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Article

Stationarity and Types of Internal Migration of Selected Foreign Groups: Insights from Italy

by
Federico Benassi
1,*,
Alessio Buonomo
1,
Raffaele Ferrara
2 and
Salvatore Strozza
1
1
Department of Political Sciences, University of Naples Federico II, 80133 Naples, Italy
2
Italian National Institute of Statistics (ISTAT), 00144 Rome, Italy
*
Author to whom correspondence should be addressed.
Soc. Sci. 2024, 13(10), 506; https://doi.org/10.3390/socsci13100506
Submission received: 29 June 2024 / Revised: 20 September 2024 / Accepted: 23 September 2024 / Published: 26 September 2024
(This article belongs to the Special Issue Exploring Residential Mobility in a Changing Society)
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Abstract

:
The geographical (im)mobility of immigrants in host countries is a significant issue due to its strong links with the integration process. This is particularly evident in Italy, a country with a long history of emigration, where the foreign resident population has now become a structural element of society. Using original data sources and adopting a (pseudo) longitudinal and multiscale approach, this paper provides new insights into the stability and types of internal migration among the main 20 foreign communities residing in Italy in 2011 and in 2018. Significant heterogeneity emerges not only among the different foreign groups but also between metropolitan contexts in the north and centre-south of the country.

1. Introduction

Foreign resident citizens in Italy currently exceed five million (about 8.5% of the total population) and are characterized by a high level of heterogeneity in terms of country of citizenship and many other variables related to migration type, migration project, and the “history” of individual communities in the country (Marini and Busetta 2005; Strozza et al. 2021). Strozza and De Santis (2017) wrote about the “many faces of the foreign presence in Italy” precisely to underline this relevant heterogeneity that is also reflected in both settlement patterns (Amico et al. 2013; Bitonti et al. 2023; Conti et al. 2023) and residential mobility (Casacchia et al. 2022).
The residential mobility of individuals is a broad topic that has always attracted the attention of many scholars from various analytical perspectives (Rogers and Willekens 1986; Cadwallader 1992; Rogers and Raymer 1999; King and Skeldon 2010). It can be broadly defined as a response to various stimuli generated by different territorial contexts, originating, for example, from imbalances between labour supply and demand, the need to appropriate new spaces, urban settlement expansion, and/or repopulation of depopulated areas, but also as individuals’ necessity to redesign their living spaces often, in line with their individual timelines (Livi Bacci 2008; Crawford and Campbell 2012).
Regarding the foreign population, the study of residential mobility is particularly relevant because it is linked to the broader concept of ‘adaptation to the destination territory’ and, in a certain way, to the integration process (Bolt et al. 2010; Bonifazi and Heins 2017). The idea is that after an initial phase of migration characterized by a concentrated settlement model with high levels of dissimilarity compared to the native population, we might observe, over time, a territorial redistribution of the various immigrant communities towards less-concentrated settlement models (Massey 1985).
Several studies have jointly addressed the themes of the territorial distribution of foreigners and their mobility. Some have particularly focused on the connection between settlement patterns and residential mobility (Rees et al. 2017; Rodríguez-Vignoli and Rowe 2018; Nieuwenhuis et al. 2020), viewed as a natural process of space readjustment. The premise is that in the initial phase of immigration the choice of residence is inevitably influenced by the presence of a support network (Bauer and Zimmermann 1995, 1997) and, at the same time, by a labour demand that allows the realization of the initial migration project. In a subsequent phase, other elements more clearly connected to the possibilities of rooting in the host country should contribute to redefining areas and places to live (Panichella 2018; Bernard and Vidal 2023). The idea that over time there could be a greater territorial dispersion of immigrant communities, even those highly concentrated in metropolitan areas or specific contexts, is based on the assumption that the stabilization and integration/assimilation processes involve adopting settlement models increasingly similar to those of the native population, responding to fundamentally similar living needs (Ferrara et al. 2010; De Valk et al. 2011; Buonomo et al. 2024). Individualistic aspirations should also lead to dispersion because upward economic mobility often requires spatial mobility. These ideas have clear references to classic theoretical frameworks, particularly the theory of spatial assimilation (Massey 1985). However, the literature also presents different logics, referring to the theories of place stratification (Alba and Logan 1991) and ethnic preference (Portes and Bach 1985). The first theory emphasizes the importance of considering geographic context in analyses of social inequality and highlights how spatial factors intersect with race, class, and other social dimensions to shape individuals’ life experience. On the contrary, ethnic preference theory highlights the significance of individual and group preferences in shaping societal patterns and underscores the need to address these preferences to promote equity and social harmony. Obviously, these theories can be seen as complementary. Indeed, moving away from areas where one’s group is numerically strong also means risking losing a range of social aspects and moral resources that impact the community’s psychological and economic well-being. A large minority dispersed across the territory risks having no ‘weight’ and no voice in any context; conversely, even a small group, if sufficiently concentrated, can have economic and political influence at the local level. For subsequent generations, maintaining the ethnic community can also have significant advantages. For communities with strong entrepreneurial vocations, for example, ethnic ties can provide benefits in terms of access to circulating capital sources, protected markets, and jobs (Garip 2008; Fraudatario 2024).
Several contributions have shown that none of the various positions described can be considered an absolute reference, as the propensity for residential mobility among immigrants can vary significantly over time, depending on the specific characteristics of individual foreign communities, their migration projects, and the employment opportunities offered by the territories (Alba et al. 1999; Wright et al. 2005; Vogiazides 2018).
With few exceptions (see, for example, Rimoldi et al. 2024) studies on internal mobility in Italy usually refer to residential migrations (i.e., residence changes) that occurred between municipalities or other territorial units like provinces or regions. The basic data used are typically those on registrations and cancellations due to residence changes (Benassi et al. 2019). Alternatively, other works have taken inspiration from retrospective information (residence five years before the survey date) from the population census or from ad hoc sample survey data (Bottai and Benassi 2016; Fornasin et al. 2019). For the native population, marked migratory routes have been highlighted; these are south–north trajectories for long-range movements (Bonifazi 2015; Pugliese 2015; Bonifazi et al. 2021) and movements from central municipalities to peripheral rings—with few exceptions, such as in Rome (Crisci 2016)—for short-range migrations, with higher intensity especially in Northern Italy (Cantalini and Valentini 2012; Bonifazi 2015). In addition to these, there are other migrations, such as those towards the central municipalities of large metropolitan areas, those from inland areas towards less peripheral and coastal areas, and the classic ones along the rural–urban axis (Bonaguidi and Terra Abrami 1996; Bonifazi and Heins 2000; Benassi et al. 2019).
In the case of the foreign population, the greater dynamism of movements compared to Italians has been noted multiple times (de Filippo and Strozza 2011; Bonifazi 2015; Bonifazi 2017; Casacchia et al. 2022), but it is particularly interesting to verify whether the migratory routes are the same or if there are divergences. For example, it has already been established that during economic crises started in 2008, the long-range internal migratory flows of the immigrant population reversed their traditional direction, moving from north to south due to the South’s ability to offer lower living costs and, especially, seasonal and irregular jobs (Bonifazi et al. 2012; Caruso and Corrado 2015; De Rose and Strozza 2015).
Furthermore, the various foreign communities residing in our country not only have different propensities to move within Italian territory but also exhibit different mobility models (Conti et al. 2010; Ricciardo Lamonica and Zagaglia 2013). In this regard, relatively few contributions have been developed at the level of individual citizenships (Conti et al. 2010; Crisci 2010; de Filippo and Strozza 2011; Casacchia et al. 2022). The limitation of most pre-existing studies is that they usually rely on cross-sectional data, while few use longitudinal information, following individuals over time, although this is recognized to be a privileged perspective in the study of the spatial mobility of individuals (Bonaguidi 1990).
Based on these premises, this contribution focuses on reconstructing the internal mobility (or immobility) trajectories of the main foreign communities residing in Italy. The research design is based upon a (pseudo) longitudinal approach. In fact, the microdata from the 2011 population census were linked, using appropriate statistical record linkage techniques, to the microdata from Municipal Population Registers (MPRs hereafter) in 2018, thus identifying the subset of foreign individuals who, enumerated as a usual resident in any Italian municipality in 2011, were also residing in Italy in 2018.
The rest of this paper is organized as follows. In Section 2, the materials and methods are presented. The results are shown in Section 3. Section 4 presents the discussion of the results and some conclusions.

