Meine Merkliste Geteilte Merkliste PDF oder EPUB erstellen

Internal migration in Germany from 1991-2022 | Western Europe | bpb.de

Western Europe Belgium Migration and Migration Policy in Luxembourg Migration and migration politics in Austria Internal migration in Germany from 1991-2022

Internal migration in Germany from 1991-2022

Jeroen Royer Jonathan Gescher Tim Leibert

/ 12 Minuten zu lesen

Annually, about four million people move across administrative borders within Germany. What are the general trends of internal migration? How have they changed over time? An overview.

A removal van stands in front of an apartment building in Berlin on June 11, 2013. (© picture-alliance/dpa, Bodo Marks)

Migration as a driver of regional demographic development

Media and politics are increasingly discussing questions of demographic change, especially migration - both internal and international. Rightfully so, as it has an important influence on the demographic development of a region. Yet, the migration balance is not the only player in the field. The natural balance, defined as the difference between births and deaths, holds significant implications for long-term demographic changes. From 1990 till 2022, Germany has witnessed 24.7 million births and 29.3 million deaths, resulting in a population deficit of 4.6 million individuals. The negative natural balance implies that Germany's population would have declined without the influx of international migrants.

A migrant is defined as a person moving across an administrative border. While this definition is straightforward, several factors merit consideration when examining migration figures, e.g. the geographical unit or the type of migration, considering subsets of total migration like age groups, gender, internal or international migration. Migration is a multifaceted phenomenon, going beyond net numbers, primary drivers, or destinations. Individual motivations for migration decisions are numerous. With this in mind, we will concentrate on the overarching trends and patterns.

The article starts with a short insight into the current trends of international migration towards Germany. This is followed by a description of the general tendencies of internal migration within Germany, focussing on the changing dynamics influenced by the longstanding East-West pattern and the redistribution and secondary movements of asylum seekers and refugees. Additionally, we take an in-depth look at Baden-Wuerttemberg as an example of changing dynamics. Furthermore, we summarise some general trends concerning the changing spatial pattern of internal migration at the district level since 1991. This is followed by an outlook on demographic developments in Germany and a conclusion.

International migration

An analysis of migration patterns and trends in Germany would be incomplete without a brief overview of international migration. In the context of an ageing society with a negative natural population development, population growth is only possible if the number of in-migrants exceeds the death surplus of the resident population.

International migration is a very dynamic component of population change, fluctuating between 1.3 million arrivals and departures in 2006 and 3.9 million in 2022. Since the early 2010s, Germany has become increasingly attractive for international migrants. Disregarding the peaks in 2015 (1.1 million) and 2022 (1.5 million), the average yearly international migration balance in the period 2010-2022 was 359,000 more arrivals than departures. In the period up to 2060, Germany would need an average annual net migration of 300,000 people to achieve a constant total population and a net 512,000 in-migrants per year to keep the size of the working-age population constant.

The geography of international migration to Germany has changed significantly in recent years. Between 2005 and 2014, countries of Central and South-Eastern Europe (e.g. Poland, Romania and Bulgaria) became the most important countries of origin after joining the EU. Since 2015, war-torn countries like Syria and Afghanistan have been among the top-5 sending countries. The quantitatively most important countries of origin of asylum seekers have been remarkably stable since 2017: Afghanistan, Eritrea, Georgia, Iran, Iraq, Nigeria, the Russian Federation, Somalia, Syria and Turkey. Asylum seekers and refugees are on average young and male – more than 50 percent are below 25 years of age.

International migration is closely connected to internal migration streams, e.g. in the form of secondary movements of refugees and asylum seekers from the initial reception centres. International migration is also highly selective, both in terms of preferred destinations and the migrants’ socio-demographic characteristics. This selectivity reinforces spatial disparities in population development. Migrants are over-represented in urban agglomerations, but there are also striking differences by nationality, and historical influences are still discernible (e.g. the destinations of the “guestworker” migration in the 1960s and 1970s). As a result, as of December 31, 2022, the share of foreign nationals in the population ranges from 3.4 percent in Erzgebirgskreis (Saxony) to 45.8 percent in the city of Offenbach (Hesse), with a national average of 15.9 percent. Just under 38 percent of foreign nationals living in Germany are EU citizens.

