The conditions for multi-level governance

The conditions for multi-level governance

Implementation, politics and cooperation in Swedish active labor market policy

Martin Lundin

DISSERTATION SERIES 2007:1 Presented at the Department of Government, Uppsala University

The Institute for Labour Market Policy Evaluation (IFAU) is a research insti-tute under the Swedish Ministry of Employment, situated in Uppsala. IFAU’s objective is to promote, support and carry out scientific evaluations. The assignment includes: the effects of labour market policies, studies of the func-tioning of the labour market, the labour market effects of educational policies and the labour market effects of social insurance policies. IFAU shall also dis-seminate its results so that they become accessible to different interested parties in Sweden and abroad. IFAU also provides funding for research projects within its areas of interest. The deadline for applications is October 1 each year. Since the researchers at IFAU are mainly economists, researchers from other disciplines are encouraged to apply for funding. IFAU is run by a Director-General. The institute has a scientific council, con-sisting of a chairman, the Director-General and five other members. Among other things, the scientific council proposes a decision for the allocation of research grants. A reference group including representatives for employer organizations and trade unions, as well as the ministries and authorities con-cerned is also connected to the institute. Postal address: P O Box 513, 751 20 Uppsala Visiting address: Kyrkogårdsgatan 6, Uppsala Phone: +46 18 471 70 70 Fax: +46 18 471 70 71 [email protected] www.ifau.se This doctoral dissertation was defended for the degree of Doctor in Philosophy at the Department of Government, Uppsala University, June 8, 2007. The third essay of this thesis contains a revised version of research previously published by IFAU as Working paper 2005:2.

ISSN 1651-4149

MARTIN LUNDIN

The Conditions for Multi-Level Governance

Implementation, Politics, and Cooperation

in Swedish Active Labor Market Policy

List of papers

This dissertation consists of the following essays:

I. Lundin, Martin. 2007. “Political Partisanship and Entity Size: When Parties Matter for Public Policy.” Manuscript, Department of Government, Uppsala University.

II. Lundin, Martin. 2007. “Explaining Cooperation: How Resource Interdependence, Goal Congruence, and Trust Affect Joint Actions in Policy Implementation.” A slightly different version of this article has been accepted for publication by the Journal of Public Administration Research and Theory and will appear in a forth-coming issue.

III. Lundin, Martin. 2007. “When Does Cooperation Improve Public Policy Implementation?” Manuscript, Department of Government, Uppsala University.

Contents

Acknowledgments ......................................................................................................7

The Conditions for Multi-Level Governance..............................................................9

Political Partisanship and Entity Size: When Parties Matter for Public Policy .....................................................................49

Explaining Cooperation: How Resource Interdependence, Goal Congruence, and Trust Affect Joint Actions in Policy Implementation.........................................75

When Does Cooperation Improve Public Policy Implementation? ..........................105

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Acknowledgments

A couple of months ago, I was about to get rid of some old binders. In one of them there were documents from my very first semester as a political science student. Among the documents was a short paper with the following title: “Implementation problems and the Swedish Active Labor Market Policy”. Evidently, I was the author. This was a surprising discovery since I did not remember that labor market policy had occupied my attention as an under-graduate student. I started to read the paper and recognized that the analysis—as most pieces of work by inexperienced students—was quite ordinary. One of the paper’s conclusions was that labor market policy in-volves coordination of authorities, which could be difficult. At the time when I formulated these unoriginal ideas, I could not dream that I would complete a dissertation on basically the same theme eleven years later.

I think this book includes more interesting findings than my early attempts. The progress is probably partly a consequence of my own hard work. But many are those who have been important for the completion of this dissertation. It is not possible to provide the complete list of contri-butors, so it has to be restricted to those who have influenced the project the most.

First and foremost, I owe my supervisors a sincere gratitude. With their sharp comments, PerOla Öberg and Jörgen Hermansson have helped me immensely during my years as a doctoral candidate. I recommend future postgraduate students to take advantage of their skills and enjoyable company.

The following readers provided constructive criticism and useful suggestions on the entire manuscript: Paula Blomqvist, Matz Dahlberg, Nils Hertting, Barry Holmström, and Sven Oskarsson. At earlier stages of research, Hans Blomkvist, Joakim Johansson, and Björn Lindberg were appointed commentators on parts of the manuscript. Their proposals also affected the final results.

The environment at the Department of Government has been inspiring. My colleagues made my years as a doctoral candidate rewarding. Thanks to all of you! Gunnar Myrberg deserves a special mention. Gunnar has been my nearest companion at the department. We were roommates for some years and we have been teaching together, studying statistics in Ann Arbor, and discussing many personal and job-related things. Kalle Lindgren has pro-vided crucial methodological advises. This means that I can forgive him for

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always trying to free ride when it comes to clean and refill the coffee machine. Sverker Gustavsson’s guidance during my first year at the depart-ment must be recognized as well. Julia Jennstål, Sara Monaco, Thomas Persson, Andreaz Strömgren, Pär Zetterberg, Jörgen Ödalen and all of those who have participated in the many enjoyable discussions in the department’s lunchroom over the years have also contributed in a positive way.

Another environment of importance is the Institute for Labour Market Policy Evaluation (IFAU). My colleagues at IFAU inspired me to apply for the postgraduate program in the first place. And IFAU has always been a great place to visit. The staff’s knowledge in labor market policy and statistical methods has been useful, but just as important are all those weird and enjoyable discussions that take place at IFAU. Perhaps surprisingly, economists can be fun.

I owe thanks to the following foundations and institutions for contributing with financial support to various parts of the research project: The Institute for Labour Market Policy Evaluation, the Swedish Research Council, the Siamon Foundation, the Wallenberg Foundation, and the Swedish Council for Working Life and Social Research.

But life is not only work. My family and friends have been important supporters, although most of you never received a good description of what my work was all about and why it was important to me. Now when I have finished my thesis you have a great opportunity to put all your interests and hobbies aside and discover the thrilling mystery of public administration. To give you a foretaste of the excitement, I provide a quotation from Essay I: “I use three different approaches to counter autocorrelation and hetero-scedasticity. Robust standard errors clustered on municipalities and standard errors based Newey and West’s heteroscedasticity and autocorrelation con-sistent covariance matrices with two lags are the first two methods.” I guess you are tempted to get started right away?

It remains for me to express my appreciation to the most important ones: Ingrid, all your colds and coughs have constantly forced me to reschedule my plans during the last half-year. But your smile, laughter, and warm embrace compensate for this by a comfortable margin: You make all the troubles associated with writing a thesis go away. Daniela, you have been the closest person to me ever since that short paper eleven years ago. You gave substantial comments on my work, but your sacrifices and encourage-ment were even more important. These last eleven years would not at all have been so good without your love. Thanks!

Martin Lundin Uppsala, April 2007

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Introduction

The Conditions for Multi-Level Governance

Contemporary political systems comprise several tiers of government. The reason for having more than one level is apparent: there are no grounds to expect a certain geographical entity to be the appropriate one for all public concerns. But bureaucracies at various levels of government are often in-volved simultaneously when political ideas are implemented at local level. Thus, a perennial problem in the business of running a country is how to manage the machinery of the state when policies are turned into actions: How can the central state direct local public units to work effectively towards public sector goals?

The three essays housed in this thesis have distinct purposes. But they have a common ambition to disentangle the course of events when agencies from different levels of government—more precisely, from the central and local levels—are involved at the same time in public policy implementation. Essay I tries to find out whether local political partisanship explains local government actions. Essay II sets out to explain cooperation between agencies. Essay III, finally, examines the impact of cooperation on policy output.

The empirical analyses are focused on active labor market policy (ALMP) in Sweden. Thus, the study centers on the fight against unemployment, which is one of the major problems in advanced industrialized societies today. ALMP is a central-government policy domain. By this I mean that it is a policy area in which the central government is clearly intended to be the main principal. But local governments also have a key role. By examining local-government involvement in ALMPs, and their relationship to central-government agencies, it is possible to uncover what is actually going on at local level. In turn, this gives valuable insights into governance processes.

The aim of this introduction is to bring the separate studies into a common framework and provide some additional information on matters that are only briefly touched upon in the essays. The introduction consists of four sections and a data appendix. The purpose of the first section is to present the problems of governance and policy implementation when various levels of government are involved in local actions. In the essays, the research setting is concisely introduced. Thus, the second section of this overture is a

Introduction

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rather detailed description of intergovernmental relations within Swedish ALMPs. The main aim is to prove that it is important to take relationships between levels of government into account in ALMPs. In the third section, the essays are summarized. Lastly, I take some license to reflect on experien-ces from the study. A data appendix is also attached: Within this research project, I have collected new data through a postal questionnaire. This in-formation is utilized in essays II and III. The appendix describes the survey.

Levels of government, governance, and implementation In this section, it is demonstrated that political steering can be difficult when central and local public units are involved simultaneously in policy imple-mentation. In addition, I outline three key research questions that are import-ant to try to answer in order to find out the conditions for governance in these contexts.

Levels of government The basic pattern of political organization in modern democracies is territorial. Almost every country in the world has more than one level of government, with only very small states as exceptions to this rule. And the complexities tend to increase. Petersson (2003, 150) notes, for example, that not so long ago, the inhabitants of the city of Gothenburg in Sweden were only represented at the local and the national levels. Nowadays, there are six levels to take into account: the European Parliament, the Swedish Parliament, the county of Västra Götaland, the region of Gothenburg, the municipality of Gothenburg, and the district councils in Gothenburg.

A very important reason for having different tiers of government is that the preferences of the inhabitants in different geographical entities are different. In order to promote values such as democracy and efficiency, these preferences ought to affect public policy (for example, Elazar 1972; Molander 2003; Thomas 1979). Gallagher, Laver, and Mair (2001) use a fictitious bridge-building project to illustrate that objectives may differ due to geographical location.

The lives of people who live right beside the bridge may be ruined by its noise and disruption. People who live in the region but not in the immediate locality of the bridge may find the bridge saves them hours each week behind the wheel of an automobile and reduces the risk of their being involved in a fatal accident. Those who live elsewhere in the country but too far away ever to use the bridge may be forced to pay for part of it with their taxes while getting, as they see it, no benefits from it. (Gallagher, Laver, and Mair 2001, 136)


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Different geographical groups of individuals tend to have different interests in the policy process, which may imply tensions. For instance, assume that two authorities are involved in constructing the bridge presented in the quote from Gallagher and his colleagues. All else being equal, one would expect the authorities’ relationship to be less conflictual if both of them are regional government agencies than if one of them is a local government actor and the other represents the regional level. In the latter case, local objectives become an issue. Thus, coordinating the activities of various governmental bodies is difficult. A lot of time and other resources have to be devoted to resolve the dilemma and it may be complicated for the central government to reach ambitions.1

Newspaper articles often describe problems of cooperation between authorities from different levels of government. Two brief examples from Sweden can serve as illustrations. Svenska Dagbladet reported in 2003 (November 16) on collaborative problems between medical services, ad-ministered by the County Councils (Landsting), and the municipal Social Services in the treatment of mentally ill patients. The article claimed that clients are often passed on between the authorities and that no authority takes full responsibility. The director-general of the National Board of Health and Welfare (Socialstyrelsen) said that local implementing agencies have trouble getting along when economic resources have to be taken from both the county and the local level.

The second example concerns the responsibility for underage refugees coming to Sweden without parents. A critical situation at a refugee center, Carslund, was reported in the media in 2002. The number of children at the center, administrated by the Swedish Migration Board (Migrationsverket), had increased substantially. Thus, the center was understaffed and the pre-mises were inadequate. Many children were in poor mental health and several suicide attempts were reported. It was claimed in the newspapers that problems of collaboration between the Migration Board and municipal authorities had contributed to the troubles. It was unclear when and how the municipalities should get involved, and which level should take re-sponsibility for costs at different stages of the process. As a consequence, the refugee center became overcrowded (for example, Dagens Nyheter, February 10 and 11, 2002; for similar discussions see Dagens Nyheter, December 30, 2003).

Governance The problems of coordinating tiers of government have also received quite a lot of attention among political scientists. In contemporary research, studies

1 For some classical studies on intergovernmental relations, see Grodzins (1966), Oates (1972), and Wright (1988).

Introduction

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often address the “governance” concept (for example, Pierre 2000; Pierre and Peters 2000; Rhodes 1997; Stoker 1998). Similar discussions are found in studies that prefer to talk about “intergovernmental management” (Radin 2003),2 “network management” (Kickert, Klijn, and Koppenjan 1997), or “multi-level governance” (Hooghe and Marks 2003; Peters and Pierre 2001; Smith 2003). The central theme in studies that use one of these trendy con-cepts is how to steer society towards collective goals given a situation in which “boundaries between and within public and private sectors have become blurred” (Stoker 1998, 17; see also Pierre and Peters 2000). It is recognized that governing is difficult and that a simple and conventional view of political steering is not adequate. That is, the central government cannot steer society “from above” independent of other actors (for example, Kickert, Klijn, and Koppenjan 1997; Stoker 1998). Accordingly, the traditional view of bureaucracies—that is, Max Weber’s legal-rational model—is not in correspondence with reality. In line with this view, linear political steering-models with the focus on formal, hierarchical relationships should be replaced with models in which relations are more fluid and different public and private actors are assumed to be interdependent in governing processes.

The governance perspective is not an especially elaborated framework. Rather, it is “a set of observations looking for a more comprehensive theory” (Pierre and Peters 2000, 7). Moreover, it does not provide a causal theory. Instead, it is a framework for describing how governing works in practice (Stoker 1998). One might wonder how useful the framework really is and what new insights it actually provides. But the perspective can at least highlight some important research questions.3 The most fundamental idea of governance research is of relevance in this thesis: the central government cannot realize its ambitions without taking other actors into consideration. For instance, local governments and their objectives and resources are going to influence central government possibilities of reaching policy goals in both federal and unitary political systems.4

Two features of the governance discourse are important to underscore here. First, governance theory and empirical studies that relate to governance are often concerned with the interaction of a large number of public and

2 Sometimes the term “intergovernmental relations” is reserved for relationships among governments within federal states. Moreover, scholars examining the European Union talk about intergovernmental relations when they analyze the relationships among member states. But similar dynamics exist in all political systems. Radin (2003) claims that it is too re-strictive to see intergovernmental relations as something that occur only in federal states or between countries. 3 Many of these questions could, however, be addressed within political science research without explicitly relating to the popular governance research discipline. 4 Note that prior research on political control, before the “new governance” approach became fashionable, demonstrated that various levels of government influence the output of national government policies (for example, Chubb 1985; Scholz and Wie 1986).


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private actors—the network. Coordination problems in these networks are the usual focus of analysis.5 This thesis is limited to the relationships of central and local government units.6 I do not consider networks at all and the separate articles are not framed within a governance perspective. I adopt more specific theories. Thus, the essays could not be classified as gover-nance research in the same way as the typical governance study of today. Nevertheless, the arguments and the empirical findings are of relevance for scholars interested in governance processes.

Second, a key discussion in governance research is the role of the central government. According to some scholars, the central government is just one of many actors in self-organizing networks that no single actor can control (for example, Rhodes 1997). That is, hierarchies are more or less unimport-ant. Some scholars think that this is normatively acceptable. Hirst (2000) claims that the “old” democratic model in which political representatives are held accountable for their actions must be rejected since politicians do not exercise a monopoly on politics. Representative institutions could and should primarily be “watchdogs.” Thus, it is necessary to adopt a “demo-cratic model, which involves devolving as many of the functions of the state as possible to society (whilst retaining public funding) and democratizing as many as possible of the organizations in civil society. The aim is to restore limited government and to ‘politicize’ civil society” (Hirst 2000, 28).

In my view, this is a dubious position both normatively and empirically. If the descriptions of Rhodes and Hirst are correct empirically, I think that the first step is not to surrender. Rather, it is important to find ways to re-instate democratically elected politicians as primary governing actors. A point of departure in this study is that the central government ought to have a significant influence—the government should govern.7

Fortunately, elected representatives and hierarchies are still likely to make a difference. The most prominent supporters of this view are Pierre and Peters (2000). Networks have become more important, they claim, but net-works are less significant than hierarchical relationships. The government is at the center of governance and the hierarchy “is the benchmark against which we should assess emerging forms of governance” (Pierre and Peters 2000, 17). Lundqvist (2001) examines the validity of the claims of Rhodes and Pierre and Peters using Local Investment Programs for Suitable Development in Sweden as a critical case. The evidence supports Pierre and

5 For an interesting theoretical discussion and four detailed case studies on collaboration in networks, see Hertting (2003). 6 For a discussion of central–local government relations, see Rhodes (1999). 7 This does not, of course, mean that I defend a position in which the central government controls all public concerns in detail. This is not likely to be very beneficial from a democratic or an effectiveness perspective. Actors such as subnational governments in both federal and unitary states should make a difference. But given that the central government is intended to be the main principal, it should definitely be able to govern.

Introduction

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Peters’ argument that government is at the center of structures of gover-nance.

Implementation To understand the conditions for governance, it is important to understand implementation at local level. At this level, political ambitions become actions. Implementation research is about the courses of events in which political ideas are put into practice, that is, what goes on between policy ex-pectations and policy results (deLeon 1999). Local practices are not always the same as the aims stated in official documents. Moreover, performance frequently varies from one local context to another and from time to time. In relation to classical definitions of politics, such as “who gets what, when and how” (Lasswell 1936), implementation studies become important.8 Certainly, if we do not comprehend how political ambitions and ideas fare in reality, we cannot know who gets what, when, and how.

Jeffrey Pressman’s and Aaron Wildavsky’s 1973 (1984) book Implementation is usually regarded as the starting-point of implementation research.9 Pressman and Wildavsky conducted a detailed case study of how a public program, with the aim of increasing minority employment in Oakland, California, was carried out in practice. They found large discrepancies between intentions and practice. According to the authors, an important explanation for the unsatisfactory results was that many actors had to coordinate their work in the implementation process. Pressman and Wildavsky identified about thirty major decision points that had to be clear-ed when the program was carried out. Several participants were involved in the process and making all the actors work together was a difficult task, leading to management problems. Thus, besides bringing implementation onto the political scientists’ research agenda, Pressman and Wildavsky pinpointed the dilemmas of interorganizational policy implementation.

The research body that followed the Pressman/Wildavsky-study is rather messy. As O’Toole (2004, 310) puts it, “theories about policy implement-ation have been almost embarrassingly plentiful, yet theoretical consensus is not on the horizon ... After hundreds of empirical studies, validated findings are relatively scarce.” Similar conclusions are drawn by scholars such as Matland (1995), deLeon (1999), and Rothstein (1994, ch. 3). But one of the 8 Among the most influential implementation studies are Brehm and Gates (1997), Elmore (1979), Goggin et al. (1990), Hjern and Porter (1981), Lipsky (1980), Mazmanian and Sabatier (1989), and Pressman and Wildavsky (1984). There are also several overviews of the literature, such as Lester et al. (1987), Matland (1995), and Winter (2003a; 2003b). 9 But Pressman and Wildavsky were not the first scholars to address questions of implementation (Winter 2003a, 203; Hill 1996, 127–28). For instance, Herbert Kaufman (1960) examined implementation in the book The Forest Ranger many years before Imp-lementation was published. Nonetheless, it was the work of Pressman and Wildavsky that placed the issue of implementation in a paramount place on the research agenda.


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few things scholars agree on is the conclusion by Pressman and Wildavsky that we have to take into account that many actors influence implementation if we want to understand what is going on at local level (O’Toole 2003).

Interorganizational relationships were subject to intense scrutiny in early studies. For example, Hanf, Hjern, and Porter (1978) studied local networks carrying out adult labor market training in Sweden and Germany. They indicated that the implementation of these training programs required assistance from many public and private organizations. Another contribution is an analysis by Hjern and Porter (1981), who argued that clusters of organizations normally carry out public programs. A multiorganizational unit of analysis is therefore appropriate when describing and evaluating public policy implementation. O’Toole and Montjoy (1984) is yet another pioneering study. They analyzed different types of ties between organizations and discussed how these relationships are likely to affect policy implementation. The focus on multiple actors has remained a re-current theme in empirical research.10 O’Toole (2003, 237) concludes:

The topic of interorganizational relations will remain important for administrators tasked with helping to make policy implementation succeed. Accordingly, it is critical to understand how to make sense of such institutional settings for improving prospects for implementation success.

Usually, interorganizational policy implementation involves an intergovern-mental aspect. According to Kettl (1993, 414), “nearly 80 percent of all of the entries for programs and organizations in one standard implementation textbook are for programs and organizations that have an important intergovernmental dimension.” Thus, the implications of these relations for public policy implementation are worth paying attention to.

A seminal work in this context is Goggin et al. (1990). Goggin and his colleagues argued that research had neglected the role of the state level in research on implementation of federal mandates in the United States. The authors suggested a model of intergovernmental policy implementation. Interests and motives, incentives and constraints, and power and resources at various levels were assumed to affect how political ideas were turned into practice. Case studies of hazardous waste policy, waste-water treatment projects, and family planning programs suggested that several levels of government should be taken into account. In an earlier study, Thomas (1979) discussed similar things. Thomas stressed the importance of working out jurisdiction between levels of government. Implementation at local level would otherwise become difficult.11

10 Studies such as Agranoff and McGuire (2003), Bardach (1998), Hudson et al. (1999), Jennings (1994), Jennings and Ewalt (1998), and O’Toole (1983) contribute to the debate. 11 In a more recent study, Cho et al. (2005, 33) claim that the literatures on intergovernmental relations and policy implementation, to a large extent, “run parallel rather than intersect.”

Introduction

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Research questions The journey thus far has showed that it can be difficult for central govern-ment to realize ambitions at local level and that subnational actors are likely to have a stake in implementation. From a democratic perspective, elected representatives should be able to govern. Thus, the problem is how to co-ordinate various levels and actors. These actors may be politicians or public servants. Hence, three research questions are important to penetrate in order to comprehend local actions.

First, we need to discern the role of local politics: Do local government actions dependent on what political parties control the local legislature? Or can the central government expect local units to act in a similar manner re-gardless of who governs? There is a large literature on the effect of political parties on public policy. A number of studies are concerned with the sub-national level (for example, Besley and Case 2003; Petterson-Lidbom 2006). The insights from this body of research can be used to improve our understanding of central government steering possibilities. Essay I builds on and contributes to this literature.

Second, in order to coordinate activities of local units, it is important to find out what factors explain cooperation between agencies: How can the government make agencies work together? Many studies try to explain inter-organizational cooperation in policy implementation (for example, Alter and Hage 1993; Bardach 1998; O’Toole 2003). Essay II adds to this research and reveals some conditions for cooperation across organizational and govern-mental boundaries.

Third, we cannot assume that cooperation always improves policy implementation. Thus, the impact of interorganizational cooperation on policy output and outcome is also a key topic: Does cooperation between agencies affect policy implementation? Some studies have focused on this question (for example, Jennings 1994; Jennings and Ewalt 1998). The pur-pose of Essay III is to take a close look at the effects of cooperation.

The role of local governments in Swedish active labor market policy What is an appropriate case for studying the questions of interest in this thesis? Two features are of certain interest. First, two different public authorities, representing different levels of government, must be involved in the implementation process. Second, there has to be some potential conflict of interest between levels of government. Additionally, an important and high-prioritized policy area is, of course, preferred over an issue of less importance. ALMPs in Sweden is one case that fulfills these requirements.


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In this section, the relationship between central and local government authorities in Swedish ALMPs is described. The section is divided into six subsections. First, I provide a short account of the role of local governments in the Swedish political system. Second, the central government role in ALMPs is portrayed. Third, I show how local governments are involved in ALMPs. Fourth, the objectives of central and local government actors are discussed. Fifth, it is demonstrated that the agencies interact to a con-siderable extent. Lastly, a short summary is offered.

Local governments in Sweden Sweden is a unitary state, but has a long constitutional tradition of local government liberty. There is a county level (landsting), but local govern-ments (kommuner) are more important. As of 2007, there are 290 local governments (or municipalities) in Sweden with an average population of approximately 30,000 inhabitants. The largest municipality is Stockholm and the smallest is Bjurholm: Stockholm has almost 800,000 residents and Bjurholm fewer than 3,000. The municipalities provide a lot of services of the welfare state, including day care, care of the elderly, social welfare services, and primary education. As a result, they employ around 20 percent of the total Swedish workforce. To a large extent, local services are financed by local income taxes: only around 20 percent of their income is from grants. Municipalities can set the tax rate freely, there are no restrictions on borrowing, and municipalities decide on their own organization.12 In a comparative perspective, local governments in Sweden are considered to have a high degree of autonomy (Lidström 1996; Norton 1994).

But local government liberty is not unconditional. The central govern-ment regulates activities through various steering mechanisms, such as laws and decrees. A common criticism is that the central government has de-centralized a lot of responsibilities without providing the necessary funding (Johansson 1996; Montin 2002). Furthermore, some scholars argue that there has never been a genuine desire to diffuse much real power down to the local level (Dahlkvist and Strandberg 1999). But most scholars agree that there has been an overall tendency towards decentralization and that municipalities have a key role in the Swedish political system, even though there are obvious restrictions on actions (Montin 2002; Peterson 1994).

ALMPs – A central government responsibility Municipalities manage a considerable part of the Swedish welfare sector. At the beginning of the twentieth century, labor market activities were also a

12 For a description of the Swedish municipalities, see Gustafsson (1999), Montin (2002), and Petersson (1994).

Introduction

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local government concern. But in 1940, intended to be a temporarily solution in turbulent times of war around the world, the national government took over responsibility from the local governments. It did not turn out to be a provisional solution. The National Labor Market Administration (Arbets-marknadsverket) was institutionalized in 1948 in order to give nation-wide effect to labor market activities (Thoursie 1990).

Labor market policies are usually split into two broad categories: passive (PLMP) and active (ALMP) measures. Unemployment benefit is the main type of passive support. Labor market training, subsidized employment, work practice, and diverse job brokering activities are typical examples of active programs. The active policy is primarily guided by ideas introduced by trade union economists Gösta Rehn and Rudolf Meidner in the 1940s and 1950s. An extensive and active policy was necessary in order to combine the policy objectives of high employment, low inflation, wage solidarity, and endorsement of economic growth. Mobility-enhancing activities, such as labor market training, were to be used so that workers risking unemployment could be moved from low-productivity sectors to high-productivity sectors. The policy was therefore an important part of Sweden’s economic policy, and national government control was considered important (Rothstein 1996, 56–64).

