Intersectoral and transversal effects and their impacts on the effectiveness of public policies in Ceara’s municipalities

Abstract

Identifying under what circumstances transversality and intersectoriality take place within the scope of public policies is fundamental to increase their effectiveness. Thus, two theoretical frameworks related to poverty and attractiveness were integrated, aiming to capture the existing effects. The econometric estimation with data for Ceara’s municipalities showed, for example, that economic growth and the public policies that stimulate it, besides favoring the reduction of poverty levels, can also increase the attractiveness of a given municipality. On the other hand, initiatives that stimulate the urbanization and the requalification of spaces, increase their attractiveness and, also, favor the reduction of poverty. In addition, it was emphasized the need to investigate how the characteristics of the place and its population can affect the effectiveness of policies.

Keywords:
public policy; intersectoriality; transversality; effectiveness; Ceará

Resumo

Identificar em quais circunstâncias a intersetorialidade e a transversalidade ocorrem no âmbito das políticas públicas se mostra fundamental para aumentar sua efetividade. Assim, este estudo integrou dois arcabouços teóricos relacionados à pobreza e à atratividade, visando a captar seus efeitos. A estimação econométrica com dados para os municípios cearenses evidenciou, por exemplo, que o crescimento econômico e as políticas públicas que o estimulam, além de favorecer a redução dos níveis de pobreza, também podem aumentar a atratividade de determinado município. Por outro lado, iniciativas que estimulam a urbanização e a requalificação dos espaços aumentam sua atratividade e, ainda, favorecem a redução da pobreza. Assim, ressalta-se a necessidade de pesquisar como as características do local e de sua população podem afetar a efetividade das políticas públicas.

Palavras-chave:
políticas públicas; intersetorialidade; transversalidade; eficiência e efetividade governamental; Ceará

Resumen

Identificar en qué circunstancias la transversalidad y la intersectorialidad se producen en el contexto de las políticas públicas es esencial para aumentar su efectividad. Por ello, este estudio integró dos marcos teóricos relacionados con la pobreza y la atractividad, con el objetivo de captar sus efectos. La estimación econométrica con datos para los municipios de Ceará evidenció, por ejemplo, que el crecimiento económico y las políticas públicas que estimulan y favorecen la reducción de los niveles de pobreza también pueden aumentar la atractividad de un determinado municipio. Por otro lado, las iniciativas que fomentan la urbanización y la recalificación de espacios aumentan su atractividad y también ayudan a reducir la pobreza. Asimismo, se resalta la necesidad de investigar cómo las características del lugar y de su población pueden afectar la efectividad de las políticas públicas.

Palabras clave:
políticas públicas; intersectorialidad; transversalidad; efectividad; Ceará

1. INTRODUCTION

Recent literature has emphasized the major challenges that governments have been facing over the last few years in order to raise levels of efficiency, efficacy and effectiveness of public policies, particularly in a context where the population has more access to information and has more awareness of their rights, demanding public goods and services that actually meet their needs and aspirations (Andrews, 2013, Catelli & Santos, 2004, Holanda & Rosa, 2004, Macroplan, 2016, Nogueira & Pontes, 2013, 2015).

In this context, a particular challenge for the success of public policies and the achievement of consistent and lasting results is the difficulty to integrate the various policies, optimizing the intersectoral and transversal effects (Macroplan, 2016; Nogueira & Pontes, 2013, 2015; Oliveira, Miro, & Barreto, 2013).

More specifically, Nogueira and Pontes (2013, 2015) analyzed the changes undertaken in the scope of the elaboration of the Pluriannual Plan 2012-2015 of the State of Ceara indicating that, in spite of them, there was still, in general, limited ability to take advantage of intersectorality and cross-cutting nature of the various initiatives, with the exception of a number of multisectoral programs, coordinated by the Governor’s Office, targeting youth, women, ethnic and racial equality, drug control, the elderly and the disabled, and human rights. In fact, in accordance with the in-depth interviews conducted, it was found that even in these cases there was still a lack of integration between the actions of the secretariats, since they did not act in a more systemic way.

Thus, since intersectorality and transversality are important aspects to consider when seeking better long-term results, then, an interesting question arises: how governments can identify these intersectoral and transversal effects, and measure their impacts on the effectiveness of their policies?

This paper, therefore, aims to contribute to the response of this relevant question, assuming that theoretical references are fundamental to map the channels that lead to the results of each set of policies seeking, when possible, to integrate existing approaches trying to verify how these intersectoral and transversal effects take place. By measuring these effects, it is then possible for governments to assess how their management structures can be adapted or reformulated in order to promote greater integration between the various policies and consequently to obtain greater levels of effectiveness in their proposed intervention strategies.

More specifically, the contribution proposed here is based on an example that seeks to integrate two theoretical frameworks: Bourguignon’s so-called poverty-growth-inequality triangle (2003, 2004) and one dealing with local attractiveness proposed by Campos and Fusco (2009). Next, the system of equations resulting from the integration proposal of the approaches for the case of Ceara’s municipalities, considering data from the years 2000 and 2010, is estimated through a regression analysis as evidence that there are intersectoral effects and transversality between these policies and that their effects can be quantified, favoring a higher level of effectiveness.

The relevance of this paper can be considered from various perspectives. Firstly, the study has theoretical relevance, since it aims to contribute to the answer of a complex question and, to this end, seeks to verify how two different theoretical frameworks can be related. The article also has empirical and contextual relevance, since it estimates the integrated framework proposed for the municipalities of Ceara, which in many cases have a significant proportion of poor and low attractiveness, conditions that challenge public managers and their policies. Finally, it is also of practical relevance, since the estimates and analyses are designed to better target policies to combat poverty and those that affect local attractiveness in Ceara.

2. THEORETICAL BACKGROUND

2.1. INTERSETORIALITY AND TRANSVERSALITY OF PUBLIC POLICIES

According to Macroplan (2016) and Moreira (2016), public administration is currently more strongly influenced by three paradigms: the (Traditional) Bureaucratic Paradigm, New Public Management (NPM), and the Public Governance Paradigm (and related approaches, such as the New Public Service - NPS).

Among the various aspects and visions concerning each paradigm, it is considered in particular in this article the issues of intersectoriality and the transversality of public policies. More specifically, based on the literature on these themes, it is possible to argue that the low flexibility and the hierarchical vision, pertinent to the Bureaucratic Paradigm, makes difficult to treat these aspects (Holanda & Rosa, 2004; Nogueira & Pontes, 2013).

Under NPM, the simplification of complex problems so that they become more quantifiable and manageable leads to a fragmentation of public sector structures, which together with centralized decision-making and low participation of employees and society, makes it difficult to explore positive effects (Angelis, 2015; Carneiro & Menicucci, 2011; Catelli & Santos, 2004; A. C. C. Medeiros, 2010; A. C. C. Medeiros, Rosa, & Nogueira, 2008; Macroplan, 2016; Nogueira & Pontes, 2013, 2015).

