3 - Design of the Study

Summary

In this chapter, we describe the main elements of our empirical design for studying the refugee crisis. In the first part of the chapter, we describe our case selection, which involves two steps. In the first step, we classify EU member states into five main types: frontline, transit, open destination, closed destination, and bystander states. In the second step, within selected countries, but also at the EU level, we study the crisis by breaking it down into key policymaking episodes. The policymaking episodes we have chosen involve legislative acts as well as administrative decisions and novel practices by state institutions. In the second part of the chapter, we expand upon the empirical approaches we employ for studying the crisis. Our book draws upon a variety of original datasets involving various methods of data collection. While many of these are mixed throughout the book, the central dataset we rely on uses policy process analysis (PPA), an original method for capturing the policymaking and politics surrounding policy debates using media data, which we describe more thoroughly in this chapter.

Introduction

In Chapter 2, we described our theoretical approach for studying the refugee crisis in a multilevel polity. We have also already introduced the outline of our empirical design. In this chapter, we describe the main elements of this empirical design, including our case selection strategies and the types of data used.

In the first part of the chapter, we describe our case selection, essentially delimiting the empirical scope of our study. As our theoretical approach is based on the perspective of the EU as a multilevel polity involving asymmetrical and interdependent relations between member states, our empirical universe consists of the unfolding of the crisis at both the EU level and the level of the member states. Within this empirical universe, our case selection strategy involves two steps. In the first step, taking into consideration the variation in policy heritage of European countries in the immigration domain, the immediate crisis situation they were facing, but also their centrality in the unfolding of the refugee crisis, we classify EU member states into four main types: frontline, transit, open destination, or closed destination states. In addition, we consider a fifth type, bystander states, which we, however, do not study in detail.

In the second step, within these selected countries, but also at the EU level, we study the crisis by breaking it down into a set of key policymaking episodes, which are triggered by salient policy proposals. Some of the policies we have chosen are legislative acts, such as reforms to the countries’ asylum systems, while others are administrative decisions and novel practices by state institutions, such as the reimposition of border controls in a period of heightened problem pressure. In the next section, we describe our episode selection strategy based on systematic media and secondary source analysis.

In the second part of this chapter, we focus on the empirical approaches we employ for studying the different stages and elements of the crisis. As our theoretical framework involves an ambitious design that aims to study the interplay of both supply-side and demand-side dynamics, our book draws upon a variety of original datasets involving various methods of data collection. While many of these methods are mixed throughout the forthcoming chapters depending on the elements of the crisis on which we zoom in (e.g., the crisis situation, policymaking during the crisis, political competition dynamics), the central dataset upon which the book is based uses policy process analysis (PPA), a method that relies on the systematic coding of media data for capturing the policymaking and politics surrounding policy debates. Drawing upon political claims analysis (PCA) (Koopmans and Statham 1999), our original PPA dataset incorporates into a single framework information about all the major components of an empirically delimited policy episode in a country of interest. PPA is complemented with core-sentence analysis (CSA) for studying political competition dynamics in election campaigns, survey data for capturing public opinion on immigration, and speech analysis for studying rhetorical devices employed by key right and radical right actors during the crisis. In the following text, we detail the methodology behind these empirical approaches, and we point to the various parts of the book where they are employed.

Selection of Countries

Our theoretical approach is based on the perspective of the EU as a multilevel polity involving both dynamics at the EU level and asymmetrical and interdependent relations between member states, and domestic dynamics that shape the available policy options and outputs. Therefore, we study how the refugee crisis is unfolding in its various aspects at both the EU level, and in the various EU member states. By complementing a within-country perspective with an EU level perspective, we aim to provide a comprehensive account of the European refugee crisis’s origins, ongoing developments, and consequences.

For breaking down the variety of EU member states and the role they played in the crisis, we categorize these states into the four main types we already mentioned: frontline, transit, open destination, and closed destination. The fifth type, bystander states, was hardly affected by the crisis and therefore played a marginal role in its unfolding. While not studied in depth, we do mention these bystander states when zooming out on broader aspects such as the salience of the immigration issue in the public across member states or when they get involved in any political dynamics in our countries of interest or at the EU level. This country typology is guided by several criteria related to the policy heritage in the immigration domain of these countries; the immediate crisis situation they were faced with; but also, more generally, the migration trajectories in Europe. We selected two countries per type based on their centrality in the unfolding of the crisis: Greece and Italy as frontline states, Austria and Hungary as transit states, France and the UK as closed destination states, and Germany and Sweden as open destination states. It is in these eight countries and at the EU level that we study the specifics of policymaking and political dynamics during the crisis, while in the rest of the member states we adopt a more birds-eye view. In the following text, we describe our two main classification criteria: the crisis situation and the asylum policy heritage.

The first criterion on which we base our classification is the crisis situation. In this respect, the incidence of the crisis across EU member states was asymmetric, with countries experiencing different types and levels of problem pressure with regard to the number of entries and asylum requests. These asymmetries mainly result from the countries’ geographical location and their attractiveness as destination states for asylum seekers. Countries that are geographic points of entry into the EU are frontline states, countries that are desirable destinations for migrants are destination states, while countries situated along migration trajectories are transit states.

