Country Case Study Spain


In Spain, welfare has historically incorporated some of the most characteristic features of the continental „conservative corporatist“ model of European social policy, although it has also been labelled by the literature on comparative welfare as „familistic“ due to the key role that the family plays in the overarching architecture of the welfare system, particularly for children and dependent individuals.

Since its integration to the European Community (1986), Spain has followed a pattern of welfare convergence in three domains: (1) universalisation of social entitlements (education, health, pensions), (2) welfare expenditure increase, and (3) a diversification in the provision of social services by private and subsidised organisations. Thus, the Spanish social model or welfare state can be defined as both Bismarckian and Beveridgean traditions, as it combines universal and targeted access to services and benefits.

One the most relevant factor conditioning the social model and welfare development in Spain is the importance of government decentralisation both at the level of planning and policy implementation, from central to regional to local government. It is generally acknowledged that greater regional and local say in areas of policy-making closer to citizens’ perceptions have often been claimed on cultural or identity considerations. Such demands have been facilitated by the devolution of powers to regions and municipalities. These, in concurrence with central institutions of the European Union, are considered key actors in the service provision.

Nonetheless, the hierarchy of benefits is inversely coherent with the principle of territorial subsidiarity: the ‘better quality’ benefits are also the more centralised ones. It is also noticeable that access to ‘better quality’ benefits is independent from the family income, while the lower levels are family benefits strictu sensu.

With regard to policies, there is not an only one policy with regard to service provision, but different measures oriented to different groups of population. Generally, the Spanish ‘safety net’ of service provisions can be divided into two main groups: (1) Contributory Benefits (CB), and (2) Non-Contributory benefits (NCB). Eligibility for the former (CB) depends on having met certain conditions regarding social insurance contributions and certain contingencies such as old-age, widowhood, disability or unemployment. The amounts received depend on contributions and, in some cases, on a range of personal circumstances. Eligibility for the latter (NCB) depends on certain contingencies such as old-age, widowhood, disability or unemployment and, generally, on an income test. Eligibility in this case does not require a minimum amount of contributions and most non-contributory benefits are income-tested. The income test is usually related to a range of personal and family circumstances and to total individual or family income.

Criteria of identifying beneficiaries and distinguishing from non-beneficiaries generally take into consideration the following:

  1. Nationality and residence. Although nationality is not necessarily a requirement a certain period of registered residence of the beneficiary often in the region or Comunidad Autónoma is required in all programmes.
  2. Household formation and composition. Although applications are submitted by an individual, benefits have families as units of reference (and the individual applicant is responsible for its family distribution).
  3. Age. Most requirements set age limits between 25 and 65 years. Protection for citizens over 65 years rests mainly with non-contributory pensions.
  4. Economic resources of the beneficiaries. Access to benefits is means-tested, using the family (or household) as income unit. Means-testing can be applied differently depending on whether family income is derived from labour and other social benefits in order to avoid a reduction of protection, or to produce labour disincentives.
  5. Commitments and obligations. All benefits establish a number of obligations to be accomplished by the beneficiaries, which basically refer to cover basic needs of the household and to inform of any variations in the family unit.

It is important to note that variations in the awarding of the benefits depend on institutional milieus and civil servants discretionary criteria (at all three state, regional and local levels of government).

Practices and routines of past and current service provision (prior to AI use):

Generally, if individuals are not entitled to receive contributory benefits a non-contributory benefit is available, which is means-tested. As a general rule, the means-tested benefit system assesses entitlement according to family (or household) income unit. The family unit is, in general, the nuclear family. However, note that some non-contributory benefits, such as non-contributory old-age pensions, consider other cohabiting individuals within the family unit. It is worth noting that all benefits for the low-income (which are means-tested) may vary in some aspects. For instance, some benefits are paid to people already receiving contributory pensions, or to unemployed who exhausted their contributory unemployment benefit period. Further to this, some subsidies are differential benefits that increase existing income to an established minimum, whereas others are provided as final amounts. All these benefits provide cash amount which are lower than the legally established minimum wage. In other words, they provide a lower protection than that they could get were they to be active and employed in the formal labour market. The different benefits are ordered ranging from those which offer a better coverage to those more limited (in duration and intensity), and more conditioned with the compliance of activities related generally to labour activation.

