Over the long term, the key drivers of economic growth are innovation, technological advances, and productivity gains. However, the weak growth in Germany’s potential output over the next ten years will also be strongly influenced by labour input. One key reason for this is the decline in labour supply as a result of demographic change. 

Demographic change is squeezing Germany’s labour supply primarily through two channels. First, the number of persons of working age will decline, especially in the coming years as the baby boomers enter retirement. Second, the share of older persons among the working-age population is rising. This lowers the labour force participation rate, as older workers tend to have lower participation compared with younger workers (age structure effect). 

It is not only Germany’s future GDP growth that is affected by the labour supply shortages. Bundesbank calculations show that the age structure effect has, in arithmetical terms, already resulted in a decline in economic growth of around 0.4 percentage point per year over the past ten years. In the coming years, this negative effect is likely to increase to around 0.6 percentage point per year. The shrinking population will then contribute to growth diminishing by an additional 0.2 percentage point. Further analyses show that demographic ageing also has an impact via an indirect channel in that it is slowing productivity growth in Germany. This means that demographic ageing is weighing on both labour input and productivity. In the past, high immigration and rising labour force participation among women and older people counteracted these dampening effects. However, these counteracting impulses are likely to be less pronounced in the coming years.

When estimating the potential for higher labour input, it is worth considering labour force participation and hours worked among different population groups. The labour force participation rates of older people and women in Germany are now quite high by European standards. However, under the existing framework conditions, older people frequently retire before reaching the statutory retirement age. Furthermore, in many cases, older people and women work part-time with low average weekly hours of work. This results in low average hours of work. However, this is mainly a reflection of the fact that many of the people who now work part-time would not have worked at all in the past. Despite this development – which is, in fact, positive – there are indications that women, in particular, often want to increase their number of working hours beyond their existing hours. It is not uncommon that the existing framework conditions restrict women’s incentives and opportunities to increase their hours of work. These include inadequate childcare facilities and adverse financial incentives to work for married second earners. 

A key lever for mitigating the economic repercussions of demographic change is thus to increase the number of hours worked by part-time employees. However, there is also scope for action with regard to labour force participation and immigration. If this were utilised, potential growth could be considerably higher. This would require better framework conditions in terms of economic policy. The present article discusses various measures that would contribute to this.

This article examines the impact of demographic change on labour supply and economic growth in Germany. Growth in potential output is determined by developments in technological advances, capital stock, and labour input. Over the long term, the main drivers of growth and prosperity are productivity gains through innovation and the successful use of new technologies. However, due to demographic ageing in Germany, the decline in labour input will be a key reason for the weak growth in Germany’s potential output over the next ten years. Demographic change has been shaping developments in Germany for a longer period of time now. However, an especially large number of people will enter retirement over the coming years. In addition, in the past, the impact of demographic ageing on labour input and growth has long been masked by high immigration and rising labour force participation among women and older people. For these reasons, demographic pressures will become more apparent in the future. This situation raises the following question: which components of labour input could help mitigate the expected decline in labour input, and how much potential is there to do so?

Macroeconomic growth remains an important target variable for economic policy, even for an ageing and prospectively shrinking population. Per capita growth is often used as the usual metric of welfare. Nevertheless, per capita growth is also under pressure from demographic change. For instance, demographic ageing reduces the share of employed persons in the population and thus the labour input per inhabitant. Demographic ageing can also weaken productivity growth. The number of employed persons that have to support the overall population and, in particular, the growing number of older people is also crucial with regard to social security systems. In addition, the financial leeway available for defence, infrastructure, education and other government tasks is dependent on aggregate economic output. The same applies to the sustainability of public finances. Given the major challenges in the coming years, aggregate growth therefore remains of key significance for economic policy.

The labour market has been a stabilising factor in recent years. Demographic change also contributed to this. Despite the various economic crises and, in some cases, weak macroeconomic developments over the past ten years, unemployment rose only in phases and only moderately. At the same time, employment remained stable overall for a long period of time. Many enterprises initially refrained from cutting jobs, partly because they feared increasing shortages of skilled labour. This is because many people are currently reaching or approaching retirement age. Furthermore, additional jobs were created, especially in the health and social work sectors. Demographic change is causing personnel requirements in these sectors to rise (see the supplementary information entitled “Changed employment structure against the backdrop of weak labour market dynamics”).

While demographic ageing will increasingly weigh on growth, its impact on labour input can be mitigated. Labour supply will continue to decline as a result of the ageing of the population. However, there is still considerable potential for counteracting this. This holds particularly true with regard to the hours worked by part-time employees. However, in order to exploit this potential, further reforms are likely to be necessary. This article sheds light on the outlook for the coming years and discusses options for bolstering the supply of labour.

Demographic change in Germany is pronounced by international standards. Following the baby boom in post-war Germany, birth rates have persistently fallen since the early 1970s, and life expectancy has risen. Since then, the average number of children per woman has fluctuated around 1.4 children per woman. 1 This corresponds to around two-thirds of the basic population replacement rate from one generation to the next (2.1 children per woman). This process is similar in many demographically “mature” industrial countries and is reflected in significantly rising old-age dependency ratios. Currently, the baby boomer generation is increasingly entering retirement and the old-age dependency ratio is rising to a greater degree. 2

Demographic change is reducing labour supply in several ways. First, the working age population is in decline. In Germany, it is falling at an increasing rate. Second, there is a rising share of older persons, who have a lower labour force participation rate compared to younger age groups, while there is a declining share of prime age workers, who have high labour force participation rates. For instance, the now ever-growing generation of those aged 55 to 64 as well as the group of those aged 65 to 74, which will grow strongly in the coming years, have considerably lower labour force participation rates than the cohort of those aged 35 to 54. Taken in isolation, this shift in the age structure is reducing the aggregate labour force participation rate and the potential labour force. 3 In recent years, this age structure effect has been offset by rising individual labour force participation within individual population groups as well as by immigration. In future, however, these counteracting impulses are likely to be less pronounced. 