Today, Public Employment Service (PES) offices (Arbetsförmedlingar) implement central government decisions at street-level. There are about 300–350 PES offices in Sweden. Some of them are specialized in the rehabilitation of unemployed with work disabilities and others work within a particular business sector. But the vast majority of agencies provide services to all kinds of job-seekers and employers, and can use the full set of ALMPs available. The average number of employees is approximately 22, but some offices only have a couple of employment officers, and others a staff of 100 members or more.13

Historically, the recruitment policy at all levels within the administration has been based on ensuring the staff’s ideological commitment to national policy objectives, rather than on formal education and merits. Promotion policy and the training of employment officers have also aimed at guaranteeing a commitment to overall national goals. The reason behind this kind of staff policy was that a flexible organization with large discretion at local level was preferred in order to make the policy efficient. At the same time, to ensure that the policy worked according to national government

13 These figures are based on the National Labor Market Administration’s personnel statistics from 2003.


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intentions, it was important that street-level bureaucrats understood and approved of policy objectives (Rothstein 1996, 116–30).14

The overall goal of the policy is an effective national labor market with full employment and good economic growth (Runeson 2004, 10). In order to reach this goal, management by objectives (målstyrning) is the principal mechanism for governmental control over the National Labor Market Administration and for supervision within the administration (Lundin 2004; Nyberg and Skedinger 1998). There are, of course, laws, rules, and guide-lines, but the local employment officers are relatively free when deciding the appropriate actions in a particular case (Lundin 2004). The following list, based on Runeson’s (2004, 9–13) survey of official documents, summarizes the administration’s central tasks when trying to reach the overall goal of an effective labor market:15

• Match job-seekers with vacancies • Improve the skills of unemployed individuals • Enhance flexibility in the labor market • Protect and take special measures for weak groups in the labor market • Counteract inequalities between men and women in the labor market • Treat clients uniformly all around the country • Adapt activities to conditions in different parts of the country • Adapt labor market programs to the individual and improve his or her

chances of getting a job • Provide financial security to job-seekers through the unemployment

insurance system, but monitor that job-seekers follow the official requirements for receiving benefits

• Programs should not distort competition and displacement effects should be minimized

• Activities should not distort the ecological balance

These general tasks are complemented by specific quantitative goals adapted to each PES office.16 It is apparent that ALMPs are primarily focused on macroeconomic performance, that is, an effective matching procedure bet-

14 This is primarily a historical account of how the labor market administration was organized in the 1950s, 1960s, and 1970s. Systematic evidence on the contemporary organization is, to my knowledge, lacking. Formally, recruitment should be based on skills and experience rather than on ideological commitment today. 15 The National Labour Market Administration is primarily regulated by the following official laws and decrees: Law (2000:625), Ordinance (2001:623), Ordinance (2000:628), and Ordinance (2000:634). 16 For example, in 2003 and 2004 there were quantitative goals concerning long-term unemployed clients, unemployed youth, part-time unemployed individuals, and unemployed persons with work disabilities. Moreover, there were also quantitative goals to measure the output of labor market training, the share of clients having an individual action plan, and employers’ satisfaction with the local PES office (Lundin 2004, 15–17).

Introduction

20

ween available jobs and job-seekers. It is also obvious that local interests must not be prioritized over the national goal of decreasing unemployment. For instance, the Swedish government notes that “narrow municipal interests must not be prioritized over the goal of reducing unemployment and bottle-necks on the labor market since these interests may have negative effects on the functioning of the labor market” (Government Bill 1999/2000:98, 70).17 Nevertheless, the government recognizes that within overall macroeconomic objectives, activities ought to be adapted to local conditions and to clients’ needs and skills. In the next subsection, I will demonstrate that local govern-ments have a key role in this process.

Local government involvement in ALMPs Although the national government took over responsibility for ALMPs in the 1940s, the municipalities have remained important actors. For example, they organized public relief works throughout the twentieth century (Olli Segendorf 2003). In several governing documents, the Swedish government makes clear that the National Labor Market Administration must carry out activities in close collaboration with the municipalities.18 Besides these general exhortations, the Swedish government has also taken a number of steps in order to increase municipal involvement in ALMPs. Most of these decisions were made in the 1990s when there was an unemployment crisis in Sweden. Some examples are presented below.19

• At local level in Sweden there are joint cooperative and advisory

bodies with the purpose of adapting ALMPs to suit local conditions. These bodies are called Employment Service Committees (Arbets-marknadsnämnder). Some kind of local advisory bodies have existed in Sweden since the 1970s, but in 1996 the committees were reformed. The national government wanted to strengthen the municipalities’ role in ALMPs. Thus, municipal representatives should constitute the majority of the committee members. In addition, the municipalities were given the right to nominate the committee chairman. This construction is somewhat peculiar since ALMPs are supposed to be a responsibility of the central government. But committee representatives from the National Labor Market Ad-

17 This is my own translation of the following quote in Swedish: “De snävt kommunala egenintressena får inte prioritieras framför bekämpningen av arbetslöshet och begynnande flaskhalsar eftersom det kan ge oönskade effekter på arbetsmarknadens funktionssätt.” 18 For example, in Ordinance (2000:623) the PES offices are urged to work together with the municipalities. 19 This list can be developed further. For additional examples, see Government Bill (2002/03:44) and Forslund, Fröberg, and Lindqvist (2004).


21

ministration were supposed to stop decisions that run counter to national objectives (Lundin 1999; Lundin and Skedinger 2006).20

• Another policy change in the 1990s concerned programs for

unemployed youth. In 1994, the government declared that no young person should remain unemployed for more than 100 days without taking part in an active program. The government’s ambition was that every individual under 25 years of age should be offered a labor market program if he or she was unable to find a job within three months of registration as unemployed at the PES. The government encouraged the municipalities to take part in the actions by instigating two labor market programs. The Municipal Youth Program (Kommunala ungdomsprogrammet) was introduced in 1995. In 1998, the UVG-guarantee (Ungdomsgarantin) was implemented. The former program was directed towards youth below 20 years of age; the latter concerned youth aged 20–25. Both programs implied that the municipality should arrange activities for young unemployed while getting some financial compensation from the PES office (Carling and Larsson 2005).21

• An additional policy change with implications for the municipalities’

engagement in ALMPs was a change in the Social Service Act in 1998. The reform made it possible for the municipalities to demand those social assistance recipients whose major problem was considered to be unemployment to participate in work related pro-grams in exchange for social allowances. Municipalities were allowed to reduce benefit if clients refused to take part in work related pro-grams.22 This resulted in a lot of municipal labor market related activities for unemployed social assistance recipients (Hjertner Thorén 2005; Salonen and Ulmestig 2004).23

Municipalities are involved in many labor market programs. Lundin and Skedinger (2006) estimate that in 1999, 40 percent of the participants in all the National Labor Market Administration’s active programs were, in fact, organized by the municipalities. The target groups are often youth (Carling and Larsson 2005) and social allowance recipients (Salonen and Ulmestig 20 The Local Employment Service Committees are regulated by Ordinance (2001:623). See also Government Bill (1994/95:218), Government Bill (1995/96:25), Government Bill (1995/96:148), Government Bill (1995/96:222), and Government Bill (1999/2000:98). 21 See Law (2000:625) and Ordinance (2000:634). See also Government Bill (1994/95:218), Government Bill (1997/98:1), and Government Bill (1999/2000:98). 22 See Law (2001:453) and Government Bill (1996/97:124). 23 Salonen and Ulmestig (2004, 35) estimate that around 12,000 persons were activated in such measures at any given point in time in 2002. This corresponds to approximately 10 percent of all the individuals participating in labor market programs in Sweden.

Introduction

22

2004). Job-search assistance and work practice are some of the activities municipalities arrange.

Many local governments have established a labor market administration to handle labor market issues. This is probably a consequence of increased municipal engagement in ALMPs in the 1990s. In 1995, about two in ten municipalities had instigated such an administration. Three years later, in 1998, the share had increased to approximately seven in ten (Swedish Association of Local Authorities 1999).24

Why are municipalities taking part in ALMPs? The central government wants local governments to be involved since they can contribute with diverse forms of local resources. From a municipal viewpoint, unemploy-ment entails considerable problems. For instance, the local unemployment rate impinges on municipal revenues; high local unemployment will result in low tax revenues. Unemployment also increases municipal costs. For in-stance, unemployed persons not qualifying for unemployment benefits financed by the central government often need social allowances paid for by the municipalities (Wetterberg 1997). Unemployment may also make citizens leave the municipality in order to get jobs in other parts of Sweden. Thus, for reasons such as securing the local tax base, decreasing expenditure on social allowances, and stopping emigration, the municipalities may try to help the PES offices out.25

Central and local government objectives By now we know that both central and local government authorities are involved in the implementation of ALMPs in Sweden. But what objectives do the authorities have? Should we expect conflicts of interest?

There is no reason to doubt that both the central and the local level share the overall goal of decreasing unemployment. But interests may diverge within this general goal. A simple example can be used as illustration: emigration is a serious problem for municipalities in Sweden—the tax base is endangered. From a national labor market perspective, however, geo-graphical mobility is important. The PES offices’ task becomes easier if unemployed clients move from a troublesome labor market environment to areas where the chances of getting a job are better. Accordingly, whereas municipalities probably are more focused on finding a local solution, PES

24 Note that municipalities that do not have a special labor market administration manage labor market issues within another administration, for example, social services. 25 Recently, centralization tendencies have become more apparent in Swedish ALMPs. For example, the municipal youth programs discussed above were abolished in spring 2007 (Government Bill 2006/07:100; Ministry of Employment 2007), since evaluations indicated poor results (for example, Carling and Larsson 2005; Forslund and Nordström Skans 2006). However, there is no systematic knowledge on centralization tendencies and it is too early to say that subnational levels have lost influence.


23

offices are likely to be more open to activities that do not benefit local governments.26 In a study of the Local Employment Service Committees, Lundin (1999) found that 60 percent of the committee members were of the opinion that there were conflicts between central and local interests in local level activities.27 Thus, there are reasons to assume that a central–local dimension gives rise to certain dilemmas when ALMPs are implemented.

Within the present research project, questionnaire data on the relationships between PES offices and municipalities have been gathered. These data are used in essays II and III. Details are reported in the appendix attached to this introduction. The respondents were PES managers, managers of municipal labor market administrations, and local politicians in charge of municipal labor market activities. A set of questions concerned the agencies’ objectives. Table 1 shows—by denoting the share of respondents claiming that a certain goal receives “very high” or “fairly high” priority—how the authorities allocate priorities among different goals.

The findings are decisive. As expected, reducing unemployment is very important to both organizations. Both of them also give high priority to unemployed youth, clients with severe difficulties in the labor market, and matching procedures. But the overall impression is that agencies prioritize objectives in a different manner.

The PES offices put much more emphasis on formal directives and guide-lines from the central government. While 98 percent of the PES managers said that central government rules and guidelines have high priority, only 58 percent of the municipal managers and 31 percent of the politicians gave the same answer. In addition, municipal representatives do not consider the goals of the National Labor Market Administration to any significant extent. Because subsidizes are for the most part paid by the central government, it is not surprising that shifting persons from subsidized to unsubsidized jobs is another objective primarily of concern for the PES offices. Furthermore, monitoring is more important for PES offices, whereas municipal officials give somewhat more priority to clients’ own needs and requests.

26 A concrete and real example demonstrates this: in the Local Employment Service Committee of Arjeplog, the municipality acted in order to shift financial resources from a central government mobility grant to local labor market programs (Protocols of Local Employment Service Committee February 21, 1997 and October 29, 1997, municipality of Arjeplog). These activities were halted, but it indicates that local representatives may act in order to benefit their own commune in the implementation of ALMPs. 27 A couple of open comments may illustrate this further. A handful of representatives from the National Labor Market Administration said that “the municipality wants to increase local population, whereas the PES ought to increase geographical flexibility on the labor market”, and “municipalities like to improve their budget through national labor market resources”. On the other hand, some municipal representatives concluded “local initiatives are blocked by national rules on how the labor market policy should work” (Lundin 1999, 45–6).

Introduction

24

Table 1. Objectives in ALMPs: Percentage Claiming that a Certain Objective is Given “Very High” or “Fairly High” Priority

PES Municipality Objective Managers Managers Politicians Difference

Attaining the quantitative goals of the National Labor Market Administration

97 37 35 + 61

Following central government rules and guidelines

98 58 31 + 53

Monitoring clients 91 53 58 + 36

Shifting people from subsidized to unsubsidized jobs

72 52 62 + 15

Improving matching between available jobs and unemployed persons

97 70 82 + 11

Ensuring that there are labor market programs for groups of unemployed with severe problems in the labor market

94 80 86 + 11

Ensuring that there are labor market programs for young people under 25

98 92 95 + 4

Reducing unemployment 91 89 95 - 1

Taking clients’ own requests and needs into account

62 82 69 - 13

Improving municipal services for the local population

12 49 52 - 38

Activating unemployed persons living on social assistance in labor market programs

29 79 89 - 55

Increasing or maintaining the local population

16 68 92 - 61

Reducing expenditure on social assistance

6 83 92 - 81

Notes: Data come from questionnaires distributed to managers of PES offices, managers of municipal labor market administrations, and local politicians having responsibility for labor market questions. Formulation of question: “How are the following objectives prioritized at the PES (in the municipality’s labor market activities)?” The question directed to the politicians was slightly different: “How are the following objectives prioritized by the political majority in the municipality?” A scale of five categories was used: “Very high,” “Fairly high,” “Neither high nor low,” “Fairly low,” and “Very low or not at all.” The number of respondents for each item was between 258 and 264 among the PES offices, between 238 and 242 among municipal managers, and between 231 and 242 among the politicians. The difference column presents the percentage point difference between answers from the PES offices and the average of managers’ and politicians’ answers in the municipalities.


25

Municipalities think that objectives of a local character are important. Two examples underscore this. First, among the PES managers, 16 percent regarded population goals as important. About 68 percent of the municipal managers and 92 percent of the local politicians noted that maintaining or increasing the local population is an important objective in local ALMPs. Second, the PES offices do not pay for social assistance. This is probably why decreasing these expenditures and activating unemployed persons living on social assistance in programs are objectives to which they do not give priority. More or less all municipal actors claimed that these matters are im-portant.

A couple of objectives are prioritized somewhat differently among municipal managers and politicians. The elected representatives give less attention to central government rules and guidelines. Furthermore, they think that population goals are even more important. By and large, however, the two groups of municipal representatives provide a rather similar picture.

In another survey question, I asked whether there had been any conflicts between the PES and the municipality in 2003. Around 28 percent of the PES managers, 50 percent of the municipal managers, and 32 percent of the local politicians reported minor or major conflicts. Most of these respondents marked the response alternative “yes, minor conflicts.” Thus, it is probably not correct to describe the relationship as extremely problematic. Never-theless, I believe that it is safe to conclude that there are conflicts of interest that emerge as a consequence of the fact that the authorities represent different tiers of government.

Do PES offices and municipalities interact? A final question to consider before this description of the research setting is complete is to what extent the authorities interact in local activities. In the questionnaire, the respondents were asked to report the level of contact bet-ween the authorities. They also reported how much they communicated with other groups of actors involved in ALMPs. The answers to these questions are presented in Figures 1–3.

Introduction

26

Figure 1. Frequency of Communication between PES Offices and Diverse Categories of Organizations (Answers by PES Office Managers, n = 263)

Figure 1 indicates the level of communication according to PES managers. More than nine in ten reported that the PES has at least weekly contacts with the municipality. About 50 percent noted daily contacts. Only private firms and other PES offices are contacted to a greater extent. Most potential work opportunities are located within the private sector and actions probably need to be coordinated among neighboring PES offices. It is therefore not surprising that these groups of actors are contacted more often. Note that the PES offices seem to interact more with municipalities than with key actors such as unions, employers’ associations, and even the County Labor Boards.28

The answers from municipal managers are reported in Figure 2. The picture from Figure 1 is underscored. Communication within the municipal organization is, of course, rather intense. But the municipalities’ interaction with the PES offices is frequent as well: around nine in ten report that the authorities contact each other at least on a weekly basis.

28 The County Labor Board (Länsarbetsnämnden) is the body within the National Labor Market Administration located at the county level.

0% 20% 40% 60% 80% 100%

Private firms

Other stakeholder organizations

Employers associations

Unions

Other public authorities

County Council

County Administrative Board

Social Insurance office

Municipality

National Labour Market Board

County Labour Board

Other PES

Daily contacts Weekly contacts


27

Figure 2. Frequency of Communication between Municipal Labor Market Administrations and Diverse Categories of Organizations (Answers of Municipal Labor Market Managers, n = 248)

Figure 3 presents the answers from municipal politicians. At first glance, Figure 3 seems to show a somewhat different picture. But unlike the managers, the politicians were supposed to provide an answer that reflected how often they personally communicate with other actors in labor market related issues. This means that their answers are not an account of the municipal labor market administrations’ communication with various groups of actors. Very few politicians speak to civil servants at the PES office on a daily basis. Around 20 percent indicate at least weekly communication. On the other hand, in comparison to other groups of labor market actors, the PES offices are important.

All things considered, there seems to be a lot of contact between PES offices and municipalities. In general, they do not operate in isolation from each other.

0% 20% 40% 60% 80% 100%

Private firms



Unions


County Council



Association of Local Authorities and Regions


County Labour Board

Local PES

Other municipalities

Other administrations within the municipality


Introduction

28

Figure 3. Frequency of Communication between Local Politicians in Charge of Labor Market Activities and Diverse Categories of Actors (Answers of Municipal Politicians, n = 237)

Governance and Swedish ALMPs It is obvious that it is important to take relationships between levels of government into account in Swedish ALMPs. The central government has ambitious goals within labor market policy. A large and strong national public authority is intended to take care of labor market operations. But at local level, local governments are also involved when decisions are turned into actions. Central and local government agencies interact to a great extent in policy implementation. And even though reducing unemployment is a top priority for both actors, objectives diverge to a considerable extent. This means that governance may be complicated.

In the essays to follow, the conditions for governance within ALMPs in Sweden are analyzed. It is examined whether political partisanship at local level influences municipal policy within ALMPs: Does it matter whether the left wing or the right wing governs at local level? Furthermore, explanations to cooperation between PES offices and municipal administrations are studied: What factors boost cooperation? Lastly, I take a look at the impact

0% 20% 40% 60% 80% 100%

Elected representatives at central level

Private firms



Unions


County Council



Ministry of Ind., Employment and Com.


County Labour Board

Local PES

Association of Local Authorities and Regions

Other municipalities



29

of cooperation on policy output: When does cooperation improve public policy implementation? In the next section, the essays are summarized.

Lessons from the essays The three essays of this thesis pose general research questions, with distinct purposes beyond ALMPs in Sweden. This means that the study provides insights both to the particular case and to common problems in most policy areas.

Lesson one: Political partisanship explains local government policies, but only in large local entities Do political parties make a difference for public policy? This question constitutes a large political science literature. Essay I adds to this body of research. The focus is local governments and it is hypothesized that political partisanship has a greater impact on public policy in large local entities than in small ones. The hypothesis rests on the idea that politics is more prag-matic, and party antagonisms less pronounced, in small subnational entities.

Empirically, local government involvement in ALMPs in Sweden is analyzed. There are strong reasons to suspect leftist local governments to be more involved in ALMPs than right-wing ones since these policies primarily benefit the core voters of the left. But if politics are more pragmatic in small entities, and if party politicization becomes more important as entity size in-creases, the effect should be larger in more sizeable entities.

The analysis is based on quantitative panel data from 1998 to 2005. The amount of resources used for ALMPs per local inhabitant is employed as the dependent variable. These data allow for hard empirical tests. In accordance with the hypothesis, the effect of political partisanship turns out to be con-tingent on local population size. In the smallest entities, it is not important who governs—ALMP expenditures are not affected by political partisanship. As population size increases, partisanship begins to play a much more essential role. Left-wing governments spend, on average, more money on ALMPs than right-wing governments. Thus, forthcoming studies on the importance of local political partisanship for public policy should consider a possible interaction term between partisanship and size.

The study also reveals that local needs explain local government involve-ment in ALMPs to a large extent. A factor such as unemployment is, not surprisingly, an important explanation.

The findings can primarily be generalized to countries in which local governments have a lot of autonomy and to policy areas in which there is an apparent left–right political dimension. But there is no strong reason to

Introduction

30

assume that the idea does not apply in other settings as well since the argument is general. More research could reveal whether this is correct.

Lesson two: Trust and similar goals increase cooperation only when they exist simultaneously A perennial problem of public administration is how to make agencies work together. In Essay II, the task is to explain levels of cooperation between agencies. Previous research shows that resource interdependence, goal con-gruence, and mutual trust boost interorganizational cooperation. These three factors are also examined in Essay II. The empirical findings show that all three are important. But it is argued that interaction effects must be con-sidered in order to fully understand the relationships. The argument is not restricted to the study of ALMPs in Sweden, or to intergovernmental relations. It is a general claim concerning how cooperation between org-anizations and between individuals ought to be understood.

The study is based on 203 dyads of Swedish PES offices and municipal labor market administrations in 2003. I find that mutual trust is necessary if goal congruence is to increase cooperation between agencies. It is argued that this is because objectives cannot be communicated in a credible way when one party does not trust one another. Furthermore, mutual trust has a positive effect only if organizations have similar objectives. The idea is that trust can make cooperation easier, but if actors do not want the same thing it does not matter how reliable they find one another; trust is not sufficient by itself. Thus, the common claims that trust and goal congruence affect cooperation should be modified. Cooperation will increase when trust and goal congruence exist simultaneously. Thus, if a management strategy aimed at increasing cooperation only focuses on organizational objectives or the level of trust, it is likely to fail.

But the study indicates that the effects of trust and resource inter-dependence are not contingent on each other. My argument that resource interdependence and trust should be interacted is therefore not supported by evidence from ALMPs in Sweden. This may be a result of methodological problems, but it is also possible that resource interdependence is enough to guarantee that actors are honest and stick to an agreement. Research projects with the aim of solving this puzzle would be valuable.

The findings of the study are robust, but it necessary to be cautious when it comes to causal statements since the analysis is conducted within the limits of a cross-sectional design. One fundamental question is the causal order between trust and cooperation. Accordingly, additional studies seeking to discern the importance of interaction terms between trust on the one hand, and resource interdependence and goal congruence on the other hand, would be valuable.


31

Lesson three: Cooperation improves implementation of complex tasks Essay III is concerned with the fundamental question of policy implement-ation: What factors explain policy output? Interorganizational cooperation is often considered valuable in the public sector. If cooperation increases, so the argument goes, political objectives will be reached to a greater extent. But in Essay III it is proposed that the impact of cooperation is contingent on the type of policy being carried out.

It is suggested that the effect of cooperation on implementation performance increases with task complexity. It is likely that the benefits from cooperation are rather low when the task does not demand a wide range of intense actions. In these situations, the capacity to carry out decisions is not enhanced that much through cooperation—the most important resources are already available within a certain agency. Working across organizational boundaries implies costs. For instance, time and other resources are necessary to establish and maintain a productive relationship. If cooperation does not imply that many benefits, there is a significant chance that costs will be high in relation to benefits. But as complexity increases, so do the benefits. Cooperation becomes a more value adding activity. Accordingly, I expect no or very little impact from cooperation when the task is not com-plex and a stronger positive effect in the case of complex tasks. To my knowledge these arguments have not been discussed and studied in the context of local policy implementation before.

Two policies within Swedish ALMPs are examined: programs for unemployed youth and activities for clients with an especially demanding situation on the labor market. The fundamental difference is that the youth policy corresponds to standard duties, while the activities for clients in a particularly difficult situation are much more complex. The prediction is that cooperation is a more fruitful strategy in the latter case.

In agreement with the hypothesis, the empirical test suggests that policy matters. A positive effect of cooperation is indicated only when the policy is complex. I argue that Swedish ALMPs constitute a critical case in an im-portant sense. There are strong reasons to expect that cooperation generally is a good strategy. First, information requirements are high. Second, both authorities share the overall goal of reducing unemployment. Third, the client groups of the two policies are highly prioritized by both agencies (see Table 1 in this Introduction). Fourth, both the PES offices and the municipalities have resources that can be valuable in the implementation of measures for both client groups. Given the empirical findings, there is no reason to expect a positive effect of cooperation in situations in which the conditions are less favorable if the task is not complex.

The main lesson of Essay III is that we should not take for granted that cooperation makes implementation better. Thus, scholars should develop and test theories on when interorganizational cooperation is a good strategy for

Introduction

32

making political ambitions come true. And practitioners should perhaps not see cooperation as a panacea for improving public sector performance.

Routes to better governance I started this overture with a question: How can the central state direct public bodies to work effectively towards public sector goals? Obviously, this thesis cannot decisively answer this grand question. The essays deal with questions that ultimately are about causality—and causality is always in-tricate in the social sciences. All ideas introduced in the thesis must be analyzed in additional contexts before distinct, generalized knowledge is possible.

The thesis indicates a number of ways that research can be improved. For instance, more quantitative studies on policy implementation are needed, especially from European countries. Pooled cross-sectional time-series data sets would be particularly welcome. Closer looks at the causal mechanisms that are suggested in the three essays are also valuable. Moreover, additional indicators of key variables—for example, implementation output and re-source interdependence—would also be helpful. A last important lesson for future research is the significance of interaction effects: All three essays examine whether the effect of a certain variable differs depending on other factors. In all three cases, interactions were important. For example, political partisanship is more important for public policy in large than in small local entities. Thinking in terms of conditional impacts can be helpful for im-proving both theory and empirical analysis. General law-like theories such as “partisanship matters for public policy” are, of course, more appealing. But integrative theories can often make our claims more precise. The fortunes and problems of interaction effects have been discussed in many prior studies (for example, Lindgren 2006; Oskarsson 2003). But in the literatures of central interest for this thesis, studies that focus on interaction effects are rather scarce. In my view, a promising path for future research would be to consider possible interactions more seriously.

Although more research is needed, this thesis has provided important in-sights to governance processes. The main implications can be summarized as follows:

• Local agencies from different levels of government interlock in policy

implementation at local level. Although they share overall objectives, they will have different priorities as a consequence of the fact that they represent different levels of government. The objectives affect cooperation between units of government. Goal congruence boosts cooperation. But goal congruence is not a sufficient condition for in-creasing joint actions. If there is no trust, cooperation will be com-


33

paratively low, even though agencies want the same thing. Never-theless, trust does not make a difference if the actors have different objectives. Thus, it is important to consider trust and objectives at the same time.

• Local government actions are motivated by local needs to a large

extent. In addition, when agencies need one another, cooperation between them increases. This means that steering mechanisms should probably look different, depending on the local situation.

• Political ideology does not play an important role in local government

actions in small entities. But in large entities partisanship has a pro-found impact. Thus, coordination procedures should most likely take different forms in large and in small entities.

• A high level of cooperation between units of government can improve

public policy implementation. But whether this actually is the case will depend on how complex the task is. Policies that are not particularly complex are not carried out better as a consequence of collaborative endeavors. As complexity increases, it becomes more important that agencies actually work together if the central govern-ment wants to achieve its policy ambitions.

The governance literature claims that multi-level and multi-jurisdictional governance is the norm rather than the exception. Whether this is true or not, and whether this is something really new, is debatable. But in any case, the scope and focus of governing will often involve an intergovernmental dimension. I have provided information on what is actually going on at local level. How these facts should be valued from a public management per-spective is up to others. However, the findings can hopefully help us find the routes to better governance we all seeking so desperately.

Introduction

34

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Lundqvist, Lennart J. 2001. Implementation from above: The ecology of power in Sweden’s environmental governance. Governance 14(3):319–37.


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Matland, Richard E. 1995. Synthesizing the implementation literature. The ambiguity-conflict model of policy implementation. Journal of Public Administration Research and Theory 5(2):145–74.

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———. 2003b. Implementation perspectives: Status and reconsideration. In Handbook of public administration, ed. J. Pierre and B. G. Peters, 212–22. London: Sage.

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2002/03:43

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Ministry of Employment. En jobbgaranti för ungdomar. Memorandum April 11, 2007.


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Appendix: A description of the questionnaire data The essays housed in this thesis are based on large-N data. Essays II and III rely heavily on new questionnaire data collected within the research project. The survey is only sketchily described in the essays. Thus, a somewhat more detailed description is offered in this appendix.

Design In February 2004, postal questionnaires were distributed to all PES offices and municipalities in Sweden.29 Three groups were approached: (i) PES managers, (ii) managers in charge of municipal labor market activities, and (iii) municipal politicians with formal responsibility for labor market issues. The preparation time was about six months and several persons commented on the questions and the design.30 The questions focused especially on the relationship between the PES offices and the municipalities, but various issues of local labor market activities were considered.