The second criteria behind our classification refers to the immigration policy heritage and the nature of the prevailing asylum regime. First, central to the asylum policy is the Dublin principle, according to which countries that are the first point of arrival for an asylum applicant are responsible for processing their claim. This principle shifted the burden of accepting and integrating refugees to the EU border states, which became the frontline states in the refugee crisis. Second, while the Common European Asylum System (CEAS) aimed at setting common minimum standard for asylum across EU member states,¹ asylum regimes remain largely unharmonized (Kriesi, Altiparmakis, Bojar, and Oana 2021; Scipioni 2018; Niemann and Zaun 2018). Differences in these asylum regimes existed even before the crisis struck, as will become more apparent in Chapter 4. In order to obtain an idea of how the national asylum regimes actually worked in the past, we propose examining the rejection rate of asylum seekers prior to the crisis (2010–14). For our eight countries, the first column in Table 3.1 presents these rates for asylum seekers from the five countries (Syria, Afghanistan, Iraq, Pakistan, and Nigeria) that due to either political instability or sheer population size presented national asylum authorities with the greatest burden during the refugee crisis. We notice here that there are wide differences among the countries that are regularly considered as destination states for migrants. While Sweden and Germany had been open destination states for asylum seekers prior to the crisis, having rather low rejection rates, France and the UK were already more closed before the crisis. Consequently, we split the group of destination states into two categories: open and closed. The differences between these groups of countries will be studied in more depth and will become more apparent in Chapter 4, where we further inquire into their crisis situation in terms of policy heritage, political pressure, and problem pressure. While there is also some variation among the frontline and transit states, we do not divide them any further but do take into account these differences when studying individual countries.

Table 3.1 Average rejection rates 2010–14 for asylum seekers from Syria, Afghanistan, Iraq, Pakistan, and Nigeria, and annual budgets for national asylum systems in 2018 (in million euro)

	Country	Rejection ratea	Annual budgetb
Open Destination	Sweden	0.18	3,080
	Germany	0.35	1,800
Closed Destination	France	0.63	74
	United Kingdom	0.70	301
Frontline	Greece	0.92	10
	Italy	0.43	1,447
Transit	Hungary	0.75	0.3
	Austria	0.51	114
	Average	0.56	853

^a Source: Eurostat: asylum statistics

^b Source: AIDA database (Ott 2019: 26); Italian figures also refer to 2018 but are taken from European Commission, ESPN Country profile stages 3 & 4 Italy 2017–2018, Table 29, p. 107; British figures are obtained from the UK Home Office’s Annual Report and Accounts for the budgetary year of 2015–16 (UK Home Office 2016, p. 132).

Moreover, the capacity of national asylum systems to deal with asylum requests also varies considerably between member states. Unfortunately, there are no longitudinal data available for this aspect, but the figures in the second column of Table 3.1 provide a snapshot of the financial resources available for the determining authorities. The ordering of countries is closely aligned with the rejection rates, except that the UK has somewhat more resources and Austria a lot less resources than the rejection rates would lead us to expect. As these numbers suggest, the Greek, Hungarian, and French systems fall far short of what would have been required for proper functioning. The Greek asylum system had already been judged to be dysfunctional by the European Court of Human Rights (ECHR) and the European Court of Justice (ECJ) as of 2011, and in 2012, the UNHCR arrived at the same assessment for the Hungarian asylum system (Trauner 2016: 314). In other words, the national asylum systems of precisely those countries that were supposed to take care of the massive refugee inflows in the refugee crisis were least prepared to do so. Admittedly, annual budgetary appropriations are only one aspect of how effectively a given country’s asylum system functions. However, in the context of a sudden spike in requests, the available resources of the system are an important indicator of its capacity to satisfy the country’s CEAS obligations. These resources further reinforce our split of the destination states into an open and a closed type, while still pointing to significant differences in the asylum regimes of the other types of countries that will be studied in the upcoming chapters.

Selection of Episodes

Within these selected countries, but also at the EU level, we study the refugee crisis by breaking it down into a set of key policymaking episodes, which are triggered by salient policy proposals. Some of the policies we have chosen are legislative acts, such as reforms to the countries’ asylum systems, while others are administrative decisions and novel practices by state institutions, such as the reimposition of border controls in a heightened period of problem pressure. A policy episode in our framework comprises the whole policy debate surrounding these specific policy proposals that governments put forward, from the moment the proposal enters the public debate to the moment the proposal is implemented and/or discussion surrounding it is no longer salient.

Our approach of focusing on specific policymaking episodes, rather than studying the refugee crisis as a whole, brings several advantages to the analysis. First, adopting an episode-based strategy enables the systematic comparison of our countries of interest by allowing us to compare policies of a similar type across countries (e.g., asylum reforms, border control). Second, by breaking down the crisis into policy proposals and by focusing on periods of heightened salience of the immigration issue in the public debate, we can limit the resources required for an in-depth study of all the actors involved, the actions they undertake, the issues they address, and their interactions in a systematic manner. Lastly, our episode-based strategy does not preclude, but rather complements, the strategy of studying the crisis as a whole. Different aspects of the crisis are better suited to be studied by one or the other strategy; for example, general trends in salience are better studied throughout the crisis as a whole, whereas policymaking and political dynamics surrounding specific policy proposals are preferably studied in a bounded episode. Accordingly, we adopt an encompassing analytical strategy when looking at problem and political pressure (Chapter 4), at conflict configurations on the demand side (Chapter 13), and at electoral outcomes (Chapter 14). Conversely, we focus on episodes when studying the variety of policy responses to the crisis (Chapter 5), the actors and conflict structures in policymaking (Chapters 6–9), and the dynamics of policymaking (Chapters 10–12).

