# Economists, Economic Knowledge, and Central Banks

Aurélien Goutsmedt, Francesco Sergi, Juan Acosta

► To cite this version:

Aurélien Goutsmedt, Francesco Sergi, Juan Acosta. Economists, Economic Knowledge, and Central Banks. 2025. hal-05083645

HAL Id: hal-05083645

https://hal.science/hal-05083645v1

Preprint submitted on 25 May 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Economists, Economic Knowledge, and
Central Banks

**Aurélien Goutsmedt**

UCLouvain, ISPOLE; ICHEC Brussels

[aurelien.goutsmedt@uclouvain.be](mailto:aurelien.goutsmedt@uclouvain.be)

**Francesco Sergi**

Université Paris Est Créteil, LIPHA

[francesco.sergi@u-pec.fr](mailto:francesco.sergi@u-pec.fr)

**Juan Acosta**

Universidad del Valle

[juancarlos.acosta@correounivalle.edu.co](mailto:juancarlos.acosta@correounivalle.edu.co)

## Abstract

What do economists do in central banks? Why do central banks hire economists? This book investigates the evolving role of economists and economic knowledge within central banks, arguing that their current centrality is neither self-evident nor historically inevitable. While the presence and influence of economists in central banks today may seem natural, this book shows that it is the result of a complex, gradual, and uneven historical process shaped by institutional structures, disciplinary transformations, and shifting relationships between science and policy. Drawing on a rich but dispersed body of literature, the book traces how economists progressively gained authority through the establishment of statistics departments, the adoption of macroeconometric models, and the emergence of a shared cognitive infrastructure between academia and central banks. Rather than focusing on individuals or doctrines, it examines general trends and institutional shifts across a series of national case studies to show how central banks function as boundary organizations, at the intersection of policy and science.
# 1. Introduction

What do economists do in central banks? Why do central banks hire economists? The answer today comes as obvious to those familiar with economics or central banking: central banks are the institutions conducting monetary policy, and economists are the professional figures mastering, by training, 'the science of monetary policy'—as phrased by three key figures of contemporary macroeconomics (Clarida, Galí, and Gertler 1999). Thus, nothing would seem more 'natural' than seeing a large number of economists working within central banks, at different levels (including the upper echelons), and to see economists exerting a significant influence over policy decisions, based on their expert knowledge of the issues at stake.

However, several questions remain open: How is this influence actually channelled throughout the pipeline of large and complex organisations such as central banks? What does the daily life of an economist look like within a central bank? And, most importantly, is this 'marriage' between central banks and economists really so 'obvious' and 'natural'? After all, even as late as 1958 the Bank of England's Governor Lord Cobbol famously argued that his institution was 'a bank, and not a study group' (Acosta et al. 2024, 5); and, about a decade later, Federal Reserve Chairman William McChesney Martin warned against 'statisticalitis' and considered he could dispense with his staff's forecasts (Acosta and Cherrier 2021, 344).

This book provides an overview of the evolution of the role and place of economists and economic knowledge within central banks, taking a history of economics perspective to highlight general trends across various national and institutional contexts. We document that, while economists working at central banks in the beginning of the twenty-first century had certainly become more numerous and had gained more influence over policy decisions than they had at the beginning of the twentieth century, this evolution resulted from a gradual and nonlinear process. The growing influence of economists and economic knowledge has had various setbacks and faced outright rejection and dismissal. Insofar as central banks have remained political organisations—characterised by strong hierarchical structures— the 'place' of economists within these hierarchies results from existing power relationships within central banks, as well as between central banks and other policymaking institutions.
The milestones along this long and bumpy road are the changes to the type of economic knowledge that economists developed within central banks, as well as their relationship with economists in academia—or their relationship to economics as a discipline. In the following sections, we show how economists and economic knowledge gained a foothold in central banks through the collection and analysis of economic statistics and the creation of economic studies departments, at the beginning of the twentieth century (2.); after consolidating this statistical tradition, economists in central banks adopted more complex forms of economic knowledge, notably macroeconometric models, in the 1960s and 1970s (3.). The use of macroeconometric models continues to this day; however, as we document, economists' activities remained somewhat marginal within central banks until around the 1990s. The decisive shift towards a more significant influence of economists within central banks came from the progressive building up of a common 'cognitive infrastructure' for understanding monetary policy, which was shared among academics and central bankers—both staff economists and policymakers (4.). Following this turn in the late 1990s, central bank economists began to exert significant influence not only over monetary policy, but also over economics as a discipline—especially throughout academic publications (5.). This historical perspective allows a broader understanding of the recent challenges to, and future prospects for, economists and economic knowledge within central banks (6.).

This book, although adopting a particular perspective (history of economics; cf. *infra*), relies on various strands of literature in the social sciences. Readers will thus find extensive (though not exhaustive) references to different literatures. Our purpose, however, is to propose a new, encompassing view, unifying the extant scholarship—otherwise dispersed across various disciplines within social sciences (political sciences, history, sociology, science studies, economics, etc.) and uses a variety of qualitative and quantitative approaches.

Social scientists have recently shown a keen interest in central banks, particularly regarding the role of economic knowledge produced by economists as a cornerstone of central banks' legitimacy and authority. This topic is actually related to a broader one: the relationships between economists/economics and policy (beyond central banks), and the different ways economists (and their ideas and tools) can shape policymaking. In their compelling 'Do Economists Make Policies? On the
Political Effects of Economics', Hirschman and Berman (2014) distinguished three main mechanisms through which economists and economic knowledge shape policymaking.<fnref n="1" /> First, the growing prestige of economics as a discipline, built along the twentieth century (*cf. infra*) confers 'professional authority' to individuals exhibiting 'economics' credentials (training, professional identity). Second, economists exert influence via their 'institutional position' within the policymaking process, which allows them to weigh in (to various extents) on decisions: economists chairing central banks constitutes one of the typical illustrations of this channel. Finally, and more indirectly, economists contribute to shaping the 'cognitive infrastructure' of policymakers, thus framing the way policymakers think about economic problems and constraining the set of possible answers to solve them.

Despite the acquaintance with these broader questions and its reliance on a broad spectrum of contributions from the social sciences, this book takes a *history of economics* perspective. Graduate students and researchers in economics will thus also find here useful materials to complement their perspectives on monetary policy and its operation. To be clear though, this is not an intellectual history of doctrines about monetary policies, and it is not an institutional history of central banks (how their mission and role at the interface between the State and the markets have evolved). Our approach follows a recent trend in the history of economics, that focus on the *practices* of economists (see Stapleford, 2017), that is, on the production of economic knowledge (such as theories), embedded in material artefacts (such as models), within specific intellectual communities (in or outside academia, like economists in central banks), and for specific purposes (such as producing expertise for policy).

