The impact of policy legacies on the implementation of Citizen Income in Italy: A policy feedback perspective
Abstract
enThe Citizen Income (Reddito di cittadinanza—RdC) is the most extensive program to fight poverty ever adopted in Italy. RdC is a Minimum Income Scheme that grants a cash amount to beneficiaries but obliges some specific groups to participate in active measures and in social inclusion programs. After 4 years of implementation, RdC seems not to have fully achieved its goals and scholars blame policy legacies as one of the main causes of its failures. Drawing on the literature on policy feedback, the paper proposes an analytical framework that identifies the mechanisms related to resources, incentives, and meanings affecting policy actors (public administration, organized civil society, and citizens). The framework is then applied to the case of RdC to detect through what specific mechanisms deriving from past anti-poverty, active, and social policies impacted on the implementation of the RdC. The paper is moreover aimed at advancing the debate about policy legacies and their effects on current policies through the elaboration of a framework specifying the mechanisms through which policy feedback produces change or stability.
摘要
zh公民收入计划(Reddito di cittadinanza—RdC)是意大利有史以来实施的最广泛的消除贫困计划。RdC是一项最低收入计划，其向受益人发放现金，但要求某些特定群体参与积极措施和社会包容计划。经过四年的实施，RdC似乎并未完全实现其目标，学者则将其失败的一个主要原因归咎于政策遗产。本文借鉴政策反馈文献，提出了一个分析框架，该框架识别了一系列机制，后者有关于影响政策行动者(公共行政、有组织的公民社会、公民)的资源、激励措施和意义。然后将该框架应用于RdC案例，以检测积极的社会政策通过哪些具体机制(这些机制来自以往反贫困举措)来影响RdC的实施。此外，通过阐述一项框架(关于政策反馈产生变化或稳定性的机制)，本文旨在推进有关政策遗产及其对当前政策影响的辩论。.
Resumen
esEl Renta Ciudadana (Reddito di cittadinanza—RdC) es el programa de lucha contra la pobreza más amplio jamás adoptado en Italia. RdC es un régimen de renta mínima que concede una cantidad en efectivo a los beneficiarios, pero obliga a algunos grupos específicos a participar en medidas activas y en programas de inclusión social. Después de cuatro años de implementación, RdC parece no haber logrado plenamente sus objetivos y los académicos culpan a los legados políticos como una de las principales causas de sus fracasos. Basándose en la literatura sobre retroalimentación de políticas, el artículo propone un marco analítico que identifica los mecanismos relacionados con los recursos, incentivos y significados que afectan a los actores políticos (administración pública, sociedad civil organizada y ciudadanos). Luego, el marco se aplica al caso de RdC para detectar a través de qué mecanismos específicos derivados de políticas antipobreza, activas y sociales del pasado impactaron en la implementación de la RdC. Además, el documento tiene como objetivo promover el debate sobre los legados políticos y sus efectos en las políticas actuales mediante la elaboración de un marco que especifique los mecanismos a través de los cuales la retroalimentación de las políticas produce cambio o estabilidad.
INTRODUCTION
The Citizen Income (Reddito di cittadinanza—RdC) is the most extensive program to fight poverty and inequalities ever adopted and implemented in Italy.1 The RdC is a conditional Minimum Income Scheme (MIS) that combines a cash transfer paid by the National Security Insurance Agency with participation in employment or social activating programs implemented at the local level. The employment pattern is managed by Employment Centers where case managers support beneficiaries in defining their personal activation programs, called Employment Pacts. The social pattern is managed by Social Services and involves beneficiaries in a social assistance program designed in the Social Inclusion Pact. Remarkably, notwithstanding the huge investment made by the Italian central government to introduce and support this measure, over 4 years since its adoption, the RdC has achieved quite contradictory results and its impact on the activation, employment, and social inclusion of beneficiaries is still unclear (Alleanza contro la povertà, 2019; Caritas Italiana, 2021; Comitato Scientifico per la valutazione del Reddito di cittadinanza, 2021; Gori, 2021, 2023; Sacchi et al., 2023; Triventi et al., 2023).2
To explain the implementation gaps which emerged in the active and social programs for the RdC's beneficiaries, scholars invoked high variations in employment and social services' capacity to take on beneficiaries and to design their personal programs across regions (Bruno et al., 2022; Comitato Scientifico per la valutazione del Reddito di cittadinanza, 2021; Gubert & De Capite, 2021; Nesti et al., 2023; Sacchi et al., 2023) and, more in general, the design of the policy and path dependence as prominent explicative factors (Arlotti & Sabatinelli, 2020; Busilacchi et al., 2021; Sacchi et al., 2023). However, while the characteristics and relevance of the RdC's design in determining the implementation deficits of the measure have been reported by several Italian scholars, the analysis of what policy legacies influenced RdC implementation and how they impacted on it is still underdeveloped.