Asylum seekers are distributed to Laender (federal states), districts and municipalities based on quotas (e.g. the “Königsteiner Schlüssel”), which means that they have limited choice regarding their final destination. The idea that all Laender and districts should receive a “fair share” of the asylum seekers, has the “side effect” that some regions of Germany which would otherwise be unattractive for international migrants, e.g. structurally weak rural areas, become home (at least temporarily) to foreign nationals who would probably not have chosen to settle there.

Furthermore, the age-selectivity of international migration to Germany is also reflected in the population structure. The immigration of comparatively young people positively influences the age-structure of the working-age population and is therefore an important factor in sustaining future economic growth and prosperity. To illustrate the need for immigration into the labour market: 35 percent of Germany’s workforce is currently older than 50 – this means that one in three employees will retire in the next 15 years, adding to the already existing skills and staff shortages in many branches of the economy.

Figure 1: Volume of migration flows between Länder 1991-2022 by nationality. The distinction between nationalities is only consistently available from 2000 to 2020. Source: Destatis (2023 c,d) (© ifl. 2024. Inhalt: J. Gescher / Grafik: S. Dutzmann)

General trends of internal migration in Germany

Since 1991, the volume of internal migration has remained relatively stable with around four million moves across municipal borders per year. In the same period, an annual average of 1.0 to 1.2 million persons have moved between the 16 German Laender (Figure 1). There is an age-selectivity to these migration streams as illustrated in Figure 2. Children and older individuals tend to move less frequently, while young adults are highly mobile, often motivated by education or work-related factors.

Figure 2: Migration rates across state (Länder) boundaries by age group 1991-2020. Migration rates are calculated as the number of moves per 1,000 inhabitants of the particular age group. Source: 1991-1999: Statistische Ämter des Bundes und der Länder (2022); 2000-2020: Statistisches Bundesamt (Destatis) (2023i) (© ifl. 2024. Inhalt: J. Gescher / Grafik: S. Dutzmann)

Both the years 2001 and 2016 stand out as periods of particularly high internal migration activity, although for different reasons. The peak in 2001 was caused by larger migration flows of German nationals moving from one federal state to another (Figure 1: orange line), especially from the eastern to the western part of Germany. On the other hand, in 2016, there was a larger share of foreign nationals (Figure 1: green line) migrating across Laender borders caused by the redistribution of refugees and asylum seekers discussed above.

The changing pattern of East-West migration

Figure 3: Volume (and balance) of migration between East and West Germany (without Berlin) 1991-2022. Source: Destatis (2023 e) (© ifl. 2024. Inhalt: J. Gescher, T. Leibert / Grafik: S. Dutzmann)

Migration between the eastern and western Laender plays a crucial role in Germany's internal migration patterns. Figure 3 shows the migration streams between East and West from 1991 to 2022. Until the mid-2000s, East-West migration accounted for at least one-fifth of the total internal migration volume. After a significant outflow in the early 1990s, there was a new wave of out-migration from East Germany in 2001. The numbers of East-West migrants have been decreasing steadily ever since. In 2022, around 17 percent of moves across state borders were from the West German Laender to the East German states. Migration from West to East has remained remarkably stable. Since 1994, around 100,000 persons have moved from the western Laender to the East each year. With this number constant and declining East-West migration, there was a shift in the migration balance in favour of the eastern Laender in the mid-2010s. Since then, the migration balance has been nearly levelled between the two parts of the country.

Migration flows from East to West Germany are driven by 25- to 29-year-olds. Typical motives for their migration are vocational or university education and taking up employment. By contrast, flows from western Germany to the country’s eastern Laender are dominated by migrants between 30 and 49 years of age. This is partly due to return migration, which makes up about half of all West-East moves and is especially high in the family formation phase, and for highly educated individuals returning for economic reasons.