The addresses of the PES offices were taken from the webpage (http://www.ams.se) of the National Labor Market Administration: 366 workplaces were identified. The 290 municipalities were contacted in advance by telephone in order to locate the responsible politicians and managers. In the municipality of Stockholm, labor market operations are handled in 18 different offices organized geographically (kommundelar). This was recognized after data collection had started. Thus, I administered the survey by e-mail to the city districts of Stockholm. Three different forms were designed, one for each group of respondents. Three postal reminders and one reminder by phone were conducted. Data collection ended in May 2004.

Response rates The response rates were satisfactory (see Table A1). I removed eight PES offices from the original population. Some of these offices had been closed down or merged with other PES offices, while others only had support functions without responsibility for clients. About 75 percent of the 358 offices remaining in the population participated in the survey. In Stockholm, 56 percent of the municipal managers answered the questionnaire, whereas 85 percent of the managers in other parts of Sweden participated. Finally, 84 percent of the municipal politicians took part in the study.

29 The Institute for Labor Market Policy Evaluation (IFAU) financed the survey. ARS Research AB collected and registered the data. 30 Many thanks to Hanna Bäck, Hans Ekholm, Jörgen Hermansson, Vivi Libiets, Karl-Oskar Lindgren, Linus Lindquist, Daniela Lundin, Gunnar Myrberg, PerOla Öberg, Thomas Persson, and Michael Söderström for valuable comments.

Introduction

42

Table A1. Response Rates PES

Offices Municipalities

Managers Managers in Stockholm

Managers in other parts of Sweden

Politicians

Population 1 366 18 289 290

Removed from population 8 0 0 0

Population 2 358 18 289 290

Responses 268 10 246 245

Non-responses 90 8 44 45

Response rates (%) 75 56 85 84

Are non-responses worrisome? Although the response rates are good, it is worthwhile taking a closer look at respondents and non-respondents in order to find out whether it is reasonable to assume that the missing values have only a negligible impact on the findings. Below, I examine the four groups presented in Table A1.

A first step was to compare those who actually responded with the population in terms of background characteristics. If the respondents are similar to the populations, data are likely to be trustworthy. Table A2 pre-sents information on PES offices, while Table A3 deals with the municipalities.

Table A2. Background Characteristics: PES Offices (%) Population of

PES offices Responding PES offices

PES organized by area 83.9 87.2

PES located in large city (Stockholm, Gothenburg, or Malmoe)

23.8 19.2

PES located in rural areas 8.0 9.0

Municipal unemployment rate (including participants in ALMPs)

5.4 5.5

PES offices may be organized by area (geographically) or by function. Table A2 reveals that the responding group and the population are organized in a similar manner, although offices organized by function participate some-what less. Location is another factor to consider. The sample consists of fewer offices located in Stockholm, Gothenburg, and Malmoe. There is also a slight overrepresentation of offices in rural areas. These differences are,


43

however, not that large. Lastly, the average unemployment rate is very much alike in the respondent group and in the population.

Table A3. Background Characteristics: Municipalities Population Managers Politicians

Large city areas 13.5 14.9 12.8

Rural areas 20.4 20.7 19.3

Municipal unemployment rate (including participants in ALMPs)

5.3 5.3 5.3

Socialist chairman of the municipal executive board

59.3 58.4 59.0

Population over 65 years of age 19.0 18.9 19.0

Population with foreign citizenship 1.9 1.8 1.9

Number of inhabitants 30,830 28,367 32,499

Note: The figures are reported in percentages except in the case of “Number of inhabitants.”

Table A3 provides variables that make it possible to compare the municipalities participating in the survey with the whole population of municipalities. The responding groups are very similar to the population on all characteristics.

The telephone reminder made it possible to learn more about the non-responses (see Table A4). The interviewers’ first task was to remind the managers and politicians of the questionnaire. Officials that declared that they were not willing to participate in the survey were given the opportunity to answer a couple of questions by telephone instead. Around 40 percent of the PES managers, 43 percent of the municipal managers, and 31 percent of the politicians agreed to answer telephone questions (these answers are discussed later on; see Tables A5–A7). Thus, only 54 PES managers, 25 municipal managers, and 31 municipal politicians did not participate at all.

The non-participants are divided into four subgroups. The interviewers were unable to reach some individuals (no contact), even though they tried repeatedly. The elected representatives were hardest to get in touch with, but note that 56 percent only implies 25 persons. Some officials were reminded about the study and said that they were going to participate, but then never did (reminded but no questionnaire sent in). Another group consists of those who did not want to participate at all (not willing to participate). A very fre-quent reason for not taking part was lack of time. There is no indication that a high level of disputes between the authorities is an important reason for not participating, which is good. The last group of non-participants is tiny: vac-ant position, newly employed, or illness.

Introduction

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Overall, a heavy workload is probably a common reason for not participating. Admittedly, this could be a problem for data quality. It is difficult to have a specific opinion on whether, and if so in what direction, this implies biases. But recall that the non-participants are few. Accordingly, it is highly unlikely that the results are distorted to a significant extent.

Table A4. Information on Non-responses Collected through Telephone Calls (%) PES offices Municipalities Managers Managers Politicians

Non-participants 60 57 69 No contact (17) (0) (56) Reminded, but no questionnaire sent in (20) (21) (2) Not willing to participate (20) (36) (11) Vacant position, newly employed, or

illness (3) (0) (0)

Responding to phone questions 40 43 31

100 n = 90

100 n = 44

100 n = 45

In Tables A5–A7, the results from the telephone questions are reported. The purpose was to be able to compare the answers from the telephone inter-views with the answers to the same questions in the postal questionnaire: if the responses differed systematically, the reasons for being skeptical towards the data would increase. It is reasonable to assume that the answers are re-latively comparable, although telephone interviews and postal surveys are not exactly the same thing.

Table A5 shows the results in the group of PES managers (36 managers answered the telephone questions). The first question concerned the number of employees. The offices are about the same size. The respondents were also asked if a certain caseworker was assigned the task of handling youth clients and the Activity Guarantee.31 The telephone calls and the postal questionnaire showed similar results. Respondents reported frequency of communication and the answers, once again, did not diverge to any notice-able extent. Moreover, the share of offices that had signed a collaborative contract with the municipality concerning youth and the Activity Guarantee was also more or less identical. Lastly, the respondents in both groups reported the same levels of conflict.

31 The Activity Guarantee is a labor market program for clients with severe difficulties on the labor market; see Essay III for details on youth programs and the Activity Guarantee.


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Table A5. PES Managers’ Responses to Some Questions on Local Labor Market Policy (%)

Postal questionnaire

Telephone interviews

Average number of employees 22 25 Caseworker with responsibilities for unemployed youth

82 81

Caseworker with responsibilities for the Activity Guarantee

92 86

Daily contacts with the municipality 51 61

Cooperative contract with the municipality: youth clients

77 78

Cooperative contract with the municipality: Activity Guarantee

78 72

No conflicts between the PES and the municipality in 2003

72 78

Table A6 reports the answers from municipal managers (19 managers participated). Three questions were asked.32 The findings show that the share of municipalities with a special labor market administration is lower, communication between the municipality and the PES is less frequent, and conflicts are fewer according to the participants in the telephone interviews. One logical interpretation is that municipalities that do not engage that much in labor market operations decided not to participate in the study. This is not a cause for concern since the non-responses in this group are so few.

Table A6. Municipal Managers’ Responses to Some Questions on Local Labor Market Policy (%)



Existence of a labor market administration

75 47

Daily contacts with the PES 56 21


48 74

32 Actually, a fourth question concerned the number of municipal employees working on labor market issues. It is obvious that the respondents interpreted this question very differently in the postal questionnaire. Thus, I have decided not to use this information in the essays within this thesis. But it can be mentioned that the average number of employees noted in the postal questionnaire is 12, while in the telephone interviews it is 9.

Introduction

46

Table A7. Municipal Politicians’ Responses to Some Questions on Local Labor Market Policy (%)



Social democrat 56 79 Communicates with the PES at least every month 84 79 Average number of hours devoted to labor market issues every month

17 14

Political parties at local level agree on labor market issues to a “fairly high” or “very high” extent

96 100


67 79

Note: The figures are reported in percentages except in the case of “average number of hours devoted to labor market issues every month”.

Table A7 shows the answers from municipal politicians (14 persons answered the telephone questions). The telephone respondents reported less communication with the PES, fewer hours per month devoted to labor market issues, and a lower level of conflict between the PES and the municipality. Thus, politicians who did not participate in the postal questionnaire were probably less involved in ALMPs. The differences are not as obvious as in Table A6 and there is no strong reason to assume that the non-responses imply a considerable setback.

Table A8. Background Characteristics of Districts within Stockholm (All 18 Districts and the 10 Responding Districts)

Population Respondents

Average age (years) 38.7 38.2

Unemployment (%) 3.1 3.3

Percentage of inhabitants receiving welfare benefits

6.7 8.2

Percentage of inhabitants with foreign citizenship 11.1 13.0

Number of inhabitants 42,119 38,358

Note: The calculations are based on figures taken from City of Stockholm (2004), Statistisk årsbok för Stockholm 2004, available at www.stockholm.se. Participants in ALMPs are not included in the un-employment rate.

Because the data collection in Stockholm was conducted separately, telephone reminders were not possible. Nevertheless, it is possible to com-pare some important characteristics of the population of city districts and the districts participating in the survey. Table A8 indicates that the respondents are quite similar to the population as a whole. To some extent, districts with


47

many welfare benefit recipients and inhabitants with foreign citizenship participated more.

To sum up, response rates were good. A detailed analysis shows that non-responses probably do not constitute a major problem. In the group in which non-responses are most frequent—among the PES offices—all analyses indicate that missing values are not a problem. Among the municipalities, it seems that those who did not answer the questionnaire are a little bit less involved in ALMPs. But since response rates are very good, this is not particularly worrisome.

49

Essay I

Political Partisanship and Entity Size: When Parties Matter for Public Policy*

Do political parties make a difference for public policy? Does it matter whether the left wing or the right wing governs? This puzzle has occupied the attention of numerous scholars in political science and related research disciplines for a long time. Cross-national, national, and subnational data from various policy areas have been employed to evaluate the importance of political parties. Some studies indicate an effect (for example, Besley and Case 2003; Korpi and Palme 2003; Petterson-Lidbom 2006), while others reject the idea that partisanship matters (for example, Ashworth and Heyndels 2002; Faust and Irons 1999; Garand 1988). It is sometimes suggested that the effect of partisanship is dependent on other factors (Brown 1995; Imbeau, Pétry, and Lamari 2001; Schmidt 1996). That is, parties may in some settings be of minor importance for output, but make a significant difference given other circumstances. This article contributes to the literature by studying one structural factor that might influence the effect of political partisanship on local government actions—the size of the local entity.

Local political entities within a political system have different sizes. For instance, in Sweden the lowest governmental tier (the municipal level) com-prises between approximately 2,500 and 775,000 inhabitants. It is reasonable to assume that politics looks rather different in small and large localities. The basic idea in this article is that politics, for several reasons, is usually more pragmatic, and party antagonisms are less pronounced, in small subnational entities. Thus, it is hypothesized that the effect of partisanship is larger in sizeable localities.

The empirical analysis concerns local government involvement in Swedish active labor market policy (ALMP). As in most other Western democracies, ALMPs are primarily a central government affair in Sweden. A large central government administration (the National Labor Market Administration) with local branches (Public Employment Service offices, * Helpful comments were given by Paula Blomqvist, Matz Dahlberg, Jörgen Hermansson, Nils Hertting, Karl-Oskar Lindgren, PerOla Öberg, and Sven Oskarsson.

Essay I

50

PES) implements political decisions on the ground. But local governments are also involved in local actions to a considerable extent (Carling and Larsson 2005; Lundin and Skedinger 2006; Lundin 2007; Salonen and Ulmestig 2004). ALMPs mainly benefit voters of left-wing parties. Thus, it is reasonable to expect local governments in which socialist parties are strong to be more engaged in the efforts to decrease unemployment. But if politics are more pragmatic in small entities, and if party politicization be-comes more important as entity size increases, a larger partisanship effect is probable in areas in which many people live.

The analysis is based on quantitative panel data, 1998–2005. This data set makes it possible to carry out rigorous empirical tests. The analysis indicates that the effect of partisanship on local government involvement in ALMPs really is contingent on entity size. Political partisanship makes no difference in very small localities. As population size increases, partisanship begins to play a more significant role. In the group of local governments in which the population is really large, it matters a great deal who governs.

This research contributes to at least two important discussions in the literature. First, it suggests and tests one condition that can help us improve theory on when political partisanship makes a difference for public policy. It seems as if entity size—at least at local level—should be interacted with political partisanship. Ignoring interactions between partisanship and size could be a reason why some scholars have failed to identify a partisan effect. Second, within the “partisanship matters”-discourse some studies have analyzed the effects of partisanship on ALMPs using cross-national data (Hicks and Kenworthy 1998; Rueda 2005; Swank and Martin 2001; Vernby 2006). The findings are mixed. This might be a consequence of method-ological problems. In the present study, the number of observations is in-creased and I am able to hold country-specific attributes constant. Thus, the empirical test is probably more reliable. The findings suggest that scholars such as Rueda (2005) are wrong to claim that political partisanship does not affect the use of ALMPs.

The study is organized as follows: First, the theory is outlined. Second, the involvement of local governments in ALMPs is introduced. Third, I present the statistical model and measures. Fourth, findings are reported. I conclude by summing up the results and discussing possible implications.

Political partisanship and the size of local entities Political partisanship has been at the core of political science research for a long time. Studies such as Alt (1985), Downs (1957), Hibbs (1977), Korpi (1974), and Strom (1990) discuss why and to what extent we should expect parties to make a difference for public policy. It is generally agreed that the left–right political dimension is the most important aspect of political life.

Political partisanship and entity size

51

Basically, the left–right dimension boils down to views on the role of the government versus the market (Blais, Blake, and Dion 1993). Downscale social groups are the core constituency of the left wing, while the core constituency of the right wing is upscale groups. Parties are assumed to have goals related to those of their main voters.1 Accordingly, leftist governments will endorse the interests of labor, whereas right-wing ones will promote the interests of the self-employed and employed managers.

Left-wing parties and voters are normally assumed to be more positive towards government intervention (cf. Hibbs 1977). But why does the left have a more positive view of government intervention? Welfare policy can serve as an example. Korpi (2006, 173) holds that “while some life-course risks are generated by universal processes, most risks, such as those associated with aging, illness, work accidents, unemployment, poverty, and rearing of children, are instead unequally distributed among individuals occupying different positions in socioeconomic class structures.” The core voters of socialist parties are more exposed to most of these risks. In addition, they also tend to have fewer resources to cope with them. Accordingly, reducing the importance of market capacities for handling life-course risks is in the interest of the core constituency of the left. Government intervention, in the form of ambitious welfare programs, is therefore likely to be put into practice when the left wing holds office. On the other hand, upscale groups control major economic resources. They are expected to prefer market solutions to handle distributive processes since they have the economic capacity to participate in such markets. Consequently, low taxes and a relatively small welfare state are objectives of right-wing parties (Korpi 1974; 2006; see also Allan and Scruggs 2004 for empirical evidence).2

According to official documents, such as party manifestos, parties officially pursue different political objectives (Budge 2001). But empirical research seeking to estimate the impact of partisanship has produced mixed results. This is especially true if we consider studies focusing on national politics.3 On the other hand, recent research conducted on subnational data seems to corroborate the “partisan matters”-argument to a greater extent. For

1 Notice that the median voter theorem proposed by Downs (1957) suggests that vote-maximizing parties converge to the center in a two-party system (but not necessarily in multi-party systems). Thus, policies will be characterized only by the preferences of the median voter and the partisanship impact on public policy is likely to be tiny. But others have suggested that parties are not only vote seekers, but also policy seekers (for example, Strom 1990). Accordingly, in the words of Blais, Blake, and Dion (1993), it is “probably fair to predict that in most cases parties will propose moderately different policy packages” (41), and we should expect that “parties matter, but only moderately” (42). 2 Kato and Rothstein (2006), Pierson (1996), Swenson (1991), and Ross (2000) provide alternative views. 3 For an overview see Blais, Blake, and Dion (1993). For a meta-analysis, see Imbeau, Pétry, and Lamari (2001).

Essay I

52

example, analyzing Swedish municipalities, Petterson-Lidbom (2006) con-vincingly shows that left-wing governments spend and tax more than right-wing governments. Blom-Hansen, Monkerud, and Sorensen (2006) examine revenue policies in Danish and Norwegian municipalities and find that the left–right dimension explains local revenue policies to some extent, especial-ly in the Danish case. Allers, De Haan, and Sterks (2001) also find an effect of political partisanship on local taxes based on data from Dutch local governments. Besley and Case (2003) go through studies on US state data. They suggest that whereas older studies usually reject the partisanship hypothesis, recent studies support the argument to a greater extent.

An interesting contribution is Brown’s (1995) study of welfare efforts in US states. Brown argues that the parties’ voter basis varies among the states; partisan cleavages look different in different environments. He predicts and finds a large impact of partisanship on welfare efforts only in the group of states where the Democratic Party are supported mainly by Catholic, low-income, union, and female groups. What is interesting about the study for our present research is that Brown suggests that political realities are differ-ent in different subnational entities. In turn, this should lead us to assume that the influence of partisanship varies with other structural factors.4

In this article, in which the focus is the local political level, our main interest is a possible interaction term of partisanship and local entity size. By size I mean the number of local inhabitants. My claim is that politics is more pragmatic in small localities; parties agree to a greater extent and we should not assume that political partisanship makes a major difference. The impact of partisanship is expected to increase with population size; pragmatism de-creases, opinions diverge, and, as a consequence, it matters more how power is distributed along the left–right political dimension.

Why should we assume that pragmatism is more frequent in small local entities? A number of arguments are relevant. First, in large localities the representatives decide on bigger issues that concern more people and involve more money. Party organizations at local level—and at higher levels of government as well—are likely to be more interested in these distributive processes than when decisions are less important. Greater activity within political parties makes it more difficult to agree across party boundaries. Second, Dahl and Tufte (1973) argue that an increase in size implies an increase in attitudinal diversity. Accordingly, the population is expected to be more homogenous in small entities. This is likely to imply less an-tagonism among political parties. Most certainly, feelings of togetherness produce pragmatism. Third, specialization and internal diffusion of re-sponsibilities are greater in large localities (see for example, Petersson 1994,

4 In addition, Schmidt (1996) and Imbreau, Pétry, and Lamari (2001) propose that interactions between partisanship and other structural factors should have a more prominent place in future research on the effects of partisanship.


53

49), and it is therefore reasonable to assume that elected representatives are less specialized in small entities, which probably increases the influence of the bureaucracy (and perhaps also organized interests). This may lead to party ideology having less impact on decisions. Fourth, in small entities the politicians are closer to the level at which things actually happen. Prag-matism may evolve as a consequence of greater contact with inhabitants affected by decisions. In areas in which many people live, there is a greater distance between elected representatives and street-level actions. Fifth, de-cision making normally involves fewer individuals in small entities. This could generate political processes that resemble rational deliberation rather than negotiations. If decisions are made in a deliberative manner, it is likely that the influence of party ideology will be somewhat less.

There is empirical evidence indicating that party-politicization is greater in large local entities. For instance, in Sweden the number of local govern-ments has decreased significantly, from about 2,500 in 1952 to 290 in 2007. An extensive research program has evaluated the major reform between 1962 and 1974: one of the most important conclusions was that party-politicization had increased, for example, in the form of more conflicts of interest between political parties (Strömberg and Westerståhl 1983). Moreover, a recent study on size and democracy on Swedish municipal data shows that clashes of opinion are more frequent among political parties in large than in small localities (Johansson and Karlsson, forthcoming). Given the theoretical arguments and the empirical evidence, a greater impact of political partisanship should be expected in sizeable entities.

Local governments and active labor market policy in Sweden Swedish local governments (or municipalities) have the constitutional right of local self-government and an essential political and economic role. In comparative perspective, local governments in Sweden are often considered important (Lidström 1996). The municipalities are relatively large, with an average population of approximately 30,000 citizens, and provide a lot of services of the welfare state, including day care, care of the elderly, social welfare services, and primary education. Their revenues come mostly from a proportional income tax, which they can set freely. In addition, municipalities decide on their own organization and have no restrictions on borrowing. Municipalities also employ a large share of the Swedish workforce, approximately 20 percent.5

5 For descriptions of Swedish local politics, see Hanna Bäck (2003), Henry Bäck (2003), and Montin (2002).

Essay I

54

When it comes to local party politics in Sweden, Henry Bäck (2003) argues that parties have an important role in local governance and that the left–right dimension dominates political life. In addition, Hanna Bäck (2003, 63–65) shows convincingly that a left–right policy dimension describes local politics well, although there is also a green dimension. Nevertheless, some case studies indicate that ideological overtones sometimes are not that pronounced; consensus among politicians across party boundaries is not rare (for example, Henry Bäck 2003).

Municipalities implement many policies within the welfare sector. But ALMPs are mainly a responsibility of the PES offices, located within the National Labor Market Administration. ALMP refers to activities, such as labor market programs and job search assistance, targeted at the unemployed with the aim of increasing employment. A range of different programs are available, including labor market training, work practice, and subsidized employment (Calmfors, Forslund, and Hemström 2002). In comparative perspective, Sweden spends a lot on ALMPs (Martin and Grubb 2001).

Local resources, such as information and expertise, are important when ALMPs are carried out in practice (cf. O’Toole 1983). For instance, in order to be successful the PES offices need to know local development plans and what kind of training to provide. The PES offices also need places of work where unemployed clients can apply for jobs or participate in on-the-job training. In addition, labor market activities have to be coordinated with other policy areas, such as social policy, policies for immigrants, local development, and education—policies that are all municipal responsibilities. In short, PES offices are dependent on the local environment in carrying out their tasks. In these local environments, municipalities are central actors.

The municipalities are engaged in ALMPs to a considerable extent, and most of them have instigated labor market administrations (Swedish Association of Local Authorities 1999). Municipalities take part in various collaborative endeavors together with the PES offices (Lundin 2007) and, in fact, they arrange the activities for approximately 40 percent of the particip-ants in the National Labor Market Administration’s active measures (Lundin and Skedinger 2006). Diverse youth programs (Carling and Larsson 2005) and programs for social allowance recipients (Salonen and Ulmestig 2004) are examples of activities in which the municipalities are heavily involved.

But why are municipalities engaged in ALMPs? Wetterberg (1997, 91) provides three key reasons. First, unemployment has a significant impact on the municipalities’ finances since the local tax base decreases as unemploy-ment increases. This can be especially critical if unemployment also leads to out-migration. Second, the municipalities have to bear costs when the un-employment rate increases, for example, in the form of increased ex-penditures for social allowances. Third, unemployment means a worsening of national public finances. Wetterberg claims that the central government tries to pass on costs to the municipalities when public finances are bad. This


55

gives the municipalities incentives to fight unemployment. And it would be easy to come up with additional problems for municipalities brought about by unemployment.6

0

1020

30P

erce

nt

0 500 1000 1500 2000Expenditures (crowns per inhabitant)

Figure 1. The Variation in Municipal Expenditures on ALMPs in 2005 (Source: Statistics Sweden).

The extent to which municipalities are involved in ALMPs is not the same everywhere in Sweden. For example, Lundin (2007) shows that cooperation between PES offices and municipalities varies. Moreover, local government expenditures on ALMPs fluctuate. Figure 1 shows the variation in local government spending on labor market programs in 2005. The bulk of municipalities use between 500 and 750 crowns per capita on ALMPs, but there is a large variation, ranging from approximately 20 crowns to 2,220 crowns per citizen.

It is reasonable to expect that political partisanship is one factor explain-ing the pattern in Figure 1. ALMPs have always been associated with social democracy in Sweden. The National Labor Market Administration was built up by the social democratic government around 1950, and the recruitment and training policy secured a staff that was committed to the overall objectives stipulated by the Social Democrats (Rothstein 1996). Leftist

6 For instance, evidence from Sweden indicates that unemployment leads to an increase in crime (Nilsson and Agell 2003).

Essay I

56

governments have emphasized large-scale programs and a lot of financial resources have been allocated to the National Labor Market Administration. With assistance from the Left Party, the Social Democrats have been in power at central level for long periods in Sweden: between 1956 and 2006 the Prime Minister was a social democrat in 41 out of 50 years. Con-sequently, they have had a great deal of influence over labor market policy.

On the other hand, right-wing parties, mostly in opposition, have argued for cutting down on ALMPs, privatizing some parts of the policy, increasing incentives to take a job by decreasing unemployment benefits and taxes on work, lowering payroll taxes, and making laws on job security more flexible. This can be illustrated by the actions of the right-wing coalition that came to power after the election success in autumn 2006. Quickly after gaining office, the coalition of the Moderate Party, the Centrist Party, the Liberal Party, and the Christian Democratic Party decreased unemployment insurance benefits (Government Bill 2006/07:15) and the budget for ALMPs (Government Bill 2006/07:1).

Table 1. Opinions on ALMP Expenditures in Sweden 2002 (%) The amount of tax money used

for ALMPs should be...

Party sympathy Increased Unchanged Decreased Total

Left-wing 46 46 8 100 (370)

Right-wing 25 40 35 100 (274)

Note: The table is based on the data set Opinions on the public sector and the taxes 2002 (Åsikter om den offentliga sektorn och skatterna 2002) collected by Stefan Svallfors and Jonas Edlund, Department of Sociology, Umeå University. Data have been made available through the Swedish Social Science Data Service (SSD). The original researchers and SSD are not responsible for the analysis and the interpretation of the results. The survey was conducted among 2,000 individuals and the response rate was about 57 percent. Left is defined as persons who think that the Social Democratic Party or the Left Party is the best party. Right is defined as persons who think that the Moderate Party, the Centrist Party, the Liberal Party, or the Christian Democratic Party is the best party. Individuals who do not have sympathy for a certain party and individuals who adhere to a party other than those mentioned in the table are excluded from the analysis. The chi-square statistics indicate that a significant relationship exists (at least at the .01 level) between party sympathy and opinions about ALMP spending. Another question in the survey concerned ALMPs: “Would you be ready to pay more tax if you were sure that the money would be devoted to creating new jobs?” The findings are very similar if the analysis is based on this question instead.

Another indication that ALMP is a policy area involving a left–right dimen-sion is provided in Table 1. The table displays opinions on ALMP spending among a representative sample of Swedish inhabitants in 2002. It is obvious that persons who sympathize with the left are more positive towards ALMPs. More than four times as many of the persons that adhere to the right wing think that expenditures on ALMP should be reduced. In the next


57

section, I examine whether partisanship influences policy in reality and if the effect is contingent on population size.

Method and measures The empirical tests are based on a pooled cross-sectional panel design of 276 Swedish municipalities from 1998 to 2005.7 During the time period at issue, Sweden had a social democratic government. It was a minority government supported on most questions by the Left Party and the Green Party. Elections were held at the central and local levels in autumn 1998 and 2002. The total number of observations is 2,208 and I used Ordinary Least Squares (OLS) regression to estimate the model. In what follows, I present the variables and the statistical modeling strategy. Descriptive statistics are reported in Table 2.8

To assess local government involvement in ALMPs, the amount of financial resources the municipalities devote to labor market activities is utilized. The variable is measured in Swedish crowns per inhabitant.9 It is reasonable to assume that the more money the municipalities expend on ALMPs per capita, the more involved they are in the policy area. The measure includes all municipal expenditures on ALMPs. The municipalities can arrange diverse forms of programs. It is not possible to illustrate the typical municipal program since the duration of programs and their content vary to a considerable extent. But job search assistance and work practice programs are common examples. Unemployed youth and social allowance recipients are often the target groups.

