Economists and the Power of Ideas. A Social Network Analysis of Economic Advisers during the Great Recession

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PUBLIC ADMINISTRATION

INTERNATIONAL AND EUROPEAN GOVERNANCE

Economists and the

Power of Ideas

A Social Network Analysis of Economic Advisers

during the Great Recession

This research project investigates the relationship between network topology, uncertainty and paradigms on idea diffusion. Particularly the study analyses the different networks of Economists and policy advice in the United States and Germany and how they affected the diffusion of ideas during the Great Recession. Using co-publication and institutional affiliation data the study builds two separate networks, compares them and uses this data to explain the divergent narratives of the crisis in both cases. The study isolates certain ‘star’ economists explaining how they were able to affect the idea debate triggered by the end of the Great Moderation. Differences in the networks overall topology, ease of interaction and advisory independence seem to have partially caused the differing responses by both countries, as seen in Germany’s initial reluctance towards a global stimulus programme, its quick return to orthodox economic policies and the different narratives of the crisis’ causes.

MICHAEL FLICKENSCHILD (S1730959) SUPERVISOR: DR. ALEXANDRE AFONSO SECOND READER: DR. JOHAN CHRISTENSEN

11.08.2016

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List of Tables and Graphs

Tables

Table 1: Distinguishing between different kinds of knowledge-based groups; Source: (Haas, 1992) .. 18

Table 2: Pearson and Spearman test of centrality measures ... 28

Table 3: Descriptive statistics on Advisory Independence ... 31

Table 4: Advisory turnover, Government change, and other factors in the USA ... 32

Table 5: Advisory turnover, Government change, and other factors in Germany ... 32

Table 6: Comparison of both Networks ... 36

Graphs Graph 1: Social Network of German economists, institutions and main advisory body (2005-2015) .. 38

Graph 2: Social Network of US economists, institutions and main advisory bodies (2005-2015) ... 39

Graph 3: Weigthed Degree Distribution in NA and NG ... 40

Graph 4: Network map of Lazear’s 1st degree neighbours ... 44

Graph 5: Network map of Bernanke’s 1st degree neighbours... 44

Graph 6: Network map of Feldstein’s 1st degree neighbours ... 45

Graph 7: Network map of Auerbach’s 1st degree neighbours ... 48

Graph 8: Network map of Mankiw’s 1st degree neighbours... 49

Graph 9: Meltzer and Feenberg (Green) are part of Harvey S. Rosen’s (1) 1st degree network. ... 49

Graph 10: Network map of Summers’ 1st degree neighbours ... 51

Graph 11: Network map of Franz’s 1st degree neighbours ... 54

Graph 12: Network map of Schmidt’s 1st degree neighbours... 55

Graph 13: Network map of Rogoff’s 1st degree neighbours... 56

Graph 14: Network map of Tyson’s 1st degree neighbours ... 58

Graph 15: Network map of Lazear’s 1st degree neighbours ... 58

Graph 16: Network map of Feldstein’s 1st degree neighbours ... 59

Graph 17: Network map of Bofinger’s 1st degree neighbours ... 63

Graph 18: Network map of Feld’s 1st degree neighbourss ... 66

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1. The role of science and ideas

“You might say that the way to go about research is to approach issues with a pure heart and mind: seek the truth, and derive any policy conclusions afterwards. But that, I suspect, is rarely how things

work. After all, the reason you study an issue at all is usually that you care about it, that there’s something you want to achieve or see happen.” (Krugman, 2016)

This quite recent quote by economist and Nobel laureate Paul Krugman shows something what is often said, but more often forgotten, the simple truth that truth has its own agenda. The saying ‘speaking truth to power’ may be a noble one however is also a misleading one. In response to it Peter M. Haas (2004) takes the limited notion of truth as ‘usable knowledge’, whereas not every truth is usable for policy-makers. Science plays an important role in legitimizing or de-legitimizing policies and is a widely accepted tool to make policies and politics. Peter Weingart (1999) uses this notion in warning about the politicisation of science and the simultaneous scientification of politics leading to the loss of authority of science and the loss of legitimacy of politics. In our seemingly increasing complex world we rely heavily on science. Therefore we should increase the awareness of its shortcomings and improve our understanding where ideas come from, how they diffuse and how in the end they influence policy outcomes.

A strong reliance on science can be found especially in the political sensitive field of economics. The discipline of economics is often a contested battlefield of opposing ideas simply for the fact that it is closely interconnected with politics itself. In fact, Harold Lasswell’s (1958) famous description of politics being about who gets what, when and how would be also a fitting description of economics. Reading through economic literature you can sometimes get the feeling that some economist belief in the idealistic depiction of science, whereas scientists are all objective and only committed to truth (Weber, 1995), and in the case of economists also committed to society’s welfare. However, in contrast Gebhard Kirchgässner argues that objectivity cannot be derived from motivation or integrity but the prudent organisation of the science process. To put it in economic terms “Even economist maximise their own utility under boundary conditions.” (Kirchgässner, 2013, p. 201).

Interests determining the utility function are not based solely on facts but derive from the ideas and beliefs one holds. In contrast to the natural world where our understandings does not affect facts like the movement of planets, in fields like Economics and Politics ideas shape outcomes and form our societies. In the end, the truth or falsity of an economic idea depends on how broadly it is held (Blyth, 2002). For example, if everyone believes that cutting

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government spending is good investors are inclined to reward such actions. In the end, as noted by Peter A. Hall (1989), we cannot understand the political economy without looking at ideas.

Recent events like the global financial crisis and the following European sovereign debt crisis which are often combined as the Great Recession showcase such struggles between ideas and their supporters. The Great Recession saw a shift from consensus to dissension and the return of some old ideas. We experienced a short-lived resurgence of Keynesian ideas in 2008-09, even in Europe despite initial German resistance (Krugman, 2013). However this Keynesian consensus disappeared in 2010 and made place for dissension among economists leaving politicians with a grander diversity of ideas to choose from (Farrell & Quiggin, 2012). Europe’s return to neoliberal1 ideas came in the harsh form of austerity. German chancellor Angela Merkel justified austerity with the values of the Swabian housewife: Prudence, saving and debt avoidance should cure the Eurozone, while ignoring the massive German trade surplus and simple macroeconomics, like the fact that with everyone saving we all become poorer. Moreover, economists have shown that economies vary deeply from one another, there is no one-size fits all policy (Hall, 2014). This example shows that ideational change is not simply a learning process from past mistakes but incorporates a sociological component. With ideas gaining and loosing in prominence, it is not only interesting but important to analyze how economic ideas change and diffuse and what role economists play in this, because in the end politicians rely especially under uncertainty on expert advice. Their ideas provide us with blueprints to design new institutions and to steer us out of a crisis. Central to this research is the theory put forward by Henry Farrell and John Quiggin (2012, p. 44) that the appearance of consensus on an idea or a set of ideas is a product of network topology, social pressures and to some extent the processes of disinterested inquiry. The latter two factors have already been subject of many different studies. Network topology and its impact on the diffusion of ideas however remains mostly a dark spot. By mapping out two networks, one for economists and advisers in Germany and one for its American counterpart we hope to further the understanding of how they affect ideational change and why governments reacted different to the crisis. The goal is to provide some answers to the question of how we can explain variations in change and persistence of economic ideas.