To systematically select these episodes, we have resorted to a two-step strategy. In the first step, we analyzed a variety of international press sources using a broad timeframe (starting in 2013 and ending in 2020) covering the crisis so as to make sure that we capture policy processes starting before or continuing after the peak of the crisis in 2015–16. We used the international press at this initial stage based on the idea that the proposals that make it into the international news are publicly most relevant and impactful. We constructed a corpus of news articles based on general migration-related keyword and performed an initial round of in-house, manual coding for identifying policy proposals. Based on the number of times a selected proposal appeared in the media, we delimited an initial set of particularly relevant proposals. In the second step, we cross-validated this initial set of episodes by using secondary sources (various publications of think-tanks and NGOs such as the Migration Policy Institute, European Migration Network, and Asylum Information Database) and by performing similar searches in the national press with the aid of native-language-speaking coders. Finally, we ended up with five key policy episodes in each of the eight countries and six policy episodes at the EU level. Additionally, to obtain a better grasp on the interactions between the EU and the domestic levels, we also studied one of the salient EU-level policy proposals – the EU–Turkey Deal – and the debate surrounding it in four member states representing our four country types: Greece, Hungary, Germany, and the UK.

A similar process was adopted for establishing the more specific timeline of these episodes, with a few important additional steps. The initial episode timeline that was established based on the two steps described above was further refined in close collaboration with a team of native-language speakers who helped us identify episode-specific keywords that were iteratively tested and applied to national news sources. Episode timelines are, therefore, exclusively based on the characteristics of the individual episodes. We have not harmonized their duration, as we are interested in how the episodes unfolded in their entirety. The process of timeline selection is further described in the following section on policy process analysis, where we also describe the data we have collected on these episodes.

Table 3.2 summarizes the episodes we have coded via the short labels we assigned to them together with their timeline. We can classify these episodes into two main types according to their substantive scope: (1) asylum-related policy reforms (including rules of burden sharing between member states, the retrenchment of asylum law, and the introduction of integration laws and laws on return in the member states) and (2) external border control measures (including the externalization of refugee protection). Not only does the substantive focus of policymaking vary across member states and phases of the crisis (as we show in Chapter 4), but it also plays a role in how political dynamics develop in these countries. For example, in Chapter 5, we show that the dominant types of actor conflict vary by episode type: societal conflicts are prevalent across all episode types, while intragovernmental conflict is prevalent mostly in border-related episodes.

Table 3.2 National-level policy episodes in the refugee crisis

Country	Episode I	Episode II	Episode III	Episode IV	Episode V	Episode VI
EU	EU–Turkey Deal (7/2015–9/2016)	Emergency Relocation Scheme (4/2015–12/2018)	EU–Libya Deal (9/2016–2/2020)	Hotspots (6/2015–8/2016)	European Border and Cost Guard (4/2015–12/2019)	Dublin Reform (05/2015–12/2019)
Austria	Border Controls (4/2015–12/2016)	Balkan Route Closure (6/2015–3/2016)	Asylum Law (3/2015–5/2016)	Integration Law (10/2015–6/2017)	Right to Intervene (7/2015–12/2015)
France	Ventimiglia (6/2015–11/2015)	Border Controls (11/2015–2/2020)	Asylum Law (12/2017–4/2019)	Rights of Foreigners (7/2013–11/2015)	Calais (1/2015–11/2016)
Germany	“Wir Schaffen Das” (8/2015–4/2016)	Asylum Package (8/2015–3/2016)	Integration Law (2/2016–8/2016)	Deportation (1/2017–12/2019)	CDU-CSU Conflict (5/2018–7/2018)
Greece	Summer of 2015 (5/2015–10/2015)	Hotspots-Frontex (10/2015–5/2016)	International Protection Bill (9/2019–11/2019)	Turkey Border Conflict (2/2020–3/2020)	Detention Centers (11/2019–2/2020)
Hungary	Fence Building (6/2015–12/2016)	Quota referendum (11/2015–12/2016)	Legal Border Barrier Amendment (1/2017–11/2018)	Civil Law (1/2017–12/2017)	“Stop Soros” 1/2018–12/2019)
Italy	Mare Nostrum (10/2013–11/2014)	Ventimiglia (05/2015–10/2015)	Brenner Pass (1/2016–06/2016)	Port Closures (6/2018–9/2018)	Sicurezza Bis (9/2018–8/2019)
Sweden	Border Control (7/2015–11/2018)	Residence Permits (6/2015–9/2016)	Police Powers (2/2016–3/2018)	Family Reunification (12/2018–7/2020)	Municipalities (1/2015–1/2016)
The UK	Immigration Act (2014) (2/2013–6/2014)	Immigration Act (2016) (4/2015–5/2016)	Dubs Amendment (3/2016–5/2017)	Vulnerable Persons’ Re-settl. Scheme (12/2013–11/2017)	Calais (8/2014– 10/2016)
EU episode in member states	EU–Turkey Deal in Germany (9/2015–12/2016)	EU–Turkey Deal in Greece (9/2015–12/2016)	EU–Turkey Deal in Hungary (9/2015–12/2016)	EU–Turkey Deal in the UK (9/2015–12/2016)