If immigration is factored out, Germany’s population has been in decline for some time now. In past years, immigration has been more than able to offset the excess of deaths over births among the domestic population. In future, however, it will probably be insufficient to compensate for the decline in the domestic population. 

Demographic change is also dampening the average number of hours worked. Older employed persons more frequently work part-time or in marginal employment. The average number of hours worked among those aged 55 to 64 is somewhat lower than the working hours of those aged 35 to 54, while the number of hours worked among those aged 65 to 74 is around half that of those aged 35 to 54. As the share of older persons in the labour force rises, the average number of hours worked among all employees will therefore fall. 

The increasing use of artificial intelligence (AI) has barely reduced the demand for labour thus far. The rapid proliferation of AI could reduce firms’ needs for staff and thus lower labour demand. However, a new survey conducted by the Bundesbank shows that there have been only minor macroeconomic employment effects thus far, irrespective of workers’ qualifications and professional experience (see the supplementary information entitled “Productivity and labour market effects of generative artificial intelligence in German enterprises”). On average, German enterprises do not expect that there will be any significant employment effects in the coming years, either. 4 For the time being, the decline in labour supply due to demographic change is therefore unlikely to coincide with lower labour demand due to AI.

The contributions to economic growth of the various factors of demographic change can be determined arithmetically. This is achieved through a growth decomposition exercise. The starting point here is to consider aggregate output as a product of the population size, the share of the population in working age, the labour force participation rate, and output per member of the labour force (see the supplementary information entitled “Arithmetical contribution of demographic ageing to GDP growth”). 

According to the GDP growth decomposition exercise, demographic ageing will weigh more heavily on economic growth in the coming years than it has thus far. Over the past 15 years, population growth from high net immigration has provided a marked boost to GDP growth. Over the next five years, however, the population is likely to shrink. This is due, in part, to both the increasing excess of deaths over births as well as lower expected immigration. Taken in isolation, this is likely to reduce GDP growth by around 0.2 percentage point per year. A more significant factor in the decline in labour supply, however, is the effect of changes in the age structure. This has already been considerably weighing on growth over the past ten years. During this period, its contribution to growth averaged −⁠ 0.4 percentage point per year. By 2030, its estimated negative contribution is likely to increase to −⁠ 0.6 percentage point per year. At the same time, the rising propensity to work in the past provided strong impetus for economic growth. However, these contributions have recently declined. 5  

In addition to labour supply, demographic change can also affect productivity growth. A reduced labour supply might encourage firms to invest more in digitalisation or automation, thereby bolstering productivity. 6 However, productivity growth could also be dampened by demographic ageing. Studies show that start-up and innovation activity is lower in countries with older populations. 7 In addition, consumption patterns tend to change with age. Demand for services with comparatively low productivity is likely to rise. 8

This article aims to isolate the effect of demographic change on productivity by analysing demographic developments across individual regions. As the population ages, technology and economic policy often change at the same time. These developments may themselves be a response to demographic ageing. As a result, it is often unclear which aspects of productivity growth are actually attributable to demographic change itself. From a methodological point of view, this means that its impact is difficult to isolate from other developments. However, as the rate of demographic ageing varies between regions, there is scope to draw comparisons. 9 These can be used to estimate the causal effect of demographic ageing on productivity growth. 10  

Novel estimates for Germany show that demographic ageing hindered productivity growth. The results show that an increase of 1 % in the share of the population aged 60 to 74 (among those aged 20 to 74) reduced hourly productivity by around 0.1 %. 11 Overall, in the period from 2000 to 2021, the dampening effect on growth in aggregate labour productivity amounted to around 0.1 percentage point per year. Demographic ageing thus played a role in the already prolonged weakness in productivity growth in Germany. 12  

In addition to the domestic population, immigration played an important role for labour input in Germany. Its contribution to employment growth has recently shrunk significantly, however. The developments over the past years provide indications of the outlook for immigration and its importance for labour supply in the years ahead.

The structure of immigration to Germany has undergone fundamental change over the past decade and a half. Following a period of low immigration rates in the 2000s, the expiry of the restrictions on free movement of labour in May 2011 for the Central and Eastern European countries that joined the EU as of 2004 marked an important turning point. 13 In the years that followed, labour market-oriented immigration increased considerably. More recently, however, it has been in decline and refugee migration has gained in importance.

In the 2010s, labour market-oriented immigrants from the new EU Member States gave a considerable boost to employment growth in Germany. 14  The main reason why they made such a strong contribution to Germany’s potential labour force was that they often possessed the skills that were needed in Germany. That observation is borne out by the relatively low unemployment rate among people from those countries in Germany. 15 In addition, many labour market entrants educated and trained in Germany were increasingly looking to take on higher-skilled jobs (those of specialists or experts). The age groups entering retirement, however, had previously, for the most part, been working in middle-skilled professions (skilled workers). This, too, pushed up demand – in particular for skilled workers, but also for relatively low-skilled labour (helpers). 16 Immigration, then, has not only added considerably to employment growth in Germany, but also supported structural change in the labour market. 