1_{Throughout the study the word ‘neoliberal’ is used quite freely, because there is no single definition and its}

meaning changed quite often over time. For example, Philip Mirowski (2014) divides neoliberalism into three main different strands, the Austrian School (Hayek), the Chicago School (Friedman, neoclassical), and the German ordoliberal strand. However some Austrian economists like the Mises Institute do not see themselves as neoliberals.

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2. Theory

“Who claims to be able to judge value-free over economic policy is wrong.” (Lars P. Feld,

Member of the German Council of Economic experts, in Schmidt et al., 2015, p. 168)2

With the importance of ideas for economics and in general policy making in the back of our head we now need to take a step back and look at how ideational change happens, the role of consensus versus dissension, the diffusion of ideas, economists in politics, and the concept of networks. In order to get everyone on the same level, let us delve now into the existing literature on each of these topics. After that we come to the research’s theoretical framework and how this study supplements previous research.

2.1. Literature review

Let us now look into the literature on several areas of importance for our theoretical framework. These areas include idea and policy diffusion, ideational and institutional change as well as economists and social networks.

2.1.1. Idea and Policy Diffusion

Diffusion is a very broad field of study with many different existing mechanisms and theories, especially in the field of policy diffusion. In contrast, idea diffusion is far less researched. However many concepts of policy diffusion are as well applicable to idea diffusion. While naming conventions on diffusion mechanisms may differ and some criticize the lack of a coherent theoretical framework (Braun & Gilardi, 2006), there seems to be a consensus on four main mechanisms: Constructivism, coercion, competition, and learning (Braun & Gilardi, 2006; Dobbin, Simmons, & Garrett, 2007; Gilardi, 2016; Shipan & Volden, 2008; Simmons & Elkins, 2004). Constructivism diffuses policies via norms propagated by epistemic communities and international organisations. Coercion explains diffusion as actors distorting the incentives of other actors by the use of carrot and/or stick. Competition explains it as the struggle to attract investment or other gains. Finally, learning constitutes a process of taking lessons from own experiences and the experiences of other actors. In practice, diffusion of ideas and policies is probably a mixture of all four mechanisms. For example the Washington Consensus in developmental economics was diffused by international organisations like the World Bank and the International Monetary Fund propagating

2

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neoliberal norms, while also using the carrot (debt relief) and the stick (conditionality). Competition enforced this process because early adopters were suddenly seen as sound economies and therefore could attract capital. Learning as a mechanism, was already involved inside international organisations and developing states due to past failed development policies (Gore, 2000; Krugman, 1995; Rodrik, 2006). However, let us now have a look at a combination of two of those mechanisms, namely constructivism and learning.

This approach is called social learning and has been used by many different scholars in varying ways. Learning, on its own, was first developed as an independent theoretical field by Hugh Heclo in the mid-1970s. Summarized, Heclo (2010, p. 305) suggested that public policy-making is often more than just a process of transforming societal pressures into rules and institutions: “Governments not only ‘power’ [. . .]; they also puzzle. Policy-making is a form of collective puzzlement on society’s behalf; it entails both deciding and knowing”. He combines the notions of ‘powering’ and ‘puzzling’ into the process of social learning. Hall (1993), sees two problems with this concept. First, that it had yet to construct a comprehensive image of how ideas change and how they fit into the policy process. Second, it was unclear whether these processes of social learning are affected by societal development or take place only within the state itself. In regard to the second problem he argued that even in a technical field as macroeconomics, policy change is a response to an evolving societal debate and not simply the consequence of autonomous state actions. Ideas condition policy-making and ideational change is tethered to the concept of policy. Hall conceives the state and society as generative of social learning, but paradoxical uses two different logics, Constructivist (powering) and Bayesian (puzzling), to explain how this learning takes place (Blyth, 2013). Mark Blyth argues that Bayesian learning resembles a process of rational updating by policy-makers and society. It drives the constructivist story but cannot achieve a paradigm change because it only accumulates new knowledge and does not erode the existing paradigm3. He argues that the absence of paradigm change in the financial crisis supports the constructivist perspective, because despite of the apparent failure of neoliberal policies and a short experimentation period with Keynesian policies no learning happened and the neoliberal paradigm prevailed. Using as well Heclo’s approach of learning, Farrell and Quiggin (2012) elaborate on the concept: They distinguish between two major lines of argument. They use Heclo’s terms of ‘puzzling’ and ‘powering’. Expert ideas matter in both they argue, but in the latter power and bargaining play a greater role which, however, quite resembles the concept

3_{A paradigm is simply an idea, a concept or a set of ideas and concepts considered as prevalent and legitimate}

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of social learning. This reflects the arguments already made by Hall (1993) and Blyth (2013) however they clearly defined ‘puzzling’ as the learning, ‘powering’ as the constructivist, and the combination as the social learning approach.

In fact, social learning seems to be better applicable not only looking at diffusion on the level of politics but already among the academic profession since competition and coercion are less likely to contribute to diffusion.4 However to analyse if social learning occurs becomes quite tedious at a grander scale. A more simplified mechanism easier to use in a Network analysis is the concept of contagion. Diffusion within social networks is an important element of network theory. According to Wasserman and Faust (1994), social network analysis focuses on individual actors (nodes) and the relationships (edges) between each other. Diffusion in social network theory is the transmission of information across these links from one node to another. Charles Kadushin (2012) compares diffusion of information or ideas through society to the spread of a disease. In its simplest form, contagion argues that knowledge travels when two subjects interact. In fact, research shows that diffusion of ideas is closely connected to the diffusion and creation of knowledge (Vitanov & Ausloos, 2012). Ideas can spread from an active (infected) node out to its neighbours and then spread to the neighbours of the nodes which turned active as well. Contagion gives a very materialist and reductionist account of ideas and their effect which makes explaining diffusion easier without needing to research at the micro-level and the processes of persuasion. However it is not a prerequisite for ideational change, since strong beliefs will not be easily changed by new knowledge. Farrell and Quiggin (2012) use this concept to explain how ideas spread through a process of infection during the Great Recession. They explain how the infection of certain ‘star’ economists and the uncertainty of the crisis had an effect similar to an epidemic in a network leading to the Keynesian resurgence, but new events causing a new epidemic reversed this process.