Data Collection and Analysis

Policy Process Analysis (PPA)

The main method we rely on for studying the political dynamics during the crisis and the variety of policy responses across our selected EU and country episodes is policy process analysis (PPA) (Bojar et al. 2021a). PPA intends to be a comprehensive method for the data collection and analysis of policymaking debates. As such, PPA aims at capturing the public face of policymaking, that is, the subset of actions in a policymaking process that are presented to the general public through the mass media. The method relies on analyzing media data based on systematic hand-coding of indicators related to the actors involved in the policy debate, the forms of action they engage in, the arena where the actions take place, the issues addressed, and the frames used to address these issues. The resulting dataset allows for the construction of more aggregate indicators at different levels of analysis (at the episode level, at the actor level, at different time units) for studying the policymaking debate and the political dynamics surrounding it from multiple angles, both statically and over time.

In its design, PPA is a specific form of political claims analysis (PCA) (see Koopmans and Statham 1999) and also incorporates elements from other methods previously employed to study protest events (protest event analysis [PEA]) (see Hutter 2014; Kriesi et al. 2020) or contentious politics (contentious episodes analysis [CEA]) (see Kriesi, Hutter, and Bojar 2019; Bojar et al. 2023) by making use of the systematic coding of media data. At its core, PPA is also an event-based methodology that focuses on identifying distinct actions undertaken by a variety of actors addressing particular issues and how they unfold over time. However, while PEA and CEA are usually limited to identifying either actions in the form of protest events or actions initiated by a limited set of actors (government versus challengers) to study mostly contentious politics, PPA enlarges the empirical scope to the study of entire policy debates.

Its encompassing scope and event-based focus make PPA a specific form of political claims analysis (PCA) (Koopmans and Statham 1999). Starting from a critique of protest event and political discourse newspaper analysis as being too “protest-centric” and focused primarily on nonroutine protest actions, PCA argues for the need to include events that occur outside the context of reported protest but that are important for understanding conflict. As such, PCA extends event coding to including actions that take on institutional forms, such as legal actions, and including public and institutional actors beyond social movements. Our PPA methodology takes this critique seriously by also enlarging the empirical scope of the analysis to include both institutional and noninstitutional actions and actors. Where PPA departs from PCA is in its focus. PCA originated as a method primarily focused on studying the demand side of politics by taking as its starting point claims making (“strategic demands made by collective actors within a specific contested issue field”) (Koopmans and Statham 1999: 206) and attempting to enlarge the study of contentious politics and placing it into its wider context. By contrast, our PPA methodology is essentially supply-side focused by having as a starting point policymaking processes and specific policy debates while attempting to place these in their wider political context. It is this supply-side focus that drives our strategy of analyzing selected empirically delimited policy episodes rather than general contested issue fields and studying the policy debate surrounding them in a systematic fashion.

In its supply-side focus, PPA also comes close to another approach to the study of policymaking processes – the comparative policy agendas (CPA) project (Baumgartner, Green-Pedersen, and Jones 2006). However, rather than focusing particularly on the agenda-setting phase of policymaking as the CPA does, PPA systematically incorporates into a single framework information about all the major components of a policy debate. Therefore, as further detailed in the section below, PPA documents actions ranging from formal steps in the policymaking process to administrative and nonstate actions but also protest events and even single verbal claims. Due to its goal of studying both the politics and the policymaking surrounding a particular episode, the actors documented in PPA are not restricted to solely governments; rather, they include all actors involved in the debate – political parties, civil society actors, supranational actors, and third-country actors.

Similar to CEA, PPA attempts to capture the middle ground between a qualitative narrative approach and a quantitative approach to describing the chronology of policy processes (see Kriesi et al. 2019). By including extensive string descriptions of each action, PPA provides a rich body of qualitative information on the politics and policymaking surrounding policy debates. At the same time, by coding specific action characteristics, it allows for the construction of systematic, comparative indicators at various levels: countries, episodes, and actor types. In its qualitative inclination, one could think of this approach as being related to process tracing in that we seek to document all the various chains of actions involved in a policy debate as they unfold over time in a systematic fashion. However, process-tracing is aimed mainly at single-case inferences about the intervening causal process, that is, on the causal mechanisms that link a given cause to an outcome in a single case (George and Bennett 2005: 206–207; Beach and Pedersen 2016: 4–5). In contrast, our method is aimed at combining such single-case inferences with cross-case inferences, making it essentially a comparative method. We therefore analyze the refugee crisis by comparing the variety of countries and episodes based on a combination of both qualitative evidence on the sequences of events in the form of descriptive narratives and systematic, quantitative indicators measuring relevant characteristics of these episodes (e.g., politicization and conflict intensity, as further detailed in the next section). In doing so, we aim to study within-country policy processes and how they evolve from problem pressure via domestic actor constellations and conflicts all the way to policy outcomes but also to compare such policy processes in a systematic fashion.