Figure 1 shows that the expenditures on ALMPs are positively skewed. The observations are not evenly distributed around the mean value—some municipalities spend much more than others. The pattern is not altered if other years within the time frame are examined. This means that OLS assumptions may be violated. In the analyses to follow, I use the natural logarithm of the expenditures as the dependent variable. This variable, which I call Log(ALMP spending), is more normally distributed. Nevertheless, the analyses have been conducted on the unmodified variable as well—the con-clusions remain the same, although the findings are somewhat less robust. 7 There are 290 municipalities in Sweden: 14 municipalities are not included in the analysis due to missing values on some key variables in some years. 8 The local unemployment rate is based on data from the National Labor Market Admini-stration. All other variables are taken from Statistics Sweden. 9 Unfortunately, I do not have data on municipal expenditures on ALMPs in 1998. But information from 1997 and 1999 is available. By intrapolation—that is, taking the mean value of 1998 and 1999—reasonable estimations of expenditures in 1998 are obtained. In addition, I have conducted a number of analyses using data from 1999–2005, and also analyses using data from 1997 and 1999–2005. The conclusions are the same, although some findings are less robust.

Essay I

58

The main independent variable is partisanship. If we assume that parties can give fuller expression to their ideology as their position becomes stronger, the proportion of seats held in the local council by the left seems like a reasonable operationalization of the main independent variable (cf. Blom-Hansen, Monkerud, and Sorensen 2006). But there are other ways of measuring the strength of the left and the right. One possibility is to focus on whether the left wing or the right wing has the majority of seats in the local council. Another option is to concentrate on what party the chairman of the local executive board represents. In this article, the percentage of seats in the local council is utilized. The other two possible measurements are employed as robustness checks.

But what parties should be considered leftist parties? The standard approach when studying Swedish municipalities is to treat the Social Democratic Party and the Left Party as socialist parties (cf. Pettersson-Lidbom 2006). The right-wing bloc consists of the Conservative Party, the Centrist Party, the Liberal Party, and the Christian Democratic Party. I rely on this classification. Accordingly, partisanship is defined as the percentage of seats in the local council held by the Social Democratic Party and the Left Party.10 The more seats these parties control, the stronger the left wing is assumed to be. Another thing must be noted: elections were held in 1998 and 2002. Thus, there are only two temporal shifts in the variable. This means some restrictions on the analyses to follow, which I will return to later.

Population size is an important variable in this study. Thus, the natural logarithm of the number of citizens (in thousands of inhabitants) is included in the empirical model. It is logical to use the logarithm since a one-unit change in the number of inhabitants is probably more important when the municipality is small than when it is large. I call the variable Log(size). In order to find out whether the effect of partisanship is dependent on entity size, an interaction term of the variables partisanship and log(size) is also computed.

Several control variables are added. Local needs may explain municipal engagement in ALMPs. The most obvious control is therefore unemploy-mentt-1. This is the percentage of municipal citizens, aged 16–64, who are unemployed or taking part in labor market programs. It is an annual average based on monthly data. In order to lessen the problems of causal order, the 10 The Green Party is also represented at the local level. Although the Green Party has collaborated with the Social Democratic Party at the central level to a large extent, it is not a socialist party in the same sense as the Social Democratic Party and the Left Party. But I have conducted a number of analyses in which the Green Party is treated as a socialist party. Other analyses include a dummy variable when the Green Party holds the balance of power in the local council. Results are robust. In some local councils, local parties control some of the seats. These parties are usually small and often one-issue parties. Sometimes they hold the balance of power. I am not able to classify the local parties along the left–right dimension, but including a dummy variable measuring whether there is a local party that holds the balance of power does not change the results substantially.


59

unemployment rate is lagged one year.11 The unemployment rate is normally included in studies on expenditures on ALMPs based on cross-national data (for example, Rueda 2005; Swank and Martin 2001; Vernby 2006).

Table 2. Descriptive Statistics Variables Mean /

Proportion SD Min Max

ALMP Spending 555.52 327.23 20.00 3036.00

(Log)ALMP Spending 6.13 0.65 3.00 8.02

Partisanship 47.25 11.44 11.11 82.86

(Log)Size 2.92 0.89 0.94 6.67

Unemployment 7.18 3.24 1.30 23.81

Low education 23.30 6.01 4.85 41.75

Elderly inhabitants 19.03 3.68 7.74 29.99

Female 50.00 0.83 45.99 52.96

Foreign 3.97 2.77 0.70 29.26

Metropolitan 0.14 – – –

Sparsely populated 0.11 – – –

Population change 99.81 0.97 94.01 104.48

Social allowances 7.68 4.13 1.01 34.78

Tax income 108.21 19.03 71.45 256.75

State subsidy 6.61 4.50 -15.52 23.94

Note: Proportions are given in italics.

A number of measures assess the structure of the local population. The demand for services may differ depending on what inhabitants live in the municipality. The various political parties also have different levels of support in different population groups. I incorporate low education, which is the percentage of citizens aged 25–64 with an educational level lower than high school. The percentage of the population 65 years of age or older (elderly inhabitants), the percentage of females, and the percentage of inhabitants with foreign citizenship are additional controls.

In the districts of the three largest cities in Sweden—Stockholm, Gothenburg, and Malmoe—the labor market looks rather different than in

11 Note that the population, rather than the work force, is the denominator when the National Labor Market Administration calculates unemployment figures based on their administrative system. The official unemployment figures, provided by Statistics Sweden, are based on the work force. But these figures are not available at the municipal level. The population 16–64 years of age is, of course, larger than the work force. Thus, the unemployment rate (including program participants) is smaller than the figures usually discussed. This does not affect the analysis in this study.

Essay I

60

the rest of the country. A considerable part of the Swedish population lives in these metropolitan areas and there are probably many other local actors besides the local government with the ability and interest to engage in ALMPs. This might imply that local governments are less involved in ALMPs here than in the rest of the country, all else being equal. A dummy variable metropolitan is therefore entered into the model. Metropolitan areas include Stockholm, Gothenburg, and Malmoe, and suburbs in which at least 50 percent of the population commutes to one of these cities. On similar grounds, I control for sparsely populated areas. In these areas there are probably very few alternative actors to the local government. Municipalities with less than 20,000 inhabitants, with less than five inhabitants per square kilometer, are considered sparsely populated.

Population change is another control variable. It is possible that municipalities facing a decline in population engage in ALMPs in order to stop out-migration (for a discussion, see Lundin and Skedinger 2006). Population change is defined as the population in a given year divided by the population the preceding year, multiplied by 100. Thus, a value of 100 implies no change in population, whereas values above 100 mean an in-creasing, and values below 100 a decreasing population.

I also incorporate expenditures for social allowancest-1 in hundred crowns per citizen as a control. ALMPs may be used to reduce the number of per-sons living on social allowances and, as a consequence, decrease such costs for the municipalities (Lundin and Skedinger 2006). Accordingly, large social allowance expenditures one year may trigger municipal involvement in labor market activities the next year.

The control variables presented above can together be classified as diverse forms of local needs. Besides needs, municipal capacity to engage in ALMPs may be important. More resources imply a greater ability to get involved. The variables tax incomet-1 (the tax income per inhabitant in 1,000 Swedish crowns) and state subsidyt-1 (general subsidies from the central government in 1,000 Swedish crowns per inhabitant) are therefore entered into the model specification. Both variables are lagged one year to reduce problems of causal order.

The basic statistical model also includes year dummies to deal with time effects. The year dummies take care of inflation, macroeconomic shocks, and other problems of contemporaneous correlation.

The pooled cross-sectional design implies several advantages. For ex-ample, more observations can be utilized and rigorous model specifications are possible. Another benefit is that it is possible to control for unit specific effects by including a full set of municipal dummy variables (that is, the fixed effects approach). Fixed effects take all hard-to-measure variables that


61

do not change over time into account.12 One problem is that fixed effects consume a lot of degrees of freedom, which is especially cumbersome if key variables do not vary that much over time (see, for example, Gujarati 2003; King 2001). This is precisely the case here. It is therefore possible that there is not enough variation over time in the political partisanship to detect a statistically significant effect. In this article, I present models both with and without fixed effects.

Two common problems with pooled cross-sectional data are autocorrelation and panel heteroscedasticity. This means that significance testing becomes unreliable. I use three different approaches to counter auto-correlation and heteroscedasticity. Robust standard errors clustered on municipalities (Froot 1989; Kezdi 2004) and standard errors based Newey and West’s heteroscedasticity and autocorrelation consistent covariance matrices (Newey and West 1987) with two lags13 are the first two methods. The third method is to control for the amount of resources devoted to ALMPs in the preceding year, that is, the lagged dependent variable. This eliminates problems of autocorrelation. In the specifications that include the lagged dependent variable, robust standard errors14 are used to reduce the problems of heteroscedasticity.

The model specifications that include the lagged dependent variable imply very hard statistical tests, especially since the temporal variation within municipalities in the main independent variable is very small. This means that we are running a large risk of rejecting a hypothesis that we should not reject, only because there is too little variation in partisanship. Furthermore, adding a lagged dependent variable means that the analysis focuses on short time effects, despite the fact that we are more interested in a long-term equilibrium.15 It is likely that partisanship does not account for small annual changes, but makes a difference in the long run. Including the lagged dependent variable is therefore probably too demanding a test. But by

12 An alternative to fixed effects is the so-called random effects approach. This approach demands additional assumptions that are rarely tenable. A Hausman test indicated that random effects is not an appropriate method in the present research setting. 13 A rule of thumb suggested by Greene (2003, 267) is used to decide the number of lags. Findings are robust if the number of lags is set to three instead of two. 14 Instead of using robust standard errors, panel-corrected standard errors may be employed (Beck and Katz 1995). But simulation studies reveal that the panel-corrected standard errors perform poorly when there are few time periods and many cross-sections—robust standard errors are preferred in these situations (Moene and Wallerstein 2003). The present study is based on a relatively short time series. Accordingly, robust standard errors are more reliable. Note that findings are not changed if panel-corrected standard errors are used instead. 15 It is, however, possible to calculate the long-run effect of a permanent change in leftist mandates. This effect is given by βx /(1-βy-1), where βx is the regression coefficient of partisanship and βy-1 is the regression coefficient of the lagged dependent variable. For instance, given the results in Model 3a in Table 3, the long-run effect of partisanship is 0.9 percent.

Essay I

62

showing the results from various specifications we can get a sense of the robustness of the findings.16

Findings The empirical results are reported in Tables 3 and 4. In Table 3, it is assumed that the effect of partisanship is not affected by the size of the local entity. Table 4 examines whether the impact of political partisanship differs among small and large municipalities by including an interaction term between political partisanship and entity size. The regression coefficients times 100 denote the average change in percent in ALMP spending, given a one-unit increase in the independent variable, when all other variables in the model are held constant. Note that the specifications that include the lagged de-pendent variable illustrate short-run effects.

In Models 1a–3a, there is a positive and statistically significant (at least at the .05 level) impact of partisanship. This means that the effect is statistic-ally significant even when I control for the expenditures of the preceding year. Models 1a and 2a show that an increase of socialist seats in the local council by one percentage point increases average expenditures by about 0.8 percent, all else being equal. It is always difficult to evaluate the substantial importance of regression coefficients. If we focus on the mean expenditures on ALMPs—555 crowns per inhabitant—and assume a quite large increase of leftist seats by 5 percentage points, the predicted amount of money used on ALMPs increases to 577 crowns per inhabitant. I think that this is an important difference, although it probably not should be considered a very large impact. In Models 4a and 5a, unit specific effects are incorporated. The effect of political partisanship is close to zero—in fact, the coefficient is negative, although not statistically significant. As noted in the previous section, the fixed effects approach is very demanding. Tests indicated problems of multicollinearity in Models 4a and 5a. This is a probable reason why many coefficients are statistically insignificant. In sum, the overall impression from Models 1a–5a is that the impact of political partisanship is not completely robust.

I should not dwell on control variables, but some brief notes are appropriate. Not surprisingly, local needs are important. This is clearly illustrated by the fact that high unemployment boosts municipal involvement in ALMPs. An increase of unemployment by one percentage point increases the predicted expenditures by as much as 4–10 percent, depending on model 16 Note that including a lagged dependent variable in a model with a full set of unit specific dummies provides biased estimates (Nickell 1981). There are various procedures that can be used to reduce these problems, such as GMM estimators. But since the specifications that include the lagged dependent variable will be troublesome anyway, I do not make use of analyses that incorporates both the previous year’s expenditures and municipal fixed effects.


63

specification, holding all other variables constant. The effect is statistically significant at least at the .05 level in all specifications. Surprisingly, municipalities with more money use fewer resources per inhabitant on ALMPs, all else being equal. The effect of tax incomes is especially robust and is statistically significant at the .01 level in all model specifications. One possible explanation is that large tax incomes imply that the individuals living in the area are prosperous and that the demand for ALMPs is not that high.

I have conducted a large number of robustness tests. Some of these checks have been noted in the course of the article, while some others are briefly brought up here. First, dropping control variables does not make a substantial difference. Second, diagnostic plots showed some influential outliers. I have no obvious reason to exclude the outliers. Nevertheless, regressions where these observations are removed have been carried out and the results stay about the same. Third, various operationalizations of parti-sanship have been examined. If a dummy variable for a socialist majority is used as the indicator of political partisanship, instead of the percentage of seats, the effect becomes larger and even more robust. On the other hand, focusing on the chairman of the local executive board renders small and usually statistically insignificant regression coefficients.

In Table 3, I have not taken into account that the effect of partisanship may be contingent on population size. This may be an important reason why the findings are not robust. The purpose of the analyses presented in Table 4 is to find out whether this is the case.

The effects of the control variables are approximately the same in Tables 3 and 4. In addition, robustness checks indicate the same strengths and weaknesses as prior robustness tests. Thus, it is possible to go directly to the heart of Table 4, that is, the interaction term of partisanship and size. If the coefficient is positive and statistically significant there are good reasons to assume that politics matter more in large than in small municipalities. This is exactly the case. In all six models, the interaction term is positive and significant at least at the .05 level. This means that even the hard tests of Models 3b–5b indicate that the impact of partisanship varies with the size of the local entity.

But interaction effects, and statistical tests with interactive hypotheses are always conditional (Allison 1977; Friedrich 1982). In order to find out the details, it is therefore necessary to take the analysis a step further and cal-culate conditional effects and standard errors. That is, the impact of partisan-ship should be determined at various municipality sizes.

Tab

le 3

. The

Eff

ects

of P

artis

ansh

ip o

n M

unic

ipal

Invo

lvem

ent i

n A

LMPs

in S

wed

en, 1

998–

2005

(n =

2,2

08, S

tand

ard

Erro

rs in

Par

enth

eses

): A

dditi

ve

Reg

ress

ion

Mod

els w

ith L

og(A

LMP

Spen

ding

) as t

he D

epen

dent

Var

iabl

e

1a

2a

3a

4a

5a

Pa

rtisa

nshi

p 0.

008

(0.0

02)*

**

0.00

8(0

.002

)***

0.

001

(0.0

01)*

* –0

.002

(0.0

04)

–0.0

02(0

.003

)

Log

(Siz

e)

–0.0

54(0

.046

) –0

.054

(0.0

31)*

–0

.011

(0.0

12)

–0.0

98(0

.710

) –0

.098

(0.5

48)

Une

mpl

oym

ent t–

1 0.

094

(0.0

13)*

**

0.09

4(0

.009

)***

0.

016

(0.0

04)*

**

0.04

3(0

.016

)**

0.04

3(0

.012

)***

Low

edu

catio

n –0

.011

(0.0

08)

–0.0

11(0

.005

)**

–0.0

02(0

.002

) –0

.055

(0.0

23)*

* –0

.055

(0.0

17)*

**

Elde

rly p

opul

atio

n –0

.019

(0.0

13)

–0.0

19(0

.009

)**

–0.0

05(0

.004

) –0

.032

(0.0

30)

–0.0

32(0

.022

)

Fem

ale

0.00

5(0

.035

) 0.

005

(0.0

26)

–0.0

03(0

.010

) –0

.006

(0.0

31)

–0.0

06(0

.026

)

Fore

ign

0.02

1(0

.014

) 0.

021

(0.0

09)*

* 0.

003

(0.0

02)

–0.0

17(0

.032

) –0

.017

(0.0

23)

Met

ropo

litan

–0

.274

(0.1

01)*

**

–0.2

74(0

.069

)***

–0

.067

(0.0

28)*

* 0.

056

(0.7

91)

0.05

6(0

.609

)

Spar

sely

pop

ulat

ed

0.36

5(0

.139

)***

0.

365

(0.0

92)*

**

0.06

7(0

.032

)**

0.28

9(1

.961

) 0.

289

(1.4

76)

Soci

al a

llow

ance

s t–1

0.01

7(0

.008

)**

0.01

7(0

.005

)***

0.

003

(0.0

03)*

–0

.004

(0.0

09)

–0.0

04(0

.006

)

Popu

latio

n ch

ange

–0

.005

(0.0

25)

–0.0

05(0

.021

) –0

.006

(0.0

12)

–0.0

19(0

.016

) –0

.019

(0.0

14)

Tax

inco

me t–

1 –0

.017

(0.0

05)*

**

–0.0

17(0

.004

)***

–0

.004

(0.0

01)*

**

–0.0

20(0

.007

)***

–0

.020

(0.0

05)*

**

Stat

e su

bsid

y t–1

–0

.043

(0.0

17)*

* –0

.043

(0.0

12)*

**

–0.0

11(0

.004

)**

–0.0

11(0

.017

) –0

.011

(0.0

13)

Log(

ALM

P sp

endi

ng t–

1)

0.

855

(0.0

29)*

**

Con

stan

t 7.

297

(3.4

13)*

* 7.

297

(2.7

56)*

**

1.65

8(1

.387

) 11

.856

(3.5

47)*

**

11.8

56(2

.939

)***

Stan

dard

err

ors

Clu

ster

ed

New

ey-W

est

Rob

ust

Clu

ster

ed

New

ey-W

est

Mun

icip

al d

umm

ies

No

No

No

Yes

Y

es

Yea

r dum

mie

s Y

es

Yes

Y

es

Yes

Y

es

Adj

uste

d-R

² 0.

42

0.42

0.

83

0.81

0.

81

* p

< .1

0; *

* p

< .0

5; *

** p

< .0

1.

Tab

le 4

. The

Eff

ects

of P

artis

ansh

ip o

n M

unic

ipal

Invo

lvem

ent i

n A

LMPs

in S

wed

en, 1

998–

2005

(n =

2,2

08, S

tand

ard

Erro

rs in

Par

enth

eses

): R

egre

ssio

n M

odel

s with

Log

(ALM

P Sp

endi

ng) a

s the

Dep

ende

nt V

aria

ble

and

Incl

udin

g an

Inte

ract

ion

Term

bet

wee

n Pa

rtisa

nshi

p an

d Lo

g(Si

ze)

1b

2b

3b

4b

5b

Pa

rtisa

nshi

p –0

.019

(0.0

08)*

* –0

.019

(0.0

06)*

**

–0.0

03(0

.002

)*

–0.0

15(0

.008

)*

–0.0

15(0

.007

)**

Log

(Siz

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< .0

1.

Essay I

66

Table 5. Conditional Effects of Political Partisanship on ALMP Spending Model Municipality size 1b and 2b 3b 4b and 5b

Small: 5,000 citizens Log(size) = 1.609

–0.003 (0.004)[0.003]

–0.001 {0.001}

–0.007 (0.005) [0.004]

*

Medium: 30,000 citizens Log(size) = 3.401

0.015 (0.003)[0.002]

*** ***

0.003 {0.001}

***

0.002 (0.004) [0.002]

Large: 100,000 citizens Log(size) = 4.605

0.027 (0.006)[0.004]

*** ***

0.005 {0.002}

***

0.008 (0.005) [0.005]

Very large: 450,000 citizens Log(size) = 6.109

0.042 (0.009)[0.006]

*** ***

0.008 {0.003}

***

0.015 (0.009) [0.008]

* *

Note: Clustered robust standard errors are provided in parentheses, standard errors based on the Newey-West procedure are given in square brackets, and robust standard errors are presented within curly brackets. The conditional effects are given by βpartisanship + βpartisanship x Log(size) × Log(size). See Allison (1977) and Friedrich (1982) for more thorough discussions on conditional effects and how to compute the standard errors of these coefficients.

* p < .10; ** p < .05; *** p < .01.

Table 5 reports the importance of partisanship as municipality size varies. I present the effects at four arbitrarily selected unit sizes between 5,000 and 450,000 citizens. The table makes clear that the effect of partisanship increases significantly with size of municipality. In small municipalities the average impact is more or less zero. In middle sized municipalities, the effect is quite small and in some specifications statistically insignificant at conventional levels. In municipalities with a population size of 100,000 inhabitants, the average impact is more substantial although not statistically significant in Models 4a and 5a. Lastly, in very large municipalities political partisanship plays a considerable role. An increase in the number of socialist seats in the local council of one percentage point increases the average expenditures on ALMPs by around 1.5–4.2 percent, holding everything else constant. This implies that if the leftist parties strengthened their position in the local council by five percentage points—a quite large but not uncommon change between two elections—the predicted amount of resources devoted to ALMPs would increase by 7.5–21.0 percent, all else being equal.

To conclude, the overall impression is that the hypothesis that political partisanship matters more in large local entities receives quite empirical strong support. Nevertheless, it must be acknowledged that the fixed effects approach suggests a smaller effect than the other model specifications, and demands a greater population size before the effect is statistically sig-


nificant.17 But there are problems of multicollinearity in Models 4b and 5b. This is a common setback in specifications including interaction terms. The large number of dummy variables amplifies the problem. This is probably the reason why the effect is statistically significant only given a very large population.

Conclusion It is difficult to imagine a modern democratic state without political parties. Parties structure the political world, recruit political elites, offer a linkage between ruled and rulers, and aggregate citizens’ interests. In this article, I have examined the hypothesis that political partisanship affects public policy to a greater extent in large local entities than in small ones. Empirically, the study has considered municipal involvement in labor market activities at local level in Sweden. I show that partisanship makes no important difference in small entities, but as population size increases partisanship becomes a relevant factor. A strong left wing boosts expenditures on labor market programs, especially when the number of local inhabitants is very large. Thus, the study offers conditional support for the “partisan matters”-argument.

The pooled cross-sectional design provides great opportunities to control for alternative explanations and the results appear to be quite robust (alt-hough there are some caveats). In future research, scholars interested in the effects of political partisanship on public policy should recognize the possibility of an interaction effect between partisanship and population size. Previous failures to identify an impact may have been a consequence of a misspecified model. And scholars who have indicated an effect could per-haps have refined their claim by examining interactions.

More research in various settings is needed, of course, before we can be certain that political partisanship has a larger effect on public policy when the population is sizeable. But the theoretical statements are general, so there is no strong reason to assume that the idea does not apply in other settings. However, the empirical findings in this study can be generalized primarily to countries in which local governments are relatively autonomous—for example, other Nordic countries—and to policy areas in which there is a clear left–right political dimension.

Nevertheless, it would be interesting to see if the findings hold in countries in which the local level has less autonomy and in policy areas in

17 Model 1b suggests that there is a positive and statistically significant effect at the .10 level when the population consists of approximately 11,000 citizens or more. The corresponding number of citizens if the estimates from the other models are used is 10,000 (Model 2b), 13,000 (Model 3b), 232,000 (Model 4b), and 116,000 (Model 5b).

Essay I

68

which the left–right dimension is not as evident. Another thing worth paying attention to is the causal mechanism. I have outlined a couple of arguments for why partisanship should make a bigger difference in large local entities. But I have not examined these mechanisms empirically. A relevant task for future research is therefore to find out what mechanisms are at work. Moreover, size is not the only variable that might interact with partisanship. Further development of theoretical and empirical research would involve searching for additional factors that impinge on the impact of partisanship.

ALMPs make up a large part of the welfare state in many advanced industrialized countries today (Martin and Grubb 2001). Thus, some studies have tried to spot the factors that affect ALMP expenditures using cross-national data. Political partisanship is a key variable. The findings are not decisive. Hicks and Kenworthy (1998) suggest a positive impact. But the conclusion is based on a small sample, and the effect is only statistically significant given a one-tailed significance test at the .10 level. Swank and Martin (2001), Rueda (2005), and Vernby (2006) provide more reliable evidence. Only the study by Swank and Martin indicates a positive and significant effect. Thus, it seems that we do not really know if partisanship influence ALMPs. This is troublesome. But the findings in the present study are helpful. If we assume that policy decisions in large municipalities can be compared to national level proceedings, there are reasons to assume that partisanship impinges on ALMP expenditures, even at the national level.

To my knowledge, the effect of political partisanship on ALMP spending has not been evaluated using local government data. I realize that local governments are not directly comparable with central governments, but this approach has a number of advantages. The Swedish case is probably especially useable since the municipalities are rather large and have a lot of autonomy (cf. Hanna Bäck 2003; Petterson-Lidbom 2006). Local level data imply that I can hold all country specific effects, such as institutional and cultural characteristics, constant. The number of observations becomes much greater too. This improves the possibilities of hypothesis testing and ex-amining rigorous model specifications. Furthermore, measurement errors are probably fewer if we focus on one country instead of many.

Lastly, it is worth briefly discussing the findings from a democratic per-spective. Local self-government is often considered valuable in promoting democracy. Local citizens should be allowed to affect activities in their own districts. If it does not matter who governs at local level, as in the case of small entities, this might be a problem. On the other hand, it is possible to contend that it is good that local partisanship does not matter in this particular case. ALMP is a central government policy domain which is supposed to be controlled by the central government. How the policy should look should be decided in national elections. And policies ought to be implemented in a consistent manner in order to guarantee that the ideas of the central government are realized and to promote uniform treatment of


clients around the country. According to this perspective, local variations should be dependent on local needs rather than on local politics. Thus, it could be argued that the problem is the partisanship effect in large entities rather than lack of partisanship effect in small entities. I conclude with these normative implications. The study contributes to the discussion by providing the necessary facts. How the facts should be evaluated is up to others.

Essay I

70

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Essay II

Explaining Cooperation: How Resource Interdependence, Goal Congruence, and Trust Affect Joint Actions in Policy Implementation*

To understand what is going on when public policies are carried out at local level, interorganizational relationships have to been taken into account (see for example, Bardach 1998; Hjern and Porter 1981; O’Toole and Montjoy 1984). Many challenges facing modern societies—such as fighting poverty or reducing unemployment—are difficult to manage within a single public authority. The virtues of interorganizational cooperation have therefore been emphasized in implementation research ever since Pressman and Wildavsky’s (1984) pioneering study of a public labor market program in Oakland in the 1960s. Laurence O’Toole (2003, 237) concludes that “the topic of interorganizational relations will remain important for admini-strators tasked with helping to make policy implementation succeed. Accordingly, it is critical to understand how to make sense of such in-stitutional settings for improving prospects for implementation success.” This article contributes to the discourse by presenting evidence on how resource interdependence, goal congruence, and trust affect cooperation between agencies in local policy implementation.