This approach entails combining an understanding of the economic knowledge produced by economists with an understanding of the conditions under which such knowledge is produced. More specifically, it requires considering what an economist 'is' and 'how' he or she 'became' one—that is, it requires considering the sociology of the economics profession.<fnref n="2" /> In this respect, three major changes have unfolded since the post-war that constitute the main backdrop for the topic of this book. First, economics as *an academic field* has undergone substantial intellectual and methodological changes.

<footnote n="1">1 See Christensen (2021) for another survey of the literature on the influence of experts on policy decisions.</footnote>

<footnote n="2">2 On the sociology of professions, see Abbott (1988). On economics and professionalisation, see e.g. Coats (1993), Fourcade (2009), Christensen (2017), and Tribe (2022).</footnote>
Intellectually, or in terms of economic *theory*, a variety of approaches and national traditions were progressively marginalised within the profession, by a “mainstream” of economists sharing core theoretical principles—often labelled as a “neoclassical economics”.<fnref n="3" /> In terms of methodology, post-war economics has increasingly relied on mathematical models and statistical techniques.<fnref n="4" /> Both these intellectual and methodological changes entailed a transformation in the *training* and *intellectual framework* that define an ‘economist’, and, thus, a transformation in the type of economists working in central banks as well—so much so that ‘economists’ working in central banks in the 1930s beared little resemblance to ‘economists’ working in central banks in the 1990s. Second, economics firmly established itself as a major *field of expertise* within society—the very same job title of ‘economist’ became commonplace in all sorts of public administrations, international organisations, and private businesses —and, thus, in central banks as well.<fnref n="5" /> Finally, economics, both as an academic field and as a field of expertise, including at central banks, has *internationalised*. This process of convergence has been mostly (although not exclusively) driven by *Americanisation*, as North American economics has played a major role in shaping the scientific and professional standards for economists around the world.<fnref n="6" />

Internationalisation is a relatively recent process and, thus, national traditions played, for a long time, a more defining role in the intellectual and professional identity of economists.<fnref n="7" /> Thus, despite economics developed in the United States came to define, today, ‘what is an economist’ worldwide, each national tradition has resisted and adapted differently to this Americanisation of economics. Addressing the role of economists in central banks *in general* is therefore not an easy task, since the identity of economists and of economics is always imbued, to some extent, with national specificities. As a result of this difficulty (and others), the story told in this book, like the extant literature on the subject, relies on case

<footnote n="3">3 On this transformation, see notably Morgan and Rutherford (1998).</footnote>

<footnote n="4">4 On these aspects, see e.g. Weintraub (2002) and Morgan (2003; 2012).</footnote>

<footnote n="5">5 The rise of economic expertise has been addressed for different periods, countries, and institutional contexts. See e.g., Schmelzer (2016), Chwieroth (2010), Christian et al. (2018), and Berman (2022).</footnote>

<footnote n="6">6 See e.g., Coats (1997), Fourcade (2006), and Goutsmedt et al. (2021).</footnote>

<footnote n="7">7 Nonetheless, it is worth pointing out that different episodes of internationalisation regarding economic expertise in central banks were observable well before the 1970s (cf. 2.3).</footnote>
studies of specific central banks and episodes.<fnref n="8" /> Moreover, most of these case studies focus on Western central banks, with an overwhelming majority addressing the case of the Federal Reserve, the Bank of England, and, for the most recent period, the European Central Bank. Thus, the story told in the following pages should be considered with this qualification: it is a story built on the current knowledge on the topic, which is mostly based on a limited set of national case studies. This also entails focusing on specific time periods that are relevant for these case studies. As we emphasise in the concluding section, extending the analysis to more diverse national cases and conducting comparative work is precisely one of the important avenues for further research.

Despite its reliance on case studies, this book is not concerned with exceptions, anecdotes, and individuals. *Single* economists, inside or outside central banks, play no significant role in our story, which pertains to general trends and structural shifts: it is not about the hero, but the chorus.<fnref n="9" /> Following this perspective, we argue that the changing role and place of economists within central banks mirrors the trajectory of these institutions as ‘boundary organisations’, straddling the State and markets (Coombs and Thiemann 2022) but also policy and science (Goutsmedt and Sergi 2025). Understanding the evolution of central banks’ positioning at the first boundary allows us to better understand the main drivers of central banks institutional history (e.g., the evolution of their missions; cf. 1.1). Similarly, the second boundary (between science and policy) provides a clear framework, throughout the book, to understand the evolving role of economists and economic knowledge within central banks. Overall, central banks moved much closer to science throughout the twentieth century—more specifically, closer to academic economics; yet, since the very beginning of the twentieth century, central banks’ activities were already tangential to some scientific activities.

What does it mean, for a central bank, to be an organisation ‘at the boundary’ between policy and science? Following Hoppe et al. (2013) and Goutsmedt and Sergi (2025), we suggest that this entails

<footnote n="8">⁸ The other major difficulty is the distinctive institutional history of each central bank, which creates specific organisational arrangements and cultures, thus creating different contexts for economists.</footnote>

<footnote n="9">⁹ This perspective does not intend to deny the influential role that some particular individuals have played in this or that specific central bank, or in this or that circumstance. Our goal is to shift the attention from a few ‘great men’ towards the collective. The reader interested in portraits of particular individuals in central banking, including some economists, will find a rich set of autobiographies and biographies available: see e.g., Carli (1995), Axilrod (2009), Volcker and Gyohten (1992), and Dow (2013).</footnote>
three characteristics. First, it entails for central bank economists to engage in a ‘double participation’ to both ‘sides’ of the boundary—living a ‘double life’: for instance, maintaining collaborations with universities and attending research events, while at the same time participating in the routines of the policy work (preparing briefs, forecasts, scenarios, etc.) and taking part in monetary policy meetings. Second, a boundary organisation is subject to ‘double accountability’. For central banks, this means that their operations and decisions are, on the one hand, assessed against their results in controlling inflation or maintaining financial stability (that is, their policy mandate or mission). On the other hand, central banks may also have to face the judgment of academic economists, particularly on the scientific basis for their policy decisions (e.g., criticism about the type model they use to analyse the economy, or about their forecasting routines, etc.). Finally, boundary organisations usually produce ‘boundary objects’: i.e., ‘intermediate’ objects coproduced by actors that belong to the field of sciences and to the field of policy, and that allow for coordination between experts and policymakers. For central banks, macroeconometric models used in forecasting procedures are typical examples of such boundary objects.

