Unity in variety. Employment dynamics and specialisation profiles of medium-sized towns in the Asti-Rovigo area, Italy (2001–2017)

23/02/2021 Sciendo

The medium-sized towns (MSTs) and small towns attract 41% of the population and generate 32% of the total GDP, according to Eurostat 2016. The development dynamics of MSTs and their specific role in urban networks are a research question that is still relevant and under discussion to this day. However, studies on MSTs have received increasing attention in recent years, not only because of their diverse settlement situations, socio-economic profiles and evolutionary trajectories, but primarily in response to a political debate focusing on metropolitan areas (established in 2014) and inland areas, both recipients of significant public funding.

The presented research considers a group of 39 towns in Northern Italy, located in the area between Asti and Rovigo and using data from the Italian National Institute of Data Statistics (ISTAT), investigated the role of MSTs in the territorial development processes, considering the case of a vast rural area of the Po Valley megalopolis that is subordinate to large urban agglomerations in that area, the dynamics of the number of the employed at businesses in the periods of 2001–2011 and 2012–2017, the different specialisations of the towns and their ability to attract employees within the respective employment areas.

The search area position is unique: it is a cluster of nine provinces positioned between the most densely populated areas of the Po Valley megalopolis, located in a line along the foothill motorway (Turin to Venice) and the ‘via Emilia’ road and lies across four of the most developed regions on a national and European scale: Piedmont, Lombardy, Emilia Romagna and Veneto and is a predominantly flat area, with a low population density, home to 24 MSTs and 15 small towns, all centres of employment areas. To identify MSTs within a network of 845 municipalities (as at 2019), researcher used a population criterion, taking into consideration those towns falling within the 20,000–200,000-inhabitant range in at least one year of the 2001–2019 period.

The research is divided into two parts. Part one reflects on the importance of MSTs in the settlement system and their diverse profiles, which pave the way for different evolutionary trajectories. Part two is the case study, focusing on 39 cities selected using a population criterion. The analysis concerns not only MSTs but also small towns to gain a better understanding of the specific behaviour of MSTs. The scientist addressed three research questions: employee dynamics in local units (private business) in the periods of 2001– 2011 and 2012–2017; specialisation profiles of the towns and how they have changed over time; reorganisation of relations on a local scale, between towns and their respective local surroundings, corresponding to the employment areas.

Between 2001 and 2011, the non-capital MSTs group experienced the greatest difficulties, with a significant decline in jobs. To draft the functional profile of each town, the industrial and service sector activities were broken down according to the level of technological and knowledge intensity. The researcher used the Eurostat classification with some changes to consider the following industries: – high- and medium-high-tech manufacturing industry; – low- and medium-low-tech manufacturing industry; – energy and mining industry; – construction; – high-tech knowledge-intensive services; – knowledge-intensive market services; – knowledge-intensive financial services; – other knowledge-intensive services; – less knowledge-intensive services: wholesale and logistics; – less knowledge-intensive services: other services.

Due to the author MSTs are precious links between urban and rural, as well as local and global. They are also elusive entities that are very different from one another: they create unity in variety. Marked differences can also be seen within the study area, both in the dynamics of the numbers of the employed and in the specialisation profiles and power relations with their respective employment areas. Thanks to their size, they enjoy larger agglomeration economies and have a diverse economic fabric, which has enabled them to be resilient in the face of recession shock. The non-capital MSTs and especially small towns struggled with the greatest difficulties. As is the case in other countries, this is more evident where the economic base is more closely linked to the industrial sector. This is also more evident for the provincial capitals and other MSTs, while small towns have more opposing dynamics. In summary, four aspects have been appeared: 1. the strength of provincial capital MSTs; 2. the crisis of more industry-specialised towns; 3. the better performance of towns close to metropolitan centres (in particular to Milan), 4. the gradual centralisation within employment areas.

Much of the study area has been hit hard by the SARS-CoV-2 pandemic that broke out in March 2020 and actually struggled with the improvement problem: the different specialisation profile of the towns and their position – whether or not one of strength – attained before the pandemic will affect recovery possibility, along with many other factors. The research could be expanded on in two areas. First of all, it could be to study in greater detail the networks of relations of the MSTs and their evolution over time, to understand how these have affected local development trajectories. Secondly, it would be useful to consider other case studies, for example, in the south of Italy, where there is a different settlement structure, which influences the identification and roles of the MSTs in urban networks.

Full bibliographic information

Maria Antonietta Clerici, Unity in Variety. Employment Dynamics and Specialisation Profiles of Medium-Sized Towns in the Asti-Rovigo Area, Italy (2001–2017), "Quaestiones Geographicae", Volume 39: Issue 4, Pages 5–22, https://doi.org/10.2478/quageo-2020-0034.
Attached files
  • Percentage change in the number of employees at local units in the 39 towns analysed (2001–2011, 2012–2017)