According to research on interorganizational relationships, mutual re-source dependence and congruent goals are among the most important antecedents to cooperative behavior. In a situation of mutual dependence, organizations will cooperate in order to exchange resources that make it

* A slightly different version of this article has been accepted to be published by the Journal of Public Administration Research and Theory (Oxford University Press) and will appear in a forthcoming issue. I would like to thank Paula Blomqvist, Matz Dahlberg, Jörgen Hermansson, Björn Lindberg, Nils Hertting, Andreas Lindemann, Karl-Oskar Lindgren, Daniela Lundin, PerOla Öberg, Sven Oskarsson, and Soren Winter for comments on earlier drafts of this article. Several participants at the seminars held at the XIV Nordic Political Science Association (NOPSA) Conference, Reykjavik 11–13 August 2005, and at the Department of Government, Uppsala University, 26 September 2005 contributed to this research as well. I would also like to thank Carolyn Heinrich, the editor for Journal of Public Administration research and Theory, and the two anonymous referees for very useful suggestions.

Essay II

76

possible to achieve organizational goals, whereas shared interests and a similar commitment to a policy make it easier to get along and can generate joint struggles (O’Toole 2003, 239–42). Another important finding is that mutual trust increases cooperation (Smith, Carroll, and Ashford 1995, 10–1) since it “facilitates interpersonal acceptance and openness of expression” (Zand 1972, 229).

In previous research, the direct additive effects of mutual resource dependence, congruent goals, and trust have been examined and corroborat-ed. However, it has not been studied whether the effects of resource interdependence and goal congruence are different in situations character-ized by high levels of trust compared to situations when agencies do not trust each other. In this article, it is examined whether a credible commitment, that is, mutual trust, is a necessary condition for goal congruence and mutual resource dependence to affect cooperation. Moreover, the effect of trust is studied when the levels of resource interdependence and goal congruence vary. It is hard to see why trust should increase cooperation if actors are not interdependent or have similar objectives. In sum, interaction effects might explain levels of cooperation better than the additive effects suggested in previous research.

The study focuses on the relationships between agencies that operate at a local level but representing different tiers of government. Policy imple-mentation often involves an intergovernmental dimension (Jennings and Ewalt 1998; Radin 2003; Thomas 1979) and “so long as there have been systems of dividing decisions and functions of governments there have been attempts to organize and manage them” (Agranoff 2004, 443). Consequent-ly, studies such as this one are of great interest.

I make use of new large-N data on the Swedish active labor market policy and examine dyads of Public Employment Service (PES) offices and municipal labor market agencies. The Swedish PES offices are central government agencies carrying out labor market policies at a local level. However, in recent years, a parallel local government system has evolved for labor market activities since municipalities now take an active part as well (Hjertner Thorén 2005; Lundin 2005; Lundin and Skedinger 2006; Salonen and Ulmestig 2004). This article takes a closer look at the interaction of the two tiers of government.

The empirical results should be interpreted with some caution, given a couple of methodological pitfalls. But the empirical results indicate that the effect of goal congruence is dependent on mutual trust. If organizations do not trust each other, similar priorities do not matter. In addition, if the authorities’ objectives diverge to a large extent, trust does not increase cooperation. However, the results do not support the idea that an interaction term between resource interdependence and trust should be included in models trying to explain collaborative behavior. In order to discern whether these effects really are causal, I encourage more empirical research.

Explaining cooperation

77

The remainder of this article is organized as follows: In the next section, theory and hypotheses are presented. The Swedish labor market case is then briefly discussed. In the two following sections, data and measures are described. The results are then reported and, lastly, in a concluding section, the findings are summarized and their implications are discussed.

Explaining cooperation: Interdependence, goal congruence, and trust Even in the most well-designed political system, authorities’ responsibilities will overlap. Accordingly, development and implementation of public policy frequently “demands multilateral cooperation, blurs or eliminates traditional boundaries and jurisdictions, and needs the deployment of many actors” (Alexander 1995, xvi). Diverging organizational goals and operational routines thus make policy implementation difficult (see for example, O’Toole 2003). A primary task of public sector management is to get the various agencies to cooperate when policies are carried out.1 Thus, detecting antecedents to cooperation is of imperative interest. In line with previous interorganizational research, cooperation in the public sector is defined as the interactions among actors aiming at solving public problems by working together rather than by working separately (cf. Smith, Carroll, and Ashford 1995, 10). Collaboration is used synonymously to cooperation throughout the article.

Resource interdependence There is an extensive and heterogeneous literature on collaboration between organizations (Oliver and Ebers 1998). However, exchange theory provides a foundation for explaining cooperation (Blau 1964; Levine and White 1961; Scharpf 1978). In this framework, cooperation is a consequence of resource interdependence. Organizations are assumed to be rational actors making conscious and intentional decisions in order to achieve their objectives. The motivation for working together is the need to overcome a lack of resources. An organization will avoid interactions with others if the benefits of co-operation do not exceed the costs since cooperation is complicated, is costly, and involves a loss of autonomy. But if organization A needs resources from organization B and organization B needs resources from organization A,

1 Note that cooperation involves costs and that implementation performance is not automatically improved by interorganizational cooperation. It is an empirical question whether the positive aspects outweigh the negative. Results in Jennings and Ewalt (1998) demonstrate that cooperation improves some aspects of policy performance, whereas there is no effect on other aspects. The effects of cooperation are not examined in this article.

Essay II

78

there is a good chance that cooperation will take place. Financial resources are, of course, of significant interest, but staff, premises, information, legitimacy, and legal authority are examples of other significant resources that can be obtained from other organizations.

Empirical evidence support the idea that mutual resource dependence increases cooperation. Levine and White (1961) indicated that health-related organizations highly dependent on resources from the local health system interacted more and had fewer disagreements with local agencies than organizations less resource dependent. In a quantitative longitudinal study of relationships among child care and health organizations in Texas, Van de Ven and Walker (1984) found that the need for resources was the most im-portant variable stimulating coordination of activities. More recent evidence exists as well. As an example, Gulati and Gargiulo (1999) examine alliance formation using longitudinal data from a sample of American, European and Japanese organizations; the effect of interdependence on alliance formation is positive and statistically significant.

Goal congruence Besides mutual dependence, goal congruence may boost collaboration. Given the assumption that organizations try to reach certain goals, we should not only focus on the need for external resources but also investigate the extent to which the organizations’ goals are similar. A shared interest can be a powerful facilitator of cooperation, whereas diverging objectives may de-crease cooperation (O’Toole 2003, 239).

Empirical results confirm that objectives are important. For example, Levine and White (1961) indicated that agreement on goals is an important aspect of interorganizational relationships. Compatibility of goals is also found to be positively associated with cooperation in Schmidt and Kochan’s (1977) study of community organizations and local offices of the US Training and Employment Service. O’Toole (1983) indicated that perceived common interest increases cooperation among local actors in a study of interorganizational implementation of labor market policies in Sweden and the Federal Republic of Germany. Moreover, Luo (2001) finds positive effects of goal congruity on personal attachment in international cooperative ventures. Personal attachment is defined as “the degree to which boundary spanners (resident board members and senior venture managers) from each party are socially bound through having developed personal relationships and interpersonal learning” (Luo 2001, 178). Luo’s operationalization include the extent to which information and skills have been transferred between the partners. Personal attachment can be regarded as a form of cooperation or, at least, as a concept closely related to cooperation.


79

Trust Trust is a key word in the social sciences. Scholars like Elster (1989), Ostrom (1998), Putnam (2000), and Rothstein (2000) accentuate trust as a mechanism for overcoming social dilemmas. In research on policy imple-mentation, Bardach (1998) stresses the importance of mutual trust in order to make agencies work together. There are various definitions of and perspectives on trust. Fritz Scharpf (1997, 137) uses the concept of weak trust.2 By weak trust, Scharpf means the expectation that another actor’s communicated preferences are honest rather than misleading and the expect-ation that the actor will stick to a commitment as long as the conditions under which it was entered are not altered dramatically (see also, Svensson and Öberg 2005). In this article, I use trust in the same sense as Scharpf.

There is an agreement among organization theory scholars that trust is an important antecedent to cooperation. In an experimental analysis using data on business executives, Zand (1972) shows that trust enhances cooperation. Muthusamy and White (2005) focuses on alliances between business firms in the United States from 1994 to 1998 and find that trust has a positive effect on transfer of knowledge between partners. The analysis of Zaheer and Venkatraman’s (1995) of insurance agencies also indicate a positive relationship between mutual trust and cooperation. In an overview article, Smith, Carroll, and Ashford (1995, 10–1) note that “although research has identified many determinants of cooperation, virtually all scholars have agreed that one especially immediate antecedent is trust.”

Hypotheses I suggest that we need to be more specific about under what conditions resource interdependence, goal congruence, and trust affect inter-organizational cooperation. The idea is that interaction effects should be considered in order to fully understand the relationships. Previous empirical research seems to have overlooked the possibility of interaction terms.

The literature implicitly assumes that the effects of resource interdepend-ence and goal congruence are the same when trust is low as when trust is high. How reasonable is this assumption? Why should an organization

2 Trust, goal congruence, and resource interdependence are treated as separate variables in the present study. It is likely that goal congruence increases trust, but mutual trust may exist even when objectives diverge. In addition, congruent goals will not automatically imply high trust since such a definition of trust is reliant upon an unrealistic assumption of perfect information about preferences. Moreover, in a situation without mutual resource dependence actor A can still think that actor B (and vice versa) has honest intents and will stick to an agreement. Some scholars, for example, Hardin (2002), seems to collapse resource interdependence, congruent goals, and trust: actor A trusts actor B when it is in B’s interest to fulfil A’s expectation. This position is, in my view, not as beneficial as treating resource interdependence, goal con-gruence, and trust as separate variables (for a good discussion see Rothstein 2000, 484–8).

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choose a collaborative strategy in a situation of resource interdependence if it cannot rely on the other organization’s commitment to the relationship? Blau (1964, 98) describes trust as an important condition for the exchange of resources to occur: “since social exchange requires trusting others to reciprocate, the initial problem is to prove oneself trustworthy”. Thus, re-source interdependence is only excepted to be a relevant factor when there is mutual trust. Below, a first hypothesis is outlined.

H1 The effect of resource interdependence on interorganizational cooperation is dependent on the level of trust; a positive effect is expected only when organizations trust each other.

Furthermore, objectives cannot be communicated in a credible way when one does not trust one another. When communication is not regarded as reliable, how can organizations be sure that they have congruent goals? Hence, I argue that trust must exist in order to make objectives a relevant factor.

H2 The effect of congruent (or diverging) objectives on inter-organizational cooperation is dependent on the level of trust. How similar or different their priorities are is only expected to affect cooperation when organizations trust each other.

How about trust then? Could we expect trust to affect cooperation regardless of the level of resource interdependence and goal congruence? I argue that it is unlikely for organizations to work together only because they trust one another. Mutual trust is not a sufficient reason. Trust can make cooperation easier, but it is not something that boost cooperation if there are no other reasons. The effect of trust ought to be dependent on the similarities between organizations’ goals and the level of resource interdependence. This suggests two additional hypotheses.3

H3 The effect of trust on interorganizational cooperation is dependent on the level of resource interdependence; the effect increases as the level of interdependence increases.

H4 The effect of trust on interorganizational cooperation is dependent on the level of goal congruence; the effect increases as objectives become more similar.

3 Note that H3 and H4, in fact, correspond directly to H1 and H2, respectively. That is, it is not possible to empirically separate H3 from H1, and H4 from H2. For example, the analysis cannot support the first proposition and then reject the third proposition. Nevertheless, I am interested in the effects of all three variables, and to make the presentation of the findings convenient, the theoretical assertions are stated as four separate hypotheses.


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Intergovernmental cooperation in local policy implementation: The Swedish labor market case The hypotheses outlined above are examined using data on dyads of central and local government agencies carrying out the active labor market policy in Sweden. Unemployment is a major problem in most countries, and govern-ments use active programs to reduce the number of persons without a job. Active labor market policy refers to “measures to raise employment that are directly targeted at the unemployed” (Calmfors, Forslund, and Hemström 2002, 5). This includes job-brokering activities and labor market programs, such as labor market training and subsidized employment.

In Sweden, the National Labor Market Administration (Arbetsmarknads-verket), a national government authority, carries out political decisions at local level through local PES offices (arbetsförmedlingar). There is a PES in nearly all municipalities, and in larger cities, there is often more than one office. Municipalities are involved in implementation of labor market activities as well, although overall responsibility is retained at the national level and the PES remain the most important local actor (Hjertner Thorén 2005; Lundin 2005; Lundin and Skedinger 2006; Salonen and Ulmestig 2004). It is estimated that in 1999 around 80,000 persons were activated in labor market programs arranged by the municipalities. This accounts for about 40 percent of the participants in all the National Labor Market Administration’s active measures (Lundin and Skedinger 2006). In addition, municipalities organize labor market programs (“active social policy”) for persons who are not “job ready” and live on social welfare benefits. Approximately 12,000 individuals were activated in such programs at any given point in time in 2002 (Salonen and Ulmestig 2004). A majority of municipalities have special labor market administrations, while others in-corporate labor market activities in their social services administration (Lundin 2005). The empirical analysis focuses on the relationship between the PES offices and the municipalities’ labor market administrations.

Besides unemployment being one of the largest problems in modern welfare states, the current research setting is suitable for at least five reasons. First, the high information requirements imply that cooperating across organizational boundaries becomes a viable strategy in labor market activities (O’Toole 1983). Second, similar dyads of central-local government agencies are analyzed, and the same political decisions are implemented around Sweden. This means that it is possible to hold a lot of characteristics constant when testing the hypotheses of interest. Third, cooperation varies around Sweden, which results in variation in the dependent variable that can be explored. Fourth, new and suitable data is available and reliable. Fifth, quantitative studies on implementation and cooperation between agencies have mainly been carried out on data from the United States. Evidence from a unitary European context is therefore of interest.

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In the late 1970s and the beginning of the 1980s, research was conducted on diverse aspects of interorganizational implementation in the realm of active labor market training in Sweden and West Germany. For instance, Hanf, Hjern, and Porter (1978) showed that implementation of programmers was dependent on interorganizational relationships to a considerable extent, and O’Toole (1983) indicated that common interest in the locale was an important factor stimulating interorganizational cooperation. PES offices specializing in labor market training were key actors in these studies. Municipalities were involved as well, although labor market training usually does not engage municipalities to any greater extent. These days, local governments have a much more profound role in the active labor market policy in Sweden than in the 1970s and the 1980s. This makes it interesting to study the relationship between PES offices and municipalities making use of contemporary data.

Data Cross-sectional data on dyads of PES offices and municipalities in 2003 have been collected. A questionnaire is the main data source, but administrative data from the National Labor Market Administration and official municipal statistics from the database KFAKTA03 supplement the survey.

Postal questionnaires were distributed to the managers of all Swedish PES offices in February 2004. The response rate was good: 268 managers replied, which implies a response rate of 75 percent. Dyadic data require information from both sides of the dyad. Thus, questionnaires were also distributed to managers of municipal labor market administrations and municipal politicians with responsibility for labor market activities. The response rates were even better in these cases: 85 percent of the managers (246 persons) and 84 percent of the politicians (245 persons) replied. In Stockholm, Sweden’s largest municipality, labor market operations are handled in 18 different offices organized geographically (kommundelar). The managers of these offices answered the Stockholm questionnaires. The response rate was somewhat lower here: 56 percent (10 persons). The non-responses are pro-bably not that problematic since the respondents resemble the population on characteristics such as location, size, and unemployment rate in all groups.

The PES managers’ answers form one part of the dyad. However, either the managers’ or the politicians’ answers could make out the other side. It is reasonable to assume managers to have more accurate information about operations. Thus, the first choice was to make use of information from this


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group. The local politicians’ responses were employed when the managers’ answers were missing to maximize the number of dyads.4

Even though the response rates are very high, the number of observations that can be used decreases in dyadic data. If one party in an agency pair is missing, it is not possible to use that information. Internal missing data on some variables also reduces the number of useable observations. In the end, the analysis is conducted on 203 cases.

Like most other researchers investigating interorganizational ties, I have to rely on reports from key informants. Managers and politicians were instructed to give generalized information about their organization. The assumption that the responses from one person represent the whole organization can be questioned. However, it is reasonable to assume that the respondents in this case are well informed and that data are trustworthy.

Measures In this section operationalizations of cooperation, interdependence, goal con-gruence, trust, and control variables are described. Table 1 lists descriptive statistics for each of the measures.

Cooperation The dependent variable cooperation is measured using five 0/1-indicators obtained from the PES questionnaire. The managers were asked if the PES office and the municipality have established cooperative groups where (a) caseworkers from the two organizations collaborate and (b) managers from the two organizations collaborate. Moreover, the managers indicated whether (c) caseworkers contact each other on a daily basis or more seldom. They also provided information about whether the PES office and the municipality have formal collaborative contracts concerning two policies: (d) actions to prevent long-term unemployment among young people and (e) a program called the “Activity Guarantee” where the target group is individuals who have been unemployed for a considerable time period. In both policies, the Swedish government encourages collaboration between PES offices and municipalities, but the authorities are not compelled to sign a collaborative contract.5

4 As a test, all analyses in the article have been performed including a dummy variable measuring whether the municipal response comes from a manager or politician. Furthermore, the analyses have been carried out using a sample solely consisting of responses from the managers. These additional tests did not alter the conclusions. 5 For more information about the Activity Guarantee, see Forslund, Fröberg, and Lindqvist (2004). The youth policy is described and evaluated in Carling and Larsson (2005).

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Table 1. Descriptive Statistics Variables Mean /

Proportion SD Min Max

Cooperation 3.60 1.27 0.00 5.00

Non-Nordic clients 7.28 6.73 1.17 61.96

Long-term clients 11.65 4.95 0.11 30.04

Goal congruence 7.43 0.97 4.38 9.85

Trust 0.45 – – –

Municipality type

Big cities 0.07 – – –

Suburbs 0.10 – – –

Larger cities 0.12 – – –

Middle-sized cities 0.14 – – –

Industry 0.19 – – –

Rural 0.09 – – –

Sparsely populated 0.09 – – –

Other larger 0.11 – – –

Other smaller 0.09 – – –

Unemployment 3.31 1.27 1.10 8.20

Non-Swedish citizens 2.21 2.78 0.00 36.25

Population change 99.84 2.33 93.59 105.99

Work rehabilitation PES 0.01 – – –

PES size 17.84 16.51 2.00 105.00

PES cooperative orientation 12.36 5.96 0.50 18.00

PES finances 0.66 0.34 0.00 3.01

Mun. LMP spending 2.99 1.97 0.04 13.19

Left parties 47.65 10.86 11.11 82.86

Mun. cooperative orientation 4.77 4.54 0.00 18.00

Mun. tax base 124.00 18.46 99.29 250.58

State subsidy 6.77 5.32 –15.70 22.14

Equal terms 0.51 – – –

Note: Mun., municipality; LMP, labor market program. Proportions in italics.


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Table 2. Principal Component Factor Analysis: Cooperation Item Factor Loadings

(a) Joint collaborative groups at the caseworker level 0.74

(b) Joint collaborative groups at the manager level 0.70

(c) Daily contacts between caseworkers 0.43

(d) Youth policy collaborative contract 0.56

(e) Activity Guarantee collaborative contract 0.53

Note: Entries are factor loadings in a principal component analysis. The retention of factors is based on the Kaiser criterion (that is, eigenvalues greater than 1.00). The eigenvalue for the first dimension is 1.82. This is the only dimension where the eigenvalue exceeds 1.00. The factor explains 36.3 percent of the variance in the variables. Bartlett’s test of sphericity indicates that we can reject the hypothesis that the correlation matrix is an identity matrix at the .05 level. Kaiser-Meyer-Olkin Measure of Sampling Adequacy is .65 (.50 or lower is usually considered unacceptable).

In Table 2, a factor analysis is presented. All items load positively on the first dimension. Since the items form a single dimension, a collaboration index is constructed ranging from zero to five. A score of zero implies that none of the activities (a)–(e) are taking place, whereas five means that the organizations have collaborative groups at the caseworker and manager levels, they contact each other on a daily basis, and have signed cooperation contracts concerning the youth policy and the Activity Guarantee. I use a simple additive index in order to make interpretation easy. All analyses in the article have been performed using the factor scores obtained from the factor analysis as well, and the conclusions remain the same.

Cooperation has been measured in various ways in prior research. Sometimes a single item is employed; other times indices are used. Measures vary depending on the context. The frequency of communication, how often clients are transferred between organizations, how much support a focal organization receives from another organization, the use of various forms of coordination techniques such as interagency committees and task forces are examples of ways to assess to what extent organizations work together (see, for example, Alter and Hage 1993; Jennings and Ewalt 1998; Schmidt and Kochan 1977; Van de Ven and Walker 1984; Wholey and Huonker 1993). The items in Table 2 are similar to the measures used in other settings, although I am not aware of any study using exactly the same approach.

Interdependence There are at least two approaches available to assess interdependence, none of them perfect. A common approach is to ask respondents directly how de-pendent they are on each other (see, for example, Provan and Skinner 1989). A potential drawback is the risk that the responses are a consequence of the

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level of cooperation rather than a cause. Another problem is that respondents may have trouble interpreting survey questions and response alternatives. This leads to problems with both validity and reliability.

Instead of assessing resource interdependence directly, it is possible to look for situations in which it is realistic to assume that organizations are mutually resource dependent. This approach is employed by Gulati and Gargiulo (1999) studying alliances in three industries in a sample of Ameri-can, European, and Japanese organizations. Gulati and Gargiulo assume that firms benefit from cooperation between niches since they have complement-ary resources. Moreover, firms that are located in different regions are understood to be interdependent; a firm needs a partner in another market.

The latter method depends on the critical assumption that it is possible to identify circumstances when organizations are mutually dependent. I argue that such variables are available in the present research setting. My claim is that a main determinant of resource interdependence is the composition of the unemployed in the locale. At the heart of the argument is that there is a net mutual benefit from collaboration when the clientele consists of many individuals in need of assistance both from the PES and from the municipality.

If a large part of the unemployed face some additional hindrance besides being unemployed, the authorities are likely to need one another. Difficulties in speaking and understanding the Swedish language, various work dis-abilities, and drug addiction problems are examples of problems that intertwine with difficulties in finding a job. Municipalities implement and fund social assistance, policies aiming at giving support to those with a handicap, and the introduction of immigrants into the Swedish society. Municipal resources, such as expertise and information, are important for the PES to obtain when many of the unemployed have problems lying within the jurisdiction of the local governments. At the same time, the PES offices’ knowledge in labor market issues and, above all, their financial resources are of municipal interest. Thus, mutual dependence is likely to be high when a large part of the unemployed have multiple problems.

I cannot observe when several clients are in need of both authorities’ actions, but there are rather good indicators available. Two variables based on register data from the National Labor Market Administration are employed. Long-term clients, measured as the percentage of clients registered with the PES as openly unemployed for more than six consecutive months in 2003, is one of the indicators (this is the official definition of long-term unemployment in Sweden). The clients should not have participated in a labor market program during this time period. Among these long-term unemployed, I expect to find a relatively large share of persons with multiple problems. The second variable, non-Nordic clients, is the percentage of the unemployed clients without a Nordic citizenship that are


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registered with the PES in 2003.6 It is reasonable to expect that a relatively large proportion of these clients are in need of support from both agencies. For example, according to the National Board of Health and Welfare (2004), 11 percent of those born in other countries than Sweden, 18 years or older, received municipal welfare benefits 2003. This can be compared with the 2 percent among citizens born in Sweden. Moreover, municipalities are responsible for introduction of immigrants into the Swedish society, including teaching the Swedish language.

I believe that long-term clients and non-Nordic clients are reasonable indicators of resource interdependence, but at least two caveats should be mentioned. First, the variables provide no direct evidence of dependence on each other’s resources. Thus, I cannot be completely sure that the indicators measure something else other than interdependence. Second, even if we accept the measures as valid indicators, one problem remains: the agencies may be mutually dependent for other reasons. This implies that the empirical study is limited to a certain kind of resource interdependence and that conclusions should be made with some reservations.

Goal congruence A direct question is often used to assess goal congruence: “to what extent are the goals of the other organization compatible with the goals of your organization?” (see, for example, Schmidt and Kochan 1977). However, to reassure that answers are exogenous, I believe it is more appropriate to let the respondents estimate the importance of certain goals and compare the answers of the actors within each dyad.

The questionnaire respondents were asked to grade, on a scale from one to five, the importance of 13 different objectives. The ratings were trans-ferred into a ranking of objectives for each agency. This approached is preferred since a ranking is more comparable between respondents. If two objectives were given the same rating by a respondent, they got the same ranking. The difference between the PES office’s and the municipality’s ranking in each dyad was then calculated.7 I inverted the measure in order to make the interpretation of the findings easier. That is, higher scores imply more congruence. In Table 3, objectives and averages are presented. The

6 A large share of the immigrants are coming to Sweden from the neighbor countries. Nordic immigrants are likely to have fewer boundary-spanning problems than other immigrants since language and cultural barriers are smaller, for example. 7 The difference between the agencies’ ranking of a certain objective is given by

2)(ii rankrank MUNPES − .

PESrank is the PES office’s ranking of the objective from 1-13 in each dyad (1 is the most important objective, 13 is the least important objective), whereas MUNrank is the corresponding municipality’s ranking of the same objective. This measure was inverted: 0 becomes 12, 1 becomes 11, and so on. Thus, a high value means similar objectives.

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minimum conceivable value is zero, which implies very different priorities. The maximum is 12, that is, both agencies in all dyads rank the objective in the same way.

Table 3. How Similar Various Objectives Are Ranked by the PES offices and the Municipalities (0 = Minimum Congruence; 12 = Maximum Congruence)

Objective Congruence

Ensuring that there are labor market programs for young people under 25 10.56

Reducing unemployment 9.85

Ensuring that there are labor market programs for groups of unemployed with severe problems in the labor market

8.90

Improving matching between available jobs and unemployed persons 8.70

Taking clients’ own requests and needs into account 7.92

Improving municipal services for the local population 7.70

Monitoring clients 7.45

Shifting people from subsidized to unsubsidized jobs 7.30

Following central government rules and guidelines 6.56

Activating unemployed persons living on social assistance in labor market programs

6.36

Increasing or maintaining the local population 5.75

Attaining the quantitative goals of the National Labor Market Administration

5.27

Reducing expenditure for social assistance 3.94

The agencies agree most on the importance of arranging labor market programs for unemployed youth and the overall goal of reducing unemploy-ment. Disagreement is highest concerning the importance of decreasing social assistance expenditures and the quantitative goals of the National Labor Market Administration. The overall goal congruence, which is the measure to be used in the analysis, is the average score of the objectives in Table 3. Descriptive statistics are reported in Table 1.

The selected goals are chosen because they are highly relevant in the active labor market policy in general, especially for the relationship between PES offices and municipalities. Objectives of importance in some relation-ships are probably missing, but I find it more reliable and more interesting to focus on certain goals rather than asking a general question on goal similarity.


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Trust Two survey questions were asked in order to cover trust. The purpose of the first question was to measure perceptions of the other actor’s intents: “To what extent do you assume that the PES office (municipality) reveals true motives to you?” The second question is aimed at capturing the agencies’ assumptions about whether the other agency will actually keep promises: “To what extent do you assume that the PES office (municipality) performs in line with its promises?” There were four possible response alternatives: “completely”, “mostly”, “partly” and “not at all”. Trust is coded as a dichotomous variable. A relationship is characterized by mutual trust when both actors respond that they believe the other actor have honest intents and will keep their promises all or most of the time (that is, the alternatives completely and mostly), otherwise the level of trust is low. Sometimes re-searchers instead employ a battery of items (for example, using a Likert-type scale) to measure trust. Some researchers also distinguish between diverse forms of mutual trust. It is not possible for me to use such measures since I have no access to that kind of data.