The present paper is aimed at filling this gap by proposing an exploratory analysis of what mechanisms deriving from previous policies shaped RdC implementation and with what effects.
To date, there has been little discussion on the concept of policy legacy and its impact on policy implementation. In view of this, the paper draws on the concept of policy feedback and develops an analytical framework that identifies the mechanisms generated by past policies impacting on the current RdC's implementation process. Our hypothesis is that past choices made in the context of anti-poverty policy combined with decentralization of competences and policy reforms that occurred in the employment and care sectors in the last 30 years triggered policy feedback mechanisms that affected actors' behavior, and ultimately had an impact on the implementation process and arrangements (Casula, 2022; Sager & Gofen, 2021; Steinebach, 2022).
The paper is structured as follows. Second section introduces the concept of policy legacy and reviews the literature on policy feedback outlining its characteristics and contribution to the analysis of policy implementation. It then proposes the analytical framework and identifies the mechanisms through which policy feedback operates according to the actors affected by them, and their potential effects. The framework draws on Pierson's seminal work on policy feedback (Pierson, 1993) and on more recent literature on the topic (Béland, 2010; Béland & Schlager, 2019; Campbell, 2012; Mettler & SoRelle, 2014). Third section illustrates the research questions, the hypotheses, and the methodology. The analysis of the case study has been conducted using a mixed method approach (Timans et al., 2019), based on desk research and the analysis of data collected through empirical qualitative research carried out on RdC in previous years (Caritas Italiana, 2021; Sacchi et al., 2023). In fourth section the analytical framework is applied to the implementation of the RdC in a Italian region. Through the framework, the policy feedback mechanisms deriving from past policy legacies are identified and their effects on the RdC's implementation process are explained. The concluding section discusses the paper's theoretical contribution to literature, highlights its methodological limitations, and proposes avenues for future research.
POLICY LEGACIES AND POLICY FEEDBACK MECHANISMS: A PROPOSED ANALYTICAL FRAMEWORK
The use of the concept of policy legacy is quite diffused among policy scholars, although a shared definition of this term is not available in literature. Sometimes “policy legacy” is also used as a synonymous of “path dependence,” albeit the two terms refer to different aspects of institutional and policy processes. The concept of path dependence has been extensively discussed in political science to explain how institutions are created and reproduced through self-reinforcing mechanisms (Hall & Taylor, 1996; Koelble, 1995; Pierson, 2000). The concept of policy legacy refers to institutions, processes, and ideas belonging to past policies that still persist in the present and affect the way policies are designed and implemented.
Historical institutionalism first conjectured that past policy choices impact on policies and that the latter, in turn, reshape politics (Immergut, 1998; Skocpol, 1992; Steimno, 2009; Steinmo et al., 1992; Thelen, 1999). Paul Pierson further developed this idea in his article “When effect becomes cause” (Pierson, 1993) where he argues that policies are not only the output of the political process, but also an important input into it since they shape the economic, social, and political environment where it takes place (p. 595). According to Pierson, policies operate through feedback mechanisms that provide resources, incentives, and cognitive frames to government elites, interest groups, and the mass public. These mechanisms affect political actors' goals, actions, and values, they shape institutional capacities, procedures, and governance structures, and therefore, they also impact on policy development (Béland, 2010; Mettler & SoRelle, 2014). As clearly stated by Béland, “the concept of policy feedback refers to this impact of previously enacted policies on future political behavior and policy choices. In other words, policy feedback is a temporal concept that points to the fact that over time, policy can shape politics” (Béland, 2010, p. 570).