It is, therefore, with the Public Governance Paradigm that these topics gain priority status (Angelis, 2015; Avelino & Santos, 2014; Fernandes, Castro, & Maron, 2013; Macroplan, 2016; Souza, 2015).

More specifically, in the context of the Public Governance Paradigm, “public policy presupposes a complex challenge and a set of multiple and diverse actors that act in an integrated, superimposed and crossed way, in the pursuit of a convergent goal” (Macroplan, 2016, p. 34). In other words, intersectoriality and transversality become essential aspects so that public policies can create adequate solutions to problems with a high degree of complexity (Avelino & Santos, 2014; Dias & Cario, 2012; Fernandes, Castro, & Maron, 2013; Macroplan, 2016; Paradela & Costa, 2013; Ruzzi, 2016; Souza, 2015).

Regarding intersectoriality, Avelino and Santos (2014) consider that in the same way as in the field of knowledge the way to deal with the problem of watertight disciplines was through the idea of interdisciplinarity, from the perspective of public administration, the complexity of relationships and social problems must be tackled with an intersectoral perspective, i.e., the problem must be confronted by the “articulation of knowledge and experiences in the planning, implementation and evaluation of actions, with the objective of achieving integrated results in complex situations, aiming at a synergistic effect on social development” (Junqueira, 1997 apud Quinhões & Fava, 2010, p. 79).

The problem, as Veiga and Bronzo (2014) point out, is that, in many cases, public administration is verticalized and compartmentalized, making it difficult to deal with heterogeneous, spatially differentiated multidimensional phenomena that are caused by both structural and conjunctural factors. Thus, according to Ruzzi (2016, p. 2), “intersectoriality emerges as a relevant strategy for public management, seeking to respond to the demands of integrality and efficiency to social problems considered as complex or with public marked by vulnerabilities”.

Therefore, it is important to consider that intersectoriality allows the opening of new channels for collaborative and participatory governance, since it is a more permeable arrangement for the participation of society (Souza, 2015). This is very important because,

in the areas of planning, management and execution, integrality would translate into intersectoral arrangements, since it would require the involvement of various sectors of public administration, as well as other social actors, not always guided by convergent agendas and interests (Veiga & Bronzo, 2014, p. 599).

Additionally, according to Veiga and Bronzo (2014), new governance structures associated with intersectoral articulation strategies among the various actors involved are necessary for governments to achieve higher levels of effectiveness.

This discussion is fundamental, since intersectoriality finds difficulties in its implementation, called by Brugué (2010) as fundamental reasons (those that refer to sociocultural aspects that emphasize individualism and competition) and surface reasons (lack of capacity and tools to carry out the work together). Therefore, the author suggests that the government work relationally so that the attitudes are shared among the multiple actors involved in order to allow a continuous articulation among them and to obtain some consensus, for example in the case of the goals and objectives; in the elaboration of diagnostics; and with regard to budgets and information systems.

According to Bichir, Oliveira, and Canato (2015), Fernandes, Castro, and Maron (2013), Ruzzi (2016) and Souza (2015), it is important to consider that the establishment of sectoral policy networks can also facilitate the operationalization of intersectoriality, by proposing governmental initiatives that contemplate a synthesis between knowledge, experiences and ways of seeing public policies. Veiga and Bronzo (2014) also discuss the articulation between different sectors, and consider that there would be a high density intersectoriality when organizational arrangements are capable of changing the dynamics, institutional processes, design and contents of sectoral policies.

An important observation at this point is that, given the context described, the political environment must be seriously considered, since it may or may not make these intersectoral articulations feasible. As Cunill-Grau (2005), Ruzzi (2016), and Veiga and Bronzo (2014) warn, only public agents with mandates have the legitimacy to induce or not, according to their interests and the context, the participation and effective involvement of actors and relevant sectors in an intersectoral perspective.

In any case, Costa and Bronzo (2012) warn that if decisions and attitudes are taken towards intersectoral articulation, then a centrality will be needed in management, that is, coordination, which will be more difficult depending on the number of actors involved and the level of heterogeneity between them. Thus, a great challenge would be to find effective ways to bring together institutions with different objectives, dynamics and organizational cultures.

In order to illustrate the complexity of this aspect, Costa and Bronzo (2012) argue that social programs aimed at publics in risky situations, poverty and social vulnerability require or depend on the actions of multiple actors (e.g., governmental organizations, NGOs with diverse profiles, councils, associations, philanthropic and religious entities etc.), which present different views on the problem and the means of confronting it. Thus, the governance of intersectoral policy would have the important mission of seeking to accommodate the interests, levels of commitment, resources, incentives, etc. of such actors in order to achieve greater levels of effectiveness.

The same authors conclude that, despite its importance, the introduction of an intersectoral perspective in models of management and organization is not an easy task, because it needs time to involve a change of mentality and in the organizational culture. In addition, they conclude that effective coordination mechanisms can reduce duplication and overlap of tasks, as well as reduce inconsistencies in activities (Costa and Bronzo, 2012). Veiga and Bronzo (2014, p. 600) corroborate this argument by stating that “intersectoriality would imply organizational and management changes, changes in the conceptions of professionals, in the organizational culture of different sectors and in the allocation of financial, technical and human resources, among others”.

This brief discussion therefore demonstrates that the issue of intersectoriality involves a number of relevant aspects that require a strong improvement of the management model so that they can be implemented successfully. In fact, as stated by Bichir, Oliveira, and Canato (2015) and Ruzzi (2016), it is essential to investigate the factors, instruments and relationships that make policy effectiveness broadened through intersectoriality as a means of management.

It is also important to analyze these and other issues related to other concepts such as transversality. In this case, although it bears some resemblance to intersectoriality, transversality differs from it and acquires its own identity due to the substantive factor to which it is applied (Bichir, Oliveira, & Canato, 2015; Souza, 2015). Thus, according to Gallo (2007 apud Avelino & Santos, 2014, p. 11), transversality can be understood as

the mutual crossing of the fields of knowledge, which, through their peculiarities, interpenetrate, intermingle, mingle, without losing their own characteristic, which only grows amid this multiplicity. Uniqueness of knowledge and multiplicity of fields.

In this sense, transversality consists in the search for the integration of compartmentalized areas in the social policy sectors, i.e., it is an attempt to bring together and articulate various sectors, to stimulate the participation of the multiple actors involved, and to maintain relations of interdependence, reciprocity and collaboration among them (Avelino & Santos, 2014; Brugué, 2008; Quinhões & Fava, 2010; Souza, 2015).