Case study: Baden-Wuerttemberg

Figure 4: Yearly net migration from and to Baden-Wuerttemberg per 1.000 inhabitants (Source: Statistisches Bundesamt (Destatis) 2023e) ©ifl. 2024, Content: J. Gescher / Cartography: A. Kurth

Baden-Wuerttemberg provides an intriguing case study of the changing dynamics of internal migration between East and West, North and South (Figure 4). In the 1990s and 2000s existed a noticeable North-South migration pattern, next to the widely discussed East-West movements. Over the whole period from 1990 to 2022, Baden-Wuerttemberg gained more people net from Lower Saxony than from any other state. Like the East-West migration, this pattern has been changing in recent years. While in 2001, Baden-Wuerttemberg gained nearly 45,000 residents through internal migration, in 2022, it lost around 10,000 residents to other Laender. Notably, this population loss extended beyond neighbouring federal states and encompassed almost the entire country (Figure 4).

Figure 5: Net migration from and to Baden-Wuerttemberg in the age group 30 to 50 in 2001 and 2022 (Source: Statistische Ämter des Bundes und der Länder 2022; Statistisches Bundesamt (Destatis) 2023i) (© ifl. 2024. Inhalt: J. Gescher / Kartographie: A. Kurth)

A closer examination of migration statistics by age groups reveals a significant shift in patterns. In 2001, Baden-Wuerttemberg gained migrants across all age groups. The most important groups of in-migrants were those under 25 and between 30 to 49 years of age. By 2022 this pattern had reversed with the 30 to 49-year-olds having the most significant net out-migration (Figure 5). Overall Baden-Wuerttemberg lost population across all age groups to the other Laender that year.

As discussed above, this only reflects internal migration. When considering international migration, Baden-Wuerttemberg gained approximately 180,000 residents in 2022 – more than enough to compensate for the negative internal migration balance.

Internal migration at district level

Most internal migration movements occur over short distances. On average, 40 percent of all internal migrants in Germany move to a neighbouring district. From 1990 to the early 2000s, the share of people in East Germany moving to neighbouring districts was (in most years) lower than in western Germany due to the previously mentioned East-West migration. As a result, most districts in East Germany lost population due to net out-migration over longer distances (see Figure 6). However, suburban districts around cities in the East like Berlin, Leipzig and Rostock were exceptions to this trend in the second half of the 1990s. After 2001, many east German cities, most notably Leipzig and Potsdam, started to benefit from a re-urbanisation trend. As a result, the proportion of immigration from neighbouring districts in eastern Germany has developed similarly to that in western Germany.

Figure 6: Evolution of the internal migration pattern from 1991 to 2022. Source: BBSR (2023), Statistische Ämter des Bundes und der Länder (2023a, e,), Destatis (2023h), Leibert et al. (2022). ©ifl. 2024, Content: J. Gescher / Cartography: S. Dutzmann

Since 2014, the large-scale influx of asylum seekers to Germany has had a significant impact on internal migration. In 2015, most districts in both East and West Germany were net receivers of internal migrants. However, some districts like Göttingen, Osnabrück and Oder-Spree have been characterised by intense out-migration. Both the large net out-migration of certain districts and the net in-migration in most other districts are consequences of the internal redistribution of asylum seekers from the districts of initial arrival in reception centres to the rest of the country. This illustrates how internal and international migration are closely linked.

Figure 7: Internal migration rate (left) and internal migration rate to neighbouring districts (right) for 2022. Data sources: Statistische Ämter des Bundes und der Länder (2023a), Destatis (2023h) (© ifl. 2024. Inhalt: J. Royer / Kartographie: S. Dutzmann)

Since 2017, a new spatial pattern breaking with the East-West pattern has started to emerge. The East had a positive net migration for the first time since reunification. However, there is some regional variation. Figure 7 shows a pattern with internal migration losses in urban districts and gains in the surrounding rural districts. This shows that there has been a new suburbanisation trend since the end of the 2010s, caused by rising housing prices and costs of living in urban areas. Additionally, the impact of the COVID-19 pandemic played a role in the negative migration balance in urban areas. However, the migration from the big cities to the suburbs was a trend that had already started before the pandemic and therefore cannot (only) be attributed to changes in housing preferences and needs caused by the lockdown experiences during the pandemic.