2. Materials and Methods

2.1. Data Sources and Rationale of the Empirical Analysis

The data used in the empirical analysis come from two sources: the population census of 2011 and MPRs of 2018. Through these two temporal points (2018-sourced MPRs and 2011-sourced census), it was possible to reconstruct the internal mobility (and immobility or stationarity) “careers” of the 20 main foreign nationalities residing in Italy and of the total foreign population.
This longitudinal analysis was made possible thanks to the process carried out by the Italian National Institute of Statistics (ISTAT) on individuals present in the administrative records that are annually acquired by the Institute. Each individual, before being (anonymously) placed in ISTAT’s thematic statistical registers, undergoes an identification process. The individual is searched within an integrated archive of the Institute (which gathers all previously known individuals) through a hierarchical record-linkage operation using their direct identifiers (name, surname, date of birth, and tax code). A unique national numeric code is then assigned to the individual. This code allows for tracking the individual across various statistical registers and over time. In our research, using the individuals’ unique identification code, it was possible to search in the municipal registries of 2018 for foreigners who were enumerated in the 2011 population census. It should be noted that the record linkage is not affected by the acquisition of Italian citizenship because the variable ‘country of citizenship’ is not used in the construction of the individual code.
Naturally, the analysis excludes all individuals who, registered in MPRs in 2018, were not recorded in the 2011 population census, as well as those recorded in the 2011 census and not present in the registry in 2018. The latter are classified as ‘other’. We also do not know what happened in the years between 2011 and 2018, during which the same individual could have left and returned to Italy multiple times or made multiple internal moves only to return to the original municipality and therefore appear stationary, even if they had made many moves. Moreover, we do not know anything about migration occurring at a sub-municipality level.
It is important to underline that these two sources are not immune to some limitations essentially caused by under-coverage and over-coverage. The Italian National Institute of Statistics certified that the 2011 population census had an under-coverage error of about 11.1% for the foreign resident population (ISTAT 2015a). It is important to bear in mind that one of the aims and scopes of the census is to correct MPRs from under-coverage and over-coverage errors.
Despite these limitations, we believe this study represents the first attempt in Italy to read the internal mobility of foreigners in such an analytical way and following a pseudo-longitudinal logic.
The empirical analysis focused on two different processes: stationarity (or immobility) and internal migration. Stationarity refers to foreigners who resided in the same municipality in 2018 as they did in 2011. Internal migration refers to foreigners who resided in a different municipality in 2018 compared to 2011. Internal migration can be further categorized—with a certain degree of approximation—into three types:
(i)
Short-range migration: different municipality within the same province.
(ii)
Medium-range migration: different municipality in a different province within the same region.
(iii)
Long-range migration: different municipality in a different province and different region.
Obviously, stationarity and the types of internal migration take on different meanings depending on the geographical scale adopted in the analysis (Gober-Meyers 1978). We will discuss this and other related points in the next subsection.