In recent years, the interest in how policies, once established, impact on political behavior and policy change, has led to the emergence of a “policy feedback scholarship” (Béland, 2010; Béland & Schlager, 2019; Mettler & SoRelle, 2014). This field of research investigates the relevance of feedback in explaining how past and existing policies impact on actors and on future courses of actions. Policy feedback theory, in fact, “provides insight into the ability of policies – through their design, resources, and implementation – to shape the attitudes and behaviors of political elites and mass publics, as well as to affect the evolution of policymaking institutions and interest groups, and through any of these dynamics potentially to affect subsequent policymaking processes” (Mettler & SoRelle, 2014, p. 152). Albeit the main research focus of policy feedback scholars is represented by politics and by the mechanisms through which politics is shaped by policies (Hacker & Pierson, 2019), some ambiguities still remain regarding its use to explain stability and change in the context of public policies.
Lacking a clear definition of the concept of “policy legacy,” we opted to draw on the concept of “policy feedback mechanism” and to adapt it to investigate how past policies impacted on RdC implementation. We built, therefore, on Pierson's analysis of policy feedback (Pierson, 1993), and we apply it to the concept of policy legacy. As highlighted by Mettler and SoRelle: “Pierson's ideas helped a more precise identification of the mechanisms at work, as well as the circumstances under which feedback might be expected to occur and with what effects” (Mettler & SoRelle, 2014, p. 154). We slightly adapted Pierson's original framework to policy actors and processes, and we assumed that policies can affect actors' behaviors and identities, and therefore, policy implementation processes and arrangements (Sager & Gofen, 2021). Actors are government elites, interest groups, and citizens (or mass publics) while the main policy feedback mechanisms originating from policies are resources and incentives, and interpretive processes (Pierson, 1993). Resources can be material or immaterial, but both create structures that induce actors to make choices, while interpretive mechanisms refer to the information and meanings provided by policies that help actors to cope with complexity and make sense of the environment that surrounds them. The type of mechanisms that could be activated by policies for each actor are indicated in Table 1.
| Actors affected by mechanisms | |||
|---|---|---|---|
| Government actors | Interest groups | Mass publics | |
| Type of mechanisms | |||
| Based on resources and incentives | Administrative capacities
|
Spoils | Benefits
|
| Organizing niches | |||
| Financing | |||
| Access to policymakers | |||
| Based on information and meanings | Policy learning | Policy learning | Policy narratives
|
- Source: Adapted from Pierson (1993).
Past policies can modify or expand the capacities of government actors. Administrative capacities represent the abilities that a government should possess to deal with complex problems (Lodge & Wegrich, 2014). They pertain to four policy aspects (Lodge & Wegrich, 2014; Terracciano & Graziano, 2016). Policies can attribute new capacities to governments through the adoption of new regulations and/or the expansion of regulatory power; the assignment of programming and management roles, including budgeting control and accounting; and the allocation of coordination, analysis, and evaluation responsibilities. The presence of administrative capacities helps bureaucracy to fulfill their duties, simplifying their activities and constraining their future actions. When administrative capacities are well developed, the impact on policy implementation is positive and leads to favorable policy results. In contrast, when capacities are scarce and/or undeveloped, they negatively impact on the policy process.
The presence of resources and incentives allows for the formation and expansion of interest groups. Organized interests can be mobilized through spoils, or benefits for their constituencies. They can also take advantage of policies that create the opportunity to occupy a particular niche and gain a monopoly over an issue. Policies can also give funds to particular groups that would, therefore, attract more members, and expand their influence in that policy domain. Policymakers can also grant specific groups privileged access to the agenda-setting and policy formulation stages in order to create and consolidate a stable policy network on a specific topic.
Last, policies can provide the mass public with resources that incentivize their mobilization and political participation. Institutions can grant citizens access to benefits such as goods, services, and programs and these benefits affect citizens' capacity and will to participate in public life. On the one hand, the design of access criteria affects individuals' participation in policy programs (the so-called take up of a measure). On the other hand, the entitlement to benefits identifies who is included in a political community and who is not, it lowers the cost of participation, and it therefore impacts on access to citizens' rights and on the propensity to be politically engaged (Mettler & SoRelle, 2014).