According to Oliveira (2014, p. 22), “being transversal is not only articulating different secretariats, it is bringing a new way of thinking about management and allowing results to be achieved, understanding the multidimensionality of the problems involved in these issues”.

Furthermore, the issue of transversality is also important in the context of public policies, since, according to Brugué (2008), cross-cutting policies put different points of view in contact, generating what has been called collective intelligence, which contribute to better decision-making processes. In addition, the same author states that by stimulating interaction and collaboration between different actors and sectors, it allows a better use of resources and an increase in efficiency.

Finally, it is possible to argue that many of the considerations previously made regarding intersectoriality also have an adherence to the issue of transversality, since, when the channels in which its effects are manifested are identified, there will be a great challenge in organizing and coordinating the different actors involved in order to achieve higher levels of effectiveness in public policies (Avelino & Santos, 2014; Brugué, 2008; Quinhões & Fava, 2010; Souza, 2015).

2.2. THE POVERTY-GROWTH-INEQUALITY TRIANGLE

The so-called Poverty-Growth-Inequality Triangle assumes that poverty is associated with the fact that certain individuals do not have sufficient income and wealth to give them access to goods and services at levels considered adequate according to the current pattern of consumption in a society (Assis, Medeiros, & Nogueira, 2017; Bourguignon, 2003, 2004; Nogueira & Forte, 2016).

Additionally, this theoretical framework considers that poverty reduction is directly linked to economic growth and to the improvement of income distribution, and thus, public policies should be designed and implemented within a development strategy in order to stimulate these effects (Assis, Medeiros, & Nogueira, 2017; Bourguignon, 2003, 2004; Nogueira & Forte, 2016).

Hence, it can be considered that the referred triangle contemplates two basic hypotheses:

• H₁ ^B: There is a negative relationship between economic growth and poverty.

• H₂ ^B: There is a positive relationship between income inequality and poverty.

This discussion can be represented graphically by Figure 1.

Figure 1
The poverty-growth-inequality triangle

J. L. Oliveira (2013), for example, consider that a successful policy to combat poverty must have as one of its fundamental aspects the integration of programs and actions. And, this would be due precisely to the possibility of taking advantage of intersectoral effects in order to increase its effectiveness. So, in practice, considering this triangle, this integrative view would be based on the search for a combination of distributive and growth policies, considering the specific characteristics of a given locality, so that satisfactory results can be achieved given the existing resources.

It should also be considered that the Poverty-Growth-Inequality Triangle, while not explicitly considering all the dimensions that affect poverty, has the potential to affect other important outcomes through intersectoral and transversal effects. An empirical illustration of this is done using data referring to Ceara’s municipalities in the year 2010. In this case, correlations between the proportion of poor people or the poverty rate (POVR), which considers the participation of the population with per capita household income equal to or below BRL 255.00 per month (in Reais of August 2010), and other selected indicators are presented in Table 1.

Table 1
Correlations between the poverty rate (POVR) and other selected indicators, calculated from municipal data - Ceará, 2010

INDICATORS	POVR
APCI	-0.877**
GINI	0.323**
HDI-M	-0.851**
LIFE_EXP	-0.435**
TOT_FERT	0.646**
ILLITR_15	0.748**
P_GARB	-0.357**
P_ELECTR	-0.472**
WAT_SEW	0.398**

• Source: Elaborated by the authors.Notes: * Significant at 5% level. ** Significant at 1% level.

Based on the Table 1, it can be seen that, in general, the poverty rate is negatively correlated with average per capita income (APCI) and positively with the Gini Index (GINI), which would be compatible with what was proposed by Bourguignon (2003, 2004). These would be precisely the intersectoral effects proposed in this case.

In addition, considering the transversal effects, it is shown that the municipalities with the highest values for the Municipal Human Development Index (HDI-M), for life expectancy at birth (LIFE_EXP), for the percentage of the population in households with garbage collection (P_GARB), and for the percentage of the population in households with electricity (P_ELECTR) tend to have a lower poverty rate, while the municipalities with the highest values for the total fertility rate (TOT_FERT), for the illiteracy rate of the population aged 15 years or over (ILLITR_15), and for the percentage of people in households with inadequate water supply and sanitary sewage (WAT_SEW) tend to show higher values for the considered rate.

It is worth noting that this information illustrates that, despite the limitations listed in the literature of using monetary measures of poverty, they tend to demonstrate significant relationships with other indicators that express the quality of life of a population, although, in some cases, the magnitudes of the correlations found were not particularly high, for example in the cases of GINI, LIFE_EXP, P_GARB, P_ELECTR and WAT_SEW. This is particularly important because relatively low or moderate correlations in this context may indicate that poverty reduction policies may have generated reduced intersectoral and transversal impacts due to the poor integration of initiatives.

2.3. THE ATTRACTIVENESS OF A LOCATION MEASURED BY POPULATION GROWTH

Recent population growth has been especially due to migration, since vegetative growth has been declining considerably in recent years. Thus, this variable would be a good proxy for attractiveness, since the population is attracted basically to places where there are relatively better living conditions and more opportunities to have a decent life (Campos & Fusco, 2009).

Therefore, what would be the factors that can impact the attractiveness of a specific locality? Campos and Fusco (2009) considered some key variables: economic growth, rate of urbanization and population density. According to these authors, these variables are related to population growth (attractiveness) according to the following hypotheses:

• H₁ ^CF: There is a positive relationship between economic growth and population growth (attractiveness).

• H_2a ^CF: There is a positive relationship between the rate of urbanization and population growth (attractiveness).

• H_2b ^CF: There is a positive relationship between population density and population growth (attractiveness).

Graphically, these arguments are summarized by Figure 2.

Figure 2
Factors determining the attractiveness of a locality

This relationship between economic growth and population attractiveness seems to be very intuitive, since greater employment opportunities and the possibility of obtaining higher wages in more dynamic locations are certainly factors that attracts new residents. More specifically, in the context of a globalized economy, cities or metropolitan areas that are more involved in the process tend to be more attractive (M. L. P. M. Costa, 2010; Campos & Fusco, 2009; Polèse, 1998).

Regarding the other factors, the literature indicates that both urbanization and density are relevant variables for attractiveness, since they indirectly synthesize factors that generate this attraction. Thus, better urban conditions, agglomeration economies, greater market density and larger scale, which favors the provision of public services, tend to increase the attractiveness of the place (Campos & Fusco, 2009; M. L. P. M. Costa, 2010; P. M. Jannuzzi & N. Jannuzzi, 2002; C. N. Medeiros, Oliveira, Menezes, & Rodrigues, 2014; Nogueira & Lopes, 2008; Polèse, 1998; Rocha, 1998).