From this perspective, economists have become more ‘central’ in central banks. First, at the macro level, it means that ‘double participation’ has progressively become commonplace: individuals with academic credentials in economics are now legion within central banks, often occupying positions at the highest hierarchical levels. Second, it reflects the growing importance of scientific ‘accountability’ over the past decades. When providing a rationale for their policy decisions, central bankers deliberately employ technical language that echoes economists’ framing of economic problems. Central banks also derive institutional prestige from their staff’s ability to publish in academic journals, thereby making the organisation more attractive to highly qualified economists. Moreover, the tools they use are increasingly subject to scrutiny by economists in academia and other institutions. Finally, economists’ centrality in central banks is also evident in the continuous development of new boundary objects—such as macroeconometric forecasting models, or stress-test models—which have become integral to central banks’ daily policy routines and decision-making processes.
## 2. Measuring the Economy: Statistics and Studies Departments

In April 1928, the rococo ‘Galerie Dorée’ (‘Golden Hall’) of the Banque de France hosted an unprecedented event: an international conference of ‘central bank statisticians’, gathering 24 representatives of European and North American central banks. The purpose of the discussion was to harmonise the way central banks gathered, analysed, and disseminated economic statistics. In the previous decades, statistics had become a crucial activity within all central banks participating in the conference: statistics illuminated ‘the economic life of the country’, as argued by the Finnish delegate, making it possible to ‘observ[e] economic phenomena as a whole without theoretical prejudice’, as noted by the Hungarian delegate (Yee 2023, 16).

Central banks involved in the 1928 Paris conference had already come a long way during the previous decades (for some of them) or centuries (for a few others): each one had experienced an idiosyncratic evolution of its mission and role, of its internal organisation, etc. An abundant scholarship has documented this institutional history of central banks.<fnref n="10" /> For the purpose of this book, we should retain only one major feature from this institutional history: central banks are organisations located at a moving boundary between the State and the market (commercial banks, financial actors, and the more general public of non-financial firms and households); henceforth, one can understand their institutional history as the evolution of their positioning at this boundary. These movements have been shaped both by economic conditions and by policy debates. In the latter, economic knowledge (e.g., early monetary theories) produced, in general, outside central banks, played an important role, although not always a decisive one (2.1). In turn, this evolving position drove the type of economic knowledge produced inside central banks. In this section, we highlight the production of ‘economic statistics’ (i.e., the definition, collection, and statistical treatment of data about ‘the economy’) and ‘economic studies’ (i.e., the analysis of such data) as the earliest forms of such knowledge incorporated and developed

<footnote n="10">10 This literature is quite large and includes contributions by economists (including central bankers themselves), economic historians, historians, and political scientists. For institutional histories of some national central banks see e.g., Goodhart (2018), Hetzel (2023), Conti-Brown (2016), Meltzer (2003, 2010a, 2010b), Toniolo (2022), Lie et al. (2020), Rougier and Sember (2018). For a comparative perspective and a compact presentation of the histories of various central banks, see e.g., Edvinsson et al. (2018), Ugolini (2017), Singleton (2011), and Siklos (2006). Also, central banks are notorious for sponsoring and editing in-house histories: see e.g., Watts & Rymes (2014), Reis (1996), Kynaston (2017), Uribe (2017).</footnote>
within central banks. This encompassed, notably, statistics and studies about the banking sector, about monetary and economic exchanges with the rest of the world (the 'balance of payments'), and, later, about 'the economy' more broadly understood (output, price level, etc.). To produce economic statistics and economic studies, new administrative entities ('Statistical Departments', 'Economic Sections', 'Research Divisions', and the like) were progressively created by central banks across the world between the end of the nineteenth century and the postwar period (2.2). This general movement towards producing economic statistics and studies was evidently shaped by idiosyncratic patterns, related to the specificity of each national central bank's position at the boundary between the State and markets. However, as the 1928 Paris conference of 'central bank statisticians' shows, various forms of cooperation across national central banks drove a significant convergence in the scope, methodology, and use of economic statistics and studies (2.3).

## 2.1 A Special Type of Bank

The term 'central bank' only began to be used during the late nineteenth century, to refer to commercial banks that had been granted some special privileges by the government (such as complete or partial monopoly of issue, holding government's deposits, etc.). The oldest 'central banks'—previously referred to as 'banks of issue'—date back to the seventeenth and eighteenth centuries: the Sveriges Riksbank (established in 1688), the Bank of England (1694), the Banco de España (1728). They were thus commercial banks that had been moved towards the boundary with the State—often, following financial crises or other exceptional and pressing economic circumstances. The nationalisation of central banks, all along the twentieth century marked a further displacement of these boundary organisations towards the State. Especially after World War II, central banks, now acting as public administrations, progressively embraced new missions, similar to those familiar to us today, especially, monetary policy and supervision of commercial banks and other financial actors.<fnref n="11" />

In addition to these specific economic circumstances, public debate also played an important role in the transformation of central banking during the nineteenth and twentieth century. Notably, it played a

<footnote n="11">11 Some central banks had already embraced their 'public' role even before their actual nationalisation (Singleton 2011, chap. 3). On the missions of central banks, see e.g., Blinder (2004) and Bordo and Siklos (2018).</footnote>
crucial role in shaping the general opinion about what a central bank should and could do, and the specifics about how to do it. The public scrutiny and discussion of central banks took various forms—including pamphleteering, debates in the press, congressional and parliamentary hearings—and the politicisation of their mission and organization only increased as central banks’ special position—their boundary status—became more apparent to the public, the governments, and to central bankers themselves.<fnref n="12" /> Economic arguments often played a role in these debates, but matters pertaining to central banking were definitely not perceived as being the exclusive domain of economic expertise alone.<fnref n="13" /> Economic knowledge thus had only limited influence in the debates about the status, missions, and organization of central banks up to the mid-twentieth century. However, these debates did have a substantial effect in progressively establishing economics as a field of expertise and in shaping economic literature—most notably monetary theories.

The history of monetary theories has been addressed by an abundant scholarship. It covers extensively the evolution of economic ideas about the nature of money, the functioning of the monetary and financial system, the role of commercial banks and financial markets, and the relation between money and ‘real’ activity (output, employment, etc.)—all of which, in turn, have fuelled a wide set of conceptions about the role of central banks, both in positive (descriptive or analytical) and normative (pushing projects for reform) terms.<fnref n="14" /> For the purpose of this book, two features highlighted by this literature are essential. First, debates about the Bank of England during the nineteenth century had an overarching influence over economic monetary thinking, far beyond England, and extending into the twentieth century (see e.g., Sayers 1957).<fnref n="15" /> The centrality of these debates can be explained, on the one

<footnote n="12">12 This process is perhaps best illustrated by one of the most famous images in the history of central banking: the cartoon ‘The Old Lady of Threadneedle Street’ (1797), which presented the Prime Minister wooing an old lady representing the Bank of England. For the context of this episode, see Kynaston (2017, chapter 4). On the political debates about the creation of a central bank in the US, see e.g. Singleton (2011, chapter 4), Mehrling (2010), and Lowenstein (2015).</footnote>