2.2. Geographical Scale of Analysis and Measures

Before proceeding further, it is important to note that Italy is divided into macro-regions, regions, provinces, and municipalities (Figure 1). In the empirical analysis, two geographical scales were used: the national and the metropolitan scale.
The decision to use administrative geographies, specifically the provincial capitals of metropolitan cities in the second part of the analysis, rather than functional geographies such as Functional Urban Areas (OECD 2012) or Local Labour Systems (ISTAT 2015b), is driven by several reasons. First, administrative geographies allow us to evaluate migration according to self-contained territorial patterns. In our opinion, and at least at this exploratory stage of the study, this also ensures easier interpretability of the results. In fact, unlike Local Labour Systems, for example, there are no provinces that belong to more than one region. On the other hand, for territorial planning purposes, we felt it more appropriate to base the analysis on territorial divisions that reflect governance and administration rather than other geographies defined by commuter mobility. Finally, there are strong connections between commuter mobility—which underpins the construction of FUAs and LLSs—and residential migration (Vickerman 1984; Bottai and Barsotti 1994, 2006), which, given the exploratory nature of the study, we are not yet able to account for.
At the national scale, we consider all municipalities as possible origins and destinations of migration flows in the observed period. If the two are the same, we categorize this as stationarity (i.e., we assume that the individual did not change residence from 2011 to 2018). Otherwise, we assume that the individual changed residence, which can be classified into one of the three types defined in Section 2.1.
At the metropolitan scale, we consider the four major metropolitan municipalities of Italy as possible origins of migration flows: Turin and Milan for the North, Rome for the Centre, and Naples for the South and Islands. It should be mentioned that these are the four largest municipalities in Italy and are among the most important poles of attraction for international migrants (Strozza and De Santis 2017). To provide an idea, it is sufficient to note that in 2011, 13.5% of the total foreign resident population in Italy (slightly more than 4 million, see Table 1) were settled in these four municipalities. This proportion rose to 16.2% in 2018.
The two analyses (national scale and metropolitan scale) should be considered complementary, since they allow us to appreciate different dimensions of stationarity and types of internal migration. Following Pumain (2006), when we consider the metropolitan scale, we can see the migration that occurs from the centre (capital of the metropolitan cities: Turin, Milan, Rome, or Naples) to the ring (the rest of the same province, i.e., the rest of the metropolitan city) as centrifugal migration (centre-ring). This form of mobility—which, at the national scale, we define as short-distance migration (see Section 2.1)—is roughly comparable to suburbanization processes (Champion 2001; Biagi et al. 2011; López-Gay 2014). At the same time, at the metropolitan scale, stationarity can be seen as a form of being rooted in the urban fabric of the different contexts.
For the computation of the measures related to stationarity and internal migration (by type), we followed a very simple procedure. First, we reconstructed the municipal geographies of 2011 to match those of 2018 so that we have the same number of municipalities in both years with the same shape1. This allows us to make correct comparisons from a spatial point of view. Then, for each foreign group, we constructed cross tables with the place of residence in 2018 compared to that of 2011: same municipality, different municipality within the same province, different municipality in a different province within the same region, and different municipality in a (different province and) different region. By relating these numbers to the population of each foreign group enumerated in 2011, we obtained a set of pseudo-rates: stationarity rate (percentage, for each foreign group, that reside in the same municipality in 2018 as in 2011); and internal migration rate (percentage, for each foreign group, that reside in a different municipality in 2018 as in 2011). This last, as mentioned before, can be decomposed into three different types.

