GO-Mobility

[Demographic] Winter is Coming

Perspectives on the population to come, and its mobility

When we think about the future, we tend to think about the new generations. Even in the field of mobility, all expectations are placed on the trends of younger people, whose attitudes and habits are monitored and studied in the hope that they will lead to a turning point towards a more sustainable, innovative, and equitable mobility system. But the future is not just about the younger generations. On the contrary, we have known for some time that one of the defining features of the next future is an increasingly aging population: the so-called demographic winter. How will the mobility system have to adapt to this transformation? But above all, are we really understanding the extent of this social change? Together with Trenord, through the DARWIN system that GO-Mobility helped to design and implement, we wanted to carry out a simulation to answer these questions: what could the mobile population of 2040 look like? Who will use trains, buses, and stations in a future populated mainly by elderly people?

1.1. The meaning of Demographic Winter

According to forecasts by the Italian national institute for statistics (Istat), the proportion of elderly people in Italy is going to rapidly increase in the next decades. By 2051, the over-65s could represent 34.5% of the population, or more than one in three, compared to the current 24.4%.

It is now well recognised that fewer and fewer children are being born in Italy: the decline in the birth rate has been going on for decades. In the post-war period, the ratio was around 20 new births per thousand inhabitants, while in 2023 it will be 6.4. The decline in births is caused by a reduction in the average number of children per woman (currently 1.2 children per woman), combined with structural factors such as increasingly delayed parenthood (as evidenced by the average age at first birth rising to 32.5 years) and the decline in the female population of reproductive age (down by 2.3 million in the last 10 years)[1].

The numbers of population aging in Italy. Source: infographic from Permanent Census of Population – Istat

As announced by the president of Istat, Francesco Maria Chelli, even in the most favorable birth rate scenario, there will still be “an amplification of the imbalance between new and old generations,” which will have “a significant impact” on social protection policies, as they will have to meet the needs of a growing (and longer-living) proportion of elderly people. The mechanism driving the demographic winter is, in fact, a combination of a decline in births and an increase in longevity: according to data announced by Prof. Chelli, while 2024 saw around 4,000 fewer births in Italy than in the first seven months of 2023, there was also a parallel decrease in deaths, which were 17,000 fewer than in the same period in 2023. Today’s elderly population enjoys better health than previous generations, benefiting from greater longevity.

The aging of the population brings with it a trend toward smaller and smaller family units: with the increase in elderly people living alone and the decrease in the number of children per capita, families are expected to become smaller and more fragmented in the future. The average number of members will fall from the current 2.25 people per family to 2.18 in 2031 in just seven years. The number of people living alone will rise from around 9.4 million in 2024 to 9.9 million in 2031.

Old-age dependency ratio in Italy. Source: infographics on Permanent Census of the population by Istat

One of the most debated aspects of this scenario is undoubtedly the impact on the labor market and the welfare system. The ratio between the working and non-working populations is set to decline dramatically over time (by 2050, the working population could fall by 9 percentage points to 54.4%), with a significant increase in the retirement age (from 67 to 70). But what other important areas of our daily lives will be affected by this demographic trend?

Interactive figure on Flourish https://public.flourish.studio/visualisation/20745885/ (non mi ricordo se si può incorporare)

1.2. The effects of demographic winter on mobility

In addition to having a major impact on retirement and welfare system, the imbalance between young and old will also have a significant impact on the transport system, especially local public transport (LPT). For the first time, the impact of demographic decline on mobility demand has been included in the analysis of the 21st Report on Italian Mobility, Isfort’s annual report. The observatory’s projections show that the demographic decline could, on average, lead to a 2% drop in travel over the next 20 years. However, the greatest impact will be on travel by the youngest population (-28%), while mobility among the over-75s will actually increase (39%). Considering that the student population (14-19 years old) is known to be the group that relies most on public transport, while the erratic travel of retired people is more related to private motorized mobility, what will this mean for the survival of the LPT sector?