2.1.2. Ideational and Institutional Change

Karl Polanyi’s seminal work “The Great Transformation” (Polanyi, Stiglitz, & Block, 2001), first published in 1944, shows how ideas influence and promote systemic change and how ideologies interplay often with particular interests. In the introduction of the 2001 edition, Fred Block (ibid. 2001, p. xviii) states that the book “provides the most powerful critique yet produced of market liberalism.” However Polanyi’s work is more than just a critique of

4

Still, coercion might affect the diffusion of ideas in the scientific community via the carrot (grants) and the stick (refusal of publication). Similar, competition could affect diffusion by favouring certain fields over others through the competition for available grants.

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market liberalism, it provides us with some important insights into the world of ideational change. Polanyi argued that market liberalization in the 19th and early 20th century, caused an inevitable response in concerted efforts to protect society from the market. Similarly to Newton’s third law of motion, Polanyi reasoned that when a body exerts force on another body, the second body simultaneously exerts a counterforce in the opposite direction. He called it the ‘double movement’ by which the disembedding of markets in form of classical liberalism led to labour demanding a re-embedding in form of protection by a strong state. In fascism, he saw an extreme result of this ‘double movement’. The post-war economic system, which becomes to be labelled as embedded liberalism (Ruggie, 1982), is a less extreme response to the liberal forces. Beginning in the 1970s with the dissolution of the Bretton Woods system, we again experienced a disembedding of markets. While we have not seen a return to embedded markets yet, we have seen many forces resisting this disembedding, for example the Anti-globalization movement, the Occupy Wall Street movement, and most infamously the rise of radical and populist politicians throughout Europe and America who want to make the nation state great again in some way or another.

Mark Blyth (2002) continues on Polanyi’s theory and explaining the second great transformation. This transformation is the above mentioned return to a disembedded market in the 1970s and 1980s under the helm of neoclassical ideas. Blyth, though argues that Polanyi’s theory of institutional change is limited. The ‘double movement’, similar to other interest-based explanations, takes the viewpoint of comparative statics whereas one compares two different equilibrium states but leaves the process of change in-between out. Often the change from equilibrium to another is simply explained by an automatic response to an event, a punctuation in-between, like an economic crisis. This solely exogenous change however neglects the endogenous process leading to people readjusting their interest. For this readjustment, two factors are important, uncertainty and the set of available ideas. Blyth uses the concept of ‘Knightian’ uncertainty which he derives from Frank H. Knight’s (2014) “Risk, Uncertainty and Profit” first published in 1921 and its adaption in Sociology. Jens Beckert (1996, p. 807) explains that “Knight distinguishes between changes in the economy to which probabilities can be assigned, and situations where the individual has no information on which to base a calculation of probabilities.” The former he calls ‘risks’ and the latter ‘uncertainty’. Mark Blyth applies this concept of ‘Knightian’ uncertainty to explain how ideas matter in crises because they give answers where there have been none. Ideas not only diagnose what has gone wrong but also determine what should be done; they make the crisis manageable by providing blueprints to the actors and thereby decreasing the uncertainty. “Therefore, in

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periods of economic crisis, it is imperative to attend to the economic ideas that key economic agents have” (Blyth, 2002, p. 10).

Uncertainty in some kind of role was always important for theories on ideational change. Most notably Thomas S. Kuhn’s paradigm cycle (Kuhn, 1996) explains shift in paradigms in scientific fields, whereas times of heightened uncertainty like increased discrepancies between theory and reality lead us to question prevalent ideas. With the accumulation of inconsistencies in the ‘normal science’ people increasingly start doubting their beliefs and begin looking for alternative explanation. They start experimenting with new ideas until a new paradigm emerges. Kuhn’s concept of scientific revolution was a revolution in itself since it saw science not as a process of accumulating ideas but as a cycle which acknowledges that old ideas could be falsified. Peter A. Hall (1993) takes Kuhn’s concept of paradigm shift and applies it to politics, and argues that ideas are central to policy-making. He divides Kuhn’s paradigm shift in first, second, and third order change. First and second order change constitute ‘normal’ policy-making without challenging the overall terms of the current policy paradigm. This resembles what Kuhn called “normal science”. In contrast, third order change is more radical, it constitutes a paradigm change. It involves the accumulation of inconsistencies and a period of experimentation or paradigm innovation leading to a change in authority over policy and thereby to third order change. These stages used by Peter A. Hall are often replicated in similar studies on ideational change (Blyth, 2002; McNamara, 1999). An example for a third order change is the shift in the hierarchy of goals from unemployment as the top concern to inflation which changed not only economic policy but dissolved the authority of Keynesianism and governments subscribing to it. Hall explains this with the example of the rise of Thatcherism in the United Kingdom (See also: Hay, 1996; Rogers, 2013).

Kathleen McNamara (1999; 2006) uses Hall’s concept to explain how European Monetary Cooperation was able to culminate into a common currency by arguing that the rise of Monetarism made price stability more important than independent monetary policy. Inflation became the biggest concern, leading to the neglect of other dangers in a non-optimal currency area. Mark Blyth (2013), as mentioned above, instead analyses the global financial crisis where a third order change should have happened, but did not. This led him to the conclusion that for a paradigm change it needs more than simple Bayesian learning. Replicating one of Thomas Kuhn’s arguments, he argues that truth has two separate roles: One is the empirical fact and the other a sociological convention. “As a result, the superiority of one theory to

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another is something that cannot be proved in the debate. Instead, […] each party must try, by persuasion, to convert the other” (Kuhn, 1996, p. 198). Both Blyth and Kuhn call this the incommensurability of science. To explain the absence of a paradigm change after the financial crisis, Blyth argues that the sociological can trump the scientific because of authority. He sums up that, “it is politics not economics, and it is authority, not facts that matter for both paradigm maintenance and change” (Blyth, 2013, p. 210). However science can often also be a source of authority as the next paragraph shows.