A second category of policy feedback mechanisms is information and structures of meanings that help actors cope with complex situations. Past policies can promote policy learning among government elites that guide them in framing issues, and in pre-structuring policy alternatives. Learning can generate adjustment of existing courses of action and change. But if this mechanism adopts past experiences as anchorage for policy action, it could tend to perpetuate existing patterns, fix only marginal aspects, and limit change (Lindblom, 1959; Simon, 1983).
Policy learning can also influence interest groups' policy frames and their capacity to participate in policymaking. Mobilization of organized interests can, in fact, take place also at an ideational level. Groups supporting the dominant paradigm can have more chances to access the policy arena, and learning processes help groups adapt their advocacy strategies to the context and specific lobbying targets.
Last, policy feedback mechanisms affect the way mass publics define their identities, aims, and strategies of action through the elaboration of policy narratives. This is particularly true in the case of social policies. As Mettler and SoRelle claim: “some policies convey messages to beneficiaries that they are deserving of the support they receive, whereas other policies are stigmatizing and imply lack of deservingness or second-class citizenship” (Mettler & SoRelle, 2014, p. 159). The social construction of beneficiaries also impacts on political actors' propensity to grant them a benefit, as clearly pinpointed by Béland and Schlager: “politically powerful and positively constructed groups receive mostly benefits and few burdens from public policies; whereas politically weak and negatively constructed groups receive mostly burdens and few benefits” (2019, p. 193).
Remarkably, an output of policy feedback dynamics is the production of lock-in effects. Drawing on Douglass North's work (North, 1990), Pierson explained this point claiming that there “is the possibility that policies provide incentives that encourage individuals to act in ways that lock-in a particular path of policy development” (Pierson, 1993, p. 606). Lock-in effects are produced because mechanisms constrain and channel actors' future actions, raising the costs of an exit from the path that could generate a loss of advantageous positions, then contributing to reproducing the status quo (Hanger-Kopp et al., 2022; Pierson, 2000).
RESEARCH QUESTIONS, HYPOTHESES, AND METHODOLOGY
Data related to the activation programs highlight that in 2022 only 44% of recipient households out of the total were referred to Employment Centers while 43% were referred to local Social Services. Among the latter, 38% of households were engaged by the Social Services but only 16% signed the Social Inclusion Pact (Ministero del lavoro e delle politiche sociali, 2023). The picture is slightly better for employment services, where 46,2% of beneficiaries had signed an Employment Pact by the end of 2022 (ANPAL, 2023). A more controversial output of the RdC is its capacity to find jobs through active employment programs. Definitive data related to the beneficiaries who were able to find a job due to the RdC are not available, but a report published in 2021 by the National Agency for Active Employment Policies estimated that the probability of finding a job after having signed an Employment Pact is around 10% (ANPAL, 2021).
Previous research on RdC mentioned local welfare traditions, the different organization of local services, and the presence/lack of a network of local partners as the main legacies determining the capacities of local territories to comply with the RdC's policy goals and to implement it effectively (Arlotti & Sabatinelli, 2020; Bruno et al., 2022; Busilacchi, 2020; Busilacchi et al., 2021; Lodigiani & Maino, 2022; Maino & De Tommaso, 2022; Sacchi et al., 2023; Vittoria, 2019). Drawing on this research, we hypothesize that policy feedback mechanisms determined by past choices in the Italian anti-poverty, active, and social policies shaped RdC implementation leading to an overall negative effect on the RdC's results but with high subnational variations. The paper is therefore aimed at identifying and detailing in a systematic way the specific policy feedback mechanisms that impacted on the implementation process at the local level.
To this aim, we first carefully traced the historical development of anti-poverty measures and their intersection with activation and social policies, and decentralization processes. We mainly drew on historical analysis undertaken by Madama (2010), Graziano and Raué (2011), Graziano and Winkler (2012), Arlotti and Sabatinelli (2020), and Saraceno et al. (2022). Also particularly helpful were the study on the development of Italian MIS by Natili (2019) and Jessoula and Natili (2020) and the analysis of local welfare networks by Nesti and Graziano (2021).