Flourish interactive figure Incorpora? https://public.flourish.studio/visualisation/20744715/

1.3. Understanding mobility with big data

Together with Trenord, we wanted to explore in depth the impact of demographic winter on mobility in the Lombardy region, especially public transport, using the data and strategic analysis tools developed for the Darwin project. What is it about?

Based on Vodafone’s telephone data and integration with other traditional data sources, GO-Mobility has developed a predictive model capable of analyzing overall mobility demand on a regional scale and facilitating its interpretation. It is a tool to support short- and long-term decision-making processes, providing a systemic response to mobility demand and designing a service that is consistent and economically sustainable.

These data, together with those in Trenord’s Darwin Data Lake on transport services (number of lines and journeys, number of passengers boarding and alighting at stations, types of tickets sold, etc.), help to calibrate models of people’s mobility choices. To simulate mobility dynamics in 2040, the current choice models for different categories (age groups, student population, workers, etc.) are therefore applied to the population configuration that, according to Istat projections, we will have in 2040.

1.4. Winter is coming… in the hinterland

As highlighted in the infographics of the Permanent Census of the population conducted by Istat, smaller municipalities are those that suffer most acutely from the effects of demographic decline.

Population decline in municipalities with different dimensions. Source: infographics on Permanent Census of the population by Istat

In fact, looking specifically at the Lombardy region as our case study, projections show that the demographic winter will affect the hinterland towns very differently from the provincial capitals.

In hinterland towns, the phenomenon is more pronounced, dictating the overall average: according to projections, the proportion of the mobile student population (aged 14-19) will fall from 7% to 5.8% (-21.7%), while that of the over-65s will rise from 12.5% to 18.7% (+39.9%). However, it is the decline in the intermediate age groups that is particularly significant: there is a 9.2% decline in travel among the 26-40 age group and a 14.9% decline among the 41-65 age group, which falls from 51.2% to 46.7%. The different composition of the mobile population translates into a 6.7% decline in overall travel, mainly due to the decrease in the student and working populations. We are talking mainly about inter-municipal travel, i.e., medium- to long-distance travel, the category most affected by demographic fluctuations.

Overview of mobility habits (Vodafone data) in the hinterland towns by time slots, age classes, time profile, origin (inhabitant, non-inhabitant, foreigner), number of trips, user type (frequent, regular, occasional). Source: dashboard developed by GO-Mobility for Trenord with data from Vodafone and Istat

Considering only the provincial capitals, it can be seen that the impact of demographic winter is much more attenuated, if not almost absent: the decline in the proportion of younger age groups is almost imperceptible (the 20-25 age group is even slightly increasing). Travel remains heavily influenced by the 41-65 age group, which is experiencing a much smaller decline than in the province (-3.2% compared to -14.9%), although it is more pronounced in the 26-40 age group (-16.2%). The overall decline in travel is in fact only -1%. The characteristics of travel, such as regularity and number of daily trips (user type and cardinality, respectively), also remain largely unchanged, unlike in the provincial areas, where there is a more noticeable decline in all categories.

Overview of mobility habits (Vodafone data) in the province capitals by time slots, age classes, time profile, origin (inhabitant, non-inhabitant, foreigner), number of trips, user type (frequent, regular, occasional). Source: dashboard developed by GO-Mobility for Trenord with data from Vodafone and Istat

The overall result of demographic winter is therefore greatly influenced by the weight and habits of the people who live in the provinces, areas that often suffer from the exodus of large numbers of young and active people, attracted by better opportunities for work and study in larger cities. On the other hand, it is well known that Italy is nothing more than a large province: as we discussed in this article, more than half of the Italian population lives in small municipalities (up to 10,000 inhabitants), areas from which most journeys originate, often by private motorized transport.