To sum up, PPA is well suited for our research goals in studying the refugee crisis for two main reasons. First, its broad empirical scope allows us to focus on a wide variety of actions and actors in systematically reconstructing the various policy debates both at the EU level and at the level of the member states. We can therefore use PPA for identifying the policymaking repertoires employed at these different levels, as well as for systematically studying the wide variety of actors involved in these debates, their configurations, and their discursive strategies. Second, by aiming at the middle ground between quantitative and qualitative approaches, PPA allows us to combine systematic, comparative indicators of the various aspects of politics and policymaking surrounding policy debates with the reconstruction of the narrative chronology of these policy debates by the use of a rich body of qualitative evidence.

Having set up our empirical universe as bounded segments of the policy debate that take the form of distinct policy episodes embedded in the broader context of the 2015–16 refugee crisis, the first step in constructing our PPA dataset was defining and gathering the media corpus to be analyzed. Therefore, the first decision we were confronted with was source selection, that is, the selection of news media to be studied. Depending on the level of policymaking, we selected either international news sources (for the EU level) or national news sources (for the level of the member states). We used the news aggregator platform Factiva for document retrieval, as it provided us access to a large number of media outlets, which allowed for systematic multicountry comparison together with transparent and replicable selection criteria on the source.

Following good practice standards in working with media data from methods such as protest event analysis (Hutter 2014; Kriesi et al. 2019), we also tried to engage with issues of selection bias (e.g., Earl et al. 2004; Ortiz et al. 2006), that is, with the biases associated with news source selection and their coverage of debates, actions, or events. In order to mitigate such biases, we adopted several strategies. First, we relied on a wide variety of media sources, rather than a single source, in order to be able to capture as many aspects of the policy debates as possible. Second, as just mentioned, in order to mitigate biases related to newsworthiness and proximity, we selected news sources that are proximate to the level of analysis: For EU debates, we focused on large news agencies (Agence France Presse, Associated Press, Reuters, Financial Times, Euronews, ANSA, BBC, MTI), while for national debates, we relied on national media. Third, in order to mitigate biases related to the political motives of the various sources and their potential impact on news coverage, we selected news sources on different sides of the political spectrum. Consequently, for each of the eight selected sources, we selected one major newspaper left of center and one right of center in terms of ideological leaning (with some minor exceptions related to data availability).

After selecting the news sources, the second decision related to corpus construction consisted of the identification of the keywords used for the retrieval of articles related to a particular episode. One of the main considerations at this step was achieving a balanced relevance ratio – the ratio between false positives (irrelevant articles that the keyword combination retrieved as positive hits) and false negatives (relevant articles that the keyword combination filtered out as negative hits). Since our data is manually coded, we aimed for a relatively slim but robust corpus. That is, our corpus needed to be manageable in terms of the number of articles identified so as to not make the coding process too cumbersome and resource intensive, but it still allowed us to capture the full range of actions in a given policy episode without missing relevant articles filtered out by a too restrictive keyword combination.

In practical terms, the selection of keywords related to each of the EU and country episodes was performed by the authors of the book in close collaboration with a team of native-language-speaking coders (mostly comprised of political science PhD students who were also knowledgeable about the subject at hand – the refugee crisis). At this stage, we took advantage of the capabilities of the news aggregator Factiva, which allowed us to construct complex search strings using Boolean algebra and its standard logical operators. For each episode, we chose an initial set of episode-specific keywords based on secondary sources (policy reports, secondary scientific literature, etc.) and initial search queries in the national press. We then further refined this initial keyword selection through an iterative process of going back and forth between the selection and the corpus obtained. We selected those keyword combinations that passed the initial reading of the selected articles and achieved a satisfactory balance between the size of the corpus and the number of events filtered out.

After having constructed the corpus, the last step in the PPA coding process consisted of action coding. As already mentioned, PPA is an event-based methodology and hence the unit of observation at the level at which the data is collected is an action. An action in our framework is defined as “an act, or a claim by an actor with a prominent role in the political world that has a direct or indirect relevance for the policy debate” (Bojar et al. 2023). Therefore, within our framework, actions can be steps in the policymaking process, verbal claims, episode-related protest events, and other types of actions that we outline in the coding scheme below. This definition is rather open-ended because the relevance of an action is contingent on the specificities of the actual policy debate at hand.

Note that while the lowest level of observation is an action, the unit of analysis at which we draw conclusions can be pitched at any level of aggregation (actor types, issue categories, entire episodes, types of countries, etc.) depending on the research question, as will become apparent in the following chapters. In order to measure the various features of actions, action coding is based on a common core of variables that are coded for each of the actions in each episode: the arena where the action takes place, its (procedural) form, its (substantive) type of engagement with the policy, its overall direction vis-à-vis the policy, its direction vis-à-vis target actors, the organizational characteristics of the actor undertaking them, the organizational characteristics of the target actor, the issues it engages with, and the normative frames used by actors to present their positions to the public (Bojar et al. 2023).