<footnote n="13">13 See, for instance, the participation and impact of political economists like David Ricardo and Henry Thornton in the ‘bullionist controversy’ of the early nineteenth century about the convertibility of paper money. See e.g., Kynaston (2017, 89–98), Laidler (1989), Arnon (2011).</footnote>

<footnote n="14">14 On different ‘traditions’ in monetary thinking, see e.g. O’Brien (2007), Mehrling (2010), Laidler (2010), and Dimand (2010).</footnote>

<footnote n="15">15 This influence is particularly relevant with respect to three major topics: the issue of convertibility (guaranteeing the convertibility of Bank of England’s notes into gold at a fix rate) and its effect on prices; the actions needed to manage gold inflows and outflows; and the role of the Bank as the ‘lender of last resort’, which refers to offering loans to commercial banks</footnote>
hand, by the key position of the Bank of England in the international monetary system of the ‘gold standard’.<fnref n="16" /> On the other hand, the influence of these debates echoes the intellectual preeminence of British writers in the development of economics.<fnref n="17" /> The second important element outlined by the history of monetary theories is the growing influence, starting from the 1920s, of different North American traditions whose positions were shaped by the debates about the establishment of the Federal Reserve in 1913—and by the previous, unsuccessful attempts of establishing a ‘central bank’ in the United States.<fnref n="18" /> The growing influence of US-based economists in post-war academic economics worldwide—the process of Americanization of economics (cf. 1.)—overlapped with the key role that the Fed played in the international monetary system after Bretton Woods (the ‘dollar-gold standard’).<fnref n="19" />

## 2.2 Statistics, Studies, and Economists in Central Banks

Central banks were not passive observers in these debates. Central bankers would regularly participate in public hearings or debates in the press, offering their views—defending or explaining the bank's actions. However, their credentials were those of experienced practitioners in the field of finance and banking; and not, in any case, based on their expertise in monetary theory. Yet, towards the end of the nineteenth century, new practices had begun to be adopted, turning central banks into producers of economic knowledge and laying the ground for economic expertise to develop in the following decades: the production of economic statistics and economic studies. These activities are to be understood broadly, especially insofar as different central banks relied on different methodologies and techniques for the definition, collection, storage, statistical treatment, and analysis of their data about ‘the economy’.<fnref n="20" />

<footnote>in times of financial crisis to maintain the stability of the whole banking system. Bagehot (1873)'s rule is perhaps the most well known contribution to this third issue: see e.g., Mehrling (2010) and Leloup and Trautwein (2024).</footnote>

<footnote n="16">16 On the history of the gold standard see e.g. Eichengreen (1992) and Bordo and Schwartz (2009).</footnote>

<footnote n="17">17 British economics (or, rather, ‘political economy’) built a distinct disciplinary identity and institutions sooner than in other countries (see e.g., Tribe 2022).</footnote>

<footnote n="18">18 On American monetary thinking, see notably Mehrling (1997).</footnote>

<footnote n="19">19 On the history of Bretton Woods international monetary system, see e.g., Abdelal (2009), Gindin and Panitch (2012), and Daunton (2023).</footnote>

<footnote n="20">20 On the emergence of the notion of ‘the economy’, that is, an understanding of how different economic actors and sectors are interconnected by the flow of goods and money, see notably Mitchell (1998), Schabas (2009), Hirschman (2015), and Angeletti (2023).</footnote>
They constituted a novelty for central banks for sure, but, more generally, also for society and for economics as a field. The literature on the social history of quantification has notably analysed this trend as the growing tendency of ‘governing by numbers’: this highlights the role played by statistics in managing the economic and social world, while, at the same time, they conventionally define and reshape the image of the world (via the categories, classifications, and concepts used).<sup>21</sup> In short, central banks were not the only institutions developing these activities: statistics were also on the rise in governments, statistical offices, international organisations, as well as think tanks, foundations, and other private actors.<sup>22</sup>

The earliest departments of economic statistics and studies within central banks identified in the literature correspond to the three major central banks in existence at the end of the nineteenth century: the Bank of England, the Banque de France, and the German Reichsbank.<sup>23</sup> In France, recognition that the Banque de France was lagging behind in data collection—particularly in comparison to the Bank of England—led to the creation of a dedicated unit, the ‘Service des Etudes Economiques’ in 1872 (Martín-Aceña and Tortella 2016). In Germany, Reichsbank president Richard Koch initiated the establishment of a statistical department in 1895. It should produce analysis ‘from a scientific point of view’, and provide the Reichsbank with arguments in favour of Germany’s participation in the gold standard (Yee 2023, 5). The Bank of England did not establish an ‘Economic Section’ until 1921, although the collection of statistics was already a well-established routine by then (Acosta et al. 2024, 5). It should not come as a surprise that many banks had no such departments in the late nineteenth and early twentieth centuries, as their core missions were largely limited to issuing currency and financing public debt. However, the economic and financial consequences of World War I—inter-allied debts, German reparations, and efforts to return to the gold standard—significantly increased the demand for

<footnote n="21"><sup>21</sup> See Porter (1996), Desrosières (2011) and Stapleford (2009). See Mennicken and Espeland (2019) for a recent survey of the literature on quantification.</footnote>

<footnote n="22"><sup>22</sup> On these three last actors, see notably Fritsche et al. (2020).</footnote>

<footnote n="23"><sup>23</sup> In Italy, soon after the creation of the central bank in 1894, the first governor Giuseppe Marchiori created the ‘Ufficio Gabinetto del Direttore Generale’ to collect economic information and translate relevant foreign economics papers (Martín-Aceña and Tortella 2016, 144). However, a proper statistical unit, the ‘Servizio Studi Economici e Statistica’, was only created in 1926, after the Banca d’Italia was granted a monopoly on currency issuance, as well as the supervision of commercial banks (ibid. 141). See also Scatamacchia (2003).</footnote>
enhanced statistical capacity within central banks (Feiertag 2005b). As summarised in Table 1, more and more central banks started their own economic studies or statistical service in the 1920s.

Building statistical and analytical expertise became a means for central banks to justify and legitimise their policies during this politically sensitive era. By the early twentieth century—and even more after the war—many central banks had come to recognise their role as both the backbone of the national financial system and as guardians of monetary stability. In doing so, they increasingly adopted a public service ethos (Feiertag 2005a, 19; Singleton 2011, 35). Owning these statistics was also essential: it allowed central banks to reduce their dependence on external data providers and to move away from a mere reliance on surveys and consultations with commercial banks and other financial actors. As a 1928 report from the Banque Nationale de Belgique's 'Service des Etudes Economiques' stated, as long as the 'best way to audit an economic nation' remained 'direct contact with trade and industry', the resulting information would continue to be 'so vague,' and 'so questionable, due to errors and fraud' (Yee 2023, 7). Finally, as the need for expertise grew, a self-reinforcing dynamic emerged: projecting the image of a technically competent central bank—through the regular publication of statistics and analytical reports —became a strategy for attracting highly qualified personnel.