The Case Study

The Case Study includes different City council employees (service providers and policymakers) and local representatives (beneficiaries and users) among its stakeholders in order to carry out the empirical social research for all sectors of service provision, as follows:

  • Barcelona City Council, with Barcelona Activa as its main ally, represents a key stakeholder as the capital city of Catalonia and the second largest city in Spain. The inclusion of Barcelona is important due to its leading role in service provision in the region and the implementation of Artificial Intelligence in this area.
  • Girona City Council. Girona is the capital of the province of the same name and a major metropolitan city. The city of Girona can be considered a regional player in terms of service provision. Artificial Intelligence is not yet in use for service provision.
  • Mataro City Council. Mataro is a major city within the province of Barcelona. The city is also an important service provider within the Maresme region (north-east of Barcelona). Some steps have been taken towards the implementation of Artificial Intelligence for service provision.
  • Olot City Council. Olot is a town within the province of Barcelona. The town can be considered an important service provider within the Garrotxa region (west of Girona). Artificial Intelligence is not yet in use for service provision.

Further, the Case Study includes among its stakeholders the Catalan Department of Labour, Social Affairs and Families, which acts both as policymaker and technology provider, particularly for small municipalities. This regional department provides a range of social services and technical support for municipalities. While primary social services are generally run by municipalities, the towns and cities with more than 20,000 inhabitants manage such services directly. The councils of municipalities with less than 20,000 inhabitants can choose to manage them directly or to leave that task to the regional council.

Finally, the Case Study also counts with an important umbrella organisation from the voluntary and economic sector consisting of non-governmental organizations and other non-profit organizations among its stakeholders: The Table of Associations of the Third Sector. This organisation is leading the digital transformation of the Third Sector entitlements and represents a key player in the ecosystem of innovation in the service provision.

One may argue that so far the societal discourse around Artificial Intelligence in the area of service provision is generally positive rather than negative. This seems to be primarily related to the idea that using Artificial Intelligence will allow policymakers to make better informed decisions with regard to social assessment and, at the same time, to free social workers from doing simple, manual tasks and allocate time for more creative tasks and personal interaction with beneficiaries and users.

The Case Study from the University of Girona plans to use a three-stage methodology to obtain relevant information during the project. First, it will carry out various focus groups with City council employees and local representatives from the abovementioned five municipalities. Second, it will conduct up to 10 in-depth interviews with key informants from City councils and local representatives of the five municipalities under study. Finally, it will examine local and national discourses around the use of Artificial Intelligence in general and the implementation of Artificial Intelligence for social assessment in particular.

Own research of case study partners (previous projects, publications etc.) on the chosen domain:

Recent participation as Co-I in the following relevant projects:

(2017-2019) “Demography, Migration and New Statistical Frontiers: Big Data and Longitudinal Registers” (Ref. CSO2017-85670-R). Financed by the Spanish Ministry of Economic Affairs and Digital Transformation (€108.900). Co-Investigator.

(2016-2017) “Economic Change and Internal Population Dynamics: An Innovative Study of New Residential Mobilities in Scotland” (Ref. ES/N004701/1). Financed by the Economic and Social Research Council, Regne Unit (€129.682). Co-Investigator.

Some publications that are related (particularly with regard to the compositional element) of the Case Study:

Norman, P., Simpson, L., & Sabater, A. (2008). ‘Estimating with Confidence’and hindsight: new UK small‐area population estimates for 1991. Population, Space and Place, 14(5), 449-472.

Sabater, A., & Simpson, L. (2009). Enhancing the population census: a time series for sub-national areas with age, sex, and ethnic group dimensions in England and Wales, 1991–2001. Journal of Ethnic and Migration Studies, 35(9), 1461-1477.

Sabater, A. (2015). Between flows and places: Using geodemographics to explore EU migration across neighbourhoods in Britain. European Journal of Population, 31(2), 207-230.

Sabater, A., Graham, E., & Marshall, A. (2019). Does having highly educated adult children reduce mortality risks for parents with low educational attainment in Europe?. Ageing & Society, 1-36.

Galeano, J., Domingo, A., & Sabater, A. (2017). Economic crisis and pauperization in the metropolitan region of Barcelona: a demo-space approach using data from Caritas (2005-2013). ENCRUCIJADAS REVISTA CRITICA DE CIENCIAS SOCIALES, 14.

Sabater, A., Bayona, J., & Domingo, A. (2012). Internal migration and residential patterns across Spain after unprecedented international migration. In Minority internal migration in Europe (pp. 293-311).

Sabater, A., Galeano, J., & Domingo, A. (2013). La transformación de las comunidades mayoritarias y la formación y evolución de los enclaves étnicos residenciales en España. Migraciones. Publicación del Instituto Universitario de Estudios sobre Migraciones, (34), 11-44.

Domingo, A., & Sabater, A. (2010). El empadronamiento de la población extranjera en los municipios catalanes de 2004 a 2008. Scripta Nova. Revista Electrónica de Geografía y Ciencias Sociales, 14(34).

Sabater, A., & Domingo, A. (2012). A new immigration regularization policy: The settlement program in Spain. International Migration Review, 46(1), 191-220.