We then identified the gaps that affected the implementation of activation and of social inclusion programs through the review of literature on RdC, in particular by Caritas Italiana (2021), Nesti et al. (2023), and Sacchi et al. (2023). Desk research has been integrated with information drawn from a dataset comprising 56 semi-structured interviews, one survey, three focus groups with case managers from local employment and social services of the Italian region) Veneto, one survey administered to Navigators,3 and a survey conducted at the national level among beneficiaries (n. 395) and potential beneficiaries (n. 607) of the RdC. These data were also integrated with findings from 13 focus groups held with key informants from the regions Campania, Lazio, Lombardy, Sardinia, Tuscany, and Veneto (Caritas Italiana, 2021). The empirical research was carried out between 2020 and 2023.
Finally, we utilized literature and data to also identify the specific resources and interpretative mechanisms that affected the actors of the RdC included in the framework with a specific focus on the regional level.
In our analysis, we use the categories “government elites” to identify public officials, “interest groups” to identify all the actors belonging to organized civil society, and with “mass publics,” we identify citizens and beneficiaries of the RdC.
The approach is aimed at testing the capacity of the framework to identify policy feedback mechanisms and to explain the main dynamics affecting the implementation of the RdC. For this reason, the application of the framework has an exploratory nature.
POLICY FEEDBACK MECHANISMS AND THE IMPLEMENTATION OF THE RdC IN ITALY
Anti-poverty, activation, and social policies in Italy
MISs were adopted in Italy very late in comparison to other European countries. Some experimentation took place at the regional level between the second half of the 1990s and 2015, while at the national level, anti-poverty measures were first issued under center-left governments and then reversed by center-right governments (Jessoula & Natili, 2020). All in all, this experimentation contributed to fragmenting the system of services due to their diverse design, economic entity, activities, and regulatory frameworks (Jessoula & Natili, 2018; Meo & Volturo, 2022; Natili, 2019; Natili et al., 2017; Saraceno et al., 2022).
In 2016 the first Italian MIS was introduced called “Support for the Active Inclusion” (Sostegno di Inclusion attiva—SIA), followed in 2017 by the Inclusion Income (Reddito di Inclusione—REI). SIA and REI were monetary benefits supplied under means tests and based on the participation of households in social inclusion or in labor activation projects designed and implemented at the municipal level by social services in cooperation with the local network of employment centers, health services, and non-profit organizations. These two measures incentivized collaboration among the various actors of local welfare but with strong differences among regions. Partnerships were more effective in those regions mainly in the North and the Center of Italy where the Third Sector was already developed (see below) while in other regions, activation projects barely succeeded (Gori, 2019; Pesenti & Marzulli, 2021).
In 2019, the REI was replaced by the RdC, a MIS entailing a monetary transfer granted by the National Social Security Agency according to strict eligibility criteria and providing for job activation or social inclusion measures aimed at work reintegration or at solving households' complex social needs.
Overall, the implementation of the RdC mainly relied on the REI structure, and it therefore inherited the weaknesses of activation and social policies' legacies. The existing organization of these sectors highly impacted on the RdC. The Italian system of Public Employment Services (PES) was managed until 1997 in a standardized and hierarchical way and was characterized by high inefficiencies and a low capacity to create job placements (Graziano & Raué, 2011; Graziano & Winkler, 2012; Scarano, 2021). After the mid-1990s, the adoption of flexibility principles led to a reorientation of public expenditure from passive to active measures, the decentralization of PES, education, and vocational training services, and the involvement of public actors in the implementation of employment services. The first experimentation with MIS at the end of the 1990s entailed the involvement of beneficiaries in activation programs delivered at the local level, but beneficiaries' participation rates were very different among regions. Implementation gaps mainly stemmed from different PES' administrative capacities to plan, manage, coordinate, and monitor collaborative relationships with local private partners such as private education agencies and firms (Avola et al., 2017; Graziano & Raué, 2011; Graziano & Winkler, 2012; Mandrone & Marocco, 2019; Scarano, 2021).