<table><caption>**Table 1. First research departments of major central banks**</caption><thead><tr><td>Year</td><td>First statistics/research departments</td><td>Central bank</td></tr></thead><tbody><tr><td>1880</td><td>Political economy studies section</td><td>Bank of France</td></tr><tr><td>1895</td><td>Statistical service</td><td>Reichsbank</td></tr><tr><td>1914</td><td>Office of economic and financial studies</td><td>Bank of Italy</td></tr><tr><td>1918</td><td>Division of analysis and research</td><td>Board of Governors of the Federal Reserve</td></tr><tr><td>1921</td><td>Economic section</td><td>Bank of England</td></tr><tr><td>1921</td><td>Economic study service</td><td>National Bank of Belgium</td></tr><tr><td>1928</td><td>Economic research section</td><td>Bank of Greece</td></tr><tr><td>1930</td><td>Archive, statistics, and economics studies unit</td><td>Bank of Portugal</td></tr></tbody></table>
<table><tr><td>1930</td><td>Estudy service</td><td>Bank of Spain</td></tr></table>

Sources: Acosta et al. (2024), Yohe (1990), Maes (2010), Dutilleul (2025), Martin-Aceña and Tortella (2016), Scatamacchia (2003), Tuccimei (2005).

Although often bearing similar names and reflecting a shared shift toward technical expertise, these services could in fact differ significantly in their objectives and the types of data they collected. Moreover, their priorities evolved alongside broader economic contexts and the changing role of national central banks. The case of the Banque de France is illustrative: the ‘Service des Etudes Economiques’ was not the primary institution responsible for collecting financial data in France. Since the second half of the nineteenth century, that task had been carried out primarily by private banks, especially the ‘Service des Etudes Financières’ of Crédit Lyonnais (Dutilleul 2025, 8–9). Instead, the Banque de France developed an expertise in producing different categories of data. First, one initial mission of the newly established ‘Service des Etudes Economiques’ was to produce international comparisons, particularly through the collection of weekly balance sheets of other central banks (ibid. p.9).<fnref n="24" /> Second, the Banque de France focused on ‘political economy’ studies, gathering information on economic cycles and macroeconomic variables (ibid.).<fnref n="25" /> Third, with the emergence of national credit policy as a central function in the 1940s, new demands arose to closely monitor banks. This included collecting detailed information on ongoing loans and balance sheets—a shift that marked a departure from the practices of the late nineteenth century and coincided with the decline of Crédit Lyonnais’s role in statistical production (ibid., p. 12). Initially, these statistics and research departments were not staffed by ‘economists’, at least not in the sense we understand the profession today. At the turn of the twentieth century, economics itself was only beginning to consolidate as a distinct academic discipline—a process that unfolded unevenly across countries (Fourcade 2009; Tribe 2022). Consequently, the profiles sought by statistics and research divisions often combined academic training with practical experience in banking and financial markets;

<footnote n="24">24 This involved having a multilingual personnel as well as access to a large set of foreign financial newspapers and reports produced by other central banks.</footnote>

<footnote n="25">25 In many central banks the primary task of statistical departments was to collect and circulate information related to the banking sector and financial transactions; only a few pursued, like the Banque de France, a broader, more public-oriented mission by initiating the collection of national economic data. See Yee (2023, 17) about the case of the Hungarian central bank in the 1920s and the collection of agricultural data.</footnote>
the latter would remain the most valued type of experience in central banks for several decades. As a former chief economist of the Bank of England noted in the 1960s, because ‘the City [and financial markets in general] feels rather than thinks’, central banks occupy a space ‘between Reason and Emotion’ (Dow 2013, 35). Early academically trained economists entering central banks in the first half of the twentieth century thus found themselves in institutions where their expertise had narrowly defined applications.

The individuals involved in establishing the first economic studies departments illustrate these diverse professional trajectories. Albert-Edouard Janssen and Paul van Zeeland, for instance, were both instrumental in the creation, in 1921, of a ‘Service des études économiques’ at the Banque Nationale de Belgique. In Belgium, like in most countries in continental Europe at the time, economics was a subject taught in Law faculties at universities. Janssen graduated in political science and diplomacy in 1909 and later completed a PhD on international monetary relations that integrated both legal and economic perspectives (Maes and Buyst 2005, 118). He subsequently taught courses on money and credit at the University of Leuven, while simultaneously beginning his career at the Banque Nationale de Belgique in 1908. Van Zeeland was one of his students, and in 1920 he obtained a graduate fellowship to study at Princeton, where he attended Edwin Walter Kemmener’s lectures on monetary economics (Gomez Betancourt and Maes 2021). While in the US, he obtained an internship in the newly established Statistics Department of the New York Fed, before being permanently appointed at the Banque Nationale de Belgique in 1922. Their trajectories reflect a broader pattern: law-trained professionals who specialised in economics, at a time when the discipline’s boundaries were not yet firmly defined, and who developed a form of expertise that would become increasingly valued by central banks.<fnref n="26" />

Furthermore, central banks were not always fully supportive of recruiting economists—particularly those with overly theoretical backgrounds. In 1976, the Bank of England characterised its past position towards research activities as ‘positively averse to economics’ (Bank of England 1976, 436). Practical knowledge related to central banking activities—especially in the banking sector—was often more highly valued in hiring decisions. A 1925 memorandum from the Bank of England regarding the hiring

<footnote n="26">26 For similar examples regarding the Banque de France's research department in its first years and its connection with the Statistical Society of Paris, see Dutilleul (2025) and Plessis (2005).</footnote>
of an economist stated that the candidate ‘must have a gift of applying economics to practical affairs . . . but if he had also followed [Mr. Keynes] in his progressive decline and fall . . . he would be worse than useless’ (ibid.).<fnref n="27" /> Applicants with a background in banking were thus sought as much as, if not more than, those with academic training in economics. For instance, Karl Nordhoff worked at a Hamburg-based bank before being appointed by Hjalmar Schacht to head the Reichsbank’s research department in the 1920s (Yee 2023, 7). There, he applied his technical expertise to advance the compilation of data on German private banks. Until the 1960s it was not uncommon for staff hired at the Bank of England’s economics unit to hold degrees in philosophy or history, and then get any necessary training in economics in-house (Acosta et al. 2024, 11). By the 1990s, however, a degree in economics had become a *requirement* in job advertisements (ibid.), and the recruitment of staff with a PhD in economics increased consistently thereafter (cf. 5.1).