Trust is a somewhat problematic variable to deal with. It could be argued that cooperation affects trust rather than the other way around. Thus, conclusions should be made with some reservations. The problem of causal order between trust and other variables is a recurrent problem in the social sciences. Studies trying to establish time order between trust and cooperation using, for example, panel data would be important contributions to the research field. However, in the literature on interorganizational relationships one usually treats trust as an independent variable and cooperation as the dependent variable.

Control variables The research setting makes it possible to hold characteristics of the policy and the authorities that do not vary around Sweden constant. But control variables should be added to account for variations among dyads that could affect both the level of cooperation and some of the main explanatory variables.

The local context is important to hold constant for at least two reasons. First, contextual pressure is stronger in some places than in others. Evidence reveals that when the times are turbulent and there is external pressure, organizations tend to join together (Schermerhorn 1975). Contextual pres-sure can also affect the main explanatory variables. Second, alternative collaborative partners and/or external resources are more readily available in some areas than in others. This can affect the relationship between the PES and the municipality.

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I have added four control variables to account for important variation among local contexts. All four of them are based on data from official statistical sources. A set of dummy variables are included to determine the type of municipality. The context is likely to differ among big cities, small cities, rural areas and so on but be quite alike within these groups. For instance, the number of potential partners is expected to be larger in metro-politan areas than in sparsely populated municipalities. Municipality type is based on a classification made by the Swedish Association of Local Authorities. The scheme consists of nine categories covering, for example, big cities, industry municipalities, and rural areas.8

The unemployment rate in percent in 2003 is another control variable. I also incorporate the population change between 2000 and 2003, measured as an index where the local population in 2000 is the base. High unemployment and/or decreasing population may imply external pressure. Moreover, additional resources from, for example, the Swedish Agency for Economic and Regional Growth or from the European Union often become available when the population decreases or when unemployment is high.

The last context variable is non-Swedish citizens, which is the percentage of inhabitants having foreign citizenship (in 2001, since I do not have data from 2003). Non-Swedish citizens is added mainly because I want to make sure that one of the key explanatory variables, non-Nordic clients, only account for the share of unemployed clients without Nordic citizenship. I ex-pect a relatively large share with multiple boundary-spanning problems in this group.

There a several features of the authorities that are important to take into account. As previously noted, labor market policy is a national government responsibility in Sweden. Municipalities can involve themselves when they find it appropriate. Some municipalities are therefore more active in the labor market policy than others. The level of cooperation and the main explanatory variables could be affected by municipal engagement. The agencies may, for example, trust each other as a consequence of municipal activity in the field. The municipalities’ spending on labor market policies, excluding financial contributions from the National Labor Market 8 Big cities (reference category in the regression analyses): Municipalities with more than 200,000 inhabitants. Suburbs: More than 50 percent of the employed in the municipality travel to a big city to get to their job. Larger cities: More than 50,000 inhabitants in the municipality and less than 40 percent employed in the industry sector. Middle-sized cities: 20,000–50,000 inhabitants, with less than 40 percent employed in the industry sector, and more than 70 percent living in densely populated areas. Industry: Municipalities that are not sparsely populated, with more than 40 percent employed in industry. Rural: Municipalities that are not sparsely populated, where more than 6.4 percent are employed in agriculture and forestry, and where more than 70 percent are living in densely populated areas. Sparsely populated: Municipalities with less than 5 inhabitants per square kilometer and with less than 20,000 inhabitants. Other larger: Other municipalities with 15,000–50,000 inhabitants. Other smaller: Other municipalities with less than 15,000 inhabitants. This classification is also used in, for example, Dahlberg and Johansson (2002). Data source: KFAKTA03.


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Administration, in 100 crowns per inhabitant in 2003 is employed as an indicator of municipal engagement (mun. LMP spending). What is more, a control variable for the percentage of seats in the local council held by socialist parties is incorporated (left parties).9 The active labor market policy is to a large extent a socialist project, and it is reasonable to assume that socialist municipalities are more involved in labor market programs. Both variables are based on official statistics.

Some PES offices and/or municipalities may, for some reason, be more open to cooperation with others (cf. Alexander 1995, 16). This general orientation may affect the relationship between the PES and the municipality. How can I make sure that it is not a general openness towards collaboration that drives the results? The coping strategy is to include variables measuring the level of communication between the PES and the Regional Social Insurance offices (PES cooperative orientation), and bet-ween the municipalities and the Regional Social Insurance offices (mun. cooperative orientation). The Social Insurance offices (Försäkringskassan) are common partners to the PES offices (Lundin 2005, 15) and to the municipalities (Swedish Association of Local Authorities 1999, 23). The idea is that by including these two controls, factors that impinge on the authorities’ relationship to both the Social Insurance offices and to each other can be held constant. The measures are based on questionnaire data. The respondents were asked how often they communicate with the Social Insurance office. The ordinal response alternatives were recoded into a con-tinuous variable. Various ways of doing this was tested, without any sub-stantial change in the results. The following operationalization is used: “daily contacts” is set to 18 times per month, “at least once a week” is set to eight times per month, “at least once a month” is set to two times per month, “at least once a year” is set to every second month, and “more seldom or never” equals zero times per month.

The agencies’ own resources need to be taken into account. An agency having a lot of financial resources is probably not that dependent on external resources, all else equal. Two variables based on official figures for 2003 are included to control for the municipalities’ financial strength: tax incomes (mun. tax base) in 1,000 crowns per inhabitant and state subsidies (state subsidy) in 1,000 crowns per inhabitant. Data to calculate the PES offices’ financial resources (PES finances) comes from the questionnaire. The available benefits to clients participating in active programs in 1,000 crowns per week, divided by the number of clients per week in 2003, is employed as an indicator of the PES office’s financial strength.

9 As a robustness check, I have used an alternative operationalization of left parties. According to the alternative assessment, a municipality is considered socialist if the chairman of the executive board represents the Social Democrats. Results are not substantially altered.

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The size of the PES (PES size), operationalized as the number of caseworkers at the office, is an additional control variable. The reason for including this variable is primarily that the dependent variable is not relative to office size. One of the items in the cooperation index is about frequency of communication: Do the authorities have daily contacts? A PES with around 100 employees is more likely to have daily contacts than an office with only a couple of caseworkers. Thus, cooperation is somewhat biased towards large agencies. By including size, this deficiency is taken into account. I do not have reliable data on the size of the municipal labor market administration. This does not, however, impose a big problem. Several of the already mentioned control variables are likely to account for this possible effect. Large administrations are, for example, expected to be found in large cities, in municipalities governed by left parties, and in municipalities spending a lot on labor market programs. As an additional test, I have included the number of inhabitants in the municipality as a proxy of the size of the labor market administration; the results are not substantially changed.

Some PES offices are specialized on work disabilities, and they have rather different objectives than the ordinary offices. The results may, in some way or another, be affected by this. Thus, I include a dummy variable called work rehabilitation PES that takes on a value of one if the PES is specialized on work disabilities, otherwise its value is zero.

Lastly, it is possible that the level of cooperation increases if the actors perceive the relationship to be on equal terms. If one of them think that the other is trying to dominate them, the incentives to collaborate may decrease. A dummy variable (equal terms) is constructed from the questionnaire responses as a measure. If both parties declare the relationship to be on equal terms the variable gets a value of one, otherwise zero.10

Findings Ordinary Least Squares (OLS) regression analysis is used to evaluate the hypotheses. Table 4 reports the results from six different model specific-ations, with more controls added successively. In Models 1–3, interaction terms are left out; the purpose is to demonstrate how the effects would look like if the interactions are not taken into account. Models 4–6 include interaction terms. In Models 1 and 4, environmental characteristics are used as control variables. Agency features, except finances and whether the relationship is set on equal terms, are added in Models 2 and 5. Models 3 and

10 The following question was asked: “How are the terms of your organization’s interaction with the PES office (municipality) set?” The response alternatives were as follows: “completely on the municipality’s terms”, “mostly on the municipality’s terms”, “equal terms”, “mostly on the PES office’s terms” and “completely on the PES office’s terms”.


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6 include all control variables. Internal missing values, especially concerning PES finances, imply a decrease of useable observations in the specifications including all controls. Diagnostic plots and the Breusch-Pagan test indicated problems of heteroscedasticity. For this reason, robust standard errors are used in all specifications.

The coefficients in Models 1–3 are rather similar, and interpretation can therefore be focused solely on the coefficients presented in Model 3. Long-term clients, non-Nordic clients, goal congruence, and trust affect co-operation along the lines of previous research; the signs of the b-coefficients are expected, and the effects are statistically significant at conventional levels. In a dyad where the authorities trust each other, compared to an identical dyad without mutual trust, the predicted number of collaborative activities will be about 0.45 higher, all else equal. If goal congruence improves by one unit, the average level of cooperation changes by roughly 0.23 units, holding everything else constant. An increase of one percentage point of clients being long-term unemployed or being non-Nordic citizens increases cooperation by approximately 0.05 units on average, all else equal.

To get a better indication of the joint impact of the main independent variables, it is possible to compare two fictitious dyads. In the first dyad, the agencies put mutual trust in each other, goals are rather similar (goal congruence held at the third quartile), and interdependence is relatively high (long-term clients and non-Nordic clients held at the third quartile). In the second dyad, the agencies do not trust each other, goals diverge (goal congruence held at the first quartile), and mutual dependence is low (long-term clients and non-Nordic clients held at the first quartile). In all other respects, the dyads are identical. The predicted level of cooperation will, on average, be around 1.36 units higher in the first dyad. This seems like a relatively large difference, given the scale of the dependent variable (0-5).

Note that it is always difficult to know if an effect is large or small. In addition, the estimated coefficients are average effects. Comparing predicted values is therefore a bit hazardous. Thus, caution is recommended. The impacts of the variables non-Nordic citizens and long-term clients are the most disputable ones. But we must recall that these variables only account for a small part of resource interdependence. This means that it is not rea-sonable to expect them to make an enormous difference.

Tab

le 4

. OLS

Reg

ress

ion

Ana

lysi

s with

Coo

pera

tion

as D

epen

dent

Var

iabl

e (R

obus

t Sta

ndar

d Er

rors

in P

aren

thes

es)

1

2 3

4 5

6 N

on-N

ordi

c cl

ient

s 0.

04 (0

.02)

**

0.05

(0.0

2)**

* 0.

05(0

.02)

***

0.03

(0.0

2)*

0.05

(0.0

2)**

* 0.

04(0

.02)

**

Long

-term

clie

nts

0.04

(0.0

2)*

0.04

(0.0

2)*

0.05

(0.0

2)**

0.

04 (0

.03)

0.

05(0

.03)

* 0.

06(0

.02)

**

Goa

l con

grue

nce

0.25

(0.0

9)**

* 0.

29(0

.09)

***

0.23

(0.0

9)**

* 0.

12 (0

.13)

0.

12(0

.12)

0.

09(0

.12)

Tr

ust

0.40

(0.1

7)**

0.

37(0

.15)

**

0.45

(0.1

6)**

* –1

.82

(1.4

3)

–1.9

5(1

.30)

–1

.65

(1.2

7)

Trus

t × N

on-N

ordi

c cl

ient

s

0.00

(0.0

2)

–0.0

0(0

.02)

0.

00(0

.02)

Tr

ust ×

Lon

g-te

rm c

lient

s

–0.0

0 (0

.04)

–0

.02

(0.0

3)

–0.0

1(0

.03)

Tr

ust ×

Goa

l con

grue

nce

0.

30 (0

.18)

* 0.

35(0

.15)

**

0.30

(0.1

5)**

U

nem

ploy

men

t 0.

12 (0

.09)

0.

02(0

.09)

-0

.01

(0.1

0)

0.12

(0.0

9)

0.02

(0.0

9)

–0.0

1(0

.10)

N

on-S

wed

ish

citiz

ens

0.03

(0.0

2)*

0.04

(0.0

2)*

0.03

(0.0

2)*

0.03

(0.0

2)

0.04

(0.0

2)**

0.

03(0

.02)

Po

pula

tion

chan

ge

0.10

(0.0

6)

0.04

(0.0

7)

0.05

(0.0

8)

0.09

(0.0

6)

0.04

(0.0

7)

0.04

(0.0

8)

Wor

k re

habi

litat

ion

PES

–1

.68

(0.5

4)**

* –1

.22

(0.3

6)**

*

–1.8

7(0

.64)

***

–1.2

7(0

.39)

***

PES

size

0.02

(0.0

1)**

0.

02(0

.01)

***

0.

02(0

.01)

***

0.02

(0.0

1)**

* PE

S co

oper

ativ

e or

ient

atio

n

0.06

(0.0

2)**

* 0.

05(0

.02)

***

0.

05(0

.02)

***

0.04

(0.0

2)**

* PE

S fin

ance

s

–0

.46

(0.3

9)

–0.4

6(0

.37)

M

un. L

MP

spen

ding

–0.0

3(0

.04)

–0

.01

(0.0

4)

–0

.03

(0.0

4)

–0.0

0(0

.04)

Le

ft pa

rties

0.02

(0.0

1)*

0.01

(0.0

1)

0.

02(0

.01)

* 0.

01(0

.01)

M

un. c

oope

rativ

e or

ient

atio

n

0.03

(0.0

2)

0.01

(0.0

2)

0.

03(0

.02)

* 0.

01(0

.02)

M

un. t

ax b

ase

–0.0

1(0

.01)

–0

.01

(0.0

1)

Stat

e su

bsid

y

–0

.05

(0.0

2)**

*

–0

.04

(0.0

2)**

* Eq

ual t

erm

s

–0

.26

(0.1

8)

–0.2

7(0

.18)

C

onst

ant

–10.

48 (6

.55)

–6

.90

(7.0

6)

–3.9

3(8

.53)

–8

.96

(6.7

5)

–5.0

8(7

.42)

–3

.05

(8.8

5)

Mun

icip

ality

type

, dum

mie

s Y

es

Yes

Y

es

Yes

Yes

Yes

St

anda

rd e

rror

of r

egre

ssio

n 1.

19

1.08

1.

03

1.19

1.08

1.02

N

umbe

r of o

bser

vatio

ns

20 3

202

18

7

203

20

2

187

* p

< .1

0; *

* p

< .0

5; *

** p

< .0

1.


95

Models 4–6 contain the relevant information to evaluate the four hypotheses. However, it is not possible to assess the details directly from Table 4 since interaction effects are estimates conditional on the values of the other interaction variables. The results in Table 4 can only provide a rough in-dication. The b-coefficients of long-term clients and non-Nordic clients in Models 4–6 are more or less unchanged in comparison with Models 1–3, and the interaction terms that include these two variables are small and statistically insignificant. This indicates that there is no interaction between long-term clients and non-Nordic clients, on the one hand, and trust, on the other hand. Thus, there is no support for hypotheses 1 and 3. However, the effects of trust and goal congruence changes dramatically. Moreover, the interaction term of trust and goal congruence is positive, large, and statisti-cally significant at conventional levels. This suggests that there are inter-action effects in accordance with hypotheses 2 and 4.

Table 5. Conditional Effects: The Effects of Non-Nordic Clients, Long-term Clients, and Goal Congruence as the level of Trust Changes (Robust Standard Errors in Parentheses) Trust

Low High

Non-Nordic clients 0.04 (0.02)** 0.05 (0.02)**

Long-term clients 0.06 (0.03)** 0.04 (0.03)

Goal congruence 0.09 (0.12) 0.39 (0.10)***

Note: The conditional effects are based on the estimates from Model 6 in Table 4. * p < .10; ** p < .05; *** p < .01.

As noted above, interaction effects are conditional effects, and the analysis should not stop at this point. Allison (1977), Braumoeller (2004), and Friedrich (1982) thoroughly discuss the commonly made mistakes when interaction variables are included in regression analysis. The main thrust of their argument is that the b-coefficient and the standard error of a variable included in an interaction term depend on the value of the other interaction variable. It is therefore necessary to calculate the impacts of long-term clients, non-Nordic clients, and goal congruence when trust is low and high, and to compute the effects of trust at various levels of long-term clients, non-Nordic clients, and goal congruence to find out the details. Table 5 and 6 report conditional effects based on the coefficients in Model 6 in Table 4. The results stay about the same if the coefficients from Model 4 or 5 are used instead. 11 11 See Allison (1977), Braumoeller (2004), and Friedrich (1982) for details on how to calculate conditional effects and significance in interaction models.

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In Table 5, we can see that the effect of non-Nordic clients is almost the same when trust is high and low: a one percentage point increase of unemployed clients from outside the Nordic countries yields, on average, an increase of cooperation by roughly 0.05 units in both cases (significant at the .05 level). The effect is marginally larger when trust is high, but the difference is negligible and not robust to model specification. A similar story applies to long-term clients, but in this case, the b-coefficient is a bit larger when trust is low and insignificant when trust is high. This is opposite to what hypothesis 1 suggests. But the results are not robust to model specification. In some specifications, the variable long-term clients has a significant and positive effect of about the same magnitude when trust is high as when it is low. In sum, the effect of resource interdependence does not rely on mutual trust and hypothesis 1 is therefore rejected.

However, Table 5 shows that hypothesis 2 is supported. The impact of goal congruence is statistically insignificant at any conventional level in cases of low trust. But when trust is high, the effect is significant at least at the .01 level and the size of the b-coefficient is more than three times as large as when trust is low. Thus, the effect of goal congruence of 0.23 in Model 3 hides that the impact is much stronger when organizations trust each other and is insignificant when they do not. Given mutual trust, cooperation increases by 0.39 units, on average, when goal congruence increases by one unit, all else equal.

To see how trust affects cooperation it is necessary to turn to Table 6. The Table consists of two panels. In panel A, goal congruence is set to 8.15. This is the third quartile of the variable’s distribution, and it is (arbitrarily) chosen to reflect a situation where the agencies’ objectives are rather similar. In panel B, goal congruence is set to 6.77, which is the first quartile. Consequently, panel B shows the effects of trust, given diverging objectives. In both panels, long-term clients and non-Nordic clients vary. In these cases, the third quartile represents high resource interdependence and the first quartile represents low resource interdependence.

In order to evaluate hypothesis 3—that is, that the effect of trust increases when resource interdependence increases—coefficients within each panel should be compared. There is no indication that the impact of trust becomes larger when non-Nordic clients and long-term clients take on high values. The size of the coefficients and the significance levels are about the same within each panel. If anything, the evidence is opposite to hypothesis 3. Hypothesis 3 is therefore rejected.


97

Table 6. Conditional Effects: The Effects of Trust as Non-Nordic Clients, Long-Term Clients, and Goal Congruence Changes (Robust Standard Errors in Paren-theses) Long-term clients

Few (8.14) Many (14.70)

Panel A. Effects when goals are similar (goal congruence = 8.15)

Few (3.28) 0.70 (0.23) *** 0.61 (0.18) *** Non-Nordic clients

Many (8.61) 0.71 (0.20) *** 0.61 (0.18) ***

Panel B. Effects when goals diverge (goal congruence = 6.77)

Few (3.28) 0.29 (0.27) 0.19 (0.23) Non-Nordic clients

Many (8.61) 0.29 (0.25) 0.19 (0.24)

Note: The third quartile (8.15) of goal congruence represents a situation in which goals are similar, whereas the first quartile (6.77) implies a situation when the agencies’ objectives diverge to a large extent. The first quartile of non-Nordic clients (3.28) and long-term clients (8.14) represents low resource interdependence, and the third quartile of non-Nordic clients (8.61) and long-term clients (14.70) means high resource interdependence. The conditional effects are based on the estimates from Model 6 in Table 4. The effects and the standard errors have been calculated in the same way as in Table 5; see Allison (1977), Braumoeller (2004), and Friedrich (1982). * p < .10; ** p < .05; *** p < .01.

If we instead compare figures between panel A and panel B, hypothesis 4 can be evaluated. That is, the impact of trust is examined at different levels of goal congruence. The findings are conclusive: panel A shows statistically significant and large positive effects of trust when objectives are similar, whereas panel B indicates statistically insignificant and small effects of trust given diverging objectives. This is precisely what hypothesis 4 suggests. Thus, the effects of trust presented in Models 1–3 hide the fact that the impact is much larger when goals are similar and that we cannot expect a positive impact if organizations have very different agendas.

To examine the robustness of the results, several diagnostic tests have been performed.12 The most important tests can be mentioned. First, numerous model specifications including different controls have been examined—results are robust. Second, I have examined many diagnostic plots looking for nonlinear relationships and outliers. Some outliers are de-tected, but I find no substantial reason to exclude them. Nonetheless, the models have been reestimated without them. The results remain more or less unchanged. Third, one concern when analyzing dyadic data is possible 12 See Fox (1991) for an overview of most of the diagnostic tests presented here.

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interdependence across observations: when one actor is present in several dyads there is a risk of autocorrelation (see, for example, Mizruchi 1989). Some municipalities are included in more than one dyad. Since they are few, interdependence across observations should not be a big problem. As a precaution, regression analysis excluding dyads consisting of cases that appear more than once has been performed. In some specifications, the variable long-term clients turns out to be insignificant (but not in Model 6), which implies some uncertainty regarding the effect of this variable. Fourth, I have also tested excluding dyads in which the response from the municipal side of the dyad is provided by a politician. Again, the variable long-term clients comes out insignificant in a couple of specifications. Fifth, tolerance tests for multicollinearity have been carried out. In Models 1–3, it is definitely not a problem. However, the diagnostic statistics indicate that multicollinerarity is present in Models 4–6. This is a usual setback in interaction models. But I do not worry that much in this case. The problem appears to apply mainly to the variables trust and the interaction of trust and goal congruence. The interaction term is statistically significant anyway, which indicates that the effect of trust is lower when objectives diverge and that an interaction ought to be included. It must be noted, however, that the multicollinearity problem related to the variable trust could imply that trust has a significant effect at somewhat lower levels of goal congruence than what is indicated by Table 6.

To sum up, the most important problems indicated by the robustness checks is that the impact of long-term clients is a bit hazardous and perhaps some problems of multicollinearity. Otherwise, the findings show that mutual resource dependence enhances collaboration regardless of whether the authorities trust each other or not. The findings also imply that the logic of interorganizational cooperation suggested in additive models should be developed: similar goals and mutual trust do promote cooperation but probably only when they occur simultaneously.

Conclusion Implementation of political decisions will continue to rely on joint efforts of various authorities. Governance in these contexts is challenging and know-ledge on how cooperation can be explained is of significant interest. In this article, new data on the relationships between Swedish PES offices and municipalities has been utilized in order to evaluate potential explanations of interorganizational cooperation.

Prior research suggests that authorities cooperate because they are re-source interdependent, have congruent objectives, and trust each other. This explanation holds in the present case as well. Cooperation between PES offices and municipalities is at least partly a consequence of a situation


99

where the authorities need one another to solve problems, give priority to similar objectives, and trust one another.

However, the argument in the article is that theory should be adjusted to incorporate interaction effects. The interpretation of the empirical findings must be made with some reservations since it is difficult to be certain that causal effects have been identified. But the results suggest that congruent goals do not promote cooperation if authorities do not trust each other. Furthermore, it seems like mutual trust does not enhance cooperation when authorities have very different priorities. That is, mutual trust and goal con-gruence must exist simultaneously. The empirical evidence indicates that including interaction terms probably is going to improve our understanding of interorganizational cooperation. On the other hand, the impact of resource interdependence is not dependent on a high level of mutual trust. Moreover, the effect of trust is not reliant on resource interdependence. To understand these results better, more research is required.

What are the management implications of the findings? What should public sector managers that would like to increase collaboration do? This is hard to tell and it is probably wise not to draw far-reaching conclusions. However, some speculations would do no harm. One management strategy would be to highlight what agencies have in common and introduce transparent reporting systems between the organizations. By doing this congruent objectives can perhaps be communicated in a trustworthy way. It is not a feasible strategy to build up trust if the authorities’ goals diverge to a large extent or to focus solely on objectives without establishing trust. That is, the strategy must include both objectives and trust. On the other hand, situations of resource interdependence seem, more or less, to enhance cooperation by itself.

The hypotheses examined in the article are general, although the empirical tests are focused on labor market policies in the unitary Swedish system. There is no strong reason to assume that the research setting is atypical to other situations of local policy implementation. We can expect the results to hold for other similar situations as well. Nevertheless, some cautionary points should be mentioned. First, the empirical setting implies a rather truncated range on goal congruence by comparison with other types of collaborations. Disagreements might be more severe in other settings, for example, between public agencies and private enterprises. A good way to test the robustness of the results is thus to examine how they would fare under other conditions, in other countries, and in other policy areas. Second, the measures of resource interdependence are far from being perfect since interdependence is not observed directly. The fact that the results do not indicate an interaction effect between trust and mutual resource dependence might be a consequence of the somewhat problematic measures. Con-sequently, in future research, it would be beneficial if other indicators of re-source interdependence are examined. Third, I have taken some license to

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speculate on causal relationships while operating within the confines of cross-sectional data. Obviously, a longitudinal study would be suitable to test the propositions put forward in this article. In-depth case studies, or quantitative research, focusing on potential causal mechanisms would also be valuable. Even though the mechanisms are logical, they are assumed rather than tested in this particular case. In sum, and as always, work remains to be done. However, this study has moved the research agenda forward and provided insights about interorganizational cooperation when public policies are carried out at local level.


101

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105

Essay III

When Does Cooperation Improve Public Policy Implementation?*

Relationships between authorities impinge on policy implementation (O’Toole 2003) and it is often emphasized that public policy can be carried out better if cooperation increases among agencies. Some scholars claim that interorganizational cooperation is inherently good (for example, Hudson et al. 1999; Jones, Thomas, and Rudd 2004), although empirical evidence suggests that cooperation only sometimes enhances performance (Jennings and Ewalt 1998). The purpose of this article is to enrich our understanding of policy implementation by examining when a cooperative strategy actually makes implementation output better. More precisely, it is argued that the effects of cooperation vary with the complexity of the policy carried out.

An agency that cooperates with others can make use of additional resources, such as expertise and information. Activities can hopefully also be better coordinated. This suggests that interorganizational cooperation im-proves an agency’s ability to put policy into practice. On the other hand, it is difficult to work across organizational boundaries. For example, the col-laborating authorities have to devote a lot of time and other resources to establishing and maintaining a productive relationship. Thus, we cannot be sure that cooperation improves implementation in every situation. In this article, it is suggested that task complexity is a key factor that explains why the effect of cooperation on implementation output will be greater in certain situations. Basically, the benefits of cooperation are likely to more than offset the costs if the task is complex. In contrast, when the policy is not complex cooperation adds very little value, but still involves some costs. To my knowledge, this idea has previously not been thoroughly discussed and empirically evaluated in implementation research.

* I gratefully acknowledge comments from Hans Blomkvist, Paula Blomqvist, Matz Dahlberg, Jörgen Hermansson, Nils Hertting, Anders Lidström, Daniela Lundin, Eva Mörk, PerOla Öberg, Sven Oskarsson, and seminar participants at the Department of Government at Uppsala University, the Institute for Labour Market Policy Evaluation (IFAU), and the Annual Meeting of the Swedish Political Science Association 2004 for comments on early drafts of the article. I also thank Linus Lindqvist for some very valuable data management and IFAU for funding.