The need for a full picture

Figure 8: Typology of the drivers of population development 2019-2021. Own calculations; data source: Statistische Ämter des Bundes und der Länder (2023 b,c,d) (© ifl. 2024. Inhalt: T. Leibert / Kartographie: B. Hölzel)

Internal migration is both influencing and influenced by international migration, natural population development and the age structure of Germany’s population. To highlight these interlinkages, we combined the different drivers of population development in Figure 8 for the period 2019-2021. This period was heavily influenced by the COVID-19 pandemic, including restrictions on residential mobility and international migration due to lockdown measures both in Germany and abroad. According to the basic equation of demography, population development in a given area is determined by the natural and the migration balance. Hence, there are six possible combinations of regional population development (see figure 8). As a result of Germany’s long history of birth rates below replacement level and population ageing, there are only a few districts whose population is growing due to both a positive natural balance and a surplus of in-migrants (Type 1). The positive natural population balance in most of these regions results from selective in-migration of young adults. This influx of younger people reduces the death rate. At the same time, the share of potential parents in the population rises, which increases the number of births per 1,000 inhabitants. University towns and large cities with a significant share of immigrants with higher birth rates are featured in this type. However, the suburban hinterland of major urban agglomerations, as well as some regions with historically high birth rates, notably the districts of Cloppenburg and Vechta in the Oldenburg Muensterland in Lower Saxony, also belong to Type 1. The spatial pattern of districts with a positive natural balance has been relatively stable since at least 2011.

More common is Type 2, where natural population development is negative but the number of internal and/or international migrants is high enough to compensate for the natural losses. In the past, this type was typical for economically strong regions, especially in the South – and the suburban hinterland of Berlin and Hamburg. Nonetheless, it has become the dominant type in western Germany since the mid-2010s. Changing patterns of migration connected to the COVID-19 pandemic are contributing to this trend. They are characterised by a slowdown of in-migration in many large cities or even a turnaround towards a negative migration balance and an increasing popularity of the suburban hinterland as a migration destination. The latter trend has already started in the mid-2010s, while the negative trend in the larger cities is clearly connected to the pandemic. Rising rents and housing prices play an important role, negatively affecting in-migration, especially in urban areas. Additionally, they also act as a push-factor in the largest cities, motivating inhabitants to consider relocating to cheaper areas. A closer look at the structure of in-migration reveals that without international migration, 62 of the 213 Type-2 districts would be shrinking. This is not only true for structurally weak rural areas or old industrial cities with unfavourable labour markets and living conditions. Many economically strong districts with very low unemployment rates, for example in Baden-Wuerttemberg or southern Hesse, also have a negative migration balance of German citizens.

Remote work, changing housing requirements, but also mobility restrictions due to the pandemic as well as lockdown measures like the digitalization of university education have had an additional negative impact on the migration balance of most of the major cities and university towns. As a result, natural population development is the main driver of population growth in some of the cities that used to be Type-1 districts in the early and mid-2010s (e.g. Cologne, Frankfurt, Heidelberg, Munich or Stuttgart). These cities now belong to Type 3 (natural gains overcompensate migration losses) if the surplus of births is high enough to compensate for the negative migration balance, and to Type 4 (migration losses exceed natural gains) if the number of departures is higher than the natural population gains.

Districts where the inflow of internal and international migrants is too small to counterbalance the negative natural population development (Type 5: natural losses exceed migration gains) are concentrated in regions with a long history of shrinkage and out-migration – rural East Germany, Upper Franconia, Northern Hesse, the South-eastern part of Lower Saxony, Saarland and Western Palatinate. Decades of selective out-migration have led to population ageing and therefore to a loss of reproductive potential. Most of the mentioned regions are also structurally weak and hence less attractive for job-related in-migration.

