European populations are ageing. This is the result of a remarkable increase in life expectancy across the continent, coupled with lower fertility in the last decades. Ageing – one of the better-predictable demographic processes – brings about a disbalance between workers and retirees. Fewer people inside the labour market are facing more and more people outside of it. This puts strain on European labour markets as well as social security systems. With the baby-boom generation retiring or soon to retire, this crisis is becoming more acute every day. The challenge is additionally exacerbated by population decline in some parts of Europe.
It may be tempting to consider migration as a potential remedy for the challenges of population ageing. Several European countries have been discussing an update of their immigration policies as a response to labour force decline. The imagined solution seems to be that immigrants will fill the gaps left by ageing and declining populations: that they will take vacant jobs and balance state pensions. At first glance, this idea appears reasonable, as migration is already the main driver of population growth across Europe.
However, the scientific consensus is that migration alone is not a long-term solution for the challenges of ageing. The United Nations acknowledged this as early as 2000, in the report Replacement Migration: Is it a Solution to Declining and Ageing Populations? Migration does not alter the fundamentals of demographic dynamics – migrants also age, and population change has a lot of inertia. Besides, the pool of potential migrants is limited – people have to aspire to migrate in the first place, while many do not, and among those willing, not everyone can afford to move.
For Europe, similar conclusions hold: migration alone is not a remedy against the challenges of ageing: to be sustainable, any long-term solutions need to be holistic and include other economic and demographic factors (more in Bijak et al. 2008; and Potančoková et al. 2023, forthcoming). Some ameliorating effects of migration can be seen only once it is considered together with other measures, such as: longer working lives – increasing the retirement age in line with life expectancy; increases in productivity – investing in job automation; boosts in human capital – furthering flexible education of successive generations. Another crucial prerequisite involves removing barriers to economic activity among members of underrepresented groups, such as women or ethnic minorities, some of whom would otherwise remain outside the labour market.
The idea to solve the challenge of ageing by flicking a switch in just one area of policy may seem compelling, but is completely unrealistic. The effects of ageing on our socio-economic systems are highly complex, and prone to unpredictable shocks. These shocks can be economic, such as financial crises, related to technology (productivity), for example job automation (which can bring about its own challenges as well as providing answers; more on this below), or they can be demographic, in particular, related to migration.
Policy solutions must be resilient. “Resilience” here means that a policy can flexibly respond to potentially volatile future shocks without damaging the whole socio-economic system, which would continue to thrive, even if in a different form. To assess the resilience of various policy responses to unforeseen events, including those related to migration, or to other labour market shifts, like job automation, the use of formal demographic and economic models is essential.
In shorter time horizons – from a few months up to two-three years ahead – empirical models can identify the most resilient policy response with relatively high accuracy. For longer horizons, theoretical models offer a way of constructing coherent scenarios, for example in the dynamic stochastic general equilibrium (DSGE) framework used in macroeconomics, including central banking. Such models enable examination of the resilience of the social systems they represent by stress-testing various future trajectories related to migration and other socio-economic parameters.
In particular, models can be used to study the impact of job automation in the face of inequalities in migration and labour market conditions between countries. Our earlier work (Barker and Bijak 2021) confirms that at the macro level, both migration and automation can help grow the economy. At the individual (micro) level, unsurprisingly, those migrant and native workers – typically, low-skilled – whose labour can be substituted by automation capital, are negatively affected by automation, whilst those whose skills are complementary to technological advances can benefit from them. The key source of uncertainty in the responses to shocks proved to be the skill level of newly-arriving migrants and the composition of migration flows.
Some important knowledge gaps remain. One crucial missing element of the puzzle is an explicit link between population ageing and the current European welfare models, with migration as an important intermediary variable. To examine whether and to what extent migration can enhance resilience of European social policy by allowing for the closer, dynamic matching of labour supply and demand, the analysis of the impacts of migration needs to be embedded in the context of changing – ageing and sometimes declining – populations and labour force. A crucial open question is, what kinds of resilient policy solutions can be realistically proposed under these circumstances.
Defining a menu of possible policy options would enable a systematic study of responses of different economic and social indicators to various migration scenarios in the context of technological change, driving job automation, and also in the face of increasing volatility of the social and economic processes, including migration. Such an analysis, carried out with crucial input from policy makers and practitioners, can help identify the most promising areas for policy intervention, as well as illuminating the trade-offs and vulnerabilities involved in the different policy choices, to increase the resilience of the European socio-economic system.
The work has been funded by the Horizon 2020 grant 870299 QuantMig (www.quantmig.eu) and the Horizon Europe grant 101094741 FutuRes (www.futu-res.eu), the latter also supported by the UK Research and Innovation Horizon Europe Guarantee grant 10066250. All the views and interpretations are ours.