Based on initial trial rounds of action coding, we refined these major characteristics of an action with specific categories relevant for the refugee crisis. This resulted in a detailed codebook with hierarchically organized categories at various levels of specificity. The codebook was complemented by a dedicated coding spreadsheet that was provided to the coders to make the data collection process as systematic and comparable throughout country episodes as possible. At the end of the coding process, at the national level, our team identified 6,338 codable actions for the 40 episodes, yielding 157 actions per episode on average. However, there is considerable variation in how eventful the individual episodes are, ranging from 48 actions in the Residence Permits episode in Sweden to no less than 363 actions during the quota referendum in Hungary. In fact, Hungary has proven to be the most eventful of our eight countries with 1,204 actions, followed by Greece with a total of 1,086 actions. At the EU level, we have coded 1,257 actions in the six episodes, with the EU–Turkey Deal being the most eventful one (437 actions), while the EU–Libya episode had the lowest number of actions (62). These two datasets are complemented by the EU–Turkey Deal episode and the debate surrounding it in four member states containing an additional 1,138 actions. In the following text, we describe how each action characteristic was implemented in our data collection effort.

The first set of characteristics for each action that we have identified is related to the arena where it takes place. Arena choice is an important aspect of the policy debate because it can shape the type of actors that gain access to policymaking, the size and type of audiences that participants can address, and the type of policy options on the table as a function of the gate-keeping role of agenda setters (Timmermans 2001; Lowi and Nicholson 2009; Princen 2011). Arenas are also important because procedural forms of action depend on where they take place. We identify nine types of arenas in our codebook (see Figure 3.1) varying from decision-making institutional arenas such as the national governments to less institutionalized arena types such as protest or society more generally. Furthermore, for each of these nine arenas, we also identified specific forms of the action. For some of the arenas, the set of action forms was based upon long-standing traditions in the pertinent literature, such as the set of action repertoires in the protest arena (Traugott 1995; Della Porta 2013), while for others, such as the media arena, it was decided inductively based on our trial coding.

Figure 3.1 Policy action arenas at the national and EU levels

Figure 3.1 shows that most of the actions in our dataset at both the EU level and the national level take place in the media area (these usually come in the form of statements, press conferences, interviews, etc.). Unsurprisingly, the next most prominent arenas in our dataset at the national level are national governments and parliaments, while European institutions and the cross-national arena prevail at the EU level. Beyond these arenas, our data collection effort also captured actions taking place in the electoral arena, in the protest arena, and at the level of society more generally, thereby providing us with a multifaceted picture of the policy debate not only in venues mostly dedicated to supply-side actors but also in venues where demand-side actors such as civil society organizations most often operate.

After settling the “where” of the action, the next set of characteristics refers to the type of action that actors undertake with reference to the policy proposal and to other actors involved in the policymaking process. In this respect, we included a wide action repertoire, distinguishing between policymaking steps, policy claims, administrative state actions, and nonstate actions. It is at this level that our PPA methodology is distinguished from other methods dedicated to analyzing policymaking processes such as the comparative policy agendas (CPA) project (Baumgartner et al. 2006). Rather than only studying formal steps in the policymaking process, our dataset also includes verbal claims and statements made by a variety of actors in the policy process. In fact, as Figure 3.2 reveals, the most prominent policy action forms at both the national and EU level are precisely policy claims (these usually include actions such as full verbal support/opposition of the policy, clarifications, apologies, and verbal commitments to further action).

Figure 3.2 Policy action types at the national and EU levels

Distinguishing between policy claims and formal policy steps provides us with a more nuanced picture of how the policy debates unfolded, as these substantive types of action most often also indicate whether the action implies a broad level of agreement or disagreement with the underlying policy on the table. In addition to the substantive action types, we also use a general policy direction code (positive, negative, or neutral) as an indicator of the actor’s position regarding the issue at stake. Finally, since in most of the episodes we follow up on the implementation of the policy in question and also include actions undertaken by nonstate actors (such as policy evaluations, NGOs involved in the implementation of a particular policy), we also consider administrative actions performed by state and nonstate actions.

Beyond characteristics of the action itself, the actors involved in a particular policy debate are of particular interest to us, as is shown in Part II of our book. By studying actors and the actions they undertake, we are able to analyze conflict structures and dynamics of coalition formation at both the national and EU levels, which is crucial in the negotiation stages of these policy episodes. Note that at this stage, we try to identify not only which actors undertake a particular action but also whether that particular action is targeted at other actor(s) in the policy debate. We therefore take into account two types of actions: monadic actions, which only have an initiator actor who addresses an issue, and dyadic actions, which have initiator actors who address not only an issue but also a target actor. For the dyadic actions, similar to the policy direction code, we introduce an actor direction code (negative, positive, or neutral) that captures the actor’s relational position vis-à-vis the target actor regardless of how they relate to the policy as such.

The actor characteristics that we identify in our PPA data collection are organized hierarchically at four levels: their nationalities; their broad institutional affiliations (such as the national government); their narrow institutional affiliation (a particular ministry); and, in the case of individual actors, their position within the institution’s hierarchy (executive, subexecutive, or lower rank). This hierarchical organization allows us to study actor configurations at various levels of specificity, identify both domestic coalitions and cross-national coalitions, as well as capture dominant decision-making modes such as executive decision-making or partisan contestation.