Type 6 (shrinking due to natural and migration losses) represents the most unsustainable combination of the main drivers of population change: a surplus of deaths and out-migration. Over time, the number of Type-6 districts has declined considerably, especially in East Germany, mostly because of increasing numbers of international migrants. In the 2000s and early 2010s, out-migration from East Germany in general and from sparsely populated rural districts in particular was highly selective, with young people, and especially young women between 18 and 29 being most likely to move away, leaving behind an ageing and declining population.

The development since the mid-2010s in rural East Germany is also proof that negative population trends are not carved in stone if economic conditions improve and international migrants move (or are sent) to previously declining regions. However, it will be increasingly difficult to counterbalance the negative natural population development in the future, particularly in districts with a longer history of selective out-migration and shrinkage – and especially high natural losses due to an ageing population. Most of these districts are located in Germany’s eastern Laender Brandenburg, Saxony, Saxony-Anhalt and Thuringia. In eastern Germany, the number of districts with a shrinking population due to death surplus and emigration is therefore likely to increase in future.

Looking into the future, the districts currently belonging to Types 3 and 4 appear to be at the crossroads. If international migration and the in-migration of internal migrants in the 18 to under 30 age group were only temporarily negatively affected by the pandemic, a return to Type 1 is likely. However, if the migration balance remains negative due to losses of young couples and families to the suburban hinterland outnumbering international in-migration, there is a “worst case scenario” that some of the large cities might transition to Types 5 or even 6 if the selective out-migration of potential (or actual) parents erodes the favourable “young” population structure and therefore the basis of natural gains.

Conclusion

Migration shapes regional demographic developments. After years of focussing on migration flows from East to West Germany, this picture has changed in recent years. Small-scale migration, suburbanisation and international migration have become the determining factors of population change in Germany. Rural districts are increasingly growing, while urban centres are at least struggling with the emigration of inhabitants to other districts in Germany. In order to understand regional demographic developments in the long term, it is therefore necessary to keep an eye on both internal migration and its interdependencies and interactions with international migration and natural population development. Beyond absolute population figures, the selectivity of migration as a volatile driver of population change sets the course for future developments (e.g. ageing or reproductive potential), to which the provision of housing and social and technical infrastructure (e.g. schools, water supply, public transport) must be adapted. Unfortunately, the necessary detailed migration data has no longer been provided by the Federal Statistical Office since 2018. A return to the previous provision practice would significantly improve the understanding of demographic developments, especially during the COVID-19 pandemic, and support the targeted use of infrastructure investments.

Quellen / Literatur

Brake, Klaus, Dangschat, Jens S., & Herfert, Günter (2001). Suburbanisierung in Deutschland. VS Verlag für Sozialwissenschaften, pp. 273-279.

Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR) im Bundesamt für Bauwesen und Raumordnung (BBR) (2023). INKAR – Indikatoren und Karten zur Raum- und Stadtentwicklung. Online verfügbar unter Externer Link: https://www.inkar.de/ (accessed: 12.10.2023).

Craveiro, Daniela; De Oliveira, Isabel Tiago; Gomes, Maria Sousa; Malheiros, Jorge; Moreira, Maria João Guardado; Peixoto, João (2019). Back to replacement migration. In: Demographic research 40, Article 45, pp. 1323-1344. DOI: 10.4054/DemRes.2019.40.45.

Heider, Bastian; Stroms, Peter; Koch, Jannik; Siedentop, Stefan (2020). Where do immigrants move in Germany? The role of international migration in regional disparities in population development. In: Population, Space and Place 26 (8), Artikel e2363. DOI: 10.1002/psp.2363.

Hölzel, David J.; Milbert, Antonia (2023). Grenzenlos mobil? Nah- und Fernwanderungen seit 1991 auf Basis der Wanderungsverflechtungen zwischen den Stadt- und Landkreisen. In: Stadtforschung und Statistik 36 (2), pp. 54-62.