Immigration from other EU Member States has been in significant decline in net terms for some years now, and has now largely dried up. In part, this is because more than one-third of labour market-oriented EU immigrants leave Germany again within two years. 17 To date, labour market-oriented immigration from third (non-EU) countries has been unable to offset that decline. While skilled labour from countries like India, Vietnam and Morocco has grown in importance, labour market-oriented immigration overall has fallen well short of 2010s levels for a number of years now. In addition, the high migration gains seen in the 2010s seem unlikely to return because many of those migrants’ home countries are now facing demographic challenges similar to those in Germany.

Refugee migration has become more important for the German labour market. That was the case initially for migration from the eight most important asylum countries of origin, which include Syria. As of 2022, that held true for refugee movements from Ukraine as well. Refugees mainly come to Germany seeking protection – that is, because they are fleeing war, violence and persecution. It tends to take longer to integrate them into the labour market than labour market-oriented immigrants. Refugees differ significantly from labour market-oriented immigrants in terms of both their demographic structure and skills. What is more, refugees include children, young people and single parents who, in the short term, are only available to the labour market to a limited extent or not at all. In addition, insufficient childcare facilities, language barriers or cultural obstacles sometimes prevent these people from being integrated sooner. Because of this, it often takes years to integrate refugees into the labour market. But over the long run, refugee migration has also added distinctly to employment growth.

When assessing the possible levers for boosting labour input, it is worth considering the labour force participation of different population groups and the hours they work. The main population groups of interest here are women and older people. This is because the labour force participation of men has been comparatively high for a long time and the vast majority of men work full-time. 18 Furthermore, very little can be changed about the demographically-induced contraction of the domestic population. 

Labour force participation among women and older people has increased significantly over the past two decades. This raises the question as to whether there is scope for higher labour input and what role the prevailing framework conditions play in this regard.

Female participation in Germany has risen significantly in the past years, but mainly as a result of part-time employment. Between 2008 and 2025, the labour force participation rate of women increased from 73 % to 81 %, which was higher than the EU average. 19 At the same time, Germany narrowed the gap to countries with traditionally high levels of female employment, such as Sweden. But while more women were in work, the majority of this growth was in part-time work. Accordingly, women’s average usual weekly hours of work remained low by European standards. At the same time, there are surveys that have found that many women in part-time jobs want to increase their working hours. 20 In other EU Member States with high female participation rates, women’s average weekly hours of work have also risen significantly since 2017. 

Studies attribute the high percentage of women in Germany working part-time by international standards to a combination of institutional, financial and cultural factors. 21  In general, high benefit withdrawal rates give part-time employees less of an incentive to raise their weekly hours of work. 22 This is because a part-time employee who works more will often have any government benefits reduced or pay higher taxes and social security contributions. Difficulties in balancing work and family life because, say, childcare facilities are insufficient or absent altogether are regarded as another key obstacle to a higher labour supply of women in particular. 23 In addition, studies show that adverse financial incentives to work can dampen the labour supply of second earners. 24 That usually concerns married women. 25  Factors reported in this regard notably include joint income taxation of married couples, non-contributory co-insurance of spouses in the statutory health insurance scheme, the entitlement of civil servants’ spouses to claim healthcare subsidies up to certain income thresholds, as well the possibility of working in marginal employment at the same time. 26  

Using a novel analysis of SOEP data, it is possible to assess the significance of adverse financial incentives to work relative to the childcare situation in a labour supply decision. 27 In this exercise, the average full-time employment rate of single women without children is compared with that of married women with at least one child under the age of 14 in their own household. 28 The difference can be broken down into the contributions made by marital status and children status, respectively. The “marital status contribution” captures differences between married and single women, each exclusively with and without children. It therefore largely reflects the adverse financial incentives to work associated with the marital status of being married. The “children status contribution”, meanwhile, records differences between women with the same marital status with and without children. It thus roughly reflects the more difficult conditions that working women with children face. It is not possible to isolate the significance of prevailing role models with this approach. Those role models will probably help shape the contributions of both the marital and children statuses.

The findings suggest that both limited childcare opportunities and adverse financial incentives to work for married women contributed to the comparatively low full-time employment rate of women in Germany. 29 In arithmetical terms, around two-thirds of the gap in the full-time employment rate between single women without children and married women with children is attributable to the fact that the latter have children. Roughly one-third is explained by the contribution of the marital status of “married”. The finding that the full-time employment rate is lower among married women, both those with and without children, still holds when married women are compared only with those single women who co-habit with a partner in a shared household without being married. It would therefore appear that the contribution of the marital status of “married” originates not from co-habiting with a partner but from characteristics that are specifically associated with the legal status of “married”. 

The relative significance of marital status and children in the household differs by household situation and phase of life. The full-time employment rate declines significantly with the number of children and rises noticeably with the age of the youngest child. This suggests that balancing work and family life becomes increasingly challenging as the number of children rises. But even when children are older, full-time employment rates are still significantly lower than they are for childless women. 30 Moreover, as women’s level of education rises, full-time employment rates rise significantly and the contribution made by the marital status of “married” becomes less important. 31 Meanwhile, the contribution of the marital status of “married” gains in importance if the spouse has a higher level of education and thus typically a higher income. Consistent with this, a higher joint income is taxed more under the progressive tax regime. For this reason, any additional work done by a second earner will be subject to relatively high tax rate, even if their own individual income is fairly low, thus significantly reducing the incentive to work.