On the other hand, special consideration should be given to the fact that very high densities may cause the previously existing benefits to be offset by the negative effects of so-called agglomeration diseconomies. More specifically, with high densities, a number of problems can arise, such as congestion in public services and transport, the sharp rise in prices of real estate and services, an increase in crime, etc., which can become factors that discourage migrations to these localities (Campos & Fusco, 2009; M. L. P. M. Costa, 2010; P. M. Jannuzzi & N. Jannuzzi, 2002; Nogueira & Lopes, 2008; Polèse, 1998).

Moreover, in this case, intersectoriality would be between policies that seek to stimulate economic growth and those that seek to promote the requalification of spaces, which are very necessary in places with greater participation of urban population and with high population densities. More specifically, there can be important synergies between the growth of the city’s economy, the setting up of new businesses and the stimulation of higher productivity, and the efforts to make these urban centers more dynamic and offer a better quality of life to its inhabitants. The integration of these policies would have the potential to increase the attractiveness of these places.

3. A PROPOSAL TO INTEGRATE THE POVERTY AND ATTRACTIVENESS APPROACHES

In an attempt to integrate the two approaches presented before, it is first necessary to consider that there is no evidence or theoretical justification underlying a direct relationship between the evolution of the poverty rate and attractiveness (Rocha, 1998). On the other hand, there are common aspects between the determinants of these variables that must be considered.

In general, considering the integration of these approaches, it is argued that demographic density and urbanization should enter as controls of the model that describes the evolution of poverty. In terms of the expected signs, if on the one hand the aspects that generate the attractiveness associated with the higher levels of urbanization and the greater demographic density, mentioned before, tend to increase the attractiveness of the place, attracting poor people from other localities or from rural areas, it can be argued that these factors also favor poverty reduction, and therefore, it is expected that negative relations in these cases (Campos & Fusco, 2009; P. M. Jannuzzi & N. Jannuzzi, 2002; C. N. Medeiros et al., 2014; Nadalin & Igliori, 2015; Nogueira & Lopes, 2008; Ravallion, Chen, & Sangraula, 2007; Rocha, 1998; Walton & Araújo, 2003).

Detailing this discussion specifically with regard to poverty and urbanization, the literature contemplates two main strands in this respect. On the one hand, urbanization can be a factor that promotes the concentration of the poor in cities, especially in the peripheries of large urban centers. On the other hand, it is regarded as a positive force to promote development, especially when economies migrate from rural to higher value-added activities, consequently increasing the possibility of generating higher incomes for workers (P. M. Jannuzzi & N. Jannuzzi, 2002; Nadalin & Igliori, 2015; Ravallion et al., 2007; Rocha, 1998; Walton & Araújo, 2003).

In this sense, Walton and Araújo (2003, p. 63), for example, argue that

In the long run, rural-urban migration will be an important source of poverty reduction. Urban work opportunities, better education in rural areas and better communication infrastructure will jointly support this migration process. (...) In addition, it is often observed that rural areas continue to show the highest levels of poverty and the worst social indicators.

Ravallion, Chen, and Sangraula (2007), with a sample of more than 200 household surveys carried out in 90 countries in 1993 and 2002, tend to solve this controversy, since they show that, in general, over time, as the participation of the urban population increases, the poverty rate (total, urban and rural) tends to decline, particularly due to the considerable reduction of rural poverty. So, despite several problems identified in areas with a rapid urbanization process, the experiences analyzed suggest that it has a positive role in reducing the poverty rate (although the absolute number of poor can be high in urban centers).

Another control that can be considered is the proximity of the locality with a dynamic center. More specifically, as this center tends to concentrate a significant part of the GDP, to be the largest consumer market, and to have the best physical infrastructure, with a considerable network of universities, training centers, health services of higher complexity, financial services, etc., it is argued that these factors are capable of generating significant externalities for other municipalities and, the closer they are, the more they can benefit (Barreto & Menezes, 2014; Nogueira & Lopes, 2008). Thus, one could argue that the smaller distance in relation to the dynamic regional center can both raise the attractiveness and help reduce the proportion of the poor due to these externalities.

Therefore the integrative proposal can be graphically synthesized according to Figure 3.

Figure 3
Proposed integration of the poverty and attractiveness approaches

Next, the case of Ceara (Brazil) is discussed and a methodology is proposed to estimate these relationships in the context of its municipalities.

4. RECENT ADVANCES IN PUBLIC MANAGEMENT AND POLICY INTEGRATION IN CEARA

Due to the limitations of the Bureaucratic Administration, in recent years the State of Ceara (Brazil) has sought to modernize its management in order to make it more dynamic and innovative and to better meet the needs of citizens, seeking to obtain long-term results (Holanda & Rosa, 2004; Macroplan, 2016; Nogueira & Pontes, 2013).

It is then possible to make a brief outline of Ceara’s case. In fact, since 2003, the State has sought to consolidate a public management model, which aims at incorporating elements contained mainly in the last two paradigms previously mentioned, especially New Public Management, but with a strong emphasis on the search for long-term results, willing to enhance popular participation and the integration of public policies in order to take advantage of their intersectoral and transversal effects (Macroplan, 2016; Medeiros, 2010; Medeiros, Rosa & Nogueira, 2008; Nogueira & Pontes, 2013, 2015).

With respect to intersectorality and transversality, one could argue that there was only a more evident movement to consider them seriously after the preparation of the Pluriannual Plan 2012-2015. It is worth noting that, in relation to previous pluriannual plans, this plan underwent important methodological changes based on the suggestions made by the Federal Government and adjusted to the reality of state planning and the execution of its programs and actions. This new plan also showed more adherence to the public management model aimed at by the State, whose basic characteristics were listed above (Nogueira & Pontes, 2013, 2015).

More specifically, it is possible to consider two specific contexts within the scope of the Pluriannual Plan 2012-2015 in which it helped to promote actions that may generate intersectoral and transversal effects.

First, there is the participatory process of the plan, since during the elaboration workshops there was interaction between representatives of the various departments and organs of state public administration, which allowed a greater integration between the actions of the sectors and a greater intersectoriality and complementarity of actions (without cross-cutting effects), since participants could exchange ideas and information to increase the effectiveness of proposals (Nogueira & Pontes, 2013, 2015).

The second instance was the introduction of multisectoral programs (including cross-cutting effects) articulated by the Governor’s Office into specific areas such as youth, women, ethnic and racial equality, drug control, elderly people, people with disabilities and human rights, totaling seven programs. However, analyses show that there was a tendency for each actor to play his part in an autonomous and fragmented way, which tended to limit the expected intersectoral and transversal effects and, consequently, the levels of effectiveness of the government initiatives (Nogueira & Pontes, 2013, 2015).