Farrell and Quiggin (2012) argue that it is of importance if there is an apparent consensus or ‘dissensus’ in a scientific field, because a consensus empowers scientists and give their ideas more authority while dissension among them gives politicians more manoeuvrability to chose ideas fitting to their interests and beliefs. The second part also reflects Peter Weingart’s (1999) argument about the legitimating and de-legitimating function of science. Science here is used as a second authority next to public consent in order to promote or dissuade policies. Farrell and Quiggin explain in their study the rise and fall of Keynesianism during the crisis. The Keynesian resurgence was empowered by a sudden appearance of consensus among economists to pursue stimulus policies; however it was short-lived due to increasing degree of disunity in the profession. In order to discern how consensus and dissension emerges among economists they look at the way the economist community is structured and how ideas spread through networks. They hypothesize that the appearance of consensus is a product of network topology, social pressures, and to some extent the processes of disinterested inquiry by scholars of epistemic communities (Farrell & Quiggin, 2012, p. 44). Using this theory, our research takes a closer look at the mostly unchartered waters of network topology. Particularly the networks of economists in Germany and the United States in order to answer how we can explain variations in change and persistence of economic ideas during and after the global financial crisis, as well as the effect of economists on policy outcomes.

2.1.3. Economists and Social Networks

Before coming to the theoretical framework we have to look at two more important aspects for this study: The profession of Economists and Social Network Theory.

Despite the public appearance a real consensus on any economic topic is quite a rare thing. Many articles showcases this by the example of President Truman wishing for a ‘one handed economist’ who would not advice him saying “on the one hand ... but on the other hand” (Frey, Pommerehne, Schneider, & Gilbert, 1984, p. 986). Or of Winston Churchill stating that

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with two economists in a room, “you get two opinions, unless one of them is Lord Keynes, in which case you get three” (Freeman, 2009, p. 23). Inquiring upon this, Frey et al. (1984) conduct a survey among economists seeking to determine the degree of consensus and dissension in the USA, Germany, Switzerland, France and Austria. They conclude that while consensus is the strongest on the price system and the effectiveness of markets, there is not much consensus on other propositions. However, especially American, German and Suisse economists are more in favour of the market price system, competition and overall neoclassical economics and see government interventions more undesirable. While they find that some individual Monetarist and Keynesian proposition find a consensus, there is no overarching consensus on either of them. Arguably this could show again the important role of authority and political actors campaigning on ground of such ideas. As shown by the successes of Monetarism under Thatcher in the United Kingdom and Reagan in the United States as well as the failed attempt of the French government in 1981-83 to return to Keynesian policies and consequently the success of the neoliberal advocates in the French government (Helleiner, 1995).

A more recent study (Fuchs, Krueger, & Poterba, 1998) comes to similar results and declares that there are a great deal of disagreements. Furthermore it finds out that policy positions seem to be closer related to differences in values than differences in positive judgements. The research shows also that Economists display a great deal of overconfidence in their judgements despite some of their beliefs being far from any consensus. Gebhard Kirchgässner (2014) assesses the economic profession after the financial crisis and comes to the conclusion that there is disagreement among economists not only about their responsibility for the crisis as well as on the issues of government debt, minimum wage and the European Central Bank’s policies. He argues that there is quite a lot of consensus on microeconomic questions but much less on macroeconomic questions. “This often allows politicians and interest groups to select as advisors [...] those who are closest to their political conceptions in order to get scientific support” (ibid. 2014, pp. 18–19). The only instruments available to prevent errors and manipulation, he argues, are competition between economists and open discussion between researchers.

Marion Fourcarde (2006; 2009) takes a closer look at the global network of economists, the transnationalization of the profession and more in detail the profession in the USA, France and Britain. She shows how the field has become increasingly defined in global terms with standards coming mainly from the United States. This internationalization has been felt also

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in Germany with an increasing number of publications in English and in International Journals (Haucap & Thomas, 2014). Other studies come to a similar conclusion on internationalization, however point out that the international impact of German (and French) journals is greater than their Spanish and Italian counterparts (Pons-Novell & Tirado-Fabregat, 2010). “The Superiority of Economics” (Fourcade, Ollion, & Algan, 2014) investigates the dominant position of economics within the social sciences. The overconfidence already attested by Fuchs, Krueger and Poterba (1998) and the profession’s unique position to advice on policy is explained by their “far-reaching scientific claims linked to the use of formal methods; the tight management of the discipline from the top down; high market demand for services, particularly from powerful and wealthy parties” and “high compensation” (Fourcade et al., 2014, p. 2). The hierarchical structure leads to a situation where a few actors in the profession field incomparable authority. Together with a strong tendency to look inward and not outside the discipline, Fourcade argues that there is either more consensus or more control or a mix of both in the discipline than in other social sciences. On the control side she notes the high importance of the top departments in the field and the horizontal integration of norms and on the consensus side she points at two studies (Hansen, 1991; Lamont, 2009) showing the high similarity in graduate educations, core principles, and standards of evaluation.

This study focuses more on the domestic influence of economists and how they affect their government’s policies. However the overall high influence of American economists can be seen also during the Great Recession with many American economists pressuring their German colleagues as well as politicians to change their stances towards economic ideas (Beutelsbacher, 2015; Handelsblatt, 2010; Piper, 2015). Instead, examples for the other way round are very rare (Cogan, Taylor, & Wieland, 2009). In a study about the network of economists the authors argue that the economic profession is an emerging small world with the average distance between individuals (measured by co-authorship) having fallen over time. In small world networks the mean geodesic (i.e. shortest-path) distance between nodes increases sufficiently slowly compared to the overall population of the network. Moreover they found out that the distribution of co-authorships is very unequal leading to a network with many stars (highly connected economists). These highly interconnected economists become very important in the diffusion of ideas since they connect different groupings of economists with each other.

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2.2. Theory, Concepts, and Hypotheses

In the following three paragraphs the analysis’ theoretical framework will be established, after that the main concepts defined and our hypotheses presented.