Participation among people aged 55 to 64 in Germany has also risen significantly in recent years, while their average hours of work have fallen. Between 2008 and 2025, this age group’s labour force participation rate rose from 59 % to 77 % and is now higher than the EU27 average. 32 Their average usual weekly hours of work, meanwhile, dropped from 35.9 to 34.2 hours and remained well below the European average. Many additional employed persons in this age group work part-time or are using glidepaths into retirement. 

The current framework conditions provide incentives to retire early. The statutory age of retirement age in 2024 was 66 years. According to the German Pension Insurance, the average age at which people retired to draw an old-age pension in 2024 was far lower than that, at 64.7 years. One important reason for that is the option of drawing a full pension – that is, a pension with any benefit reductions – after 45 years of contributions. This is the second most frequent point at which people enter retirement, after the statutory retirement age. In 2024, roughly 269,000 people, or around 29 % of all new retirees, retired in this manner. 33 It is often said that this rule enables people in physically or mentally stressful jobs to retire earlier. A DIW study, however, shows that this channel was also being used by many people who did not work in such demanding professions. 34 What is more, the fairly small deductions that are applied when people retire early are another factor that weakens the incentives for older people to work. 35  

The comparatively low average weekly hours of work in Germany show, first and foremost, that women and older people have been successfully integrated into the labour market. Thus, today’s part-time workers tend to be people who, in the past, would have stopped working or would not have been working in the first place. This has been due, in part, to reforms such as expanding childcare facilities, raising the statutory age of retirement and limiting the scope for retiring early. 

Nevertheless, the existing framework conditions discourage women and older people from working more in some cases. A higher labour input would strengthen not just growth, but the financing of the social security funds as well. Reforms that raise the incentives to work would therefore deliver twin benefits: they would increase total hours worked, thus boosting growth, and they would curb the demographically-induced rise in social security contributions. 36 This is because higher labour force participation and longer working hours reinforce the funding base of the social security funds. By the same token, permanently higher contribution rates would weaken incentives to work and dampen labour input. 37 That is relevant in Germany, in particular, because the tax and social security burden is already high by international standards. 38

Scenarios for immigration, labour force participation and hours worked are considered to create an estimate for the scope for a higher potential labour force over the medium term. The analyses so far show that women, older people and immigrants have made a considerable contribution to the expanded labour supply in Germany in recent years. Overall, the question arises as to what degree more immigration, higher hours worked for part-time employees and a further increase in labour force participation can mitigate the reduction in labour input due to demographic change. Scenarios are defined and extrapolated to answer this question. 

The baseline scenario depicts the likely evolution of potential labour supply. It assumes that immigration will moderate somewhat compared with recent years, that age-specific labour force participation will continue to rise – taking into account the already sharp rise in labour force participation rates – and that the current downward trend in hours worked will weaken. This baseline scenario takes into account changes in the economic policy framework provided that these have already been adopted or planned out in sufficient detail by the Federal Government. The projection of the potential labour force extends over the next ten years up to 2035. It is calculated in full-time equivalents (FTEs) to reflect the impact of hours worked. 39  

In the baseline scenario, the potential labour supply will decline from this year onwards. It will fall by just under ½ % on average per year over the next ten years. Despite the assumed further rise in age-specific labour force participation, the negative effects of demographic ageing are predominant. On balance, the resulting decline in labour input reduces potential output growth by 0.3 percentage point per year. The decline in labour input is thus an important factor in the weak potential growth of only 0.3 % per year.

To illustrate the potential for a greater labour supply, the analysis features varied scenarios for immigration, labour force participation and hours worked. In the baseline scenario, net immigration is assumed to be 250,000 persons per year. 40 Between 2010 and 2025, net immigration – excluding the exceptionally high influxes of refugees in 2015 and 2022 – averaged around 370,000 persons per year. However, it has declined significantly of late and amounted to 235,000 persons in 2025, according to data from the Federal Statistical Office. The variant migration scenarios include a high average (annual net immigration of 350,000 persons over the medium term, based on the volume in recent years), a low average (150,000 persons) and a balanced level of migration. 41 With regard to labour force participation, the favourable scenario is based on coupling the retirement age to life expectancy after 2031. 42 In addition, it is assumed that labour force participation rates in Germany will gradually increase further up to 2035, converging with Swedish levels. This is because Sweden is considered an example of best practice in Europe in terms of labour force participation. This particularly applies to women and older people. 43 The favourable scenario for hours worked mainly assumes that women would work longer hours. 44 In another variant with constant individual working time behaviour – in which only the age structure effect has an impact – the result lies between the favourable and the baseline scenario.

The strongest stabilising effect for the labour supply occurs in the scenario featuring an increase in hours worked. In this scenario, the average hours worked increase by 1.3 hours per week compared with the basic variant. This would close slightly less than half of the gap of around 3 hours per week compared with the average of other EU countries. By contrast, the reserves available to increase the labour force participation rate – beyond what was already expected – are only relatively small. With regard to migration, it is unlikely that the high numbers of immigrants in recent years will be maintained over the next few years. If immigration stopped entirely or was only at a low level, this would place a considerable further strain on labour input. 