Another important advance came with the participative methodology of building the Pluriannual Plan 2016-2019, which was supported by civil society and divided the State into 14 planning regions aimed at guiding governmental action to regional needs and promoting territorial development, in line with what had been proposed in the government plan. This plan sought to advance in the definition of initiatives and actions in order to further promote the intersectoriality and transversality of policies. However, it is still possible to argue that there is still a lot of room to move forward (Macroplan, 2016), which makes Ceara’s case important to analyze.

5. Methodology

5.1. database

The database used in this paper is described in Box 1.

Box 1
Variables considered, their definitions and sources of the data

5.2. Estimation method

According to the integration proposal of the poverty and attractiveness approaches, two basic equations can be considered, namely:

Poverty:

${\mathrm{D}\mathrm{L}\mathrm{P}\mathrm{P}\mathrm{O}\mathrm{B}}_i=\mathrm{C}\left(1\right)+\mathrm{C}\left(2\right).{\mathrm{D}\mathrm{L}\mathrm{R}\mathrm{D}\mathrm{P}\mathrm{C}}_i+\mathrm{C}\left(3\right).{\mathrm{D}\mathrm{L}\mathrm{G}\mathrm{I}\mathrm{N}\mathrm{I}}_i+\mathrm{C}\left(4\right).{\mathrm{L}\mathrm{D}\mathrm{E}\mathrm{N}\mathrm{S}}_i+\mathrm{C}\left(5\right).{\mathrm{U}\mathrm{R}\mathrm{B}}_i+\mathrm{C}\left(6\right).{\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{X}}_i+{\mathrm{u}}_i$

Attractiveness:

${\mathrm{D}\mathrm{L}\mathrm{P}\mathrm{O}\mathrm{P}}_i=\mathrm{C}\left(7\right)+\mathrm{C}\left(8\right).{\mathrm{D}\mathrm{L}\mathrm{P}\mathrm{I}\mathrm{B}}_i+\mathrm{C}\left(9\right).{\mathrm{L}\mathrm{D}\mathrm{E}\mathrm{N}\mathrm{S}}_i+\mathrm{C}\left(10\right).{\mathrm{U}\mathrm{R}\mathrm{B}}_i+\mathrm{C}\left(11\right).{\mathrm{P}\mathrm{R}\mathrm{O}\mathrm{X}}_i+{\mathrm{v}}_i$

According to the theoretical background and the subsequent discussion summarized in Figure 3, C(3), C(8), C(9), C(10) and C(11) are expected to be positive whereas C(2), C(4), C(5) and C(6) should be negative.

Some specific aspects regarding the equations deserve comment. Firstly, in the poverty equation, it is important to explain that it was chosen a specification that translates as directly as possible what was represented in Figure 1. Then the so-called “Bourguignon’s standard model” (Bourguignon, 2003) was used as in the study done by Annegues et al. (2015), for example.

Another important point is that demographic density was inserted in logarithm in both equations. This specification comes from the perception that agglomeration economies tend to grow non-linearly with density because, as it rises, agglomeration diseconomies may begin to interfere. This effect was previously perceived by other authors such as Nogueira and Lopes (2008).

Additionally, in regard to economic growth, it is worth explaining that it was measured by the variation in per capita household income in the case of poverty and by the approximate variation of GDP in the case of attractiveness. This is basically due to the dependent variables considered. In the case of poverty, POVR is already relative to the size of the population, which is not the case of attractiveness, where the dependent variable is the population change itself.

Finally, in the models proposed above, the terms u_i and v_i represent, respectively, their error (disturbance) terms. They capture the effect of all unobserved factors that impact the dependent variables, such as particular characteristics of each municipality and other external factors that affect the local economies.

Since the explanatory variables of each model are not exactly the same, if the estimated residuals of the two equations (estimated separately), u* and v* are significantly correlated, it makes more sense for the two equations to be estimated simultaneously by the seemingly unrelated regression (SUR) method (Hill, Griffiths, & Lim, 2011).

According to Hill, Griffiths, and Lim (2011), it is then possible to carry out a test considering the following hypotheses: H₀: σ_u,v = 0 e H₁: σ_u,v ≠ 0, where σ_u,v represents the population covariance between u and v. The test statistic would be given by LM = n.r² _u*,v*, where n represents the number of observations and r² _u*,v* the squared sample correlation coefficient between u* and v*. The authors indicate that if the null hypothesis is true, then LM ~ χ² _(gl), so that the number of degrees of freedom is given by M.(M-1)/2 in large samples, where M is the number of equations. Thus, if the null hypothesis is rejected by the test, when LM is greater than the critical value of the chi-square distribution, it is suggested the joint estimation of the equations of the model by the seemingly unrelated regression method.

It is important to consider that a significant correlation between these residuals is expected because, even though there is no theoretically defined relationship between the models’ dependent variables, both processes can be affected by the same unconsidered factors, i.e., by the idiosyncratic characteristics of each municipality.

6. Results and discussion

The proposed models were first estimated independently by ordinary least squares. From these estimates the residuals of each equation were then calculated, obtaining a correlation between them equal to 0.3483, significant at 1% (t_obs = 5,01 and p-value = 0,000). Considering the test explained above, one should find that:

$\mathrm{L}\mathrm{M}=\mathrm{n}.{{\mathrm{r}}^2}_{u^{*},v^{*}}\mathrm{}=\mathrm{184.0,3483}=\mathrm{64,0872}>\mathrm{3,84}={\mathrm{\chi }}^2$ (1)

Therefore, the null hypothesis that σ_u,v = 0 should be rejected and the equations must be estimated together. Thus, Table 2 presents the estimates obtained through the seemingly unrelated regression method.

TabLe 2
Models’ estimation results

equation	constants and variables	CoefFicients	Estimates	t statistic	P-value
1	CONSTANT	C(1)	0.078250	2.886030	0.0041
	DLAPCI	C(2)	-0.174280	-6.013126	0.0000
	DLGINI	C(3)	0.200604	4.267883	0.0000
	LDENS	C(4)	-0.021408	-4.024798	0.0001
	URB	C(5)	-0.001691	-5.419931	0.0000
	PROX	C(6)	-0.000389	-2.372401	0.0182
2	CONSTANT	C(7)	-0.239651	-8.535216	0.0000
	DLPIB	C(8)	0.256693	8.505949	0.0000
	LDENS	C(9)	0.025239	3.776756	0.0002
	URB	C(10)	0.001037	2.673881	0.0078
	PROX	C(11)	0.000577	2.769777	0.0059
Goodness-of-fit	Equation 1	R2	0.447707	Adjusted R2	0.432193
	Equation 2	R2	0.474984	Adjusted R2	0.463252

• Source: Elaborated by the authors. Notes: (1) Number of observations: 184. (2) Total system (balanced) observations 368. (3) Estimation method: seemingly unrelated regression (SUR).

As can be seen, the models were reasonably was well fitted with the data according to the values of R-squared and adjusted R-squared, and all estimated coefficients can be considered statistically different from zero according to the statistics t presented.