King, Russell; Okólski, Marek (2019). Diverse, fragile and fragmented: The new map of European migration. In: Central and Eastern European Migration Review, 8 (1), pp. 9-32. DOI: 10.17467/ceemr.2018.18.

Lehmann, Robert; Nagl, Wolfgang (2019). Explaining spatial patterns of foreign employment in Germany. In: Regional Studies 53 (7), pp. 991-1003. DOI: 10.1080/00343404.2018.1515479

Leibert, Tim (2019). Demographischer Wandel ade? Aktuelle Einwohnerentwicklung in Deutschland. In: Nationalatlas aktuell 13 (01.2019) 1 [31.01.2019]. Leipzig: Leibniz-Institut für Länderkunde (IfL). URL: Externer Link: http://aktuell.nationalatlas.de/Einwohnerentwicklung-1_01-2019-0-html/

Leibert, T. (2020). Wanderungen und Regionalentwicklung. Ostdeutschland vor der Trendwende? In: Becker, Sören; Naumann, Matthias (eds.): Regionalentwicklung in Ostdeutschland: Dynamiken, Perspektiven und der Beitrag der Humangeographie. Berlin, Heidelberg, pp. 199-210.

Leibert, Tim (2021a). Alterung und Stillstand auf dem Arbeitsmarkt. In: Nationalatlas aktuell 15 (05.2021) 2 [12.05.2021]. Leipzig: Leibniz-Institut für Länderkunde (IfL). URL: Externer Link: http://aktuell.nationalatlas.de/arbeitsmarkt-2_05_2021-0-html/

Leibert, Tim (2021b). Ausländische Beschäftigte – die Antwort auf den demografischen Wandel? In: Nationalatlas aktuell 15 (11.2021) 7 [01.11.2021]. Leipzig: Leibniz-Institut für Länderkunde (IfL). URL: Externer Link: http://aktuell.nationalatlas.de/arbeitsmarkt-7_11_2021-0-html/

Leibert, Tim; Friedrich, Klaus (2023). Sind Geschlechterdisproportionen unter jungen Erwachsenen noch ein relevantes raumplanerisches und demographisches Thema? In: Stadtforschung und Statistik 36 (2), pp. 63-70.

Leibert, Tim; Wolff, Manuel; Haase, Annegret (2022). Supplement of Shifting spatial patterns in German population trends: local-level hot and cold spots, 1990–2019. In: Geographica Helvetica, 77(3). Externer Link: https://doi.org/10.5194/gh-77-369-2022-supplement

Osterhage, Frank; Kaup, Stefan (2012). Reurbanisierung als neue Phase der Stadtentwicklung? Eine Analyse der Bevölkerungs-und Beschäftigtenentwicklung in Deutschland 1999 bis 2009. In: Jahrbuch StadtRegion, 7(1), pp. 125-141.

Osterhage, Frank; Albrecht, Janna (2021). Schwankungen – Verschiebungen – Brüche. Veränderungen beim bundesweiten Wanderungsgeschehen in den vergangenen zwei Jahrzehnten. Dortmund. ILS-Trends 3/2021.

Ravenstein, E. G. (1885). The Laws of Migration. In: Journal of the Statistical Society of London 48 (2), S. 167. DOI: 10.2307/2979181.

Rosenbaum-Feldbrügge, Matthias, Nico Stawarz, and Nikola Sander (2022). 30 Years of East-West Migration in Germany: A Synthesis of the Literature and Potential Directions for Future Research. In: Comparative Population Studies 47.

Statistische Ämter des Bundes und der Länder (2022). Wanderungsmatrix 1991 bis 2017 insgesamt. Harmonisiert und bereitgestellt vom Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR).

Statistische Ämter des Bundes und der Länder (2023a). Kreiswanderungsmatrix (KWM) 2022. Externer Link: https://www.statistikportal.de/de/veroeffentlichungen/kreiswanderungsmatrix (accessed: 12.10.2023).