Extending labour input would significantly strengthen potential growth. In the scenario with higher hours worked, potential growth would be 0.6 % per year on average between 2026 and 2035. The average annual growth rate would thus be 0.3 percentage point higher than in the baseline scenario. In addition to the direct potential effects of a higher total hours worked, positive indirect effects on capital input also play a role here. This is because, in the medium term (i.e. between 2029 and 2035), developments in the formation of tangible capital are assumed to be based on developments in the labour supply. 45 If hours worked and labour force participation rise simultaneously, potential growth could even be 0.4 percentage point higher than in the baseline scenario. By contrast, if there were no improvements and net immigration fell to 150,000 persons per year, potential growth would be 0.1 percentage point lower per year. 46 In the balanced net migration scenario, potential growth per year would be 0.3 percentage point lower. 

The scenarios show that the demographic decline in labour input can be mitigated at least in part. The scenarios regarding hours worked and labour force participation reflect potential that is not fully exploited under the current framework conditions. Increased hours worked and greater labour force participation appear to be achievable if reforms are implemented. By contrast, the scope for immigration is more limited. Given demographic ageing is also happening in many countries of origin, the higher immigration scenario is unlikely to be permanently achievable solely due to better framework conditions. Nevertheless, reforms remain important to promote labour market-oriented immigration.

Demographic change can hardly be halted, but its economic consequences can be limited. In the coming years, it will significantly dampen labour input and growth. Many employed baby boomers will then retire. The Federal Government has already initiated individual measures to strengthen incentives to work and limit rising social security contributions. These include reforms to the basic allowance system and projects intended to dampen the rise in social security contribution rates for the statutory health and long-term care insurance schemes. Nevertheless, there are still considerable additional opportunities for action. 

An important lever for increasing the labour supply is likely to be to improve the framework conditions for longer hours worked for part-time employees. Further expansion of childcare could facilitate full-time and near-full-time employment. Despite progress, there are still gaps in care. This applies not only to the number of spots, but also to childcare hours and reliability. 47 In addition, the tax and social contributions system could be used to strengthen incentives to work for second earners. Amongst other things, changes are currently being discussed to the non-contributory co-insurance scheme for the statutory health and long-term care insurance schemes, to marginal employment (“mini-jobs”) and to splitting income taxation between married couples. A (moderate) reduction in the non-contributory co-insurance scheme is currently being discussed as part of the reform plans for the statutory health insurance scheme and the long-term care insurance scheme. In addition, the lump-sum contribution rate in marginal employment is set to rise to the average contribution rate. There are various reform proposals for splitting income taxation between married couples, which can also increase incentives to work for second earners. These differ greatly in their effects on labour supply and tax revenue, as well as in their legal scope. 48  

Other factors are relevant in terms of overall incentives to work. For example, it is important to limit the foreseeable sharp rise in contribution rates for the social security funds as far as possible. This would also be helped by increased labour input. The high benefit withdrawal rates are also important. 49 It is certainly also a factor here that transfers in the event of unemployment are geared to the willingness to work.

Labour supply can also be strengthened by reducing incentives to retire early. Data on the actual retirement age suggest that individual age limits play an important role. The option of a full pension after 45 years of insurance contributions provides considerable incentives for early retirement. In addition, the pension reductions for early retirement appear to be too low overall. Moreover, it has become apparent that, when the minimum ages are raised, the actual retirement age follows the statutory retirement minimum ages fairly closely. To extend working lives, it is therefore important to link the statutory retirement age (for the period after 2031) and the minimum age for retiring early on a reduced pension to life expectancy. Additional years of life should be partly spent in a longer period of employment. These measures would not only increase the labour supply but also limit the increase in social security contribution rates. 50

Qualified immigration from third countries should be facilitated further. The Skilled Immigration Act (Fachkräfteeinwanderungsgesetz) already creates a comparatively liberal framework for this. However, bureaucratic obstacles to visas, recognition of educational qualifications and integration continue to make immigration of skilled workers considerably more difficult. More digitalisation, uniform procedures and central points of contact could speed up processes. The planned Work and Stay Agency could help here. However, rapid and consistent implementation is crucial. At the same time, Germany should retain foreign skilled workers more strongly in the long term, for example through better integration, language promotion and reliable prospects for staying.

Further education is becoming increasingly important as a result of technological and structural change. Expertise is becoming obsolete more quickly and job profiles are constantly changing. Employed persons and enterprises should therefore make greater joint efforts to promote further training. Labour market policy can also strengthen incentives for qualifications. Stronger incentives could be gained, in particular, by the low-skilled unemployed for longer-term training measures. Especially in times of rapid technological change, current skills are becoming increasingly important in order to use new technologies profitably for higher productivity growth.

An instrumental variables approach from the literature is used to estimate the causal growth effects of demographic ageing. 51 The data basis comprises regional data on GDP, total hours worked and persons in employment from the regional accounts of the federal states as well as population data at district level (400 districts) from the Federal Statistical Office (Destatis) for the period from 2000 to 2021. 52 The causal estimation of ageing effects is complicated by possible interactions between demographic ageing and GDP growth (endogeneity). For example, regional differences in economic output can affect migration or mortality. 53 Younger people may, for instance, increasingly move to districts where the economic output is high or expected to be high. On the other hand, higher economic growth can lead to a greater increase in life expectancy than in less rapidly growing regions. This can be the case, for example, if economic development contributes to rising living standards and healthier lifestyles.