2.3. The Selected Foreign Population Groups

In this study, the 20 largest foreign communities at the beginning of 2018 were selected. We referred the selection to 2018 to have an updated picture of the foreign presence in Italy. The identifying criterion for each ‘population group’ (or community) is represented by the variable ‘country of citizenship’. In all analyses, the total foreign population is also considered. The selected communities include social groups with a longer history of settlement in Italy (such as Moroccans or Poles), as well as those of more recent immigration, such as those originating from Pakistan, Bangladesh, and, to a lesser extent, Romania and Ukraine (Table 1).
The 20 communities, totalling over 3 million individuals in 2011, represented about 82% of the total foreign population recorded in the 2011 population census, with Romanians alone accounting for 1/5 of that contingent and slightly less than 1/4 of the top 20 communities. The selected foreign groups, which exceeded 4 million individuals at the beginning of 2018, represent a very significant share of the foreign population (81%), with Romanians leading the way, surpassing 1 million residents and increasing their relative weight, both in relation to the total foreign resident population (23.1%) and within the top 20 most numerous communities (28.5%). It is worth noting that Romanians are one of the two communities among those analyzed here that belong to an EU country.
If in 2011, 12 out of the top 20 nationalities had fewer than 100,000 residents, by 2018 this number decreased to 6 (Peru, Poland, Tunisia, Ecuador, Macedonia, and Kosovo), 3 of which had over 90,000 residents. During the period considered, the foreign population grew by 29.2%, which, although very high, is slightly lower than that recorded by the rest of the foreigners—that is, the foreign population excluding the communities selected here—which stands at 33.8%.
The reasons for this difference, at least for the groups selected here, are related to the fact that, in the interval of 2011–2018, not all 20 communities grew, and some grew very weakly. Among the contracting communities, we find Macedonians, followed by Kosovars, Albanians, and Ecuadorians. Moldovans registered a slight growth. On the opposite end of these communities, we find those in rapid growth: Nigeria, Egypt, and Pakistan.
There is a clear distinction between communities in relation to gender. In some cases, the female component is predominant—Ukraine, Moldova, Poland, Peru, Romania, and the Philippines—while in others, males prevail—Senegal, Bangladesh, Pakistan, Egypt, Tunisia, and India. Communities characterized by a roughly balanced gender structure include those originating from China, Albania, Macedonia, Morocco, and Kosovo.
Thus, a classic dual pattern emerges, with communities characterized by an imbalanced gender structure (either females or males) where, presumably, the migrant is prevalently a single woman or man, and there is not yet, or at least not fully, a strategy of family mobility. Within this group, we find the highest average age where the female component predominates (Ukraine, 47.2 years for females and 43.9 years for both sexes), and, conversely, the lowest average age where the male component predominates (Nigeria, 26.7 years for males and 26.8 years for both sexes). Conversely, communities characterized by a balanced gender structure tend to have an average age not far from the national average (that of the foreign population as a whole), likely due to family-type migrations.
This heterogeneity in demographic characteristics and geographical areas of origin (approximated by the variable ‘country of citizenship’), and thus in migration models/plans, makes these population groups particularly interesting for studying the characteristics of their (im)mobility patterns.

3. Results

In the next subsections are presented the results of the analysis conducted at the national scale (Section 3.1) and that conducted on the four largest Italian metropolitan municipality, namely Turin and Milan for Northern Italy, Rome for Central Italy, and Naples for Southern Italy (Section 3.2). As mentioned, these two analyses are complementary, as they highlight different aspects—albeit interacting—of foreign mobility from a multiscale analysis perspective.

3.1. Stationarity and Internal Migration at the National Scale

A primary dimension of analysis is stationarity (or immobility). As we can see from Figure 2, a polarized reality emerges among the various foreign groups. Comparatively high rates of stationarity are recorded for the Philippines, Albania, and Ecuador, which present indicator values well above the level recorded for the total foreign population (69.7%). Some other communities record, on the opposite end, lower level of stationarity. Among these, Kosovo, China, and Egypt stand out for having very low indicator values.
It therefore appears that greater mobility (hence, lower stationarity to mobility) is particularly recorded for the communities characterized by a higher proportion of males and less representative of family-type migrations. Conversely, high levels of residential ‘immobility’ are recorded in communities that are expressions of particular forms of employment (such as Filipinos, who often live with the family they work for) or exemplify family-type migrations (Albanians). The Chinese seem to be a special case; although they are characterized by family-type migration, they show a rather low immobility (thus, a high, in comparative terms, propensity to mobility).
From Figure 2, we can observe that eight communities record an internal migratory rate higher than that of the entire foreign population (16.3%). Notably, the Chinese (over 30%), Senegalese (20.6%), Moldovan (20.5%), and Indian (20.4%) communities stand out among these. The other twelve communities record lower migratory rates, with particularly low values for the Philippines (9.2%), Egypt (9.4%), Kosovo (10.7%), and Bangladesh (11.1%).
The internal migratory rates by type of movement reveal an interesting variability among the different nationalities (Figure 2). For many nationalities, consistent with what was observed for foreigners as a whole, short-range mobility (intra-provincial) shows the highest levels. Among foreigners who remained in our country and relocated, proximity mobility prevails, suggesting the existence of territorial redistribution processes of the foreign resident population that mostly occur on an intra-regional scale, particularly within the same province. This form of mobility is particularly significant for citizens of Moldova (13.8%), Morocco (13.2%), and Ukraine (12.2%).
Significantly different mobility patterns characterize the Asian communities, particularly the citizens of China and, to a lesser extent, India. For these two groups, long-range (inter-regional) mobility is an important form of migration, with notably high levels, especially among the Chinese (14.6%). In contrast, mobility within the same region but outside the province of residence (intra-regional) shows lower levels but remains noteworthy, especially for Ukrainians (3.3%).
Several factors can influence the internal mobility processes of foreigners, including the migration project, labour market integration (and its dynamics), housing market characteristics, and various stages of individual life (having children, forming a family, etc.). These factors are not controlled for in our analysis but can significantly affect the migratory behaviours of different communities. This aspect represents a limitation of the study and is important to keep in mind when interpreting the results, which, by necessity, can only be partial. However, it is crucial to highlight that for the foreign individuals present in the 2011 census and still in Italy in 2018, intra-provincial mobility, or short-range mobility, prevailed in almost all cases. This is a significant piece of knowledge that sheds light on various aspects related to the territorial integration process of the foreign population.