## 2.3 International Cooperation and Economic Statistics

In the 1920s, several central banks created their economic statistics or studies department, mirroring the activities of the Bank of England, the Banque de France, and the Reichsbank. This phenomenon corresponds to a general process (relevant to several other aspects covered in our book): ‘transplantation’, or the ‘art of moving ideas, policies, institutions, and practices from one environment to another’ (J. Johnson 2016, 28).<fnref n="28" /> Research departments, economic statistics, and economic studies are precisely the kind of institutions, ideas, and practices transplanted across central banks, especially starting from the interwar period. By the 1960s it had become inconceivable for any central bank in the world not to have a research department collecting economic statistics.

Let’s consider one early example of such transplantation. In the early 1930s, as the Spanish economy was plagued by a severe exchange rate crisis, the leadership of the Banco de España sought advice from the Banque de France, the Bank of England and the Bank of International Settlements (BIS). Among other

<footnote n="27">27 This scepticism toward economic theory is also clearly expressed in a 1929 lecture by Béla Imrédy, a director at the National Bank of Hungary: ‘While the statistical studies of Central Banks should have a basis in theoretical economics they must not be allowed to become doctrinaire and in the pursuit of theory to neglect the observation of economic phenomena which may perhaps appear of little importance from the theoretical point of view’ (Yee 2023, 14).</footnote>

<footnote n="28">28 See also McNamara (2002, 64) about the transplantation of central banks’ ‘independence’.</footnote>
actions, executives from these institutions 'recommended the creation of a Servicio de Estudios', to be
filled with expert staff, providing statistics and economic reports to answer pressing issues (Martín-
Aceña and Tortella 2016, 141, 146).

The transplantation of “studies” departments took place in a more general context of international cooperation across central banks (and, more generally, across government institutions) for building coordinated policies (James 2016). For the interwar period, such need for cooperation arose from the economic consequences of World War I (inter-allied debt, German reparations), the wish to return to the gold standard, and, later on, from the various attempts at curbing the effects of the 1929 crash and the ensuing Great Depression.<fnref n="29" /> After Bretton Woods, during the 1950s and 1960s, the dollar-gold standard also bound central banks to cooperate at various levels. The forms of cooperation established in both the interwar and the immediate postwar also went beyond the bilateral or multilateral initiatives driven by national central banks (such as the 1928 Paris conference mentioned above): two new international organisations were established, the BIS (1930) and the International Monetary Fund (1944), whose activities fostered significantly the international cooperation across central banks.<fnref n="30" />

Cooperation in the realm of policy and cooperation in the realm of research departments, economic statistics, and economic studies went hand-in-hand. Central banks' collection and circulation of economic statistics was seen as a way to promote a common understanding of the prevalent economic conditions and, thus, a convergence in the understanding and framing of coordinated or common policies. The 1928 Paris conference of central banks' statisticians addressed several aspects pertaining to the harmonisation of statistical methods, including, for instance, the proper aggregation of individual prices to calculate price indexes, as well as the need for choosing the same base year for facilitating cross-country comparisons (Yee 2023, 18–19).<fnref n="31" /> Other aspects of the standardisation of statistics were of a less technical nature, although not less controversial, such as the adoption of a common language (or two:

<footnote n="29">29 Of course, other forms of international cooperation across central banks had been in place before, such as the gold standard (cf. 2.2) and the Latin Monetary Union (Einaudi 2018).</footnote>

<footnote n="30">30 On the history of the BIS, see Toniolo (2005). On the history of the IMF, see e.g. Bordo and Schwartz (2001).</footnote>

<footnote n="31">31 This problem was notably raised by the representative of the Fed at the meeting. Indeed, the debate about ‘index numbers’ (such as price indexes) was a critical topic in the United States at that time (see e.g., Cruz-e-Silva and Almeida 2022; Dimand 1998).</footnote>
English and French) to be used by all central banks in their statistical reports and economic studies (ibid.). With respect to the mission of disseminating economic statistics and studies, central banks' research departments were also often closely associated with specialized libraries. Hosted within the central bank, libraries functioned as 'information systems', whose key role was to collect and store documentation and reports from other central banks, international statistics, and information published by economic and financial press.<fnref n="32" />

The standardisation of economic statistics was not an isolated endeavour of central banks, but a broader movement accompanying the rise of ‘quantification’. Already in the interwar period, the League of Nations promoted several initiatives to coordinate the production of statistics across countries, for various subjects (e.g., labour market statistics, produced under the responsibility of the International Labour Organisation). During this period, independent research institutes studying the business cycle (such as the National Bureau of Economic Research in the US, the Institute for Conjoncture in Moscow, and the Kiel Institute of the World Economy in Germany) cultivated a fruitful dialogue about their respective methods for collecting and analysing economic statistics.<fnref n="33" /> This movement towards a common international framework for economic statistics took an even more decisive turn in the after-war, as exemplified by the development of the system of ‘national accounts’ (a United Nations-driven initiative) and of the ‘balance of payments manual’ (published by the IMF).<fnref n="34" />

Finally, it is important to highlight that the ‘transplantation’ of studies departments was also driven by power dynamics and domination at a global scale. The construction of large empires over the nineteenth century went hand-in-hand with reshaping the monetary and financial systems of the colonised territories and the management of their economies.<fnref n="35" /> When the decolonisation process started in the

<footnote n="32">32 See Martin-Aceña and Tortella (2016, 141–42) about the Banco de España, and Maes (2010, 43–45) for the Bank of Belgium.</footnote>

<footnote n="33">33 See Cherrier et al. (Forthcoming).</footnote>

<footnote n="34">34 About the international harmonisation of national accounts, see notably Vanoli (2005, chap. 3). The *Balance of Payments Manual* was first published by the IMF in 1948: it built on previous work within the League of Nations for establishing a unified framework for measuring the economic interrelationships between a national economy and the rest of the world.</footnote>

<footnote n="35">35 On colonial monetary systems and the role of central banks, see e.g. Helleiner (2003), Gardner (2012), and Pallaver and Podestà (2021).</footnote>
postwar, the power relationships built in the previous century still permeated the relationships between Western central banks and newly established central banks in the Global South. This meant that the transplantation of central banking ideas, practices, and institutions—in the form of missions and ‘money doctors’—was not simply a matter of technical assistance and international cooperation between peers, but was also heavily permeated by political and economic interests.<fnref n="36" />

### 3. Macroeconometric Modelling

Terry Pratchett’s fantasy novel *Making Money* (2010) recounts the misfortunes of former outlaw Moist von Lipwig, taking the lead of the central bank of the fictitious city of Ankh-Morpork. Upon von Lipwig’s arrival, Mr. Bent, the Bank’s Chief Cashier, introduces him to a mad-scientist-like character, Mr. Hubert, frantically operating a mysterious machine made of glass tubes in a dark basement:

> “Mr Hubert believes that this... device is a sort of crystal ball for showing the future” said Bent, and rolled his eyes.