The econometric estimation regresses the change in GDP per capita on the change in the population share of older people.

$$ \begin{align} ln \left(\frac{GDP_{s,t+z}}{N_{s,t+z}} \right) − ln \left(\frac{GDP_{s,t}}{N_{s,t}} \right) &=  \beta \left[ln \left(\frac{A_{s,t+z}}{N_{s,t+z}} \right) − ln \left(\frac{A_{s,t}}{N_{s,t}} \right) \right]  \\ &+ X′_{s,t} \delta_t + \gamma_s + \gamma_t + \gamma_{Federal\ state,t} \\ &+ \varepsilon_{s,t+z} \end{align} $$

The focus here is the share of persons aged between 60 and 74 years of age in the number of persons aged between 20 and 74 years of age (\( \frac{A}{N} \)). As a robustness test, different time horizons (\( z \)) are used to calculate growth rates. 54 The estimated elasticity \( \beta \) measures the effect of the population structure on GDP per capita (GDP in relation to the number of persons aged between 20 and 74 years; \( \frac{GDP}{N} \)). The vector \( X \) contains control variables. This is how GDP effects resulting from district-specific differences in the sectoral structure of the economy are taken into account. This is achieved by factoring in district-variable and time-variable sectoral employment shares in the estimation. In addition, various district-invariant and time-invariant fixed effects are taken into account in the estimation. 55 This addresses cyclical and price effects at the federal and state levels (\( \gamma_t \) and \( \gamma_{Federal\ state,t} \)). Fixed effects (for the trend; \( \gamma_s \)) at the district level are taken into account as well. These fixed effects are intended to help adjust the results for effects arising from transfers or commuting. 56 \( \varepsilon_{s,t} \) is the disturbance term for district-specific GDP per capita growth. In order to be able to draw conclusions on aggregate growth and productivity effects, in the estimation the observations are weighted by the population in the starting year. The coefficients are estimated using two-stage least squares. 

District-specific variations in demographic developments independent of economic output are used as an instrument for the actual change in the population structure.

$$ \Delta \left( \frac{\hat A_{s,t+z}}{\hat N_{s,t+z}} \right) = ln \left( \frac{\hat A_{s,t+z}}{\hat N_{s,t+z}} \right) − ln \left( \frac{A_{s,t}}{N_{s,t}} \right) $$

where

$$ \hat A_{s,t+z} = \sum_{60 \leq j \leq 74} \hat N_{j,s,t+z} = \sum_{60 \leq j \leq 74} N_{j,s,t} \cdot SP(z)_{j,t} $$

$$ \hat N_{s,t+z} = \sum_{20 \leq j \leq 74} \hat N_{j,s,t+z} = \sum_{20 \leq j \leq 74} N_{j,s,t} \cdot SP(z)_{j,t} $$

As survival probabilities of individuals change little over time, the population of a district can be predicted with a high degree of accuracy. This means that for rates of change between points in time \( t \) and \( t+z \), the age coefficient in each district is extrapolated \( z \) years into the future based on the actual population of a district in the starting year \( t \)  (initial age structure). The estimation results are thus adjusted for interactions between economic output and migration. The number of inhabitants is extrapolated for different ages using aggregate statistical survival probabilities (\( SP \)) based on data from the Federal Statistical Office. 57  

According to estimation results, demographic ageing significantly dampened GDP per capita in Germany (Table 2.1). The results are statistically highly significant and very similar for different time horizons of growth rates. They show that an increase of 1 % in the share of the population aged 60 to 74 (among those aged 20 to 74) reduced GDP per capita (of those aged 20 to 74) by around 0.2 %.

According to the first-stage regression, the instruments are strong. 58 Despite the high correlation between the instrument and the instrumented change in the age structure, there are large differences between the instrumental variables (IV) estimators and the simple ordinary least squares (OLS) estimators for the ageing effect. 59 This suggests that interactions between economic output and ageing play an important role. 60  

A decomposition analysis provides insights into which channel may be particularly hindering growth. The impact of demographic ageing on GDP per capita can be broken down into the following components:

According to the decomposition analysis, around half of the negative marginal effect on per capita GDP is attributable to an ageing-related reduction in labour productivity (Table 2.2). 61  The results show that an increase of 1 % in the share of the population aged 60 to 74 (among those aged 20 to 74) reduced hourly productivity by around 0.1 %. The productivity effect is also statistically significant over different growth rate time horizons. By contrast, the results do not show any negative ageing effect on average hours worked in the past. 62 The remaining half of the marginal effect is therefore attributable to a negative impact on participation behaviour. 63 Further regressions suggest that the adverse effect of demographic ageing on participation behaviour is mainly driven by the labour force participation rate (rather than the employment rate). 64  

The results can be used to infer past macroeconomic effects. The estimated elasticities for the ageing effect on per capita GDP and labour productivity, in conjunction with aggregated data, can be used to calculate macroeconomic growth and productivity effects. In Germany, the share of older persons (share of people aged 60 to 74 in the population aged 20 to 74) rose by around 13 % between 2000 and 2021. 65 According to the estimated elasticity, this means that in the hypothetical scenario without demographic ageing, per capita GDP would have been 2.6 % higher in 2021 than with actual ageing. This corresponds to a decline in the annual growth rate of GDP per capita of 0.12 percentage point as a result of the age structure effect. The productivity effect for the same period is −⁠ 1.3 %, or −⁠ 0.06 percentage point per year.