2.2.1. Theoretical Framework

First of all, to explain variations in change and persistence of economic ideas during the great recession we use Henry Farrell and John Quiggin’s (2012) theory that the appearance of consensus is a product of network topology and social pressures. These two factors, they argue, are as much as and maybe more important than the often ascertained process of disinterested inquiry (learning). There have been analyses of past transitions in economic paradigms (Blyth, 2002; Hall, 1989, 1993; Hay, 1996; Helleiner, 1995; Polanyi et al., 2001; Rogers, 2013), and also a few on the most recent crisis where are paradigm change was absent (Blyth, 2013; Smith, 2012). Instead we experienced a short-lived Keynesian resurgence (Farrell & Quiggin, 2012), which then was followed by fiscal consolidation supported by the rise of the idea of expansionary fiscal contractions (Blyth, 2015; Dellepiane-Avellaneda, 2015; Krugman, 2013) and then an incremental change towards a new orthodoxy with increased financial regulation in form of macroprudential supervision (Wolf, 2015). More puzzling however were the different responses by countries during the crisis, especially in the case of the debate concerning the use of economic stimulus to revive the global economy. The United States (and the United Kingdom) led the debate in favour of a global stimulus package against the resistance of the German government. A resistance which only began to waver after the majority of German economists and especially the members of the German Council of Economic Experts changed their opinion and joined the global consensus on a stimulus. However, when the Keynesian consensus started to fall apart, German politicians together with dissenting economists helmed the argument for fiscal consolidation and with the Eurozone’s rising debt problems austerity gained its foothold in the debate.

Germany’s resistance to Keynesian policies is often explained by its strong and institutionalized ordoliberal beliefs (Allen, 1989; Dullien & Guérot, 2012; Nedergaard & Snaith, 2015; Newman, 2010). However, these convictions have in parts their roots in the ideas and knowledge accumulated and spread by the network of economists. It is therefore helpful to analyze the network structure of economists and policy advice in Germany to better understand the entrenchment of ordoliberalism. More importantly, an improved knowledge of the network topology could also give us some insights into the influence of individual

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German economists and more generally the impact of consensus compared to dissension. This is important especially when reflecting that expert consensus may shape broader political consensus (Farrell & Quiggin, 2012). The United States is not only interesting as a comparison but also due to the USA being on the other side of the debate and the tension between scientific advice and political pressures during the Obama administration. Moreover, the size and diversity of its economic profession makes it an interesting case to look at the influence of individual economists.

Since the focus is not on micro mechanisms but on the overall network structure itself, contagion lends itself well as the main diffusion mechanism. It is not only practicable thanks to its reductionist perspective but it suits well the narrative of the crisis in which we saw ideas change quite often and quite fast, resembling idea cascades. It is plausible that contagion as a mechanism is strengthened under the above discussed ‘Knightian’ uncertainty, because academics as well as politicians looking for answers are more likely to accept new ideas (Blyth, 2002). This can be additionally supported by an underlying paradigm. New ideas can rise easier to popularity if supported by the framework of an existing paradigm, especially when we consider the deep embeddedness of ordoliberalism in Germany (Allen, 1989; Nedergaard & Snaith, 2015). Therefore we keep the concept of social learning in mind too, since deeply rooted beliefs can often be quite resistant and hinder or support change. Moreover, the embeddedness of ideas in parts of society makes them able to ‘hibernate’ and resurface again after an initial defeat as shown by quick return to the global neoliberal orthodoxy (Mirowski, 2014). Overall, contagion and social learning seem to function quite well as complimentary mechanisms, since we can explain heightened contagion with a supporting underlying paradigm. For example, Chang Kil Lee and David Strang (2006) use the concept of social learning to explain why public sector downsizing is contagious and upsizing is not, despite no existing consensus on which is harmful or beneficial. They argue that “asymmetries in emulation and learning are a product of the dominance of neoliberal and managerialist discourses that legitimate and theorize shrinking the public sector” (ibid. 2006, p. 883).

As main theoretical model for ideational change the adaption of Kuhn’s Paradigm Cycle (Kuhn, 1996) into the fields of politics and economics is used (Blyth, 2013; Hall, 1989, 1993). Before the crisis economists and politicians were talking about the so-called ‘Great Moderation’ a period from the mid 1980s on where we saw a substantial decrease in economic volatility in the form of stable inflation and stable growing output. The term was

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first coined by economists James Stock and Mark Watson and became widely known after Federal Reserve governor Ben Bernanke used it in a speech (Bernanke, 2004; Stock & Watson). However, the financial crisis heralded the “return of depression economics” (Krugman, 2009) and thereby constitutes a crass inconsistency with the then prevalent beliefs. This policy failure increased uncertainty and led to a period of policy experimentation. First, we experienced the short return of Keynesian policies which acknowledged the return of business cycles and the need for stabilization policies. Soon, however, fear over unsustainable debt levels caused among others by the European debt crisis led to new uncertainties and changing priorities. Studies pointing towards the dangers of too high debt levels and the benefits of fiscal contraction only supported this move (Alesina & Ardagna, 2009; Reinhart & Rogoff). The change in priorities led to fiscal consolidation and in some countries the experimentation with austerity policies.5 Despite this we experienced no paradigm shift so far. While there were some changes, especially in financial regulation, these alone do not constitute a real paradigm shift (Baker, 2013). Instead, we saw a return to neoclassical orthodoxy in form of ‘growth friendly fiscal consolidation’ and the idea of market efficiency and the inefficiency of governments prevailed (Blyth, 2013).

We argue that the economic profession has a special position among the sciences, and that economic ideas are an important factor in making policies. This unique position gives economists in line with the economic paradigm or in line with the beliefs of those they advise increased authority on policies. This “superiority” allows them therefore even to change government policies when backed by an apparent consensus, as has happened in the German case. In contrast, in the American case we saw the Obama administration using the apparent consensus in its favour and choosing advisers who were in line with their beliefs. While there are studies which show that the influence of economists should not be overrated (Eizenstat, 1992; Haucap & Thomas, 2014; Haucap, Thomas, & Wagner, 2015), the profession’s overconfidence and openness to participate in policy making, as well as the high expectations towards them are attested by many other studies (Fourcade et al., 2014; Fuchs et al., 1998; Nelson, 1987; Schmidt et al., 2015). The many cases in which economists banded together in writing an open letter to their government to influence policies exemplify this affinity towards participation. For example in 2014 over 600 economist signed a letter in favour of a federal minimum wage of 10.10$ (Economic Policy Institute, 2014), followed by a letter by over 500 economists arguing against any increases of the federal minimum wage (Deutsch, 2014).

5_{The time period consisted also of many experimentations in the field of Monetary policy, see: ‘Quantitative}

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Similar cases can be found for Germany. An example is the ‘Hamburger Appell’ in which 253 German economists called out against wage increases and claimed that active fiscal policy is inherently useless just two years before the crisis (Funke, Lucke, & Straubhaar, 2005). By contrast, this is something we would hardly imagine to happen in any other field of science.