Statistische Ämter des Bundes und der Länder (2023b). Regionaldatenbank Deutschland, Tabelle 12612-01-01-4, Lebendgeborene nach Geschlecht – Jahressumme – regionale Tiefe: Kreise und krfr. Städte. Externer Link: https://www.regionalstatistik.de/genesis/online/logon (accessed: 19.09.2023).

Statistische Ämter des Bundes und der Länder (2023c). Regionaldatenbank Deutschland, Tabelle 12613-01-01-4, Gestorbene nach Geschlecht – Jahressumme – regionale Tiefe: Kreise und krfr. Städte. Externer Link: https://www.regionalstatistik.de/genesis/online/logon (accessed: 19.09.2023).

Statistische Ämter des Bundes und der Länder (2023d). Regionaldatenbank Deutschland, Tabelle 12711-04-02-4, Zu- und Fortzüge (über Kreisgrenzen) nach Geschlecht und Altersgruppen – Jahressumme – regionale Tiefe: Kreise und krfr. Städte. Externer Link: https://www.regionalstatistik.de/genesis/online/logon (accessed: 19.09.2023).

Statistisches Bundesamt (Destatis) (2023a). 12612-0100: Lebendgeborene: Bundesländer, Jahre, Geschlecht. Externer Link: https://www-genesis.destatis.de/ (accessed: 11.10.2023).

Statistisches Bundesamt (Destatis) (2023b). 12613-0010: Gestorbene: Bundesländer, Jahre. Externer Link: https://www-genesis.destatis.de (accessed: 11.10.2023).

Statistisches Bundesamt (Destatis) (2023c). Wanderungen zwischen den Bundesländern: Bundesländer, Jahre, Nationalität, Geschlecht. Externer Link: https://www-genesis.destatis.de (accessed: 11.10.2023).

Statistisches Bundesamt (Destatis) (2023d). Zeitreihe 1991-2022 Bundesländer Altersgruppen. Bereitgestellt von Destatis.

Statistisches Bundesamt (Destatis) (2023e). Zeitreihe 1951-2022 Kreuztabelle Bundesländer. Bereitgestellt von Destatis.

Statistisches Bundesamt (Destatis) (2023f). 12521-0041: Ausländer: Kreise, Stichtag, Geschlecht Ländergruppierungen/ Staatsangehörigkeit. Externer Link: https://www-genesis.destatis.de (accessed: 23.10.2023).

Statistisches Bundesamt (Destatis) (2023g). 12711-0005: Wanderungen zwischen Deutschland und dem Ausland: Deutschland, Jahre, Nationalität, Geschlecht. Externer Link: https://www-genesis.destatis.de (accessed: 18.10.2023).

Statistisches Bundesamt (Destatis) (2023h). 12411-0015: Bevölkerung: Kreise, Stichtag. Externer Link: https://www-genesis.destatis.de/ (accessed: 21.10.2023).

Statistisches Bundesamt (Destatis) (2023i). 12711-0004: Wanderungen zwischen den Bundesländern: Deutschland, Jahre, Nationalität, Geschlecht, Altersjahre. Externer Link: https://www-genesis.destatis.de/ (accessed: 04.12.2023).

Statistisches Landesamt Baden-Württenberg (2023). Wanderungen über die Landesgrenze nach Herkunft und Ziel. Externer Link: https://www.statistik-bw.de/BevoelkGebiet/ZuFortzuege/bev_wanderung.jsp (accessed: 12.10.2023).

Stawarz, Nico; Sander, Nikola (2019). The Impact of Internal Migration on the Spatial Distribution of Population in Germany over the Period 1991-2017. In: Comparative Population Studies 44, S. 291–316. DOI: 10.12765/CPoS-2020-06en.