The regional estimates are likely to provide a lower bound for the macroeconomic impact of ageing on GDP per capita and productivity. Macroeconomic effects (that is, aggregate trends) that have uniform effects across Germany or a federal state are, by construction, not taken into account in the regional estimate. However, the population is actually trending older across the whole country. Many economic consequences of demographic change (such as fiscal burdens or weaker innovation) affect all regions and can only be captured to a limited extent using regional comparisons. In addition, general equilibrium effects are hardly taken into account in this partial equilibrium framework. 66 Adjustment mechanisms can partially cushion economic burdens. For example, workers, firms and capital can be diverted between regions. However, if regional demographic ageing follows a common trend, such evasive action is much more difficult. The regional estimates presented are therefore likely to tend to underestimate the actual macroeconomic impact.

Acemoglu, D. and P. Restrepo (2017), Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation. American Economic Review Vol. 107(5), pp. 174-179.

Aksoy, Y., H. S. Basso, R. P. Smith and T. Grasl (2019), Demographic Structure and Macroeconomic Trends, American Economic Journal: Macroeconomics, Vol. 11(1), pp. 193-222

Arce, O., A. Consolo, A. Dias da Silva and M. Weissler (2025), Foreign workers: a lever for economic growth. The ECB Blog, 8 May 2025.

Baslandze, S., Z. Edwards, J. R. Graham, T. McClure, M. Sparks, B. Meyer, S. Ravindranath Waddell and D. Weitz (2026), Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives, Working Paper 2026-4, Federal Reserve Bank of Atlanta.

Bick, A. and N. Fuchs-Schündeln (2018), Taxation and labour supply of married couples across countries: A macroeconomic analysis, The Review of Economic Studies, Vol. 85(3), pp. 1543-1576.

Bick, A., B. Brüggemann, N. Fuchs-Schündeln and H. Paule-Paludkiewicz (2019), Long-term Changes in Married Couples’ Labor Supply and Taxes: Evidence from the US and Europe Since the 1980s, Journal of International Economics, Vol. 118(C), pp. 44-62.

Blömer, M., C. Fuest, A. Peichl (2021), Raus aus der Zweitverdienerinnenfalle: Reformvorschläge zum Abbau von Fehlanreizen im deutschen Steuer- und Sozialsystem, ifo Forschungsberichte No 126.

Bloom, D., D. Canning and J. Sevilla (2001), Economic growth and the demographic transition, National Bureau of Economic Research, Working Paper No 8685.

Boddin, D., M. Köhler and P. Smietanka (2023), Bundesbank Online Panel – Firms (BOP-F), Data Report 2023–07, Deutsche Bundesbank, Research Data and Service Centre.

Boelmann, B., A. Raute and U. Schönberg (2025), Wind of Change? Cultural determinants of maternal labour supply, American Economic Journal: Applied Economics, Vol. 17(2), pp. 41 - 74.

Brynjolfsson, E., B. Chandar and R. Chen (2025), Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence, SIEPR Working Paper.

Buslei, H., L. Felder, J. Geyer and P. Haan (2024), Rente nach 45 Jahren: Auch Personen mit geringer Arbeitsbelastung gehen frühzeitig abschlagsfrei in Ruhestand, DIW Wochenbericht No 48/2024, pp. 759 65.

Cortés, P., J. Hwang, J. Pan and U. Schönberg (2026), Gender Norms and the Labor Market, NBER Working Papers, No 34716.

Cutler, D. M., J. M. Poterba, L. M. Sheiner and L. H. Summers (1990), An Aging Society: Opportunity or Challenge?, Brookings Papers on Economic Activity Vol. 21(1), pp. 1-74.

Deutsche Bundesbank (2026a), Latest developments in German export market shares and their driving forces, Monthly Report, March 2026.

Deutsche Bundesbank (2026b), The role of special payments in actual earnings growth in Germany in 2025 and 2026, in: Forecast for Germany: Energy price shock fuels inflation and slows the economic recovery, supplementary information, Monthly Report, June 2026.

Deutsche Bundesbank (2026c), , Monthly Report, March 2026.

Deutsche Bundesbank (2025a), What’s behind the sustained decline in German export market shares?, Monthly Report, July 2025.

Deutsche Bundesbank (2025b), Current trends in labour hoarding in Germany, Monthly Report, May 2025

Deutsche Bundesbank (2025c), Allocative efficiency and productivity development in the German manufacturing sector since the mid-2010s., Monthly Report, December 2025.

Deutsche Bundesbank (2025d), Use of artificial intelligence – a European comparison, Monthly Report, May 2025.

Deutsche Bundesbank (2025e), Early, standard, late: when insurees retire and how pension benefit reductions and increases could be determined, Monthly Report, June 2025.

Deutsche Bundesbank (2024a), Developments in euro area business dynamism, Monthly Report, March 2024.

Deutsche Bundesbank (2024b), The adoption and objectives of artificial intelligence in German firms, Monthly Report, December 2024. 

Deutsche Bundesbank (2024c), An international comparison of the tax wedge on labour: the difference between pension contributions and taxes, Monthly Report, June 2024.

Deutsche Bundesbank (2022), Productivity effects of reallocation in the corporate sector during the COVID-19 crisis, Monthly Report, September 2022, p. 47-66.

Deutsche Bundesbank (2019), Long-term outlook for the statutory pension insurance scheme, Monthly Report, October 2019.

Deutsche Bundesbank (2018), Part-time employment in Germany and France, Monthly Report, May 2018, pp. 54-56.