3.2. Stationarity and Internal Migration at the Metropolitan Scale

In this paragraph, we focus on studying the mobility of the same communities previously analyzed, using the same “pseudo”-longitudinal approach but centering the analysis on the four most important metropolitan municipalities in Italy: Turin, Milan, Rome, and Naples.
The ethnic composition in the four capitals of the metropolitan cities is highly complex and variable, also in relation to the varying sizes of different population groups. Here, we provide some details that are useful for a better understanding of the importance of the different foreign groups in the proposed analysis.
In 2011, the largest foreign community in Turin was the Romanian community, which represented a significant 40.2% of the foreigners enumerated in the municipality. The top five nationalities also included Morocco, Peru, China, and Albania, which together accounted for more than 70% of the foreign population in the city. By 2018, the same five nationalities, while still the most numerous, with Romanians remaining in the lead, represented a smaller share of the overall foreign population (67.0%).
In Milan, the largest community in 2011 was the Filipino community, which alone accounted for just under 19% of the total foreign population enumerated in the city. They were followed by China, Egypt, Peru, and Sri Lanka. In 2011, the top five communities accounted for 56.2% of the total foreign population. By 2018, the foreign population residing in Milan had grown significantly. The most-represented communities remained the same, although they lost relative weight: Filipinos accounted for about 16% of the total foreign population, while the top five nationalities now represented 54.3%.
The situation in Rome is quite different. In 2011, the top five communities were represented by Romania, the Philippines, Bangladesh, China, and Peru. Romanians alone accounted for just over 22% of the total foreign population. This share rose to 52.2% when considering the five communities together. In 2018, the foreign resident population increased significantly, alongside changes in the composition of the top five nationalities, with Ukraine replacing Peru. The Romanian community remained the largest, increasing its relative share of the total foreign population (24.2%). In 2018, the top five nationalities represented about 53% of the total foreign population residing in the city.
In Naples, the largest community in 2011 was represented by Sri Lankan citizens, accounting for about 23% of the total foreign population. The top five positions also included Ukraine, China, Romania, and the Philippines, which together covered 60.5% of the foreign population recorded in the city. In 2018, following a significant increase in the overall foreign population, Pakistan entered the top five most numerous communities residing in Naples, replacing the Filipino community. The top five communities now represent 59.1% of the foreign population. Sri Lankans, who remain the largest community among those residing in Naples, accounted for more than a quarter (26.1%) of the foreign population in 2018.
This picture provides a general framework for a better understanding of the results, considering, however, that in only 8 out of 160 cases (20 foreign groups in four cities over two years, 2011 and 2018), the resident population is fewer than 100 people2.
The results seem particularly interesting and highlight significant variability among the different foreign communities.
In Turin (Figure 3), non-migration also registers comparatively higher rates, with its overall rate for foreigners at 75.5%. The most stationary are again Filipinos (86.4%), followed by Albanians (82.4%) and Peruvians (81.5%). Kosovars are again the least stable (55.0%). Short-range migration (from the main municipality to other municipalities in the metropolitan area) is the primary form of mobility, and as is the case of Milan, with an overall rate for foreigners of 5.2%. Notable values are recorded for Macedonia (11.4%), Kosovo (10.0%), and Poland (9.2%). All of the Eastern European nationalities show rates higher than the average: Moldova (8.7%), Ukraine (6.9%), and Romania (6.8%). This confirms the tendency of these communities to distribute along the peripheries of territorial systems, promoting processes of territorial redistribution and decentralization (suburbanization). Low levels of this indicator are recorded for Bangladesh (0.4%), the Philippines (1.6%), Tunisia (1.6%), and Egypt (1.9%).
Things change concerning intra-regional migration. The general level is very low, with the rate for the overall foreign population at just 1.0%. However, the nationalities showing a comparatively high propensity also change. Among these, only one Eastern European nationality, Ukrainians, shows a slightly above-average rate (1.1%). The highest rates are recorded by three nationalities, all Asian: Sri Lanka (2.8%), Pakistan (2.1%), and China (1.6%). This suggests a sort of geographical specialization in mobility. Particularly low rates are recorded for Macedonians and Kosovars (close to 0%, but it is important to bear in mind that the demographic dimension of these groups is very narrow), as well as for Egyptians and Tunisians (0.6%).
Longer-range migration, from the municipality of Turin to other municipalities outside the Piedmont region, marks a new change in both intensity and the hierarchies of individual nationalities. The rate for the overall foreign population is 2.3%, significantly higher than the intra-regional migration rate. High values are recorded among Asian communities, with China (9.7%), Pakistan (9.2%), and India (8.0%) standing out. Very low values are noted for communities from Kosovo, Egypt, Macedonia, and Peru, all below 1%.
Regarding the case of Milan, the first aspect that emerges clearly is that, among the foreigners recorded in the 2011 census in that municipality and still present in Italy in 2018, immobility prevailed (Figure 4): the stationarity rate for foreigners as a whole is 81.6%, much higher than all other internal mobility rates and significantly higher than the value at the national scale (69.7%, see Figure 2).