More specifically, in terms of the estimated coefficients, all obtained the same expected signals according to the integrative proposal of the contemplated theoretical frameworks.

Thus, according to Bourguignon (2003, 2004), economic growth and improvements in income distribution tended to reduce the poverty rate in Ceara’s municipalities during the period analyzed. According to Barreto (2005), the process of economic growth is fundamental for reducing poverty and has its potential impact on poverty enhanced if it is accompanied by redistributive policies. This view is supported by other authors, such as Marinho and Araújo (2012), who argue that in places where inequality is very high, policies aimed at reducing it tend to have a direct impact on poverty reduction in the short run and indirect in the medium and long run by enabling growth policies to deliver better results.

Economic growth also favored local attractiveness because when the economic activities of a given locality present a positive dynamic over time, with growth and innovation, new opportunities arise making that locality more attractive with better chances to fix current residents and their descendants, and also with greater potential to attract migrants (M. L. P. M. Costa, 2010; Campos & Fusco, 2009; Polèse, 1998).

The results show that the attractiveness was also increased by the improvement of urban conditions, which are represented in the model by the variables rate of urbanization and demographic density, as proposed by Campos and Fusco (2009). More specifically, as indicated before, when a locality becomes more urbanized, there is a tendency to improve the living conditions of the place through investments in infrastructure, with more services and facilities, such as water supply, sewage, garbage collection, public transportation, leisure opportunities, etc. On the other hand, the greater population density allows for a greater scale in the provision of public services and also allows the emergence of important agglomeration economies which makes the locality more attractive (Campos & Fusco, 2009; P. M. Jannuzzi & N. Jannuzzi, 2002; C. N. Medeiros et al., 2014; Nadalin & Igliori, 2015; Nogueira & Lopes, 2008; Ravallion et al., 2007; Rocha, 1998; Walton & Araújo, 2003).

In addition to these effects, the impacts resulting from the increase in urbanization and the greater population concentration on poverty were also measured. In view of the theoretical controversy about the direction of these impacts, the results showed that, in the case of Ceara’s municipalities in the period 2000-2010, the improvement of urban conditions, although also raising the potential to attract people in situation of poverty from other localities, generated the conditions for them to improve their living conditions, as advocated by Ravallion, Chen, and Sangraula (2007); Nogueira and Lopes (2008); Polèse (1998); and, Walton and Araújo (2003).

Finally, based on Barreto and Menezes (2014) and on Nogueira and Lopes (2008), the effect of the externalities generated by the proximity to a dynamic regional center was estimated. According to the estimates it was verified that the proximity to Fortaleza favored both the growth of the population and the reduction of poverty in Ceara’s municipalities during the period 2000-2010.

So, on the one hand, the results obtained show that different factors, elements of different policies, can concomitantly impact on the same result, indicating that intersectoriality is being captured. In addition, it confirms the perspective that variables that affect one dependent can also impact in another, configuring the transversal effect.

Now, in terms of the magnitudes of the estimated coefficients, it has been shown that the marginal effects of APCI and GINI are reasonable for the reduction of POVR, while the effect of GDP is strong for the increase in attractiveness. On the other hand, the effects of DENS, URB and PROX are relatively weak in both equations. So the low magnitudes of some marginal effects may indicate that some intersectoral and transversal effects may still be relatively unimpressive, so that these policies need to be better integrated in order for those effects to be extended over time and increase the level of effectiveness of the interventions carried out.

In addition, it is important to note that more than half of the total variation of the dependent variables were not explained by the explanatory variables and controls of the models. Therefore, there must be other variables that can contribute to the explanation and that were not included and / or there are particular characteristics of the municipalities that affect the relations, but which were not identified by the proposed models.

7. concluding remarks

This paper started from the idea that in the current stage of evolution of the conduction of public policies, governments need to seriously consider intersectoriality and transversality in order to achieve more effectiveness and to improve the quality of life of the population in a sustainable way.

In general, when discussing the topic, it is proposed that the management system be adapted in an intersectoral perspective, considering the various elements that affect a specific result, or in a transversal perspective, indicating how initiatives may have effects on many aspects (Avelino & Santos, 2014; Bichir et al., 2016; Brugué, 2008; Fernandes et al., 2013; Quinhões & Fava, 2010; Ruzzi, 2016; Souza, 2015; Veiga & Bronzo, 2014). The main argument is that these adaptations are usually made on the basis of purely conceptual analyses, in which the intersectoral and transversal effects are not actually measured.

So the present paper sought to provide a different view on this issue. More specifically, it was argued that knowing the approaches related to each specific socioeconomic problem at the theoretical level is important so that the main variables could be determined. It is also necessary to make progress in identifying common aspects of various problems and how they are reflected in the desired results. In addition, effects should be measured in each case so that potentially more effective policies could be proposed and adjustments in the management system may be implemented.

From this perspective, two theoretical frameworks related to poverty and attractiveness were considered, with a proposal to integrate them to capture the intersectoral effects and, also, the transversalities between the policies that affect them.

The estimation of the two equations proposed when integrating the approaches suggests that even if the variables under analysis (change in the poverty rate and population growth) are not formally related, it is possible that explanatory variables of a model that are the object of policies with specific objectives have significant overlaps on the dependent variable of the other. Thus, for example, economic growth and the public policies that stimulate it, besides favoring the reduction of poverty levels, can also increase the attractiveness (population growth) of a municipality in Ceara. On the other hand, initiatives that stimulate the urbanization and the requalification of the spaces in a certain locality, enhance the attractiveness of this same place and, also, favor the reduction of its poverty rate.

A key point of the discussion concerns specifically the adjustment of the estimated models. In specific, it was found that they have reasonable explanatory power, but that there are still unconsidered factors that can help to explain the behavior of the dependent variables. This serves as an incentive for the theoretical improvement of the issues dealt with and bring to attention a very relevant aspect to this analysis: that the specificities of the municipalities should be considered when determining the intervention strategies in each locality. Hence, it is necessary to investigate how the characteristics of a locality and of its population can affect the effectiveness of the policies to be implemented.

This conclusion is corroborated by authors such as Chiarini (2008), Medeiros and Pinho Neto (2012), and Nogueira and Forte (2016), who consider that the spatial analysis related to the social well-being of a region helps to determine if there is a pattern in the its distribution or if it spreads randomly across the geographic space, making it necessary to map the phenomenon under study so that more effective development strategies and focused public actions can be proposed, improving program and project management, by adapting their initiatives to the realities faced.

In addition, although the coefficient signals were compatible with what was proposed at the theoretical level, the magnitudes of some marginal effects were relatively low, which may imply that the intersectorality and transversality between these policies should be addressed by management so that stronger effects may be achieved in the future.