Deutsche Bundesbank (2017), Demographic change, immigration and the potential output of the German economy, Monthly Report, April 2017, pp. 35-47.

Dohmen, T., A. Falk, B. H. H. Golsteyn, D. Huffman and U. Sunde (2017), Risk Attitudes across the Life Course, The Economic Journal, Volume 127, Issue 605, October 2017, F95-F116,

Falck, E., O. Röhe and N. Stähler (2024), Demographics and the Decline in Firm Entry: On The Role of Population Growth and Longevity, Working Paper available at SSRN 5019366.

Federal Ministry of Labour and Social Affairs (2023), Zur Reform der Transferentzugsraten und Verbesserung der Erwerbsanreize, Forschungsbericht 629.

Federal Office of Administration (2026), Wie hoch dürfen die jährlichen Einkünfte meiner Ehegattin/Lebenspartnerin / meines Ehegatten/Lebenspartners sein, damit sie/er als berücksichtigungsfähige Person einen Beihilfeanspruch hat? Beihilfe Online FAQ. 

Federal Statistical Office (2025), Bei 10,3 % der Paare ist die Frau die Haupteinkommensperson, Zahl der Woche No 10, 4 March 2025.

Fitzenberger, B., K. Sommerfeld and S. Steffes (2013), Causal effects on employment after first birth—A dynamic treatment approach. Labour Economics, Vol. 25, pp. 49-62.

German Council of Economic Experts (2026), Frühjahrsgutachten 2026.

German Council of Economic Experts (2023), Wachstumsschwäche überwinden – In die Zukunft investieren, Annual Report 2023/24.

German Council of Economic Experts (2021), Transformation gestalten: Bildung, Digitalisierung und Nachhaltigkeit, Annual Report 2021/22.

German Federal Pension Insurance (2024), Trends in figures. Annual Report 2024.

Hammer, L. and M. S. Hertweck (2022), EU enlargement and (temporary) migration: Effects on labour market outcomes in Germany, Deutsche Bundesbank Discussion Paper No 02/2022.

Heitmueller, A. (2007), The chicken or the egg?: Endogeneity in labour market participation of informal carers in England, Journal of health economics, Vol. 26(3), pp. 536-559.

Hertweck, M. S. (2026a), Stock-flow matching in the German labour market, Deutsche Bundesbank Technical Paper (forthcoming).

Hertweck, M. S. (2026b), Financial Disincentives or Lack of Childcare: What Explains the Low Full-Time Employment Rate of Women in Germany? Bundesbank Technical Paper (forthcoming).

Joint Economic Forecast Project Group (2026), Energiepreisschock überlagert Fiskalimpuls – Wachstumskräfte versiegen, Gemeinschaftsdiagnose Frühjahr 2026

Kerkhof, A., T. Licht, M. Menkhoff and K. Wohlrabe (2024), Die Nutzung von Künstlicher Intelligenz in der deutschen Wirtschaft, ifo Schnelldienst, 2024, 77, No 08, pp. 39–43.

Knetsch, T. A., K. Sonderhof and W. Kempe (2014), Das Erwerbspersonenpotenzial zu Vollzeitäquivalenten: Messkonzept, Projektion und Anwendungsbeispiele, Schmollers Jahrbuch – Journal of Applied Social Science Studies, Vol. 134 (1), pp. 1-24.

Maestas, N., K. J. Mullen and D. Powell (2023), The Effect of Population Aging on Economic Growth, the Labor Force, and Productivity, American Economic Journal: Macroeconomics, Vol. 15(2), pp. 306-332.

Marotzke, P. (2019), The rise of part-time work: A German-French comparison, Deutsche Bundesbank Discussion Paper No 20/2019.

Merki, M., F. Schuster-Johnson and S. Gottschalk (2026), Wer Reformen will, muss Kitas bauen, Dezernat Zukunft, Policy Paper, 16 April 2026.

OECD (2025), Macroeconomic productivity gains from Artificial Intelligence in G7 economies, OECD Artificial Intelligence Papers, No 41.

Ouimet, P. and R. Zarutskie (2014), Who Works for Startups?The relation between firm age, employee age, and growth, Journal of Financial Economics, Vol. 112(3), pp. 386-407.

Paule-Paludkiewicz, H. (2024). Does the Right to Work Part-Time Affect Mothers’ Labor Market Outcomes?, Deutsche Bundesbank Discussion Paper No 12/2024.

Pötzsch, O. and F. zur Nieden (2024), Die Babyboomer: Auf dem Gipfel der demografischen Welle, WISTA Wirtschaft und Statistik, 1/2024, pp. 25-38.

Rengers, M. and T. Körner (2026), Arbeitszeiten und Arbeitszeitwünsche von Männern (und Frauen) – Anhaltspunkte zu Potenzialen für die Gleichstellung, WISTA Wirtschaft und Statistik, 1/2026, pp. 68-86.

The Economist (2026), Is AI putting graduates out of work already?, The Economist. 

The New York Times (2025), For some recent graduates, the A.I. job apocalypse may already be here, (published in print 31 May 2025). 

Weinberg, B. A. (2004), Experience and Technology Adoption, IZA Discussion Paper, No 1051.

Yotzov, I., J. M. Barrero, N. Bloom, P. Bunn, S. J. Davis, K. M. Foster, A. Jalca, B. H. Meyer, P. Mizen, M. A. Navarrete, P. Smietanka, G. Thwaites and B. Z. Wang (2026), Firm data on AI, NBER Working Paper 34836.