2.2.2. Concepts

To begin with, we look at ideas as interpretative frameworks. “Economic ideas are causally powerful [...] because they do not simply reflect the world that precedes them” (Blyth, 2002, p. 10), they are both scientific and normative because they provide blueprints and say how the world ought to be. Similarly, in arguing about the role of epistemic communities Peter M. Haas (Haas, 1992, p. 4) states that the information provided by them is “neither guesses nor ‘raw’ data; it is the product of human interpretations of social and physical phenomena.” Ideas provide us with interpretation of the world and therefore have a real impact on the world. For example, American economist Martin Feldstein argues that it “was not events but

ideas that propelled the increasing rate of inflation” it “was the result of a fundamental set of

beliefs [...] shared by economists and policy officials” (Feldstein, 1982, pp. 63–64).

Secondly, in contrast to Peter Haas’ research, this study does not look at epistemic communities, but the overall network of economists in Germany and the USA. The discipline or profession of economists differs from an epistemic community in that sense that while both have shared causal beliefs and a consensual knowledge base, the discipline itself does neither share principled beliefs nor interests (Table 1). A change in paradigm then would change the consensual knowledge base; however in economics even this base can often be quite contested.

The whole discipline of economics may be neutral, but individuals may have strong beliefs and can differ in their views. As discussed before a real consensus may be rarer than expected. However, the often displayed overconfidence of economists and the need of politicians for scientific legitimacy can leave us often with the impression of an apparent consensus. Ideational change in the overarching paradigms gives ideas closer to these paradigms increased legitimacy even if there is no clear consensus on these ideas. The interventionist force provided by embedded liberalism and Keynesianism and the deregulating force of neoliberalism showcase this. So is the contagiousness of public sector downsizing in contrast to upsizing supported by its closeness to the neoliberal orthodoxy (Lee & Strang, 2006). Consensus can exist as well in individual fields of economics, an example for this is

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the neoliberal and market oriented reform agenda of the Washington Consensus in developmental economics (Rodrik, 2006).

Table 1: Distinguishing between different kinds of knowledge-based groups; Source: (Haas, 1992)

This study uses in a similar fashion to Goyal et al. (2004) co-authorship relations between economists to build the networks. Additionally, it also includes affiliation with institutions like economic advisory councils, universities, and think-tanks to create the network map for Germany and the United States. We talk more about social networks in our methods part. Mapping out these national networks of economic policy advice and researching which actors are more powerful in spreading ideas and how different structures enable those actors is an important task in understanding the ideational political economy.

2.2.3. Hypotheses

The following sections presents a collection of hypotheses about the effects of different advisory systems, the influence of network topology on diffusion, the impact of individual economists and the different effects of consensus and dissension on the debate.

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First of all, considering that there exist essential differences between economic advice in Germany and in the USA we could explain different reactions to the crisis and to advice by these structural differences. Therefore the first hypothesis is, that the more independent an

advisory body is the more likely is it that its ideas differ from its government’s behaviour (H1.1). Consequently we can argue as well that a more independent advisory body is more likely to get into conflict with its government (H1.2). These first two hypotheses are not that

striking, however insights here can further the debate about the advantages and disadvantages of different advisory system. In the analysis we explore both these ideas with a qualitative and quantitative study about the independence of the American and German main economic advisory bodies.

After that we start the social network analysis by comparing both networks’ topology. We argue that the social network of economists in the United States is more interconnected and

thereby supports idea diffusion better than the Economic network in Germany (H2). The ease

of interaction, also called coupling parameter, is determined by factors like average path length, average degree, modularity, clustering, and density. Comparing both networks does not only improve our understanding of how the topology affects diffusion but also about inherent differences in the German and American economic profession.

At last we take a closer look at the narrative of the Great Recession in form of the political and academic debate surrounding it. Following the notion that an expert consensus, even when only apparent, can shape the broader policy consensus (Farrell & Quiggin, 2012), we take a closer look at the different stages of consensus and dissension and the main economist driving them. Their centrality in the network helps us to understand how influential they really were in shaping the broader consensus. The overall centrality of a node can be measured by its degree (Number of links), its eigenvector centrality (Importance of an agent’s neighbours), its betweenness centrality (Intermediary between different parts of the network), and its closeness centrality (Ease of reaching other agents in the network). We argue that the

higher an agent measures in centrality, the more influential he is in diffusing ideas (H3.1).

The last hypothesis concerns the different effects of consensus and dissension. We hypothesize that an apparent scientific consensus can force governments to enact policies

going against to their beliefs; au contraire, any emerging dissent is likely to be used to enforce the legitimacy of their policies (H3.2). Hypothesis 3.2 could explain the about-turns

we especially saw in German politics during the Great Recession, where we saw a change in politics while the tone of argumentation stayed the same. The overall economic consensus of

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the Governments plays a role here as well, since an administration is more amiable towards ideas close to their own paradigm and only a strong academic consensus can convince them to pursue policies going against this paradigm. In the analysis, we will try to confirm our five hypotheses. However, the mostly qualitative analysis and the limitation of only having two cases limit the prospects of confirmation. Nevertheless, having Karl Popper’s falsifiability criterion in mind we should only strive for falsification in pursuit of scientific discovery (Popper, 2002).

3. Research Design

The research design should follow the research question and show how the independent variables can explain the dependent variable. We start with taking a look at the case selection. After that we explain the methods we employ to answer our research question and hypotheses and the next paragraph then presents the data used for the analysis. The last paragraph explains the operationalisation, the dependent variables and independent variables and explores alternative explanations.

3.1. Case selection

The United States and Germany were two of the major players in the debate about economic policy after the financial crisis. The United States led the concerted effort for a global stimulus, while Germany was quite reluctant to engage in any big fiscal stimuli programmes. At first, at the outset of the crisis in February 2008, the Bush administration decided to enact a stimulus package. In contrast, the German coalition government only hesitantly enacted a limited stimulus programme months later in November 2008. This hesitation was in part due to a different economic situation; Germany was hit by the recession quite late. However, Germany’s reliance on exports and external demand made it early on likely that the recession would inevitable reach Germany. In February 2009, a more ambitious stimulus was enacted by both countries, but soon Merkel’s government opposed again any further fiscal stimulus. Germany was quite quick to return to fiscal consolidation and led the Eurozone into the direction of austerity. It is therefore quite an interesting case to analyse why Germany was such an outlier in this debate, as well as why the United States was able to adapt its policies so quickly after the financial crisis. Hence the case selection started with the puzzle, and can be considered a backward looking research design. Moreover it could be considered a most different system design as well as a most similar system design. The first, because the network of economists supposedly should be similar in both countries, especially when considering that the profession is heavily influenced by American practices and standards

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(Fourcade, 2006). Therefore, the initially different outcomes and the delayed diffusion of Keynesian ideas are a puzzle. A most different system design in contrast would refer more to the advisory systems, whereas the American variant is very close to the administration, and in contrast the German version is very independent. Overall our comparative design covers not only two different cases but each case at different points in time. These points in time are the first fiscal stimulus and its debate, the second stimulus, and at last the failed attempt at a third stimulus and the turn to fiscal consolidation. This focus on two cases and several instances in time makes our research design a ‘closed universe’ according to Keman (2011). By choosing only two cases we neglected external validity and generalization in favour of internal validity, since this permits us to include more variables and allows for a more coherent conclusion in an unexplored field as economic policy advice networks.