The Italian policy for care services was characterized for a long time by incomplete and inconsistent regulation, by a fragmented, uncoordinated system of services across the territory, managed by numerous public institutions, charities, and advocacy organizations (Jessoula & Natili, 2020) and by a rigid and prejudiced bureaucracy (Brandolini, 2021). Processes of decentralization, which started at the end of the 1970s and culminated in the 1990s with the devolution of care and social competences to the local level, gave to the Italian regions an extensive autonomy in a wide range of social matters but without central coordination. Thus, incoherent regulation proliferated at the regional and subnational levels and a territorially segmented system of services emerged, between the North, the Center, and the South of the Nation (Arlotti & Sabatinelli, 2020; Fargion, 1997; Gualmini & Sacchi, 2016).
The first Italian law for the creation of an integrated system of social services issued in 2000 (Law 328/2000) tried to overcome these problems but without significant long-term effects. Decentralization of competences to regions on social matters paved the way for a hyperproliferation of regulatory acts and to a strong differentiation among the North, Center, and South of Italy in the organization of care services. The exclusive regulatory power granted to regions hampered the attribution of coordination duties to the national level (Arlotti & Sabatinelli, 2020; Madama, 2010). Additionally, the decentralization of competencies was not accompanied by financial powers, thus regions had to rely on scarce national resources—a dynamic that hampered the creation of a strong network of public services especially in the South (Arlotti & Sabatinelli, 2020). Law 328/2000 also promoted the participation of the Third Sector in the provision of social services, but over the last 20 years, this process has led to a scattered diffusion of non-profit organizations across the territory, with marked differences among northern, central, and southern regions (as highlighted above).4 The development of the Italian Third Sector in the social policy domain was strongly influenced by the local civic culture but also by the availability of public funding, usually present in those regions where public intervention was more developed (Lori & Zandonai, 2020).
Policy feedback mechanisms through incentives and resources
The RdC was implemented, therefore, in an institutional context strongly influenced by the organization of anti-poverty, employment, and social policies and by the structure of the services already in place at the local level. Our hypothesis is that these policies generated feedback that impacted on the RdC.
The first mechanism impacting on RdC implementation concerns public administration and pertains to its capacity to deal with complex policy problems. As reported by literature, MISs combined with activation and social measures require governmental actors to cope with complex beneficiaries' needs, design multidimensional projects, coordinate the appropriate network of partners to carry out projects with beneficiaries and assess them (Nesti & Graziano, 2021). The expansion of institutional competences and related administrative capacities in the employment and social sectors took place at the end of the 1990s, through a process of decentralization. This dynamic favored more politically entrepreneurial regional administrations that were able to exploit this opportunity and improve their administrative capacities. Regulatory powers, programming, managerial, and analytical skills were granted to all regions, but they were more exploited in the North and the Center of Italy while Southern regions remained, as a result, less skilled. These territorial differences characterize regional administrations, employment centers, and also social services. Coordination capacity is less mature, and this function is particularly relevant in the case of activation and social inclusion measures where the collaboration of several partners in individual projects is fundamental. Its development was hampered over the years by the late introduction of an integrated system of actors involved in the different policy domains, while decentralization processes taking place since the 1970s contributed to hindering a strong coordination role from central government (Barberis & Kazepov, 2013; D'Emilione & Giuliano, 2022). The introduction of the REI created the opportunity to integrate employment and social services involved in the implementation of the measure. However, in this case also, some regions were more capable than others to experiment with new forms of cooperation among actors. This capacity also influenced RdC implementation.