In this context, it is important to emphasize that in addition to the relevant effort to map and measure the channels in which intersectorality and transversality manifest themselves in a particular socioeconomic problem, it is important to consider that for their effects to be increased the necessary adjustments in planning and management can be complex because integrating multi-actor policies may involve different perspectives of reality, objectives and interests which usually are difficult to coordinate. This highlights the role that regulation and incentive systems can play in harmonizing the different aspects that exist in order to widen intersectoral and cross-cutting effects.

In the specific case of Ceara’s municipalities, this set of adjustments in the direction of greater articulation and integration of actors, sectors and knowledge should be carried out in order to contemplate the policies adopted at the local level and also considering the policies and interventions carried out at the state and federal levels. Thus, the complexity in the implementation of intersectoral and transversal articulations increases greatly since in many cases it requires relevant adjustments in the existing management model and the articulation capacity of municipalities. This is particularly difficult in relatively poorer localities.

In this sense, there is an important role to be played by both the State Government and the Federal Government to facilitate the integration of policies and also to provide subsidies for municipal management to advance and be able to play a preponderant role in the transformation of their realities.

The issues discussed in this paper deserve further research. Therefore, as an indication for future studies, it is suggested a theoretical improvement of this discussion, as well as the study of other specific cases so that subsidies can be given so that governments and decision makers so they can propose truly transformative policies and initiatives in order to generate significant long-term results. It is also necessary to deepen the managerial consequences of the conclusions obtained.