3.2. Method and Data Collection

First of all, to obtain a grasp of the general differences in economic policy advice, the paper looks at the laws and regulations constituting the United States’ Council of Economic Advisers (CEA) and its counterpart, the German Council of Economic Experts, also called the ‘Sachverständigenrat’ (SVR). With this information we gain first insights into the degree of formal independence of each organisation. Then, to supplement these results, a small quantitative analysis is undertaken. The analysis looks for any correlations between advisory turnover and governmental change in both countries. In the US case the data ranges from August 1946 to the end of 2015 (n = 833); and in the German case from January 1964 to the end of 2015 (n = 624). Each unit n hereby represents a month. The beginning month represents the establishment of each advisory body. Additionally, the dataset includes also information about parties in power and about the occurrences of recessions giving us the ability to explore different partisan attitudes and the impact of economic downturns on advisory turnover. With this information we are able to obtain a good idea about the advisors’ degree of independence from political influences and moreover about how likely it is that the opinions of experts and government coincide. Furthermore, a qualitative study on the existing literature on economic policy advice for each country gives us insights into the influence of advisors on their respective governments. All this, provides us with answers for hypotheses

1.1 and 1.2 about the independence of advisory bodies and the frequencies of dispute between

advisors and politicians.

The second and larger part is the Social Network Analysis. The study collects data about the connection between economists in each country via co-publication data and organisational

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affiliation data. The co-publication data will be extracted from the Web of Science database with the help of the ‘Science of Science’ tool (Sci2 Team, 2009) and visualized with the software ‘Gephi’ (Mathieu, Heymann, & Jacomy, 2009). Knowledge and ideas are more likely to travel between agents who have contact with each other. Co-authorship and institutional affiliation are proxies for the links between economists. This should help us to map out the ease of interaction or contagion for both cases. The social networks take as their starting points the members and chairs of each advisory body during 2005 to 20156. In the United States we included also the ‘Presidential Economic Recovery and Advisory Board’ (PERAB) which was created by President Barack Obama as a response to the crisis. However only members of PERAB were included who are economists and are active academics. In Germany nothing comparable existed. Membership of the CEA and the SVR changes over time. The network maps therefore include in the surveyed period more advisers than the regular five for Germany or three for the USA amount. In the German case these are ten and in the US case twenty (24 with PERAB). In the USA adviser positions change quite often explaining the high numbers here. With these initial economists we build our network of policy advice around them. We assume that economists who are at one point in these advisory councils are closer to the government and are probably already influential before they become a member. These advisers are seen as an entry point to politics for economic ideas diffusing from the overall network.

The network is further complemented by economic institutions making it a two mode network. So-called affiliation networks consists of two elements, a set of actors and a number of subsets of actors (sometimes referred to as events) (Faust, 1997). Our actors are the economists, and our subsets consist of economic institutions. For each case we add the ten most academically influential economic institutions according to the institution ranking provided by the IDEAS website, which is part of Research Papers in Economic (RePEc) database (Federal Reserve Bank of St. Louis). For Germany these institutions include think tanks and University departments, while for the USA besides the World Bank and the International Monetary Fund only University departments made the top ten. The World Bank and the IMF, however, had to be excluded because despite them being based in the USA, their

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In the USA these are: Jason Furman*, Sandra E. Black*, Jay Shambaugh*, Austan D. Goolsbee, Cecilia E. Rouse, Christina D. Romer, Donald B. Marron, Edward P. Lazear, Carl Shapiro, Katherine G. Abraham, Alan B. Krueger, James H. Stock, Betsey Stevenson, Maurice Obstfeld, Katherine Baicker, Matthew J. Slaughter, Ben S. Bernanke, Harvey S. Rosen, Kristin J. Forbes, N. Gregory Mankiw

And in Germany: Christoph M. Schmidt*, Peter Bofinger*, Lars P. Feld*, Isabel Schnabel*, Volker Wieland*, Beatrice Weder di Mauro, Bert Rürup, Wolfgang Franz, Claudia M. Buch

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economists are recruited worldwide and only three economists in the network map were affiliated with them. Other organisations included are the two German ordoliberal think tanks, namely the Walter Eucken Institute and the Kronberger Kreis7, because of their obvious ideological alignment and their close links with many of the advisers. There exist alternative rankings for economists and institutions like the Scopus database and for Germany the Economist ranking of the newspaper ‘Frankfurter Allgemeine Zeitung’. Moreover, the data from RePEc has one shortcoming; its quality depends on the maintenance by authors themselves (Haucap et al., 2015). Nevertheless the RePEc database is the most comprehensive and includes both German and American economists and institutions. In order to further our understanding of the importance of individual economists we also included total article download numbers for economists from the LogEc database which is also part of the RePEc collection (Federal Reserve Bank of St. Louis). This helps us later in establishing a centrality ranking of economists.

The analysis focuses not only on individual nodes but also on the topology of the network and its subsystems (clusters). Previous research has shown that the global economist network is an emerging small world (low average path length compared to size of network) with a clear hierarchical structure where individual ‘star’ economists have great influence (Goyal et al., 2004). Marion Fourcade, Etienne Ollion, and Yann Algan (2014) come to similar conclusion about the hierarchical order of the economic profession. Analyzing the German and American network of economists separately can give us some insights in different diffusion patterns of economic ideas in both cases and thereby help to analyse hypothesis 2: The social network of

economists in the United States is more interconnected and thereby supports idea diffusion better than the Economic network in Germany. Here we analyse this via comparing individual

factors and the overall topology (star formations vs. fully connected networks) of both networks. Comparing average path length, average degree, clustering, modularity and density of both networks should give us some insights about the coupling parameter in each network, because the easier interaction is, the more likely two nodes will connect (Jackson, 2010). Similarly, Goyal, van der Leij, and Moraga-Gonzáles (2004) argue that the overall increase in co-authorship could be explainable by new communication methods facilitating cooperation. It would be interesting to see if there are differences between countries. Moreover their study is so far the only one which did a social network analysis for the economic profession as a

7

The Walter Eucken Institute is named after economist Walter Eucken the father of ordoliberalism and the Kronberger Kreis acts as the academic advisory body of the liberal Stiftung Marktwirtschaft (Market Economy Foundation).