In Figure 3.3, we present the share of actors involved in policy debates at the EU and national levels according to their broad institutional affiliations. National governments are the central actors in our domestic policy debates, with more than 30 percent of the actions being initiated by them. In contrast, inter- and supranational actors are the initiators of most actions (more than 80 percent) at the EU level. Despite these two categories unsurprisingly taking center stage at their respective levels, we can see that other national institutions (e.g., regional authorities), political parties both in government and in opposition, as well as interest groups and civil society actors have nontrivial shares of actions, especially at the domestic level.

Figure 3.3 Initiator actor types at the national and EU levels

Although in all the episodes we select actions relating to a particular policy proposal, most of the time the debates tend to revolve around more than one issue. Many of these proposals are in fact policy packages containing multiple issues that collectively make up the policy debate. Moreover, many actions do not directly relate to the policy but are important nevertheless because they have the potential to influence the future course of the debate. Differentiating between specific issues allows us to capture the more fine-grained thematic crisis responses, which are discussed in more depth in Chapter 5. We therefore introduce a set of issue codes organized in such a way as to capture a broad categorization of migration-related policy areas as reflected in the organization of asylum and migration policies in the EU member states.

Figure 3.4 presents the broad categorization of issues our episodes involve.² We can see that at both the EU and the national level, asylum issues and border control issues dominate the agenda. As some actions are directed toward a whole policy package (i.e., an episode), we introduce this as a specific issue. As we are interested also in some actions that do not directly relate to migration policy but are relevant for the policy debate at hand, we have complemented this with an “others” category to capture impactful actions and/or events in our episodes, such as issues pertaining to diplomatic relations between countries or humanitarian tragedies.

Figure 3.4 Issues at the national and EU levels

Finally, an important characteristic we include in our study relates to the discursive frames actors use. This essentially refers to the ways in which actors justify their action or interpret the political problem at hand. Such discursive framing is important because it can shape other actors’ attitudes and behavior (Koopmans and Statham 1999; Rucht and Neidhardt 1999). The frames employed give us an overview of the communication strategies employed by the various actors involved in the policy debate and can be used to identify discursive coalitions in the political process.

Figure 3.5 presents the main frames identified in the refugee crisis grouped into four major categories. These broad categories were constructed inductively based on several rounds of trial coding and were further adapted though the data collection process. We observe that while humanitarian and democratic frames appear to be important at both the EU and national levels, there is still a wide discrepancy between the discursive strategies that actors employ at the two levels regarding other framing categories. At the national level, sovereignty, security, and identity frames dominate the discourse, but at the EU level, international solidarity arguments take a more central place. Chapter 9 will further delve into the issue of framing, looking at the role of discursive coalitions within the refugee crisis.

Figure 3.5 Frames at the national and EU levels

If above we have presented general descriptions of the major characteristics of actions captured by our PPA dataset, these characteristics also stand behind the formation of systematic, comparative indicators used across our country episodes. One example of such an indicator that is used extensively in the following chapters is politicization (De Wilde 2011; Hooghe and Marks 2012; Hutter and Kriesi 2019b). Politicization allows us to capture the expansion of the scope of conflict within the political system (Hutter and Grande 2014: 1003). We conceive of politicization as a multifaceted concept involving a dimension of salience (the number of actions occurring in a particular episode in a particular time frame) and a dimension of polarization (the share of positive and negative actions in that timeframe), both of which are captured by our PPA dataset.³ Another indicator based on our PPA dataset that we use in Chapter 6 is conflict intensity, which is designed to capture the conflictual nature of the policy actions undertaken by actors. We define conflict intensity as a combination of the type of policy action that the actor undertakes and the direction of their actions vis-à-vis their target actors. While politicization allows us to capture the expansion of the scope of conflict, conflict intensity allows us to capture its nature, as some policy actions in our dataset are more conflictual than others (e.g., threats and denigrating opponents are more conflictual than simply proposing a new policy or negotiating) and as actions can be negative, positive, or neutral toward target actors. Accordingly, each action in our dataset is assigned an ordinal conflict intensity score on a 5-point scale based on a classification of policy actions and direction toward the target actor.

Complementary Data Collection Methods

While PPA constitutes the core data collection method used in our study, its empirical reach is not all-encompassing. First, our PPA data can unveil party competition dynamics related to the particular episode at hand but not the wider spectrum of such dynamics in the immigration field in our particular countries. Second, the PPA data described above are not suitable for capturing public opinion dynamics in the refugee crisis, such as the salience of immigration issues in the public or the public legitimacy of the policy outputs. Third, our PPA data allow us to capture the rhetorical devices employed by different actors in the refugee crises only to a limited extent. For these reasons, we complement the PPA data with various other datasets throughout the following chapters. While some of these datasets are widely known and available (e.g., major surveys such as the European Social Survey and the Eurobarometer), some others have been originally collected for the purpose of this book. We briefly describe these latter types of data collection strategies in the following sections.