Thus, we can say that, in general, there has been a tendency to maintain residence in the core of the Milan metropolitan system. We can read this indicator as a sign of the stable presence of the foreign communities that reside in the municipality of Milan and, in a certain sense, as an indicator of integration (i.e., rooted in their place of residence) (Costarelli 2023). Obviously, this does not mean that there were no changes in domicile or relocations within the municipality of Milan, but they are not observed here. In this sense, Filipinos registered the highest stationarity rate (about 91%), which can be partly explained by the type of work they perform, usually in affluent families with whom they often live (Mugnano and Costarelli 2018). The lowest stationarity rates are recorded by citizens of Kosovo (46.6%) and Macedonia (55.0%). It should be noted that in Milan, as in the other municipalities considered, these two communities are the least numerous.
Centrifugal migration, that is, migration from the central municipality of the metropolitan system to the municipalities of the rest of the province, affected 5.1 out of every 100 foreigners counted in 2011. It is comparatively high among Eastern European communities, which often exhibit migratory and residential patterns based on greater territorial distribution (Benassi et al. 2022), such as Moldovans (12.0%), Romanians (10.2%), and Ukrainians (9.0%). This cluster also includes the Senegalese (9.0%) and Nigerians (5.7%).
From Milan to other municipalities in Lombardy, following an intra-regional migration pattern, 2.7% of the selected foreigners migrated. In this case, almost all the selected nationalities show rates higher than this value. Only six nationalities fall below the average level, with Egypt at the lowest (the intra-regional migration rate for this nationality is just 1.0%). At the top are Nigerians, with a rate of 9.0%.
Inter-regional mobility is even more limited; the rate for foreigners as a whole is 2.1%. The data for the Chinese stand out with the highest value (6.9%), indicating a strong propensity for medium- and long-distance migration (if we compare the rates of these two types of transfers to centrifugal migration). The lowest rates are recorded by Kosovo and Egypt, both below 1%.
The case of Rome (Figure 5) shows that, once again, among communities still present in Italy and residing in the main municipality in 2011, immobility prevails (the rate for the overall foreign population is 79.3%). Filipinos, Ecuadorians, Peruvians, and Sri Lankans are the nationalities with the highest rates (over 90% for Filipinos). High values are also recorded for communities from Eastern Europe and the Balkans, as well as for the Chinese (82.3%). The lowest stationarity rates are recorded for communities from Kosovo, Nigeria, and Pakistan. In general, African communities have the lowest comparative values for this indicator.
A key difference from what was observed in Milan and Turin is the lack of predominance of centrifugal migration among the forms of internal mobility. In the case of Rome, long-range migration (from the municipality of Rome to municipalities in other regions) is higher. This is a significant aspect, highlighting a sort of expulsive capacity of the municipality of Rome.
The centrifugal migration rate is close to 3% for the overall foreign population, but is significantly higher for some communities; Moldova (6.0%), Romania (4.6%), and Albania (4.0%) stand out, confirming the previously observed pattern of territorial redistribution for Eastern communities (Conti and Strozza 2006; Benassi et al. 2022). Conversely, nationalities with low levels of centrifugal migration—from the centre to other municipalities of the Roman metropolitan system—include the Philippines, Macedonia, India, Egypt, Bangladesh, and Ecuador, all below 2.0%.
Intra-regional mobility is the least intense form of internal mobility originating from the municipality of Rome, with just 0.9% for the overall foreign population. A comparatively high value is recorded for Nigeria (3.7%), followed by Pakistan (1.8%) and Moldova (1.4%). However, it is the long-range, interregional mobility that records the highest values: the rate for the overall foreign population is 3.2%. Specific nationalities exhibit very high rates, namely Pakistan (11.5%), Senegal (7.6%), Nigeria (6.4%), and China (6.2%), confirming their high propensity to spread across various regions, a form of widespread migration. Poland, Romania, Ukraine, and Morocco, on the other hand, have comparatively low values, with Egypt and Ecuador at the minimum (1.0%).
The case of Naples (Figure 6) partly confirms what was seen in Rome, delineating a difference in the mobility patterns of foreigners between the metropolitan areas of the North and those of the Centre-South. Again, as in all other three metropolitan municipalities, immobility is predominant among the foreigners analyzed here (79.3% for the overall foreign population), with maximum values for Ecuador (89.5%), Peru (87.6%), and Sri Lanka (87.1%). However, as in Rome, and differently from Milan and Turin, long-range, interregional mobility is the primary form of internal mobility for foreigners still present in Italy and censused in 2011 as residents of Naples: 6.4% compared to 3.4% for centrifugal migration and 1.4% for intra-regional migration.
Centrifugal migration has particularly affected Nigeria (7.0%), Moldova (6.8%), India (5.8%), and China (5.3%). The lowest values are recorded for Kosovo, Egypt (0.0%), and Senegal (0.8%). This last figure is very interesting considering that, as shown in Figure 6, Egypt has the highest interregional migration rate (18.5%). Kosovo also records high values: 10.7%. Mobility to other regions remains high for China (11.3%), and is elevated for India (17.5%) and Romania (9.8%). This form of mobility is comparatively very low for Poland, Macedonia, and Tunisia. There is a difference of over 16 percentage points between the first nationality (Egypt) and the last (Poland).
The heterogeneity concerning intra-regional mobility is also high, which, as mentioned, is the least significant form of internal mobility for Naples (1.4% for the overall foreign population). Macedonia, Senegal, and China have the highest values for this indicator (above 3%). Very low, if not null, values are recorded for communities with very high interregional mobility: Kosovo and Egypt (0.0%). Peru follows with just 0.2%.