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The empirical focus is relations between different units of government. More precisely, the analysis concerns Public Employment Service (PES) offices and their relationship to local governments (municipalities) in the Swedish active labor market policy (ALMP). The PES is the main local labor market actor. But in recent years, municipalities have become an in-creasingly important factor (Lundin and Skedinger 2006; Salonen and Ulmestig 2004). The Swedish government encourages cooperation between these actors. But will implementation of labor market activities actually be improved if the PES cooperates a lot with the municipality? Is it possible to anticipate a positive effect on a broad range of policies, or is it only certain labor market activities that are affected positively?

Two policies are examined. One of the policies—activities for unemploy-ed youth—is not that complex. The other—activities for individuals with especially long spells of unemployment—is more intricate. Thus, I expect cooperation to be a more efficient strategy in the latter case. The quantitative analysis is based on recent data consisting of information from several sources. I make use of a questionnaire addressed to chief managers of the PES offices, and administrative data recorded by the Swedish National Labor Market Administration and Statistics Sweden.

The findings indicate that cooperation improves the implementation of activities for individuals unemployed for an especially long time. On the other hand, cooperation does not enhance the implementation of the youth policy. This indicates that complex tasks can be carried out better if a co-operative approach is employed, but that it is not reasonable to assume that interorganizational cooperation will always have a positive impact on how policies are implemented.

The rest of the article is structured as follows. First, the theoretical discourse is outlined. An introduction of the research setting comes next, followed by a section that discusses methodological issues and measures. Empirical findings are reported. I conclude by summing up the results and discussing their possible implications.

Implementation and interorganizational cooperation Local practices are not always the same as the intentions stated in official documents endorsed by politicians. In addition, performance frequently varies from one local context to another. As a result, it is wise not to assume that the study of statutes, government bills, and regulations will be enough to understand what political decisions imply “in the real world.”1

1 For overviews of implementation research, see, for example, Winter (2003b) and deLeon (1999).

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An implementation problem occurs when a political decision is not carried out in accordance with what the decision-maker wants. We assume that local practice should be in line with the elected officials’ intentions, that is, agents should follow the principal’s instructions. This perspective is easy to endorse, based on normative democratic theory. In a modern democracy, citizens freely elect representatives who can be held to account at the ballot box. Politicians cannot implement a policy all by themselves; they have to rely on a civil service to do this. But the citizens cannot replace the bureau-cracy by casting their vote. Consequently, a prerequisite for satisfactory democracy is that politicians control and govern a civil service that respects their decisions (Sannerstedt 2001).

There are arguments in favor of another point of view, which argues that the local civil service is more receptive to local desires and needs. Dis-crepancies between a decision and its implementation might therefore in practice mean a “better” policy and a greater responsiveness to citizens’ wishes. Depending on which normative starting-point is assumed, variation in—or insufficient—implementation performance is thus not always ne-cessarily a disadvantage (deLeon 1999). Nonetheless, most scholars would concur that it is troublesome if there is a gap between the law and practice (Keiser and Soss 1998). In this article, I focus on the top-down aspect of implementation, that is, implementation as compliance. It is, however, necessary to acknowledge that other angles of approach are just as relevant in implementation research.

Certain political decisions are quite easy to carry out and can be managed almost exclusively by a unitary public administration. A change in a tax rate or the level of a general welfare benefit is virtually self-implemented. But implementation is normally more complicated and involves several par-ticipants, who may be public or private. They may also be at different levels of government or operate in different policy areas. Hence, an important component in almost every contemporary framework explaining implemen-tation success and failure has to do with how interorganizational relation-ships are managed (for example, Bardach 1998; Goggin et al. 1990; Hjern and Porter 1981; O’Toole 2003; O’Toole and Montjoy 1984; Pressman and Wildavsky 1984; Winter 2003a). Furthermore, scholars have paid a lot of attention to the problem of multi-level governance in recent years. That is, how actors at various levels of government can be managed to work effectively towards public sector goals (Hooghe and Marks 2003; Peters and Pierre 2001). A particularly important subject, given a focus on multi-level governance, is how relationships between levels of government impinge on public policy.

An agency assigned the task of carrying out a political decision may use different techniques to implement a policy. For instance, the agency may try to cooperate as much as possible with other organizations. Cooperation (collaboration)—that is, all the interactions among organizations aiming at

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solving public problems by working together (cf. Smith, Carroll, and Ashford 1995)—is one of the golden words in public sector management. Through partnerships and other collaborative endeavors public sector performance is often considered to be improved. All else being equal, one would expect a public agency with access to significant resources to carry out a policy or program better than an agency which lacks resources (for example, Keiser and Soss 1998; Meier and McFarlane 1996). Organizations possess resources. An agency carrying out a political decision may thus enhance its own capacity by collaborating with other organizations (for example, Jennings 1994). The surrounding organizations may contribute with information, and they could have staff, knowledge, money, and premises, making the business of putting ideas into practice easier. By co-ordinating activities across organizational boundaries, the implementing agency can also avoid resource-consuming and conflicting activities that may result in socially perverse outcomes (Hooghe and Marks 2003). Thus, it is easy to see why interorganizational cooperation is often assumed to im-prove implementation.

But there are a number of prerequisites. First, the potential partner must have additional resources that can be of use to the focal agency. Second, the partner must be willing to share resources. Third, there are always costs associated with collaboration (for example, Schermerhorn 1975; Van de Ven 1976; Weiss 1987). Although a potential partner is willing to share valuable resources with the focal agency, cooperation may be a complicated process. To at least some extent, all organizations have different agendas and various routines to handle things. As a consequence, interorganizational cooperation may be a complicated process involving bargaining, and therefore call for considerable time and other resources on the part of the agents concerned. Another cost to be considered is that the principal’s objectives—for example, central government intentions—may be put on one side when the local agents concerned are trying to reach their best joint solution. In other words, instead of pursuing central government directives, local actors may work for other goals they can agree on. Since this study adopts a top-down perspective on implementation, such processes are not desired. In sum, the costs of cooperating might well outweigh the benefits and we should not assume that more cooperation implies that political intentions are always realized to a greater extent.2

Cooperation can, of course, have important implications for other aspects than implementation output. For instance, a public program might become

2 In an overview article on cooperation (not specifically about implementation issues) Smith, Carroll, and Ashford (1995, 17) note that research usually has a positive attitude towards cooperative activities, although cooperation in some cases can have harmful consequences. The authors underscore that “additional research is needed on the potential drawbacks of cooperation and the conditions under which a very high degree of cooperation is not desirable.”


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more effective if authorities cooperate, even if implementation is not enhanced.3 Cooperation might also imply that a decision becomes more legitimate in the eyes of the target group for a certain policy. But this study is limited to the question of how to make a political decision come true in accordance with officials’ intentions.

Jennings and Ewalt (1998) note that there is only anecdotal evidence that coordination—which in practice is measured as the level of cooperation—actually improves public services. Jennings and Ewalt examine the accomplishment of policy goals in employment and training services in the United States. In a prior article, Jennings (1994) indicated positive effects of coordination on the administrators’ subjective perceptions of performance. But in the study from 1998 objective outcome measures were employed as dependent variables. The analysis shows that coordination has a limited positive effect; most of the performance indicators were unaffected by the level of coordination. The findings suggest that although interorganizational cooperation may sometimes be a good strategy, we cannot expect it always to improve performance. There is some indication that there is a positive effect in the long run, but the evidence is not decisive.

On the other hand, Hudson et al. (1999, 238) note that “while recognizing that there are other positions, this article takes the normative position that collaboration is generally a ‘good thing’ – a stance which is consistent with the rather long history of collaboration in organization theory and public ad-ministration.” In many ways this is certainly true, but if we want to understand public administration and public policy implementation it must be better to improve theory on what the balance of benefits and costs would look like in various situations. This can tell us when cooperation actually is a good strategy.

There seems to be a lack of research on these matters. Pressman and Wildavsky (1984) suggest that the number of actors involved in an inter-organizational setting determines whether implementation will be successful; more actors mean greater probability of failure. O’Toole and Montjoy (1984) refine this argument and hold that a large number of actors makes im-plementation worse in cases of reciprocal interdependence (when actors poses contingencies for each other) and in sequential interdependence (when the output of one actor is the input of another). Contrarily, in cases of pooled interdependence (when actors contribute to a task without dealing with each other) and in sequential competitive interdependence (when there are actors competing to do the same thing in the implementation process) a larger num-ber of actors improves policy output. These scholars focus on the effects of 3 Even if a decision is carried out perfectly in line with the politicians’ intentions, that does not entitle one to say that the policy is effective. The decision itself could be based on a causal theory that is not accurate, that is, it is not certain that desired outcomes are achieved by the formula the statute or regulation suggests. This article focuses exclusively on policy outputs, not outcomes.

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the organizational setting per se, not the extent to which actors work together, which is the focus in this article. The question here is rather whether a lot of cooperation generates a better pay-off, given certain tasks. More specifically, is a high degree of cooperation especially rewarding for certain policy types?

The discussion is restricted to one policy dimension that deserves particular attention: task complexity. Task complexity is defined as the pro-duct of the scope of actions and the intensity required to carry out a policy. By scope I mean the extent to which many areas of expertise are required to fulfil the goals or, put another way, “the degree to which tasks are variable and require a multidisciplinary or multidimensional approach” (Alter and Hage 1993, 117). Intensity is a matter of how much work has to be done in order to realize ambitions; a task that requires many man-hours on the part of an agency is considered intense. Thus, a policy that has large scope and involves intense actions is complex. In research on interfirm partnerships, it is quite common to talk about joint task complexity as a function of the scope and depth (intensity) of interactions between firms (White 2005). This definition parallels the one used in the present study. Most organization theory scholars define complexity in a related vein, although there are alternatives on the same theme (see, for example, Alter and Hage 1993, 116–127).

Task complexity is an incentive for cooperation (cf. Alter and Hage 1993). A need for external resources boosts interorganizational cooperation (for example, Van de Ven and Walker 1984; Weiss 1987) and complex tasks require resources that cannot be found within a single agency. Thus, working across organizational boundaries becomes important when complex tasks are being carried out. In this perspective, actors cooperate when cooperation is needed, otherwise not.

But the extent of cooperation between two agencies, A and B, is certainly not only a direct function of the task complexity of policy X that A im-plements. Cooperation is a consequence of the agencies’ perceived total value of working together, which may be something rather different from the actual value that cooperation adds to the task of realizing policy X in accordance with official intentions. First, the agencies do not have perfect information and cannot take in all benefits and costs of cooperation. A does not know exactly what it can accomplish without a lot of cooperation and the greater value cooperation actually implies. Second, A cannot set cooperation precisely at the optimal level on its own. If B does not want cooperation to increase, A cannot do much about this since cooperation is a relational attribute. Third, the incentives and disincentives for A to cooperate with B are numerous.4 External pressure for cooperation is one example. Political representatives or other bureaucratic levels may exhort A to collaborate with 4 For an overview, see Alexander (1995, ch. 1).


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B. In some cases, a legal mandate may require A to cooperate with B. Norms and values in both organizations are other things that determine what level of cooperation will be established. Moreover, working together with B can make it easier for A to accomplish other goals than those related to policy X. Accordingly, although the net benefit of cooperation for A can be positive, this does not mean that policy X automatically becomes better implemented.

What this discussion has shown is that an agency carrying out a policy may use interorganizational cooperation to a lesser extent than another agency implementing the same policy, although both agencies would have made the same use of cooperation for realizing the specific policy in accordance with political intentions. This means that it is too restrictive to assume that task complexity impinges only on cooperation levels. It can also tell us something about the effect on policy output. Whereas the other factors mentioned above affect cooperation, it is only the cost-benefit analysis re-lated to the policy being implemented that determines the effect on imple-mentation in the specific case.

So the question is now why we should assume that the effect of co-operation would be greater as policy complexity increases. The impact of cooperation is contingent on the benefits and the costs. In a less complex policy, it is likely that the benefits of cooperation would be quite low. In these situations, the agency’s capacity is not going to increase that much by using other organizations’ resources since the most important resources are already available within the agency. Organizations are formed to perform certain tasks and in a less complex policy the most important resources are probably already available. This means that increasing levels of cooperation do not add that much value. As complexity rises, cooperation provides more benefits. The agency needs more expertise, information, money, premises, and so on. Through cooperation these resources can be attained.

The costs must also be considered before we can conclude that co-operation should be more rewarding in the case of a complex issue. As complexity increases, the costs of cooperation are also likely to increase. For instance, the risk of disputes and impediments becomes greater. But while the benefits of cooperation are very low given little complexity, there will always be costs. In fact, many costs are independent of the level of complexity. The costs of arranging and participating in a meeting are, for example, not much larger in the case of a complex policy. Cooperation is a dynamic process and decisions and activities within a policy are not in-dependent of each other. Given that actors agree on some basic things, the additional problems that arise with increasing complexity will not be that high.

In another context—interfirm alliances—White (2005) considers the costs associated with cooperation. Even though he claims that costs are higher given a complex task, he repeatedly notes that the benefits are often likely to be even greater. He claims that “additional costs of a more complex interface

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may be more than offset by the benefits possible from more extensive interaction” (1388) and if the partners have relatively similar objectives and values, “the additional marginal cooperation costs resulting from greater scope or depth-related coordination costs should be more than offset by increased benefits” (1395).

In sum, it seems likely that in a situation characterized by low task complexity there will be very little (or no) benefit from cooperation, but some costs. These costs increase somewhat as complexity increases, but the increase will be lower (and probably also diminishing) than the increase in benefits. If complexity is high, the large benefits will prevail over the costs. Cooperation is therefore a more value adding activity given complex tasks. Accordingly, we should expect the effect of cooperation on policy output to be greater given complex tasks. These arguments are perhaps not brand new, but to my knowledge they have not been discussed and evaluated empirically in the context of local policy implementation.

Intergovernmental cooperation in Swedish active labor market policy To discern whether policy complexity is an important variable, we need to know the effects of cooperation on the implementation of at least two policies: one complex task and another less complex task. Swedish ALMP provides rather good opportunities to examine this.

Unemployment is a huge problem in most OECD countries and the unemployment rate has, on average, doubled since 1973 (Martin and Grubb 2001). A government can use ALMPs to reduce unemployment. Job brokering activities and labor market programs are examples of such active measures. In Sweden, the National Labor Market Administration (Arbets-marknadsverket) implements the policy. Local PES offices (Arbets-förmedlingar) carry out most of the programs in practice. There is a PES in nearly all cities, and in larger cities there is usually more than one office.

Although the National Labor Market Administration is clearly the most important authority managing ALMPs in Sweden, other actors are involved. One feature in recent years has been more involvement on the part of local governments in the implementation of ALMPs (for example, Lundin and Skedinger 2006; Salonen and Ulmestig 2004). The municipalities take an active part by, for example, organizing labor market programs. About 40 percent of the clients involved in programs administered by the National Labor Market Administration are participating in activities in which the municipalities are involved (Lundin and Skedinger 2006). This is a large proportion. A lot of the municipal activities are targeted at social welfare benefit recipients (Salonen and Ulmestig 2004) and at unemployed youth


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(Carling and Larsson 2005). The content of the activities varies, but job-search assistance and work practice are quite common. A majority of municipalities have recently established special labor market ad-ministrations. There was an increase in the number of municipal labor mar-ket administrations in the 1990s, indicating an increased municipal involvement in Swedish ALMPs. Seven in ten municipalities had a special department for labor market issues in 1998, compared to two in ten in 1995 (Swedish Association of Local Authorities 1999).

The municipalities have a premier position within the Swedish political system. For example, they have the constitutional right of self-government; they are comparably large; they can decide on their own organization; and their incomes come mostly from a proportional income tax they can set freely.5 In comparative perspective, local governments in Sweden are often considered to have a powerful position (Norton 1994).

The municipalities provide most of the services of the Swedish welfare state. For instance, they supply day care, care of the elderly, social welfare services, introduction of immigrants into Swedish society, and primary education. Local development is another issue that concerns local govern-ments. Several of these policy areas—the most obvious example being social welfare services—clearly intertwine with ALMPs. This suggests that collaboration with the municipality could be beneficial for the PES. In addition, municipalities are also very large employers and employ 20 percent of the total Swedish workforce. Cooperating with large employers is, of course, also potentially very beneficial for the PES.

In the empirical analysis, effects of cooperation between the PES and the municipality on implementation of ALMPs are examined. The study con-cerns two policies. One of the policies is definitely more complex. The positive effect of cooperation is anticipated to be greater in this policy.

In August 2000, the Swedish government launched a new labor market program called the Activity Guarantee (Aktivitetsgarantin). The target group was individuals who had been unemployed for a considerable time period. By means of intense job-search assistance and close monitoring, persons who were, or who risked being, long-term unemployed were to be given a place in the program. All traditional ALMPs could be used within the Activity Guarantee. Accordingly, the content of the activities varies to a large extent. The political ambition was that jobseekers should be enrolled in the program after 27 months of unbroken PES registration, at the latest. What distinguishes the Activity Guarantee from other labor market programs is its intensity. All activities are assumed to be full-time activities and the participants should meet their personal PES supervisor on a regular basis, and more frequently than before they entered the program. Since the persons

5 For some descriptions of the Swedish municipalities, see Bäck (2003) and Gustafsson (1999).

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participating in the guarantee are “hard cases” and often have multiple problems, the government calls for intense treatment and encourages PES offices to collaborate with other local actors. The local governments are, in practice, the PES offices’ most common cooperation partners (Forslund, Fröberg, and Lindqvist 2004).

In 1994, the Swedish government declared that no young person should remain unemployed for more than 100 days. The government regarded long-term unemployment as devastating for future labor market prospects. Young people are defined as long-term unemployed if they are unemployed for more than 100 days. Thus, the ambition was that every individual of below 25 years of age should be offered a labor market program if they were unable to find a job within three months of registration at the local PES. The central government encouraged the municipalities to take part in actions to reduce long-term unemployment among young people in different ways. For instance, in 1995 the government introduced the Municipal Youth Program (Kommunala ungdomsprogrammet) and three years later the UVG-guarantee (Ungdomsgarantin). The PES offices are expected to collaborate with local governments in both programs (Carling and Larsson 2005).

Recall that task complexity is defined in terms of the scope and intensity of a policy. The Activity Guarantee is more intense and has greater scope. Thus, it is a good representative of a complex policy. First, consider the client groups. In the Activity Guarantee, the clients are comparatively old and they are obviously not particularly attractive on the labor market since they have been looking for a job for such a long time. It is also reasonable to assume that a relatively large part of the clients have multiple problems since the program is directed at those with the weakest position on the labor market. In comparison, youth clients have not been unemployed for such a long time. Consequently, they are probably more motivated, more homo-genous, and easier to handle. Accordingly, the treatment of clients in the Activity Guarantee needs more areas of expertise and more intense activities.

Second, although various youth activities are probably not so simple to implement, the Activity Guarantee is more complex. The activities are supposed to be rigorous and carried out in small groups. Contacts between clients and personal supervisor are also expected to be more frequent than is generally the case. In short, these activities are more intense. Moreover, the government’s intention was that the program should be flexible and contain various activities suited for the individual client. This means that the Activity Guarantee is intended to have greater scope than other ALMPs. On balance, it is safe to conclude that the Activity Guarantee is much more com-plex that the youth policy, even though some youth activities can also be said to contain complexities. Thus, I predict a greater effect of cooperation on implementation output in the Activity Guarantee.

The selected research setting is suitable for several reasons. First, unemployment is a large societal problem and a lot of resources are allocated


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to diminishing the unemployment rate all around world. Studies that can bring some clarity to what is going on when ALMPs are put into practice are therefore important. Second, this study is focused on the relationships between the same types of actors who implement the same policies around Sweden. This implies that features of the agencies and the policies that do not vary can be held constant. From a methodological point of view this is very beneficial. Third, Swedish ALMPs can be seen as a “critical case”, meaning that here, if anywhere, we ought to expect that cooperation will improve implementation on a broad range of activities. O’Toole (1983) claims that there are very high information and expertise requirements in ALMPs. Interorganizational cooperation is therefore likely to be a good strategy for gathering the necessary resources. Furthermore, there are obvious connections between the responsibilities of the PES offices and the municipalities. This means that we have good reasons for believing that cooperation is a good strategy when it comes to both policies. If cooperation does not enhance the implementation of the youth policy and not even the Activity Guarantee we should probably not anticipate general positive effects of interorganizational cooperation either.

Method and measures Whereas quantitative approaches have become increasingly common and more sophisticated in the implementation literature from the United States, studies based on large-N data in the European context are rare. The lack of quantitative studies implies at least two problems. First, it is difficult to generalize the findings when studying only one or a couple of cases. Second, it is extremely difficult to control for a large number of potential explanations in case studies; almost inevitably we end up in a situation in which several variables account for the variation in the dependent variable equally well. Goggin (1986) pointed this out several years ago and Winter (2003b) accentuated the importance of statistical approaches to implement-ation problems in an overview article in Handbook of Public Administration. Qualitative studies are still important, but right now quantitative research based on European data is probably more needed.6

To test whether cooperation is related to implementation performance, cross-section data covering 2003 were collected. The PES offices are the unit of analysis. Questionnaires were distributed to the chief managers of all PES offices in February 2004: 268 managers answered the questionnaire, which implies a response rate of 75 percent. An analysis of the non-responses showed no noticeable difference between respondents and non-

6 Daley and Layton (2004), Brehm and Gates (1997), Keiser and Soss (1998), and Meier and McFarlane (1996) are examples of studies using large-N data from the United States.

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respondents on background characteristics. Register data from the National Labor Market Administration supplement the survey. Lastly, official statis-tics, in the form of municipal characteristics, are taken from the KFAKTA03 database. Variables are discussed below (see also Appendix).

Cooperation In the questionnaire, the PES managers were asked whether the PES and the municipality had set up regular cooperative groups in which (a) caseworkers from the two authorities work together and (b) the managers collaborate. The managers also indicated whether (c) caseworkers contact each other on a daily basis or more seldom. In addition, they provided information about whether the agencies had formal collaborative contracts concerning (d) the youth policy and (e) the Activity Guarantee.

Table 1. Cooperation between PES Offices and Municipalities, Various Indicators Mean/

proportion Standard deviation

Minimum Maximum

Cooperation, five items 3.50 1.36 0.00 5.00

Cooperation, three items 1.96 0.96 0.00 3.00

Youth contract 0.77 – – –

AG contract 0.80 – – –

A factor analysis showed that all items load high on a single dimension (see Lundin 2007 or Essay II of this thesis). Thus, an index was constructed. It is a simple additive index: a value of zero implies that none of the above mentioned ways of cooperating was used, whereas agencies that use all five activities got a score of five. To make interpretation easier, the factor scores obtained from the analysis are not utilized in the article. But the analyses have been carried out based on the factor scores as well, and the conclusions are unchanged.

One problem with the index is that two of the items are directly associated with the youth policy and the Activity Guarantee, respectively. The other three items are more general. I have therefore decided to test the robustness of the results. I use the complete index with all five indicators, but also an alternative index ranging from zero to three in which the collaborative contracts in (d) and (e) are excluded. In addition, the contracts are employed as indicators of cooperation. Summary statistics are reported in Table 1.


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Implementation performance Three measures of implementation performance are employed in the article. I consider enrollment in programs among youth (Y-Enrollment) and enrollment in the Activity Guarantee (AG-Enrollment). I also study whether the PES arranges full-time activities within the Activity Guarantee (AG Activity). Obviously, there are many other aspects of the performance that ideally should be taken into account. The quality of the programs is not directly assessed in this way and it is possible that activities to some extent are meaningless. But the performance measures have certain appealing features. The variables concern vital parts of the policies, the elected representatives’ directives are also relatively clear, and quantitative data are available and reliable. These three factors make them suitable dependent variables and they are definitely important things to consider if we want to know how government ambitions have been realized.

Two variables address the implementation of the Activity Guarantee. First, unemployed persons are supposed to be enrolled in the Activity Guarantee after 27 months of unbroken PES registration at the latest. I calculate how large a proportion of the individuals with 835 days (27.5 months) or more of PES registration was activated in the Activity Guarantee on four occasions (15 February, May, August, and November). The average value indicates how well the agency manages to enroll clients. The reason for not using precisely 27 months is to avoid problems that a delay in re-gistration might entail. This variable is named AG-enrollment and a higher score implies better implementation. Data come from the National Labor Market Administration.

Second, the activities should be full-time for all participants in the Activity Guarantee. In the questionnaire, the managers were asked whether the PES arranges full-time activities for all (or almost all) of the participants in the Activity Guarantee. The information from the questionnaire is used as a second measurement of the implementation of the program. This variable can take on two values (0 = no, 1 = yes) and a score of one thus implies better implementation. The variable is referred to as AG Activity.

The central government ambition for youth unemployment is clear-cut: if individuals under the age of 25 have not found a job after 100 days of un-employment the PES should activate them by applying labor market programs. Using data from the National Labor Market Administration ad-ministrative system, I investigated the stock of persons of 20–25 years of age on four occasions (15 February, May, August, and November) in 2003 for each PES office. I counted the number of individuals unemployed for 110 days or more in sequence, without participating in a program, directly before the point of measurement. By setting the point of calculation to 110 days instead of 100, I made sure that the results were not affected by a possible delay in registration. To standardize the measure, I divided the values by the

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number of youth clients registered at the PES for 110 days on the same occasions. In order to make interpretation easier, the computed values were subtracted from one. The average of the four points of measurement was calculated. This gives the variable Y-enrollment. A higher value means better output.

Table 2. Implementation of the Youth Policy and the Activity Guarantee Mean/

proportion Standard deviation

Minimum Maximum

Y-Enrollment 0.66 0.14 0.10 0.95

AG-Enrollment 0.49 0.16 0.00 0.97

AG Activity 0.71 – – –

Table 2 describes how the offices have succeeded in implementing the youth policy and the Activity Guarantee. There are youth who do not participate in programs but who should, according to the government’s intentions. The Activity Guarantee has not been fully implemented either since around half of the target group is not engaged in activities and only seven in ten managers say that they arrange full-time activities. Note that there is a lot of variation in implementation performance.

Why should we expect that cooperating with the municipality makes it easier for the PES to improve the implementation aspects mentioned above? There are many possible reasons and I shall briefly mention two: If the municipality can contribute with money, staff, and premises it becomes easier to enroll clients and make sure that the activities are conducted on a full-time basis. If the municipality helps the PES to find work places where participants can participate in work practice, the PES can devote more time to making sure that the target group is reached and that programs are con-ducted full-time.

Control variables Unfortunately, the implementation research discourse has not been able to develop a generally accepted theory that pinpoints the precise variables to in-clude when explaining implementation. As O’Toole (2004, 310) puts it, “theories about policy implementation have been almost embarrassingly plentiful, yet theoretical consensus is not on the horizon … After hundreds of empirical studies, validated findings are relatively scarce.” But there are some broad categories of factors that merit attention. External and internal characteristics of an agency carrying out public policies may influence imp-lementation (Gill and Meier 2001; Keiser and Soss 1998; Winter 2003a).


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External characteristics that should be taken into account are the client group treated and the implementation environment (Winter 2003a). A de-manding clientele and a difficult labor market situation might affect imp-lementation positively or negatively. On the one hand, the task becomes more challenging, which may make implementation more difficult. On the other hand, the incentives to arrange appropriate programs are probably stronger since it is less likely that clients can manage on their own. There should also be greater demand for services when the labor market situation is problematical.

Three variables that describe clients’ characteristics are used as control variables. Some offices are responsible for vocational rehabilitation of un-employed individuals. These agencies’ clientele is quite different from the client group of the standard PES, and therefore a dummy variable for re-habilitation PES is incorporated in the analyses. The other two controls are the proportion of long-term unemployed clients and the proportion of clients who are not Nordic citizens (Non-Nordic clients). By including these variables, I am able to hold important clientele characteristics constant.