> “Possible futures” said Hubert [...] “The Glooper, as it is affectionately known, is what I call a quote analogy machine unquote. It solves problems not by considering them as a numerical exercise but by actually duplicating them in a form we can manipulate: in this case, the flow of money and its effects within our society become water flowing through a glass matrix [...] The geometrical shape of certain vessels, the operation of valves and, although I say so myself, ingenious tipping buckets and flow-rate propellers enable the Glooper to simulate quite complex transactions.” (Pratchett 2010, 83–84)

Pratchett’s novel captures, with some irony, the struggle for recognition of economists within central banks. Mr. Hubert’s ‘Glooper’ is inspired by an actual device, the ‘Phillips Machine’, an ‘hydraulic computer’ devised by Bill Phillips in 1949: a system of pipes and reservoirs, each representing a sector or an operation in the real economy (consumption, investment, saving, etc.), connected by a flow of water (representing money and income). As described by Pratchett, Phillips Machines could perform

<footnote n="36">36 See Flandreau (2003) and Álvarez et al. (2024) for discussions of the notion of a money doctor. See Gómez Betancourt (2022) for a discussion of the work of Ewdin Kemmerer, one of the most influential money doctors during our period of interest.</footnote>
simulations about the effects of various policies on the economy: increasing income taxes (that is, a wider opening of the ‘taxes valve’) will modify the amount of net income (the volume of water running down the pipes) and, therefore, the levels of consumption, saving, interest rates, etc.<fnref n="37" />

Pratchett’s story echoes 1950s economists’ dedication to producing and operating economic models hosted within central banks. Yet, despite some early investment in Phillips Machines by central banks (e.g. on the Reserve Bank of New Zealand; see Bollard 2016), hydraulic computers were of limited use and dissemination. Instead, the kind of models developed by economists in central banks during the 1960s and the 1970s were systems of mathematical equations, coded on electronic mainframe computers. The dominant form of modelling was, more precisely, ‘macroeconometric modelling’: this practice consisted in crafting large systems of equations—each representing an aspect of the economy (different sectors, economic agents, and their interrelationships)—and combining them with actual data, thanks to statistical techniques. In the end, like the tubes and valves of Phillips machines, macroeconometric models constituted systems that can be ‘manipulated’ by economists, to produce simulations and forecasts about the effects of various policies. ‘Macroeconometric’ modelling is still today a defining characteristic of the work of economists within contemporary central banks, although the theoretical depiction of the economy and the type of statistical techniques involved have changed (see 5.2).

This section starts with introducing to the reader the defining characteristics of the practice of macroeconometric modelling, as it originated in academia in the 1950s-1960s; we then highlight how macroeconometric modelling entered central banks in the 1970s and 1980s. From this moment, joint modelling ventures between universities and central banks were also established, making macroeconometric models ‘boundary objects’ (cf. 1.). Thus, macroeconomic modelling was instrumental in better connecting academic economics and central banks (3.1). However, central banks and central bank economists have entertained, during this period, a paradoxical relation to macroeconometric modelling. On the one hand, central banks and their economists have played a decisive role in developing this practice; and, in return, this practice was instrumental in further

<footnote n="37">37 For an example of an operating Phillips Machine: https://www.youtube.com/watch?v=rAZavOcEnLg.</footnote>
establishing the influence of economists and economic knowledge within central banks. On the other hand, such a process was slow and faced many obstacles and struggles: economists, and modellers, had to fight their way through several pushbacks by competing forms of expertise (3.2).

## 3.1 Macroeconometric Models: Born in Academia, Raised in Central Banks

The emergence of macroeconometric modelling is a phenomenon entangled with a broader transformation of post-war economics in academia: that is, an intellectual shift towards a new intellectual and methodological framework, gearing the profession, especially in the United States, towards a more intensive use of mathematical tools (e.g. Weintraub 2002).

This trend entails the emergence of neoclassical economics, and especially of general equilibrium theory, as the intellectual core of economics in the United States (see notably Morgan and Rutherford 1998). Efforts to reconcile the neoclassical framework with the intuitions laid down by John Maynard Keynes in his *General Theory* (1936) would therefore characterise much of the research conducted within a new research field labelled ‘macroeconomics’.<fnref n="38" /> One of the joint outcomes of this process is the ‘IS-LM model’, which is still familiar today to most undergraduate students in economics.<fnref n="39" /> IS-LM is itself representative of the important methodological trend of this era, when economics became ‘a science based on models’ (Morgan 2012).<fnref n="40" /> The widespread use of systems of mathematical equations as a methodology for economics is also related to the way economists started embedding these equations with economic data, following the ‘probability approach’ championed by the Cowles Commission (a US-based think tank) and outlined by a manifesto of his director Trygve Haavelmo (1944).<fnref n="41" />

With the perspective of proving the relevance of their methodology for macroeconomic analysis, Cowles Commission's economists tasked, in 1944, a young newcomer, Lawrence Klein, with building a

<footnote n="38">38 On the origins of macroeconomics, see Cherrier et al. (Forthcoming, chap. 2).</footnote>

<footnote n="39">39 On the origins and various versions of IS-LM see De Vroey & Hoover (2004).</footnote>

<footnote n="40">40 About the history and the epistemology of economic models, see Morgan and Morrison (1999), Mäki (2005), Reiss (2012), Brisset (2018), and Halsmayer (2024).</footnote>

<footnote n="41">41 On this early history of the Cowles Commission, see notably Hildreth (1986) and Dimand (2022). Besides the introduction of econometrics, the Cowles Commission fostered the renewal of general equilibrium theory, introducing new mathematical concepts and tools into economics (see e.g., Düppe and Weintraub 2014).</footnote>
macroeconometric model of the United States economy.<fnref n="42" /> Klein started with a previous model, devised by Jan Tinbergen for the League of Nations in the 1930s (see Dekker 2021, chap. 10); he then integrated the econometric methods championed by the Cowles Commission. Moreover, Klein took a theoretical perspective, largely akin to the endeavour of the IS-LM, i.e., to combine theoretical intuitions of Keynes' theory with neoclassical principles.

In the following years, Klein also travelled to Europe to discuss similar projects, notably in The Netherlands, Denmark, Sweden, Switzerland, France, and in the United Kingdom (Pinzón-Fuchs 2019, 412). Besides its initial influence on Klein's own work, this first series of travels set the bases for the future international network of modellers that Klein will develop, from the late 1960s, via its 'Project Link'—the project of building a world model, combining all national models together (Hickman 1991).