Stawarz, Nico; Sander, Nikola; Sulak, Harun (2021). Internal migration and housing costs—A panel analysis for Germany. In: Population, Space and Place, 27 (4), e2412. Externer Link: https://doi.org/10.1002/psp.2412

Stawarz, Nico; Sander, Nikola; Sulak, Harun; Rosenbaum-Feldbrügge, Matthias (2020). The turnaround in internal migration between East and West Germany over the period 1991 to 2018. In: Demographic Research 43, Article 33, pp. 993-1008. DOI: 10.4054/DemRes.2020.43.33.

Wagner, Michael; Mulder, Clara H. (2015). Spatial Mobility, Family Dynamics, and Housing Transitions. In: Köln Z Soziol 67 (S1), S. 111–135. DOI: 10.1007/s11577-015-0327-4.

Wolff, Manuel; Leibert, Tim; Haase, Annegret u. Dieter Rink (2022). Neue regionale Wanderungsdynamik durch die COVID-19 Pandemie? In: Nationalatlas aktuell 16 (01.2022) 1 [20.01.2022]. Leipzig: Leibniz-Institut für Länderkunde (IfL). URL: Externer Link: http://aktuell.nationalatlas.de/bevoelkerungsentwicklung-1_01_2022-0-html/

Fussnoten

Fußnoten

  1. Destatis (2023a); (2023b).

  2. Woellert et al. (2022).

  3. Own calculations; data source: Destatis (2023g).

  4. Own calculations; data source: Destatis (2023g).

  5. Craveiro et al. (2019).

  6. King & Okólski (2019).

  7. Bundeszentrale für politische Bildung (2023).

  8. Glorius & Nienaber (2022).

  9. Heider et al. (2020).

  10. Lehmann & Nagl (2019).

  11. Own calculations; data source: Destatis (2023f).

  12. Own calculations; data source: Destatis (2023f).

  13. Glorius & Nienaber (2022).

  14. Glorius & Nienaber (2022: 155).

  15. Leibert (2021b).

  16. Leibert (2021a).

  17. Hölzel & Milbert (2023).

  18. Stawarz & Sander (2019).

  19. Stawarz & Sander (2019).

  20. Stawarz et al. (2020).

  21. Stawarz et al. (2020).

  22. Rosenbaum-Feldbrügge et al. (2022).

  23. Statistisches Landesamt Baden-Wuerttemberg (2023).

  24. Osterhage & Kaup (2012).

  25. Stawarz et al. (2020).

  26. Wolf et al. (2022).

  27. For similar analyses on earlier periods (2011-2013 and 2014-2016) using the same approach see Leibert (2019).

  28. Number of deaths per 1,000 inhabitants.

  29. Leibert (2019).

  30. Wolff et al. (2022).

  31. Stawarz et al. (2020).

  32. Wolff et al. (2022).

  33. See Leibert (2019).

  34. See also Leibert (2019) for earlier periods.

  35. Leibert (2019).

  36. Stawarz et al. (2020).

  37. Leibert (2020); Leibert & Friedrich (2023).

Lizenz

Dieser Text ist unter der Creative Commons Lizenz "CC BY-NC-ND 4.0 - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International" veröffentlicht. Autoren/-innen: Jeroen Royer, Jonathan Gescher, Tim Leibert für bpb.de

Sie dürfen den Text unter Nennung der Lizenz CC BY-NC-ND 4.0 und der Autoren/-innen teilen.
Urheberrechtliche Angaben zu Bildern / Grafiken / Videos finden sich direkt bei den Abbildungen.
Sie wollen einen Inhalt von bpb.de nutzen?

Weitere Inhalte

is a research associate in the Mobilities and Migration research group at the Leibniz Institute for Regional Geography (IfL) in Leipzig, Germany. His research interests include regional development, urbanisation, migration and demographic change.

is a research associate in the Mobilities and Migration research group at the Leibniz Institute for Regional Geography (IfL) in Leipzig, Germany. His main areas of research are urban-rural migrations, regional development and small towns.

Dr. Tim Leibert is the deputy coordinator of the Mobilities and Migration research group at the Leibniz Institute for Regional Geography (IfL) in Leipzig, Germany. His research focuses on demographic change, regional development and migration.