Organized civil society is particularly relevant in the implementation of the RdC with reference to the local social inclusion programs. Civil society has been mobilized in the anti-poverty policy sector since the Nineteenth Century when governments left the delivery of services to religious associations mainly on a charitable basis (Saraceno et al., 2022). With the decentralization of social assistance policies and the strong emphasis put by Law 328/2000 on the principle of horizontal subsidiarity (Arlotti & Sabatinelli, 2020), associations and the Third Sector became central to local welfare networks. However, this was concentrated in some particular regions such as Veneto, Lombardy, Tuscany, and Emilia Romagna, where social capital was more developed (Bertin, 2012) and public funds were more generous. The main policy feedback mechanism activated by social policy and provided to civil society by policy makers for decades is represented, therefore, by an organizational niche. The second incentive is funding, introduced particularly in the 1990s, and then consolidated over the following decades with the expansion of the welfare mix across the regions and the adoption of contracting-out practices. Spoils, in contrast, had a limited impact, especially in the anti-poverty and social policy domains, where they were scarce and distributed to specific categories of beneficiaries. Access to policy making was granted to organized civil society from the 1990s, with the adoption of Law. 328/2000 and the participation of organizations representing the Third Sector in national and regional programming in the social policy domain. In 2013, the Alliance Against Poverty entered the anti-poverty policy arena where it was capable of lobbying the national government to introduce a MIS and became part of the policy community for at least a decade (Gori, 2020).
Policy feedback mechanisms related to interest groups were, in sum, activated mainly through organizing niches, financing, and access to policy making and led to the formation of a Third Sector with a relevant role in the field of social policy but without the same strength across the Italian territory.
Concerning the mass public, incentives provided by previous policies, impacted on their involvement in social policy programs and in political life. The intersection of feedback mechanisms generated by the three policy domains—anti-poverty, activation, and social—negatively affected the categories of beneficiaries involved in these programs especially those involved in the RdC. The category-specific nature of the measures adopted in the three policy domains, and particularly the late expansion of specific benefits targeted to the poor, combined with the characteristics of these groups (Saraceno et al., 2022) hindered their capacity to become a strong constituency capable of voicing its needs and mobilizing for themselves at a political level. Moreover, the design of MISs, and especially of the RdC, with strict eligibility criteria and conditionalities, impacted on the take-up of the measure and on its capacity to activate beneficiaries. Evaluations of the RdC demonstrate its limits in reaching all potential recipients (Caritas Italiana, 2021; Comitato Scientifico per la valutazione del Reddito di cittadinanza, 2022), while empirical data highlight that the limited success of active programs is mainly due to a mismatch between the conditionalities imposed on RdC beneficiaries and their job profiles. The type of benefits (monetary transfer and active/social programs) provided for citizens involved in the RdC, and the way rules and procedures regulating the access to the incentive were designed, has impacted on the level of take-up of the measure, but also on the capacity of beneficiaries to fully participate in the activation and social programs.
Policy feedback mechanisms through interpretative frames
The last policy feedback mechanisms that impacted on RdC implementation relate to information and meanings' structures adopted by actors to deal with complex policy issues. Policy learning among government elites was limited for a long time, due to the scarce salience assigned to anti-poverty measures by politicians. In the case of active and social policies, policy learning was influenced by the diverse administrative capacities diffused across the regions. Institutional learning was induced especially in those regions where analytical capacities (e.g. data collection, data analysis, and monitoring) and implementation arrangements were already developed. Thus, the implementation of active and social programs in the context of the RdC was facilitated in those regions where policy learning deriving from the REI generated possible changes and/or a capitalization of good practices.
The same territorial dynamic affected the Third Sector involved in the implementation of the RdC. At the local level, organizations already involved in welfare networks have been able to capitalize their experience and be involved in REI and RdC social programs.5
The policy narrative developed around the RdC is the final policy feedback mechanism that impacted on its implementation. This narrative was framed in a context of low salience assigned to anti-poverty issues at the political and electoral levels for decades (Jessoula & Natili, 2020). The salience increased when the RdC was introduced by the Conti government after being promoted by the Five Star Movement during the 2018 electoral campaign. RdC implementation was kept under observation not only by the opposition but also by most Italian newspapers since its early introduction. Namely, RdC mainly was framed not as an anti-poverty measure, but as a labor and activation policy (Baldini & Gori, 2019; Jessoula & Natili, 2020; Saraceno et al., 2022; Turco, 2020). This narrative produced a misperception of implementation results thus generating the idea that the RdC was a complete failure. Moreover, a secondary narrative promoted by some political parties and media tended to portray beneficiaries as “lazy” or “opportunist” (the so-called “RdC dodgers”) and contributed to consolidating the frame of the “undeserving poor” already developed with previous policies. All in all, these policy narratives weaken the legitimacy of the policy but also have a strong impact on citizens. First, the stigmatization of beneficiaries possibly impacted on take up rates of the measure. Second, as highlighted by our data, the narratives impacted on beneficiaries' self-esteem and their self-perception as worthy of support. Finally, they impacted on policymakers and led to the RdC's abolition.