The characteristics of the PES offices’ local context are measured by the following variables. The municipal unemployment rate, including partici-pants in active labor market measures, provides an assessment of the local labor market situation. The size of the local population is added as a control in order to address other socio-economic factors; the local labor market is very different in a large, urban area in comparison with a thinly populated municipality with a small population. A dummy variable (socialist government) indicating the presence of a Social Democratic government or a non-socialist government captures the local political context. This political variable’s importance for implementation has been stressed in earlier studies (Keiser and Soss 1998). Leftist governments are usually more positive to-wards governmental interventions such as labor market programs (Korpi 2006). Operating in a context in which socialist values are strong can make the task of implementing policy ambitions easier.

Performance could also vary due to factors internal to an agency. Keeping external circumstances constant, agencies which have employees who are more willing to carry out a policy and who have a high capacity to implement decisions will, on average, perform better (Sannerstedt 2001).

There is solid evidence that the incentives, preferences, and attitudes of bureaucrats often affect implementation (Brehm and Gates 1997). Im-plementation is likely to be improved if an agency gives a policy high priority. The questionnaire supplies data on the PES managers’ attitudes to-wards different labor market goals. Among thirteen labor market objectives, the managers rated the importance of arranging programs for unemployed young people and for unemployed individuals with severe problems on the labor market. From this rating, I have constructed a ranking of the objectives of each PES office. The rating is composed so that the goal that receives the

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highest priority gets a score of thirteen; the other goals are arranged in de-scending order so that the least important objective gets a score of one. Thus, the variables priority of youth clients and priority of difficult clients assess how important the two relevant client groups are to the PES offices.

It is difficult to obtain good indicators of an agency’s capacity. But staff and financial resources are the main factors influencing capacity. If the agencies do not have these resources they will certainly run into difficulties when policies are implemented (Gill and Meier 2001; Sannerstedt 2001). The National Labor Market Board allocates resources so that each agency receives an amount reflecting the local labor market situation and the client group (Nyberg and Skedinger 1998). Thus, if resources are allocated adequately, capacity should not vary due to staff and financial resources. Nevertheless, in the event that resources are distributed poorly, the number of clients per staff member and the amount of financial resources per client reserved for benefits for participants in programs are used as control variables.

Several organizational factors could shape the agency’s capacity (Winter 2003a). Identifying the important organizational characteristics is difficult, and the capacity may impinge on various variables we cannot observe. In this article, organizational size is employed as a control variable. This is primarily motivated by the fact that large agencies have greater opportunities to cooperate with other organizations. For instance, a large staff increases the chance that an agency will communicate with the municipality on a daily ba-sis. Another reason for including size is that this variable could be correlated with many organizational aspects that may affect implementation. The logarithm of the number of employees at the PES is utilized as a measure of organizational size. I use the logarithm since it is reasonable to assume that a one-unit change in the number of employees is more important when staff size is small than when it is large.

Findings In the following section, I examine whether the degree of cooperation can account for the differences in implementation performance depicted in Table 2. The empirical results are reported in two sub-sections.

Effects of cooperation: The Activity Guarantee Estimates from ordinary least squares (OLS) regression models are presented in Table 3. The dependent variable is AG-Enrollment. The number of ob-servations is between 201 and 212, although the number of questionnaire respondents was 268. Some agencies do not handle the Activity Guarantee


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and there are also internal missing values for some variables. Thus, the num-ber of valid cases is reduced.

Table 3. OLS Regression Analysis with AG-Enrollment as Dependent Variable (Standard Errors in Parentheses)

1 2 3 Cooperation, five items 0.030

(0.010)***

Cooperation, three items 0.027(0.012)

**

AG contract 0.090(0.026)

***

Rehabilitation –0.091(0.083)

–0.092(0.074)

–0.081(0.073)

Long-term unemployed clients 0.481(0.256)

* 0.482(0.247)

* 0.541(0.245)

**

Non-Nordic clients –0.432(0.183)

** –0.348(0.179)

* –0.375(0.176)

**

Unemployment –0.021(0.005)

*** –0.020(0.005)

*** –0.021(0.005)

***

Local population 0.000(0.000)

0.000(0.000)

0.000(0.000)

Socialist government –0.007(0.023)

–0.003(0.022)

–0.008(0.022)

Priority of difficult clients 0.004(0.004)

0.003(0.004)

0.004(0.004)

Clients per staff member –0.012(0.007)

* –0.013(0.007)

* –0.010(0.008)

Financial resources 0.046(0.035)

0.040(0.034)

0.054(0.034)

Organizational size –0.049(0.017)

** –0.043(0.017)

** –0.032(0.016)

**

Constant 0.593(0.083)

*** 0.635(0.081)

*** 0.553(0.083)

***

Adjusted R² 0.180 0.152 0.187

Standard error of regression 0.139 0.139 0.137

Number of observations 201 212 208

* p < .10; ** p < .05; *** p < .01.

In Model 1, the index that includes all five indicators of collaboration is used as the main independent variable. The results indicate a positive effect of cooperation on implementation. When controlling for internal and external characteristics, the share of clients engaged in the Activity Guarantee in-creases by roughly 3 percentage points, on average, if cooperation increases by one step. The effect is significant at the .01 level. The impact is sub-stantial but not huge. An increase in cooperation by one step is quite a large

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increase (almost a standard deviation) and this yields an increase of clients enrolled in the program by a moderate 3 percentage points. But it is not reasonable to expect that a lot of cooperation between the PES and the municipality should imply a dramatic difference. And cooperation seems not unimportant: going from the sample minimum to the maximum increases enrollment by 15 percentage points, on average.

If the cooperative contracts are excluded from the collaboration index (see Model 2) the effect becomes a little bit lower. But it is still of importance (0.027) and it is significant at the .05 level. Model 3 indicates that agencies having a formal cooperative contract, on average, manage to engage about 9 percentage points more of the target group, all else being equal. The effect is statistically significant at the .01 level. The contract seems to account for a noticeable part of the overall effect, which is not surprising since the contract is linked directly to the Activity Guarantee. To sum up, cooperation has a positive effect on implementation no matter how the variable is operational-ized.

Control variables are only commented upon briefly. Client group characteristics and the labor market situation affect implementation. More-over, large organizations perform worse, whereas agencies having few clients per staff member seem to achieve objectives to a greater extent.

To examine the robustness of the results, several diagnostics tests have been carried out. I find no problem of heteroscedasticity or multicollinearity. There are some influential outliers but the results are not substantially altered if outliers are excluded from the regression model. Diagnostic plots did not indicate any non-linear relationships. There might be some problem of endo-geneity regarding two control variables: the share of long-term unemployed clients and the unemployment rate. I have estimated models excluding these variables. Conclusions remain the same. In addition, numerous model specifications including various control variables have been tested. The results are quite robust, although the two cooperation indices turn out to be statistically insignificant in a small number of specifications. The effect of the contract is very robust.

The level of activation within the Activity Guarantee is a dichotomous variable. The estimation method when using AG Activity as the dependent variable is therefore binary logit. Results are reported in Table 4. The logit model yields information about whether the relationship is positive or negative and if it is statistically significant but the coefficients are not readily interpretable. Thus, predicted probabilities, based on logit coefficients, are reported in Figure 1.


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Table 4. Binary Logit Regression Analysis with AG Activity as Dependent Variable (Standard Errors in Parentheses)

1 2 3 Cooperation, five items 0.345

(0.175)**

Cooperation, three items 0.241(0.223)

AG contract 1.539 (0.470)

***


–0.998(1.355)

–1.289 (1.388)

Long-term unemployed clients

–3.468(4.591)

–2.068(4.422)

–2.210 (4.594)

Non-Nordic clients 3.170(4.250)

3.610(4.176)

3.701 (4.405)

Unemployment 0.450(0.137)

*** 0.447(0.134)

*** 0.464 (0.139)

***

Local population –0.003(0.002)

* –0.004(0.002

** –0.004 (0.002)

**

Socialist government –0.276(0.413)

–0.225(0.403)

–0.229 (0.418)

Priority of difficult clients 0.146(0.073)

** 0.151(0.070)

** 0.191 (0.075)

**


–0.094(0.119)

–0.085 (0.129)


–0.021(0.583)

0.167 (0.620)


** –0.556(0.326)

* –0.472 (0.313)

Constant –1.514(1.433)

–1.152(1.389)

–2.821 (1.540)

*

Pseudo R² (McFaddens R²) 0.185 0.187 0.217

Log likelihood –98.037 –102.276 –96.456


* p < .10; ** p < .05; *** p < .01.

Table 4 indicates that cooperation increases the probability of arranging full-time activities within the Activity Guarantee. But when the cooperative contract between the PES and the municipality is excluded from the index (see Model 2), the effect is statistically insignificant. The findings are very robust to model specification.

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0.2

.4.6

.81

Pr(F

ull t

ime

activ

ity)

0 1 2 3 4 5

Cooperation

Figure 1. Predicted Probabilities of Organizing Full-Time Activities within the Activity Guarantee as the Level of Cooperation Changes (Continuous Control Variables Held at Mean Values and Discrete Control Variables Held at Mode Values)

Figure 1 displays the probability of arranging full-time activities as the level of cooperation changes. In this graph, logit estimates from Model 1 have been used. The probability varies between approximately .40 and .80 depending on how much the agencies collaborate. This is a large difference. The effect is, of course, even stronger if the contract is employed as the in-dicator of cooperation, but weaker and insignificant at all conventional levels if the contract is excluded from the model specification.

A few notes on control variables are appropriate. The probability of arranging full-time activities within the Activity Guarantee increases when the PES office prioritize clients with an especially difficult situation on the labor market and when unemployment is high. Large organizations and agencies located in large cities have a lower probability of arranging full-time activities. Note that it seems that the control variables do not affect the variables AG Activity and AG-Enrollment in the same manner.

The findings presented above clearly indicate that cooperation between PES offices and municipal labor market administrations improves the PES offices’ implementation of the Activity Guarantee. There are, however, two methodological challenges to the results. First, there might be some import-ant control variables that are left out from the model specification. The capacity of the PES offices is probably the most difficult thing to assess in a quantitative study. I have tried to control for as many variables as possible


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and the problems are probably not that big. Although I recommend some caution, it seems we can be quite confident in the conclusions.

Second, the time order between cooperation and implementation might be reversed. For example, if a PES office arranges full-time activities for clients in the Activity Guarantee, the need for external assistance may increase and/or municipalities may be more interested in collaborating with the PES. In turn, this will lead to more cooperation between the authorities. This is certainly a possibility, although the assumed time order is probably more likely. But this problem should not be ignored. One way to test causal order is to check the timing. Cross-section data are limited in providing evidence of time precedence, whereas panel data have advantages (Finkel 1995). Some panel data are available for a smaller number of cases (137 agencies). I have information about whether the PES arranged full-time activities for the clients in the Activity Guarantee in 2001 and 2003. I also know if a collaboration contract existed in 2001 and 2003.7 These data can be utilized to estimate a two-wave cross-lagged effect model, which is a test of the time order between variables. The basic idea is to predict each variable (AG-Enrollment and AG Contract) in 2003 by its previous value in 2001 (the lagged dependent variable), as well as the value of the other variable in 2001.8

The cross-lagged model cannot be regarded as a definite solution to the time order problem, although it is a useable test. Data exist only for a subsample of agencies and only some of the important dependent and in-dependent variables are available. I also have to assume that the causal lags are about two years. That is, signing a contract in 2001 affects implement-ation approximately in 2003. It is reasonable to assume that there is some time lag, although two years is perhaps on the high side. To save space, a table or a figure reporting the results is not presented in the article. But the test indicates that having a collaborative contract in 2001 significantly (at the .05 level) increases the propensity to organize full-time activities in 2003. For instance, having a cooperation contract in 2001 increases the probability of arranging full-time activities in 2003 by .24, given that full-time activities were not arranged in 2001. On the other hand, the effect of arranging full-time activities in 2001 on the propensity to have a collaborative contract in 2003 is not statistically significant (although there is a small positive coefficient). This speaks clearly in favor of the time order assumed in the analyses. That is, cooperation precedes implementation.

7 Data for 2001 come from a research project at the Institute for Labour Market Policy Evaluation (IFAU); see Forslund, Fröberg, and Lindqvist (2004). 8 The cross-lagged model is compatible with the “Granger test” for causality employed in time series analysis. Finkel (1995) describes the cross-lagged model and the underlying assumptions.

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Effects of cooperation: The youth policy In 2003, the Activity Guarantee was a more complex task than the youth policy. Cooperation is therefore expected to be a less successful strategy when it comes to youth. The findings are reported in Table 5. The table shows estimates from OLS regression models. Robust standard errors are reported, due to heteroscedasticity.

The regression coefficients of the cooperation indicators are very close to zero regardless of how cooperation is operationalized in Models 1–3. The effect is also statistically insignificant. The only reasonable conclusion is thus that cooperation does not affect implementation. Instead, traditional fac-tors highlighted in the literature appear to account for the variation in per-formance. More clients per staff member and a larger share of clients with an especially difficult situation on the labor market make implementation worse. An increase of financial resources and a challenging local labor market situation result in a larger share of young unemployed clients en-rolled in labor market programs.

To test the robustness of the findings, numerous diagnostic tests have been carried out. I have also specified the model in many ways using various sets of control variables. The results are robust and there is no indication whatsoever that collaboration improves the implementation of the youth policy. I have no data to examine time order but it is reasonable to assume that cooperation is causal prior to implementation since the analysis in the previous section provided some evidence of this.

To summarize, cooperation improves the implementation of the Activity Guarantee but not the youth policy. Is this really a consequence of task complexity or does something else explain the findings? The research setting implies that many potential explanations are taken into account: for example, the policy area, the actors involved, and the local context. This means that the explanation has to do with the policies. A hypothesis competing with complexity is the agencies’ interests in the two policies. The municipalities may, for some reason, pay less attention to the youth or the agencies’ objectives concerning youth may diverge to a large extent. But quantitative evidence indicates that the target groups of both policies receive equally and very high priority from both authorities (see Table 1 the Introduction to this thesis). Thus, task complexity is a more promising explanation.


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Table 5. OLS Regression Analysis with Y-Enrollment as Dependent Variable (Robust Standard Errors in Parentheses)

1 2 3 Cooperation, five items –0.004

(0.008)

Cooperation, three items –0.004(0.011)

Youth contract –0.004 (0.018)


–0.124(0.097)

–0.033 (0.080)

Long-term unemployed clients –0.599(0.235)

** –0.554(0.229)

** –0.598 (0.222)

***

Non-Nordic clients –0.516(0.170)

*** –0.560(0.175)

*** –0.529 (0.171)

***

Unemployment 0.019(0.004)

*** 0.018(0.004)

*** 0.019 (0.004)

***

Local population –0.000(0.000)

–0.000(0.000)

–0.000 (0.000)

Socialist government 0.014(0.016)

0.010(0.015)

0.012 (0.016)

Priority of youth clients 0.004(0.006)

0.003(0.005)

0.004 (0.006)


*** –0.023(0.006)

*** –0.023 (0.006)

***


* 0.048(0.026)

* 0.046 (0.026)

*


–0.018(0.013)

–0.022 (0.012)

*

Constant 0.758(0.092)

*** 0.766(0.090)

** 0.762 (0.092)

**

R² 0.397 0.405 0.407

Standard error of regression 0.110 0.110 0.109


* p < .10; ** p < .05; *** p < .01.

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Conclusion Interorganizational cooperation is an important factor to consider in policy implementation. Contacts between various public authorities are inescapable in contemporary democratic states. Practitioners and scholars are therefore interested in understanding how interorganizational relationships impinge on the delivery of political decisions. But when does cooperation actually improve implementation? Research thus far has not provided a satisfying answer to this question. Part of the answer is offered in this study: the impact of cooperation increases with task complexity.

Collaborative efforts of Public Employment Service (PES) offices and municipal labor market administrations in Sweden have been examined. The findings indicate that cooperation improves implementation of measures directed towards persons who have been unemployed for a very long time. The implementation of measures directed towards youth is not affected. The striking difference between these policies, it is argued, is that the program for clients with an especially difficult situation on the labor market (the Activity Guarantee) is much more complex. Three questions emerge as a consequence of the analysis: How reliable are the findings? Could they be generalized? And what are the implications?

The empirical results have been subjected to numerous checks and the findings appear to be very robust. It seems that we can be quite confident of the results, although more research is always valuable. A couple of minor caveats should be reported. Data are cross-sectional, which implies some restriction when it comes to causal statements. The analysis is also limited to a couple of measures of implementation performance and to two policies.

It is always difficult to generalize the results from a study of a certain policy area to other contexts. But the present research setting provides rather good opportunities. I have argued that the case comes near to being a “critical case”. Labor market policies require a lot of resources, such as information, to be implemented effectively. The PES offices and the municipalities hold important resources, there are clear connections between the authorities, and they share the overall goal of reducing unemployment. Thus, if we do not find positive effects of cooperation on the implementation of both complex and less complex policies within this policy area, we are not likely to find positive effects when the demand for resources is less obvious and the ties between the actors are less clear.

The main conclusion of this study is that interorganizational cooperation is a reasonable strategy in order to make the implementation of political ideas better—but only under certain circumstances. This conclusion is important for central discourses in political science, such as implementation research and research on multi-level governance. There is a general positive attitude towards cooperation. The findings suggest that it is appropriate to be more careful. Decision-makers in the public sector should not always stress


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the importance of cooperation, but rather reflect on the necessity to collaborate as much as possible across organizational boundaries. Many public concerns could probably be handled quite well without extensive interorganizational cooperation. This does not, of course, mean that inter-organizational cooperation should always be completely avoided.

The idea of solving public problems by means of partnerships of actors is popular both in “real life politics” and among academic scholars. For example, several researchers taking the “governance” discourse as a point of departure praise the partnership model.9 This model, based on the idea that several local actors should collaborate in order to improve the delivery of public policy, has had a pervasive breakthrough in recent years. The findings of this study suggest that we should not be too eager to praise the partnership model. Cooperation might, of course, be valuable for other reasons than those investigated here. But for the sake of clarity, it is important to develop and test theories about when interorganizational cooperation improves public policy implementation or other important aspects of society. This is better than stipulating that collaboration is a “good thing” in general.

9 See, for example, Pierre (2000) for an overview of the governance literature.

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Appendix: Description of variables

AG Activity The PES office arranges full-time activities for all (or almost all) clients participating in the Activity Guarantee. Dummy variable: 0 = no (.29); 1 = yes (.71). Based on questionnaire data.

AG-Enrollment Proportion of persons registered for a sequence of 835 days or more at the PES office enrolled in the Activity Guarantee; average of four different points of measurement (15th of February, May, August and December 2003). Based on register data from the National Labor Market Administration. Mean: 0.49, sd: 0.16, min: 0.00, max: 0.97.

Y-Enrollment Young persons aged 20 to 25 with at least 110 days of open unemployment in sequence, divided by the total number of young people registered at the PES for at least 110 days; average of four different points of measurement (15th of February, May, August and December 2003). Based on register data from the National Labor Market Administration. Mean: 0.66, sd: 0.14, min: 0.10, max: 0.95.

Cooperation, five items Index of cooperation. Includes cooperative groups at manager level, cooperative groups at case worker level, daily communication at case worker level, cooperative contract concerning the youth policy, and cooperative contract concerning the Activity Guarantee. Based on questionnaire data. Mean: 3.50, sd: 1.36, min: 0.00, max: 5.00.

Cooperation, three items Index of cooperation. Includes cooperative groups at manager level, cooperative groups at caseworker level, and daily communication at caseworker level. Based on questionnaire data. Mean: 1.96, sd: 0.96, min: 0.00, max: 3.00.

AG Contract The PES office and the municipality have signed a cooperation concerning the Activity Guarantee. Dummy variable: 0 = no (.20); 1 = yes (.80). Based on questionnaire data.

Youth Contract The PES office and the municipality have signed a cooperation contract about youth programs. Dummy variable: 0 = no (.23); 1 = yes (.77). Based on questionnaire data.


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Rehabilitation PES office responsible for vocational rehabilitation. Dummy variable: 0 = no (.96); 1 = yes (.04). Data obtained from the Internet homepage of AMV, www.ams.se.

Long-term unemployed clients Share of clients at the PES office unemployed for six months or more in 2003. Based on register data from the National Labor Market Administration. Mean: 0.11, sd: 0.05, min: 0.00, max: 0.30.

Non-Nordic clients Proportion of clients at the PES office without Nordic citizenship in 2003. Based on register data from the National Labor Market Administration. Mean: 0.07, sd: 0.07, min: 0.01, max: 0.62.

Unemployment Local unemployment rate in percent, including participants in measures, in the municipality where the PES office is located (April 2003). Based on official municipal statistics from KFAKTA03. Mean: 5.47, sd: 2.31, min: 1.90, max: 19.60.

Local population Number of inhabitants in the municipality (in 1,000’s of persons) where the PES office is located (December 2002). Based on official municipal statistics from KFAKTA03. Mean: 95.56, sd: 192.14, min: 2.61, max: 758.15.

Socialist government The chairman of the municipal executive board represents the Social Democrats. Dummy variable: 0 = no (.33); 1 = yes (.67). Based on official municipal statistics from KFAKTA03.

Priority of difficult clients The PES manager’s rank of the objective “ensuring that there are labor market programs for groups of unemployed with severe problems in the labor market” among 13 objectives (scale 1-13, where 13 means highest priority). Based on questionnaire data. Mean: 11.16, sd: 2.46, min: 2.00, max: 13.00.

Priority of youth clients The PES manager’s rank of the objective “ensuring that there are labor market programs for young people under 25” among 13 objectives (scale 1-13, where 13 means highest priority). Based on questionnaire data. Mean: 12.21, sd: 1.85, min: 4.00, max: 13.00.

Clients per staff member The average number of clients (measured in 10 clients) per week per employee at the PES office. Based on register data from the National Labor Market Administration. Mean: 4.96, sd: 1.74, min: 0.26, max: 12.44.

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Financial resources The amount of financial resources at the PES office reserved for benefits to clients participating in active measures (in 1,000 Swedish crowns) per week divided by the number of clients per week. Based on questionnaire data. Mean: 0.66, sd: 0.35, min: 0.00, max: 3.01.

Organizational size The logarithm of the number of employees at the PES office. Based on register data from the National Labor Market Administration. Mean: 2.63, sd: 0.78, min: 0.00, max: 4.65.

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2007:5 Andersson Christian ”Lärartäthet, lärarkvalitet och arbetsmarknaden för lärare”

2007:6 Larsson Laura & Caroline Runeson ”Effekten av sänkt sjukpenning för arbetslösa”

2007:7 Stenberg Anders ”Hur påverkar gymnasialt komvux löneinkomster och vida-re studier?

2007:8 ”Forslund Anders & Kerstin Johansson ”Lediga jobb, arbetssökande och anställningar – den svenska matchningsfunktionen”

2007:9 Kennerberg Louise ”Hur förändras kvinnors och mäns arbetssituation när de får barn?”

2007:10 Nordin Martin ”Invandrares avkastning på utbildning i Sverige”

2007:11 Johansson Mats & Katarina Katz ”Underutnyttjad utbildning och lönegapet mellan kvinnor och män”

2007:12 Gartell Marie, Ann-Christin Jans & Helena Persson ”Utbildningens betydelse för flöden på arbetsmarknaden”

2007:13 Grönqvist Hans & Olof Åslund ”Familjestorlekens effekter på barns utbild-ning och arbetsliv”

2007:14 Lindqvist Linus ”Uppföljning av plusjobb”

2007:15 Sibbmark Kristina ”Avidentifierade jobbansökningar – erfarenheter från ett försök i Göteborgs stad”

2007:16 Hesselius Patrik & Malin Persson ”Incitamentseffekter och Försäkringskas-sans kostnader av kollektivavtalade sjukförsäkringar”

2007:17 Eriksson Stefan & Jonas Lagerström ”Diskriminering i anställningsproces-sen: resultat från en Internetbaserad sökkanal”

2007:18 Eriksson Robert, Oskar Nordström Skans, Anna Sjögren & Olof Åslund ”Ungdomars och invandrades inträde på arbetsmarknaden 1985–2003”

2007:19 Agerström Jens, Rickard Carlsson & Dan-Olof Rooth ”Etnicitet och övervikt: implicita arbetsrelaterade fördomar i Sverige”

2007:20 Bennmarker Helge, Kenneth Carling & Anders Forslund ”Vem blir långtids-arbetslös?”

Working Papers

2007:1 de Luna Xavier & Per Johansson “Matching estimators for the effect of a treatment on survival times”

2007:2 Lundin Daniela, Eva Mörk & Björn Öckert “Do reduced child care prices make parents work more?”

2007:3 Bergemann Annette & Gerard van den Berg “Active labor market policy effects for women in Europe – a survey”

2007:4 Andersson Christian “Teacher density and student achievement in Swedish compulsory schools”

2007:5 Andersson Christian & Nina Waldenström “Teacher supply and the market for teachers”

2007:6 Andersson Christian & Nina Waldenström “Teacher certification and student achievement in Swedish compulsory schools”

2007:7 van den Berg Gerard, Maarten Lindeboom & Marta López ”Inequality in individual mortality and economic conditions earlier in life”

2007:8 Larsson Laura & Caroline Runeson “Moral hazard among the sick and unemployed: evidence from a Swedish social insurance reform”

2007:9 Stenberg Anders “Does adult education at upper secondary level influence annual wage earnings?”

2007:10 van den Berg Gerard “An economic analysis of exclusion restrictions for instrumental variable estimation”

2007:11 Forslund Anders & Kerstin Johansson “Random and stock-flow models of labour market matching – Swedish evidence”

2007:12 Nordin Martin “Immigrants’ return to schooling in Sweden”

2007:13 Johansson Mats & Katarina Katz “Wage differences between women and men in Sweden – the impact of skill mismatch”

2007:14 Gartell Marie, Ann-Christin Jans & Helena Persson “The importance of education for the reallocation of labor: evidence from Swedish linked employer-employee data 1986–2002”

2007:15 Åslund Olof & Hans Grönqvist “Family size and child outcomes: Is there really no trade-off?”

2007:16 Hesselius Patrik & Malin Persson “Incentive and spill-over effects of sup-plementary sickness compensation”

2007:17 Engström Per & Patrik Hesselius “The information method – theory and application”

2007:18 Engström Per, Patrik Hesselius & Malin Persson “Excess use of Temporary Parental Benefit”

2007:19 Eriksson Stefan & Jonas Lagerström “Detecting discrimination in the hiring process: evidence from an Internet-based search channel”

2007:20 Agerström Jens, Rickard Carlsson & Dan-Olof Rooth “Ethnicity and obe-sity: evidence of implicit work performance stereotypes in Sweden”

2007:21 Uusitalo Roope & Jouko Verho “The effect of unemployment benefits on re-employment rates: evidence from the Finnish UI-benefit reform”

Dissertation Series

2007:1 Lundin Martin “The conditions for multi-level governance: implementation, politics, and cooperation in Swedish active labor market policy”

2006:1 Hägglund Pathric “Natural and classical experiments in Swedish labour market policy”

2006:2 Savvidou Eleni “Technology, human capital and labor demand”

2006:3 Söderström Martin “Evaluating institutional changes in education and wage policy”

2006:4 Lagerström Jonas “Discrimination, sickness absence, and labor market policy”

2006:5 Johansson Kerstin “ Empirical essays on labor-force participation, matching, and trade”

The conditions for multi-level governance

Documents

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