REFERÊNCIAS

• Andrews, M. (2013). How do governments get great? (Faculty Research Working Paper RWP13-020). Cambridge, MA: Harvard. Recuperado dehttps://research.hks.harvard.edu/publications/getFile.aspx?Id=944
  » https://research.hks.harvard.edu/publications/getFile.aspx?Id=944
• Angelis, C. T. (2015, julho/dezembro). A emergência da reforma do Estado brasileiro: a governança compartilhada e o modelo do novo serviço público. Planejamento e Políticas Públicas, 45, 13-46.
• Annegues, A. C., Souza, W. P. S. F., Figueiredo, E., & Lima, F. S. (2015). Elasticidade da pobreza: aplicação de uma nova abordagem empírica para o Brasil. Planejamento e Políticas Públicas, 44, 145-166.
• Assis, D. N. C., Medeiros, C. N., & Nogueira, C. A. G. (2017, janeiro/junho). Extrema pobreza infantil, crescimento e distribuição de renda. Planejamento e Políticas Públicas, 48, 175-210.
• Avelino, D. P., & Santos, J. C. (2014, março). O desafio do Fórum Interconselhos na consolidação das estruturas participativas de segundo nível. In Anais do 7o Congresso Consad de Gestão Pública Brasília, DF.
• Barreto, F. A. F. D. (2005). Crescimento econômico, pobreza e desigualdade de renda: o que sabemos sobre eles? (Ensaio sobre Pobreza n. 1). Fortaleza, CE: Laboratório de Estudos da Pobreza.
• Barreto, F. A. F. D., & Menezes, A. S. B. (Org.). (2014). Desenvolvimento econômico do Ceará: evidências recentes e reflexões Fortaleza, CE: Instituto de Pesquisa e Estratégia Econômica do Ceará.
• Bichir, R., Oliveira, M. C., & Canato, P. (2016). Para além da transferência de renda? Limites e possibilidades na articulação intersetorial de políticas sociais. Cadernos de Estudos: Desenvolvimento Social em Debate, 26, 81-102.
• Bourguignon, F. (2003). The growth elasticity of poverty reduction: explaining heterogeneity across countries and time periods. In T. S. Eicher; & S. J. Turnovsk(Eds.), Inequality and growth: theory and policy implications (pp. 3-26). Cambridge, MA: The MIT Press.
• Bourguignon, F. (2004). The poverty-growth-inequality triangle Washington, DC: The World Bank.
• Brugué, Q. (2008). Transversalidad: del concepto a la práctica, de las ideas a los resultados Recuperado dehttps://www.tarragona.cat/serveis-a-la-persona/serveis-socials/observatori-social-de-la-ciutat-de-tarragona/fitxers/altres/treballem-en-xarxa/transversalitat-del-concepte-a-la-practica
  » https://www.tarragona.cat/serveis-a-la-persona/serveis-socials/observatori-social-de-la-ciutat-de-tarragona/fitxers/altres/treballem-en-xarxa/transversalitat-del-concepte-a-la-practica
• Brugué, Q. (2010). Transversalidad en los proyectos locales: de la teoría a la práctica Gijón: Trea.
• Campos, L. H. R., & Fusco, W. (2009). Municípios nordestinos e crescimento populacional: correspondência entre migração e desenvolvimento. Revista Interdisciplinar da Mobilidade Humana, 17(33), 79-100.
• Carneiro, R., & Menicucci, T. M. G. (2011). Gestão pública no século XXI: as reformas pendentes (Texto para Discussão, n. 1686). Brasília, DF: Instituto de Pesquisa Econômica Aplicada. Recuperado de http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_1686.pdf
  » http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_1686.pdf
• Catelli, A., & Santos, E. S. (2004). Mensurando a criação de valor na gestão pública. Revista de Administração Pública, 38(3), 423-449.
• Chiarini, T. (2008). Análise espacial da pobreza municipal no Ceará, 1991-2000. Revista de Economia, 34(2), 69-93.
• Costa, B. L. D., & Bronzo, C. (2012). Intersetorialidade no enfrentamento da pobreza: o papel da implementação e da gestão. In C. A. P. Faria(Org.), Implementação de políticas públicas: teoria e prática (pp. 50-81). Belo Horizonte, MG: Ed. PUC Minas.
• Costa, M. L. P. M. (2010, novembro/dezembro). A urbanização e suas novas conotações. Rebatimentos sobre o processo de reestruturação do território. In Anais do1oEncontro Nacional da Associação Nacional de Pesquisa e Pós-Graduação em Arquitetura e Urbanismo Rio de Janeiro, RJ.
• Cunill-Grau, N. (2005, octubre). La intersectorialidad en el gobierno y gestión de la política social. In Anais do 10o Congresso Internacional del CLAD Santiago, Chile.
• Dias, T., & Cario, S. A. F. (2012, novembro). Governança pública: um ensaio da gênese do movimento que coloca o Estado voltado para a perspectiva paraeconômica de desenvolvimento. In Anais do 5o Encontro de Administração Pública e Governo Salvador, BA.
• Fernandes, A. T., Castro, C., & Maron, J. (2013, abril). Desafios para implementação de políticas públicas: intersetorialidade e regionalização. In Anais do 6o Congresso Consad de Gestão Pública Brasília, DF.
• Hill, R. C., Griffiths, W. E., & Lim, G. C. (2011). Principles of econometrics (4a ed.). Hoboken, NJ: John Wiley & Sons.
• Holanda, M. C., & Rosa, A. L. T. (2004). Gestão pública por resultados na perspectiva do Estado do Ceará (Nota Técnica n. 11). Fortaleza, CE: Instituto de Pesquisa e Estratégia Econômica do Ceará.
• Instituto de Pesquisa e Estratégia Econômica do Ceará. (2013). Índice de Desenvolvimento Municipal (IDM): Ceará - 2010 Fortaleza, CE: Autor.
• Jannuzzi, P. M., & Jannuzzi, N. (2002). Saldos migratórios e atratividade residencial. Atratividade residencial da cidade de São Paulo: 1980-2000. Revista Brasileira de Estudos Urbanos e Regionais, 4(1-2), 107-127.
• Lacombe, F. (2009). Teoria geral da administração São Paulo, SP: Saraiva.
• Macroplan. (2016). Levantamento de práticas de gestão pública para resultados: Benchmarking GpR Fortaleza, CE: Autor.
• Marinho, E., & Araújo, J. (2012). Crescimento econômico e concentração de renda: seus efeitos na pobreza no Brasil(Working Paper n. 24). Niterói, RJ: Associação Nacional dos Centros de Pós-Graduação em Economia.
• Medeiros, A. C. C. (2010, março). GPR no Ceará: prática de gestão em busca de resultados. In 3o Congresso Consad de Gestão Pública Brasília, DF.
• Medeiros, A. C. C., Rosa, A. L. T., & Nogueira, C. A. G. (2008, novembro). Gestão pública por resultados: uma análise comparativa entre os modelos do Ceará e do Canadá. In Anais do 4o Encontro Economia do Ceará em Debate Fortaleza, CE.
• Medeiros, C. N., Oliveira, V. H., Menezes, A. S. B., & Rodrigues, L. O. (2014). O padrão de crescimento demográfico no estado do Ceará. In F. A. F. D. Barreto , & A. S. B. Menezes (Orgs.), Desenvolvimento econômico do Ceará: evidências recentes e reflexões (pp. 11-44). Fortaleza, CE: Instituto de Pesquisa e Estratégia Econômica do Ceará.
• Medeiros, C. N., & Pinho, V. R. Neto.,(2012). Mapeamento da extrema pobreza no Estado do Ceará. In F. A. F. D. Barreto, A. S. B. Menezes, E. L. S. F. J. Sousa, & L. C. Gonçalves (Orgs.), Economia do Ceará em debate 2011 (pp. 167-190). Fortaleza, CE: Instituto de Pesquisa e Estratégia Econômica do Ceará.
• Moreira, R. M. C. (2016). O Brasil e o novo paradigma da administração pública Porto Alegre, RS: Associação dos Juízes Federais do Rio Grande do Sul.
• Nadalin, V., & Igliori, D. (2015). Espraiamento urbano e periferização da pobreza na região metropolitana de São Paulo: evidências empíricas. EURE, 41(124), 91-111.
• Nogueira, C. A. G., & Forte, S. H. A. C. (2016, novembro). Desafios no direcionamento e na priorização das intervenções das políticas de combate à pobreza nos municípios cearenses. In Anais do 7o Encontro de Administração Pública e Governança São Paulo, SP.
• Nogueira, C. A. G., & Lopes, D. A. F. (2008, março). Employment growth in Ceará: a shift-share analysis. In 8o RSAI World Congress São Paulo, SP.
• Nogueira, C. A. G., & Pontes, P. A. (2013). Planejamento e gestão governamental na esfera estadual: uma análise comparativa dos processos, conteúdos e sistemas de acompanhamento dos PPAs - Estado do Ceará (Relatório de Pesquisa). Brasília, DF: Instituto de Pesquisa Econômica Aplicada.
• Nogueira, C. A. G., & Pontes, P. A. (2015). Planejamento e gestão governamental na esfera estadual: a experiência do Ceará. In J. C. Cardoso Jr J. C. Santos, R. R. Pires(Orgs.), PPA 2012-2015: a experiência subnacional de planejamento no Brasil (pp. 123-151). Brasília, DF: Instituto de Pesquisa Econômica Aplicada.
• Oliveira, J. L., Miro, V. H., & Barreto, F. A. F. D. (2013). Princípios para uma estratégia eficiente de combate à pobreza no estado do Ceará (Nota Técnica n. 53). Fortaleza, CE: Instituto de Pesquisa e Estratégia Econômica do Ceará.
• Oliveira, M. C.(2014). Transversalidade em políticas públicas para a juventude: a experiência de trabalho de campo no Plug Minas. Revista NAU Social, 5(8), 21-28.
• Paradela, V., & Costa, M. M. (2013). Modelagem de organizações públicas Rio de Janeiro, RJ: Ed. FGV.
• Polèse, M. (1998). Economia urbana e regional: lógica espacial das transformações econômicas Coimbra, Portugal: Associação Portuguesa para o Desenvolvimento Regional.
• Programa das Nações Unidas para o Desenvolvimento, Instituto de Pesquisa Econômica Aplicada, & Fundação João Pinheiro. (2013). Atlas do Desenvolvimento Humano no Brasil Recuperado de http://www.atlasbrasil.org.br/2013/
  » http://www.atlasbrasil.org.br/2013/
• Quinhões, T. A., & Fava, V. M. D. (2010). Intersetorialidade e transversalidade: a estratégia dos programas complementares do Bolsa Família. Revista do Serviço Público, 61(1), 67-96.
• Ravallion, M., Chen, S., & Sangraula, P. (2007). The urbanization of global poverty. World Bank Research Digest, 1(4), 1-8.
• RochaS. (1998, junho). Pobreza no Brasil. Principais tendências da espacialização. Economia e Sociedade, 1998(10), 193-211.
• Ruzzi, M. C. M. (2016, novembro). Intersetorialidade na implementação de políticas sociais. In Anais do 7o Encontro de Administração Pública e Governança São Paulo, SP.
• Souza, W. F. (2015, julho). Intersetorialidade e transversalidade em políticas públicas para as juventudes no Brasil. In Anais do 8o Congresso Latino-Americano de Ciência Política Lima, Peru.
• Veiga, L., & Bronzo, C. (2014). Estratégias intersetoriais de gestão municipal de serviços de proteção social: a experiência de Belo Horizonte. Revista de Administração Pública, 48(3), 595-620.
• Walton, M., & Araújo, A.(Org.). (2003). Brasil: estratégias de redução da pobreza no Ceará Fortaleza, CE: Banco Mundial.

• [Translated version] Note: All quotes in English translated by this article’s translator

Publication Dates

• Publication in this collection
  Jan-Feb 2019

History

• Received
  10 Apr 2017
• Accepted
  07 May 2018