Election Campaign Data (CSA)

We have mentioned that while the PPA data can be used to study party competition dynamics in a particular episode, their use is limited with regard to studying the wider spectrum of such dynamics in the immigration field in the selected countries. Therefore, for studying party competition dynamics specifically, as in Chapter 14, we rely on an original core-sentence analysis (CSA) dataset (Hutter and Kriesi 2019a; Kleinnijenhuis, de Ridder, and Rietberg 1997).

Similar to PPA, CSA is also based on the large-scale content analysis of mass media. However, rather than measuring all types of actions taking place in a specific policy episode, CSA focuses on the debates among parties in election campaigns as reported in national newspapers. As parties need to develop coherent programs prior to elections, election campaigns provide a good indicator of their issue positions. The core-sentence approach is based on the decomposition of news articles into relevant sentences. Each of these sentences is reduced to its most basic structure, the so-called core sentence, indicating only its subject (the actor) and its object (actor or issue), as well as the direction of the relationship between the two, which ranges from −1 (negative) to +1 (positive). Specifically, we code all core sentences that involve at least one national party-political actor as subject and/or object without further constraints regarding the issues that we code.

The dataset built following this approach covers all elections from 2000 to 2020 in seven of our eight countries of interest (all except for Sweden). This dataset allows us to analyze the salience that different political parties in these countries attribute to immigration issues and the positions these parties adopt in public discourse vis-à-vis other parties over immigration issues.

Surveys

While some of the following chapters utilize existing major surveys (e.g., Chapter 4 relies on Eurobarometer data for measuring the salience of immigration in national publics), Chapter 13, which looks at conflict configurations in asylum policy preferences in the general public, relies on original survey data collected by our team. This survey was fielded in sixteen EU member states in June–July 2021 and is based on national samples of around 800 respondents per country, amounting to a total of 13,095 respondents. Beyond general political attitudes and attitudes toward migration, this survey allows us to complement our other empirical strategies by capturing evaluations of specific policies proposed or adopted during the refugee crisis and, hence, enabling an in-depth analysis of the conflict configurations surrounding these policies in the public.

Speech Analysis

Last but not least, while our PPA data allow us to capture the frames used by actors to justify their policy actions, they do so only to a limited extent based on a minimal frame categorization and without covering actors’ actions and discourse that are not part of specific policy episodes. We further zoom in on the rhetoric devices employed by specific actors in Chapter 9, where we examine the right-wing discourse related to the refugee crisis. For this purpose, we collected additional data on 58 speeches made by twelve key right and radical right politicians⁴ between 2014 and 2020 in six countries (Austria, Germany, Greece, Hungary, Italy, and the UK) covering all of our country types. We built our speech analysis coding scheme through an inductive, iterative process. In the first phase, we started our coding procedure from a limited set of frames corresponding to our PPA frame list, which we subsequently expanded through an initial trial-coding phase. In the final coding phase, we separated our analysis into frames and themes. Whereas “frames” refer to overarching characterizations of the refugee crisis, inducing the audience to adopt a general understanding of the crisis, “themes” are more detailed arguments that attempt to focus the audience’s attention on a specific aspect of the crisis and persuade them to either prioritize certain of its elements or view it primarily in terms of this specific aspect. We coded as many frames and themes as were found per speech, without restricting their number. Our final dataset comprises 751 instances of frames and/or themes that were subsequently aggregated into eleven frame and eight theme categories that are presented and analyzed in Chapter 9.

Conclusion

In this chapter, we have introduced the main building blocks of our empirical design for studying the refugee crisis. In order to meet our ambitious goals of studying the refugee crisis in all its stages, taking into account both its policymaking and political developments, involving both supply-side and demand-side dynamics, we have set up an equally ambitious empirical strategy.

First, this strategy relies on both a categorization of the type of countries in the refugee crisis as well as a selection of key policymaking episodes together with the political debates surrounding them. We focus on eight countries of four different types: Greece and Italy as frontline states, Austria and Hungary as transit states, France and the UK as closed destination states, and Germany and Sweden as open destination states. Most chapters in Part II, III, and IV study the refugee crisis in these eight countries by breaking it down into a set of key policymaking episodes involving salient policy debates. Additionally, since we look at the refugee crisis as taking place in a multilevel polity, EU-level dynamics are also included and studied following our episode approach both on their own (in Chapter 7) and in interaction with the domestic level (e.g., in Chapters 11 and 12).

Second, we have described our data collection and analysis strategies, which rely on several novel methods. Central to our book, we have introduced policy process analysis (PPA), a method that allows us to study these policymaking episodes in a multifaceted fashion by taking into account the actions undertaken, the fine-grained issues touched upon in the episode, the actors involved in the debate, as well as their substantive positions toward the policy at hand and their discursive framing strategies. While these data capture central aspects of the episodes we have selected, we do combine them with a variety of additional original datasets in order to capture those elements of the refugee crisis the PPA fails to measure. In particular, we have introduced core-sentence analysis (CSA), survey analysis, and speech analysis data collection efforts, which enable us to further zoom in on the collective mobilization dynamics and the political party election campaign strategies throughout the refugee crisis. The building blocks of the methods introduced in this chapter are essential for understanding the specific indicator construction and usage in the chapters to follow.