Measuring vulnerability of asylum seekers and refugees in Italy

ABSTRACT

In recent years, a growing number of forced migrants have travelled to Italy across the Mediterranean Sea. While the number of new arrivals has diminished since 2017, the Italian reception system still struggles to process the high number of applications for international protection. A significant proportion of forced migrants who arrive in Italy end up living in informal settlements, such as occupied buildings, shacks, containers and tented camps. In this study, we assess the vulnerability of asylum seekers and refugees living in informal settlements in Italy, using data from the first nationally representative survey of this population. We compare a count measure of vulnerability with a new approach based on latent trait analysis, which accounts for measurement error and correlation between indicators. This analysis shows that forced migrants from Asia are more vulnerable than those from Africa, and that vulnerability is consistently lower in informal settlements in the regions of Lazio and Piedmont, and consistently higher in Apulia. However, other factors predicting vulnerability often change depending upon the way in which vulnerability is measured. Our findings have implications for the design of social protection and inclusion policies, as well as future research that measures vulnerability.

KEYWORDS:

• Vulnerability assessment
• latent trait model
• indicators
• survey data
• informal settlement

Acknowledgements

The survey ‘Asylum-Seekers and Refugees in Italy: Informal Settlements and Social Marginalisation’ was conducted by Daria Mendola and Annalisa Busetta in collaboration with Giuseppe De Mola from Médecins Sans Frontières–MSF-Italian Section, under the scientific collaboration agreement (prot. n. 2936 on 16/11/2015) between the Department of Economics, Business and Statistics (SEAS) of the University of Palermo and MSF Italy, Rome. Daria Mendola and Annalisa Busetta wish to thank Médecins Sans Frontières–Italian Section, for promoting this survey and collaborating in all its stages. Survey data are exclusive property of SEAS and MSF. Authors also wish to thank the two anonymous referees for their helpful comments.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily reflect the views of their institutions, of Médecins Sans Frontières or of the United Nations.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The VAF procedure (UNHCR 2018b) proceeds as: a) quantitative variables (such as the amount of household’s debt or its level of expenditures) are transformed into ordinal categorical data; then b) arbitrary equally spaced scores are assigned to each categories (usually 1, 2, 3, and 4, that totally disregard true distance between categories or interval wideness); furthermore c) these scores are dealt as purely numerical values, sometimes combined through arbitrary weights, in order to produce a new score, i.e. the value of the composite index (CI); finally d) the values of the CI are categorised into four levels (from low to high vulnerability) in order to use the CI as an ordinal variable. Most surprisingly numerical scores (stage b) are assigned also to non-ordinal categories of qualitative variables (such as for the variable ‘Reason for non-attendance at school’ with its four not-ordered levels ‘Not interested’, ‘Distance to school’, ‘Financial constraints’, ‘Child marriage or disability’).

2 Most of our immigrants are refugees (22%); holders of subsidiary protection (27%); or those with residence permits for humanitarian reasons (22%). But there are also immigrants who requested asylum and are awaiting a decision (9%), as well as a mixed group of immigrants who are waiting to formalise their asylum request in Italy and/or in transit to seek protection in other European countries. For the sake of simplicity in the paper we will refer to them simply as refugees and asylum seekers. Although we acknowledge that different levels of legal protection are associated to different rights and entitlements, the small sample size does not allow to perform separate analysis of vulnerability for different levels of protection.

3 Informal settlements were defined as ‘sites with at least 50 inhabitants and characterised by some forms of self-management and lack of rental fee payment, including occupied buildings, shacks, containers and tented camps’ (MSF 2016).

4 The makeshift camp of Ventimiglia, a small Italian city seven kilometres far from the border with France, would deserve some attention paid to too. Despite the appalling living conditions of these refugees and the considerable number of refugees who have been staying in and around (see among others, Oxfam 2018 and MSF 2018), the Ventimiglia camp was excluded from this analysis due the extreme volatility in its composition and its continuing being made.

5 As highlighted by Mendola and Volo (2017) in their guidelines for composite indicators’ building: ‘Correlation analysis, for instance, could help to correctly choose the aggregation function and is one of the elements to properly distinguish between formative or reflective modeling strategies’.

6 Aggregation by sum is one of the choices inside the set of the so-called ‘compensative functions’ (including the arithmetic mean, or any linear combination). For a discussion on consequences that methodological and statistical choices have on the development of composite indicators and on their validity and even utility see Mendola and Volo (2017).

7 Note that Sicily and Calabria are the poorest regions in Italy.