Analyzing RdC implementation through the lenses of policy feedback mechanisms
The RdC is the first Italian anti-poverty measure that reached a wide target of beneficiaries in the territory. Nevertheless, after 4 years of implementation, experts estimate that the take-up rate of the measure has been low and, above all, the results achieved through active and social inclusion programs are limited and with a high variation among regions. Motivations behind this relatively unsatisfactory performance are being assessed but preliminary evaluations attribute its causes to the design of the measure and to structural limits deriving from past legacies.
The framework illustrated in the second section tries to analyze with a more systematic approach what policy legacies impacted on RdC implementation and how. Our analysis, based on Pierson's concept of policy feedback, has identified some specific mechanisms triggered by past anti-poverty, active, and social policy domains that would explain how and why past legacies influenced RdC implementation (see Table 2).
Mechanisms affecting public administration and the Third Sector create a differentiated system of services and welfare networks across the territory and a different capacity to cope with implementation's requirements. Mechanisms affecting beneficiaries hampered their capacity to participate in policy arenas and impacted on RdC take-up rates (Table 2).
| Actors affected by feedback mechanism | |||
|---|---|---|---|
| Government elites | Interest groups | Mass publics | |
| Type of mechanism | |||
| Incentives and resources |
Administrative capacities
|
Spoils
|
Benefits
|
Organizing niches
|
|||
Financing
|
|||
Access
|
|||
| Information and meanings | Policy learning
|
Policy learning
|
Policy narrative
|
- Source: Adapted from Pierson (1993).
The negative effects produced by feedback mechanisms on RdC implementation remained “locked-in” for years due to the low salience assigned to the anti-poverty issue by political actors and by civil society; the low visibility of beneficiaries and their weak capacity to voice their needs; and the characteristics of the decentralization process that strengthened the role of regions without granting compensating and coordinating powers to the center (Jessoula & Natili, 2020; Madama, 2010; Saraceno et al., 2022).
CONCLUSIONS
This article aimed to advance the debate on the RdC trying to offer a more structured analysis of what past legacies have impacted on its implementation and how. Drawing on the policy feedback approach and on Pierson's dimensions of policy feedback (Pierson, 1993), we developed an analytical framework identifying the nine mechanisms that affected government elites, interest groups, and mass public in the implementation process of the RdC. Mechanisms have been identified through the analysis of the historical development of anti-poverty, active, and social policies based on an in-depth literature review and through the analysis of empirical data.
The main limitations of our analysis concern external and internal validity. First, we concentrated our analysis on feedback mechanisms identified by Pierson, and we slightly elaborated them according to recent literature on policy feedback. We argue that this framework has a good explanatory power of policy legacies and the mechanisms through which they influence actors' present behavior. Nevertheless, to confirm that mechanisms are exhaustive and that the framework is generalizable, it should be tested in different policy domains, and in different geographical contexts using a comparative approach (Campbell, 2012). Second, we apply the framework to the case of RdC implementation with the aim of identifying the “general” mechanisms triggered in this context. However, this choice does not account for specific subnational differences. Thus, its application to some regions would help in refining our findings and in providing for a more nuanced explanation of how mechanisms operate at a subnational level.
ACKNOWLEDGMENTS
The authors are grateful to the two anonymous reviewers for their helpful comments. Open access publishing facilitated by Universita degli Studi di Padova, as part of the Wiley - CRUI-CARE agreement.
FUNDING INFORMATION
Cariparo Foundation—Excellence Research Projects, Grant Number ID52032.
CONFLICT OF INTEREST STATEMENT
No potential conflict of interest was reported by the authors.