4. Discussion and Conclusions

Internal migration, involving both nationals and foreigners, plays a significant role in shaping a territory’s social, economic, and demographic landscape (Golini 1974, 1999; Rees et al. 1998). In this study, we conducted an explorative analysis of the stationarity and patterns of internal migration among the major foreign communities residing in Italy in 2011 and 2018 using a dual scale of analysis: national and metropolitan. This approach has provided a unique perspective on the migration phenomenon, allowing us to uncover unexpected and less-studied aspects of migration in Italy.
At the national scale, stationarity prevails. Nevertheless, regarding internal migrations, a clear distinction between types of migration emerges. Specifically, short-range migration (intra-provincial movements) is the primary form of mobility for all foreign communities except the Chinese. This type of migration is associated with processes of population spatial redistribution and, to some extent, suburbanization. It appears to indicate the existence of a spatial diffusion process of the foreign presence in Italy at the national scale, thus contributing to spatial assimilation. The Senegalese, Moroccans—one of the oldest settled communities in Italy (Barsotti 1994)—and Eastern Europeans, such as Romanians, Moldovans, and Ukrainians, record the highest rates of this form of migration at the national scale. Conversely, for the Chinese community, long-range migration (inter-regional) predominates at the national scale. This may be linked to the settlement model of this foreign group in Italy, described as clustered- dispersed (Bitonti et al. 2023).
At the metropolitan scale, a more complex picture emerges, revealing a dual scheme related to metropolitan municipalities in the North and the Centre-South:
i.
In the North, a metropolitan migration model is observed where there is a preference to migrate towards the core of the metropolitan system.
ii.
In the Centre-South, a different metropolitan migration model is apparent, characterized by a preference to migrate towards other regions.
Few communities seem to deviate from this general pattern, notably Chinese immigrants, who tend to move towards more distant destinations regardless of their current place of residence whenever they decide to relocate.
These dynamics are influenced by a complex set of factors that are not easily delineated (Raymer and Willekens 2008; Bell et al. 2015; Courgeau 2021). However, it is evident that the process of territorial integration for foreign populations, as highlighted by recent empirical studies, revolves around the labour market (Etzo 2008, 2011; Benassi et al. 2023). Under similar conditions, this market is notably more dynamic and attractive in northern metropolitan areas, where the level of well-being is also higher compared to southern areas (Salvati 2013; D’Urso et al. 2022).
Additionally, it should be noted that southern regions often serve as primary settlement areas, from which significant numbers of foreigners subsequently move to other contexts, often following specific migration networks or due to the factors mentioned above.
What emerges is a polarization effect that seems to characterize the central-southern metropolises, where the main city attracts but does not redistribute towards neighbouring municipalities, unlike northern metropolises, where the main city not only attracts but also redistributes towards neighbouring municipalities. It appears, therefore, that in the northern metropolitan context of Italy, where employment rates are comparatively higher than in the South, the spatial redistribution of foreigners is a more intensive process compared to other parts of Italy (Bubbico et al. 2011; Basile et al. 2012). This aligns with studies on residential segregation patterns and determinants related to Southern Europe (Sabater et al. 2016; Benassi et al. 2020).
Inside each major scheme, significant heterogeneities arise among foreign communities (Reher and Silvestre 2009). Indeed, studies conducted for individual citizenships have allowed us to uncover migration patterns for each subgroup. In the contexts of Turin, Milan, and Rome, residents from the Philippines exhibit the highest immobility rate, which is also notably high in Naples, placing this citizenship fourth in the ranking. This outcome appears strongly correlated with the fact that this community often works and resides with higher social class families in specific parts of the city (White and Lindstrom 2005; Conti and Strozza 2006; Smith and Jöns 2016; Darlington-Pollock et al. 2019).
In contrast, residents from Kosovo and Macedonia have the lowest immobility rates among the 20 citizenships, considered in three out of the four municipalities. This can be attributed to the relatively small size of these communities and the specificity of their immigration to Italy.
Distinguishing individual citizenships has allowed us to highlight elements of continuity and discontinuity within each subgroup analyzed. Certainly, the results obtained prompt us to carry out further in-depth investigations. It will be interesting to extend the analysis to the period after the COVID-19 pandemic so that we can grasp whether it created elements of discontinuity from the past (González-Leonardo et al. 2022; Perales and Bernard 2023). In addition, it would be interesting in future studies to investigate in a more direct form the role played by gender or age differences and the family type (single-member households versus other typologies). It could also be very important to introduce some variables related to the local labour market’s condition, like the employment rate of the native population and/or of the foreign population. Moreover, the application of specific statistical models could help us interpret the phenomenon and highlight the differences in patterns among various subgroups, also considering the origin and destination of migration flows and other characteristics. With specific reference to the metropolitan context, it would be interesting to analyze both outflows and inflows to measure the net migration rate for each city, broken down by foreign groups. Indeed, in the current paper, we have only analyzed the outflow from the four major metropolitan capitals of Italy.
Being able to identify which citizenships are more mobile within the territory and which have a greater propensity to remain, as well as understanding the distances they cover, is a valuable resource for policymakers to enhance the effectiveness of the measures implemented. In particular, this information makes it possible to predict which services and infrastructures need to be preserved, and which might lose importance (DeWaard and Raymer 2012; DeWaard et al. 2017). Knowing the citizenships that are most stable in the territory and those that are most likely to leave it, as well as knowing some of their characteristics, can help in planning services for education, to facilitate the matching of supply and demand in the labour market, and to know the migration dynamics between centres and suburbs or between regions.

