234.html.
  • 2 High birth rate: Why our big cities are experiencing a baby boom, in: Die Welt from 2.5.2016, www.welt.de/vermischtes/article154937473/Warum-unsere-Grossstaedte-einen-Babyboom-erleben.html.
  • 3 'New Berlin' or Not, Leipzig Has New Life, in: New York Times from September 2, 2014, www.nytimes.com/2014//07/travel/new-berlin-or-not-leipzig-has-new- life.html
  • 4 The abbreviation NUTS results from the first letters of the French name Nomenclature des Unités Territoriales Ttatistiques. Detailed information on NUTS statistics is available from Eurostat: http://ec.europa.eu/eurostat/web/nuts.
  • 5 Census-related revisions have different effects in the regions. Some win, some lose. On average, the population decreased from 2013 to 2014. We use the population data as it is available.
  • 6 See Eurostat, http://ec.europa.eu/eurostat/data/database.
  • 7 On the raw fertility rate: World Bank, Crude Birth Rate, http://data.worldbank.org/indicator/SP.DYN.CBRT.IN/. The World Bank uses the crude birth rate to compare fertility in different countries. For the summarized fertility rate: Federal Institute for Population Research (BiB), Glossary, www.bib-demografie.de/SharedDocs/Glossareintraege/DE/Z/zgenössgefierte_geburtenziffer.html.
  • 8 When selecting the bottom 3 regions, we exclude the Saarbrücken regional association, where the fertility rates of recent years may have been skewed due to census-related revisions of the population.
  • 9 Suburban (intermediate) NUTS 3 regions are not taken into account in this second pair of opposites.
  • 10 Cf. e.g. F. Schmiedek, J. K. Wolff: Latent Growth Curve Models, in: C. Wolf, H. Best (Ed.): Handbuch der Sozialwissenschaftlichen Datenanalyse, Wiesbaden 2010, pp. 1017-1029.
  • 11 This group includes Chemnitz, Darmstadt, Dresden, Düsseldorf, Eisenach, Erfurt, Frankfurt am Main, Gera, Halle (Saale), Heidelberg, Jena, Leipzig, Magdeburg, Munich, Potsdam and Weimar.
  • 12 These are the births in the regions which had their trend reversal in the fertility rate in or before the year in question. Due to the design, the height of these columns cannot decrease. The decisive factor is when and how quickly the increase occurs. This concerns the question of whether the identified regional birth turns are statistically significant. Tests with various methods (Monte Carlo, resampling) showed in all cases that the null hypothesis that the temporal distribution of the regional birth turns is random can be rejected.
  • 13 In more detail: A. Blohme: The becoming of a turning point. Attitudes, party competition and changing family politics (1990-2008), in: WZB Mitteilungen, H. 143 (March 2014), pp. 6-9.

Title: Trend Change in German Fertility Rates - What Are the Causes?

Abstract: In comparison to other European countries, Germany is among those with the lowest birth rate and the highest median age of the population. Yet recently there are signs of a trend change in German fertility. For a decade now, birth rates in larger German cities have been on the rise, and this new baby boom has spread to smaller urban regions, leading to a trend change in overall fertility. The main years of this trend change are 2009 through 2011, parallel to the economic and financial crises of that time and following in the wake of important changes in German family policy in 2007/2008.

JEL Classification: J10, J11, J13