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whole.8 With our more limited analysis focusing on two separate national cases we can also re-examine their conclusion of economics being an emerging small world spanned by a

hierarchy of inter-connected stars.

In order to analyse the validity of hypothesis 3.1, the higher an agent measures in centrality,

the more influential he is in diffusing ideas, we need to measure centrality. The centrality of a

node can be measured in four different ways. First, degree centrality measures the amount of edges (links) a node has with other nodes. The second measure elaborates on this by including also the influence of a node’s neighbours (degree of adjacent nodes). This measure sometimes called ‘Prestige’ is the eigenvector. Third, we look at betweenness centrality, which quantifies the importance of a node as an intermediary, a bridge between different subsystems in the network. Finally, there is closeness centrality which measures the ability of a node to reach other nodes, meaning how far in terms of path length the node is in relation to all other nodes. Centrality is a very important measure in every network since it directly influences diffusion. ‘Infected’ nodes with a high centrality measure are likely to spread their ideas quite quickly trough the network, while nodes with less centrality are less able to diffuse ideas (Jackson, 2010; Wasserman & Faust, 1994). We combine our four centrality measures in an overall centrality rank by taking the mean rank of each node’s rank in the four scales and after that by sorting via overall article download numbers to avoid identical ranks. The result is the Centrality Rank (CR). The top 100 of both networks according to CR can be found in Annex A and B. While analysing the economic debate of the Great Recession we use this to explain why some economists were more and others less influential. Moreover, in answering

hypothesis 3.2, we look at the impact of academic consensus and dissension on the debate and

on politics. We argue that an apparent consensus on stimulus favoured the Keynesian resurgence which however was ended by the dissolution of this consensus and the arrival of a new consensus on the need of debt reduction switching policies towards fiscal consolidation.

3.3. Operationalisation

The two cases are our level of analysis, while the advisory bodies, individual economists, governments and economic policies and ideas are units of observations within each case. In order to explore the diffusion of economic policies, the study analyses the discourse by looking into policies and official stances of each government and its respective advisory body. The government’s position on the crisis is drawn from public statements made by politicians

8_{Recently, Oddný Helgadóttir (2015) published a network study limited to the network of economists}

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in governmental positions and the government’s actual policies. These statements are drawn from interviews in newspapers, press releases by the government or one of its bodies and the governments’ actual policies in form of fiscal stimuli. Change in the position of advisers and in general economists can be deduced from official reports by advisers, academic works, open letters and statements in the media. The latter two are especially important since they are not part of the regular work of economists and advisers but include an ambition and agenda to shape the political process. This gives us insight into the ideological position of individual economists. Part of the research includes the differences in advisory systems. While interesting to research, these differences can cause also some problems. In fact the CEA is part of the United States administration, ergo less independent. It is therefore unlikely that the experts’ opinions will deviate from the government’s official stance. However, past research on the CEA has shown that this does not prevent any conflict (Eizenstat, 1992).

3.3.1. Dependent variables: Government policies, Economic ideas

In order to explore the diffusion of economic policies, the study looks at changes in policies of both governments and also the expressed stances towards economic ideas, since policies not always coincide with the government’s positions. Furthermore we look at the economic ideas diffused in the network of economists and especially among the economic advisers. The government’s positions on the crisis and its solutions are drawn from their actions and statements made by leading politicians in governmental positions. Change in the position of experts can be deduced from their official reports on the Economy. Moreover economists’ position on certain topics and on what side of the debate they can be placed on can be deduced from their statements in the media and their attempts to influence policy.

3.3.2. Independent variables: Independence, Network topology, Centrality, Consensus & Dissension

In order to explain changes in our dependent variables we decided to focus on four independent variables. Limiting ourselves to only two cases gives us the opportunity to look into more variables. In contrast, maximising cases would have meant focusing on one or only a few variables (Keman, 2011). This broader, more exploratory, approach is due to the mostly unmapped territory of network analysis in economic policy-making and the need to look at many different aspects of it. However, at the same time we are limited in the amount of the variables by the case study’s time frame and extensive data sets we need to collect for the

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networks. For the purpose of explaining variations in economic policies and ideas the study looks at four independent variables:

We start with the degree of independence of advisory bodies and their overall structure. Independence could explain variations between diverging and conforming opinions and can be as well the cause of conflict between experts and governments. A more independent advisory body would be less able to influence its government, but it would make it easier to deviate from government opinion.

Second, overall network topology (average path length, average degree, modularity, clustering, and density) could explain differences in diffusion patterns. Comparing the overall network of economists in both cases could provide us with some answers and explain the different narratives about cause and solution to the crisis in both countries and how deeply embedded paradigms and uncertainty affect this diffusion.

Third, the interconnectedness of individual economists, their centrality, increases or decreases their influence in the overall network. As mentioned this is measured via the four centrality measures and the resulting overall Centrality Rank. Centrality can explain different diffusion patterns and varying influence between economists during the economic debate. This could furthermore show the importance of individual ‘star’ economists as blocker or accelerator in diffusing ideas.

Finally, the difference between consensus and dissension among experts could explain why some ideas get adopted by the broader political framework despite resentments. Dissenting voices enable policy-makers to hold on to their beliefs, and enable oppositional forces to attack the government’s policies. During the crisis, we did not experience a full paradigm change, but appearance of short-lived consensuses enabled politicians to enact different policies during each of its periods. As argued before, dissension generally weakens the influence of experts, but also broaden the diversity of solutions possible, however it also weakens the influence of ideas (Farrell & Quiggin, 2012) and may even lead to inaction and stagnation.

3.3.3. Alternative Explanations and Limitations

I am aware that scientific advice is only one of many factors influencing policy making. Other factors, like external pressure from other governments, were important in shaping policy

Economists and the Power of Ideas. A Social Network Analysis of Economic Advisers during the Great Recession