Author Contributions

Conceptualization, F.B. and R.F.; methodology, R.F.; software, A.B.; validation, R.F., A.B. and S.S.; formal analysis, R.F.; investigation, A.B.; resources, F.B.; data curation, R.F.; writing—original draft preparation, F.B., R.F. and A.B.; writing—review and editing, S.S.; visualization, A.B.; supervision, S.S.; project administration, F.B.; funding acquisition, F.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the PRIN 2022-PNRR research project “Foreign population and territory: integration processes, demographic imbalances, challenges and opportunities for the social and economic sustainability of the different local contexts (For.Pop.Ter)” [P2022WNLM7]. Funded by European Union—Next Generation EU, component M4C2, Investment 1.1. We acknowledge co-funding from the PON “Research and innovation” 2014–2020 (PON R&I)—ACTION 4. Title “Digital literacy as a determinant of the social inclusion of migrants and their children” [CUP E65F21003040003].

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data used in the paper were produced as part of Istat’s thematic research project—laboratory of social and demographic research “La presenza straniera in Italia: modalità di integrazione territoriale” (PI’s: Federico Benassi and Raffaele Ferrara).

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Notes

1
We passed from 8092 municipalities in 2011 census to 7960 at the beginning of 2018.
2
Data are available from the Authors upon reasonable requests.

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Figure 1. Geographical context of analysis.
Figure 1. Geographical context of analysis.
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Figure 2. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and total foreign population. Italy, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018.
Figure 2. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and total foreign population. Italy, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018.
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Figure 3. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Turin municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
Figure 3. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Turin municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
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Figure 4. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and total foreign population. Milan municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
Figure 4. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and total foreign population. Milan municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
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Figure 5. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Rome municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
Figure 5. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Rome municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
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Figure 6. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Naples municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
Figure 6. Stationarity rate (%) and internal migration rate by type of migration (%). Selected foreign groups and foreign population. Naples municipality, 2011–2018. Notes: the internal migration rate is equal to the sum of the 3 types of internal migration; “other” includes the percentage of foreigners who are no longer residents in Italy in 2018; for better readability of the figure, numerical values below 2% are not shown.
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Table 1. Population size and the main characteristics of the foreign population and selected foreign groups for the empirical study. From the 2011 population census and 2018 Municipal Population Registers.
Table 1. Population size and the main characteristics of the foreign population and selected foreign groups for the empirical study. From the 2011 population census and 2018 Municipal Population Registers.
Country of CitizenshipResident Population 2011Resident Population 2018Index Number (2011 = 100)
Absolute Values% by
Citizenship		Absolute Values% by
Citizenship		%
Female		Av.
Age		Av.
Age
(M)		Av.
Age
(F)		%
<18 y.o.
Romania823,10020.41,204,76523.157.533.530.935.521.0146.4
Albania451,43711.2441,9948.548.932.131.332.826.597.9
Morocco407,09710.1418,8348.046.732.032.131.927.2102.9
China194,5104.8293,8715.649.630.830.431.328.3151.1
Ukraine178,5344.4238,7624.678.043.932.247.29.6133.7
Philippine129,0153.2169,3313.356.736.834.138.821.8131.2
India116,7972.9153,6843.040.731.631.831.217.3131.6
Bangladesh80,6392.0133,8242.626.728.930.524.618.9166.0
Moldova130,6193.2131,9482.566.435.529.638.518.9101.0
Egypt65,9851.6121,3412.332.627.730.023.132.4183.9
Pakistan69,8771.7116,1752.230.129.130.426.023.3166.3
Sri Lanka71,2031.8109,3832.146.733.934.433.423.5153.6
Nigeria47,3381.2109,1712.140.726.826.727.023.6230.6
Senegal72,4581.8107,2572.125.733.034.927.420.4148.0
Peru93,9052.397,8201.958.235.833.137.720.0104.2
Poland84,6192.196,0671.873.640.434.442.511.8113.5
Tunisia82,0662.094,6431.837.832.033.629.327.0115.3
Ecuador80,6452.080,4181.557.133.130.035.323.699.7
Macedonia73,4071.864,8611.248.131.230.931.526.688.4
Kosovo41,5751.040,1740.845.527.327.127.532.296.6
Top 20 3,294,82681.84,224,32381.296733.331.335.022.7128.2
Other 732,80118.2980,18518.853.536.233.238.915.6133.8
Total4,027,627100.05,204,508100.051.933.931.735.921.1129.2
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Benassi, F.; Buonomo, A.; Ferrara, R.; Strozza, S. Stationarity and Types of Internal Migration of Selected Foreign Groups: Insights from Italy. Soc. Sci. 2024, 13, 506. https://doi.org/10.3390/socsci13100506

AMA Style

Benassi F, Buonomo A, Ferrara R, Strozza S. Stationarity and Types of Internal Migration of Selected Foreign Groups: Insights from Italy. Social Sciences. 2024; 13(10):506. https://doi.org/10.3390/socsci13100506

Chicago/Turabian Style

Benassi, Federico, Alessio Buonomo, Raffaele Ferrara, and Salvatore Strozza. 2024. "Stationarity and Types of Internal Migration of Selected Foreign Groups: Insights from Italy" Social Sciences 13, no. 10: 506. https://doi.org/10.3390/socsci13100506

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