1.5. Vacant seats: mobility prospects for 2040

The results of the simulation outline various scenarios for the Lombardy Region, which serves as an example for many other Italian regions. In the most pessimistic scenario, a -13.2% decline is expected in public transport journeys and a -13% decline in passenger*km (the sum of the number of passengers transported multiplied by the relative km travelled), mainly due to the sharp decline in the student population, which is known to be a significant portion of commuters, especially in smaller municipalities.

In this field, the study of passenger*km is particularly important: since public transport fares are based on kilometers, this indicator shows the profitability of the service and its financing capacity. A 13% decline, as projected, raises several doubts about the economic sustainability of a service that already relies mainly on public funding. Currently, in fact, local public transport is financed on average by 65% from the National Fund for Local Public Transport, while 30-35% of revenues come from ticket sales. At that point, it becomes increasingly less sustainable for operators to provide this service.

On the other hand, as people age, they tend to travel less and less frequently than younger and more active populations. As the proportion of a less mobile population increases, there is also likely to be a decrease in the number of car journeys (-4.5%), as well as in the total distance travelled on the road network, which is expected to fall by 6.2%. The end result is therefore less congestion. But while this may seem like good news, it also means that freer roads will make cars even more attractive, especially for other categories of users who will face a struggling public transport system. In this context, there might be a rebound effect in the form of an increase in private car ownership, fueling a vicious circle.

These prospects will be particularly exacerbated in provincial areas. As we have seen, it is mainly these areas that dictate demographic trends and pay the highest price in terms of the transport system:

• While public transport in major urban centers seems to be holding up, thanks to the lesser impact of an aging population, the same cannot be said for the rest of the province.
• A comparison of the impact on travel in different areas shows that, especially in the morning, public transport in the hinterland towns will suffer a decline more than six times greater than that of the provincial capitals (-21.1% compared to –3.3%).

Source: own elaboration of Vodafone Data by GO-Mobility for Trenord Analytics https://public.flourish.studio/visualisation/21096116/

1.6.  Lessons learned: working on scenarios to anticipate change

What can we learn from all this? First of all, the importance of mental exercises that involve imagining the future. From the most dystopian scenarios, which help us understand the scope of trends whose consequences are difficult to conceive of in concrete terms today (as is the case with climate change), to the most optimistic scenarios, which help us imagine what the ideal future might look like. Both approaches encourage us to hypothesize innovative and disruptive solutions that completely shake up the status quo and the course of events.

In this case, simulating the effects of demographic winter in the field of transportation helps us understand that we need to act immediately on this trend in order to anticipate changes. Local public transport must change form and substance, seeking to adapt to the needs of an older population and the changing demands of current transport, which is no longer structured solely around the rigid patterns of study and work of the last century but is flexible, dynamic, and erratic. It is essential that the sector abandons its current approach, which is limited to providing an alternative means of transport for those who have no other options.

The GO-Mobility study highlights the need for radical change and strategic planning capable of anticipating and studying measures that can ensure the economic, social, and environmental sustainability of mobility systems.

Public transport, as we know it today, will no longer be sufficient to meet the new needs of the population. Even the issue of infrastructure is currently conceived and planned with the idea of creating ever more capacity, which will always be saturated. It will be necessary to systematize the enormous amount of data available to study trends and habits and rethink the entire system, getting used to approaching planning through the analysis of scenarios, risks, and risk management.

Certainly, for provincial areas, one of the possible directions for the evolution of local public transport is the introduction of on-demand services (DRT – Demand Responsive Transport), a solution particularly suited to areas with low demand, where travel is more dispersed and less predictable.

DRT is part of a demand-driven approach aimed at making transport services more efficient and sustainable, including from an economic point of view (we discussed this here). Even if they undoubtedly represent a valid solution (both in terms of type of service and technology), the issue of how these types of services work within service contracts between administrations and operators need to be further discussed in order to avoid the overestimation of the effectiveness of DRT services and better integrate this approach within the public service, as a key for making it a real, accessible alternative for depopulated and marginalised areas.

[1] Hearing of the President of the National Institute of Statistics, Prof. Francesco Maria Chelli. Full text available here.