Klein continued his model-building activities at the University of Michigan (1949-1955). There, he scaled-up the size of his model, working with a larger team (Klein and Goldberger 1955). The novelty of this effort resided in progressively 'disaggregating' the economy in the model—that is, 'breaking down' economic sectors (agriculture, banking, etc.) and institutional sectors (households, firms, public sector) in more fine-grained and detailed representations of the United States economy. Although this ambition was not entirely fulfilled in the Michigan model, its 'disaggregation' approach became the distinctive characteristic of the practice of 'large-scale' macroeconometric modelling.<fnref n="43" /> The disaggregation approach entailed a division of labour within a team of modellers—making large-scale macroeconometric modelling a collective practice. This encompassed both 'disaggregation' as theoretical work (devising the key economic mechanisms driving the functioning of various sectors) and 'disaggregation' as an empirical enterprise (collecting the appropriate data). For both aspects, the corresponding workload had to be shared across different modellers, with different specialisations and skills; but also, most often, with different professional affiliations—for instance, from different public administrations, so that they could each access different sorts of data. Finally, another characteristic of Klein's Michigan model was the input of data and equations into an electronic mainframe computer, to

<footnote n="42">42 On Klein training and life, see Bjerkholt (2014) and Pinzón-Fuchs (2019).</footnote>

<footnote n="43">43 On this point, see e.g., Hoover (2012) and Renault (2022).</footnote>
obtain econometric estimations and dynamic simulations. This made macroeconometric modelling a
very expensive practice, given the cost of operating computing infrastructures in the 1960s-1980s.<fnref n="44" />

Despite the ambition of their creators that these models would provide useful expertise for
policymaking, they remained rooted in their academic hosting institutions, especially in the US. In
Europe, nonetheless, during the 1950s, various economic modelling practices were used to support
economic planning in a handful of countries (e.g., in the Netherlands, in Norway, in France, and in
Italy).<fnref n="45" /> Policymaking institutions, and eventually central banks, became involved with ‘large-scale’
macroeconometric modelling mainly in the 1960s. In the US, the first step towards the integration of
large-scale macroeconometric modelling to policymaking was the construction of the SSRC model
(1960-1963), sponsored by the Committee on Economic Stability of the Social Science Research
Council.<fnref n="46" /> Klein and James Duesenberry led this modelling team, comprising more than 20 researchers,
coming from academia, think tanks, and government agencies. The new level of disaggregation
envisioned for this model—more than 150 equations, an order of magnitude larger than anything built
during the previous decade in the United States or abroad—required the collaboration between
academic and non-academic economists: on the one hand, both existing theory and expert knowledge
was deemed relevant to guide equations’ specification; on the other hand, the volume and specificities of
the required data led to a close and constant communication with the government agencies that could
provide them. As a result, the SSRC model crucially increased the visibility of macroeconometric
modelling outside academia and spurred the development of macroeconometric models at government
agencies, most notably at the Federal Reserve Board of Governors.

The Board launched the building of a large-scale macroeconometric model in 1966, commissioning a
team led by Frank de Leeuw (Board of Governors, Division of Research and Statistics), Franco
Modigliani (MIT), and Albert Ando (University of Pennsylvania). The resulting model became known

<footnote n="44">44 That is, in the era preceding the generalisation of personal computers. On this, see notably Duarte and Sergi (2023).</footnote>

<footnote n="45">45 For The Netherlands, see e.g., van den Bogaard (1999) and Kayzel (2019). For Norway and Italy, see respectively, e.g., Halsmayer (2017), and Rancan and Sergi (2024, chap. 1); for France, see Courbis (1991) and Muniz Duarte (2023).</footnote>

<footnote n="46">46 See Duesenberry et al. (1960) and, on the history of this model, Acosta and Pinzón-Fuchs (2019).</footnote>
as the FMP/MPS model.<fnref n="47" /> De Leeuw and Ando had been part of the SSRC project. Building the FMP/MPS model took several years: this timing was rather fitting with the pace of the academic modellers involved, whose priority was to reach adequate specifications for equations, rooted in clear theoretical foundations. By contrast, the Fed Board economists were impatient about having a complete system that could be used for analysis as soon as possible, and thus consolidating the space for modelling within the Fed. Finally, a working model was delivered in 1970. In 1971, its maintenance (that is, ensuring its continuous re-estimation against new data, its theoretical development, the maintenance of the computer code, etc.) was entrusted to University of Pennsylvania's Wharton Business School—while economists at the Board continued to resort to the model for their works. The FMP/MPS model thus initiated the long-lasting tradition of the Federal Reserve Board (and, later, of its Reserve Banks) to promote the building of large-scale macroeconometric models.<fnref n="48" /> The development of the FMP/MPS model is thus illustrative of the way macroeconometric modelling, originating in North American academia, found its way towards the Fed, then constituting a 'boundary object'.

<table><caption>**Table 2. First macroeconometric models developed in central banks<fnref n="49" />**</caption><thead><tr><td>Year</td><td>Model</td><td>Central bank</td></tr></thead><tbody><tr><td>1969</td><td>RDX1</td><td>Bank of Canada</td></tr><tr><td>1970</td><td>FMP/MPS</td><td>Board of Governors of the Federal Reserve</td></tr><tr><td>1970</td><td>M1BI</td><td>Bank of Italy</td></tr></tbody></table>

<footnote n="47">47 The name reflects the changes in the organisations involved: the Federal Reserve Board, MIT, and the University of Pennsylvania during 1966-1970 (thus FMP), and MIT, the University of Pennsylvania, and the SSRC afterwards (thus MPS). Different aspects of the history of this model have been covered by historians of economics: see notably Backhouse and Cherrier (2019), Acosta and Rubin (2019), Rancan (2019; 2022). For an insiders' history of modelling at the Fed, see Brayton et al. (1997).</footnote>

<footnote n="48">48 After the FMP/MPS, the Board developed a multi-country model, then the FRB-US model (see e.g., Brayton et al. 1997). More recently, in the beginning of the 2000s, economists at the Board were also important contributors to the development of new types of models (cf. 5.2).</footnote>

<footnote n="49">49 Dates are approximative and refer to the published—or more or less definitive first versions—of these models that can be identified in the primary and secondary literature available. However, these models were oftentimes built and already used several years before any documentation was made published.</footnote>
<table><tr><td>1972</td><td>SIMPLET</td><td>Banque de France</td></tr><tr><td>1972</td><td>Bank of Finland Quarterly model</td><td>Bank of Finland</td></tr><tr><td>1972</td><td>Bank of Japan Macroeconometric model</td><td>Bank of Japan</td></tr><tr><td>1972</td><td>BoE model of the UK economy</td><td>Bank of England</td></tr><tr><td>1975</td><td>NA</td><td>Bank of Greece</td></tr><tr><td>1975</td><td>Econometric Model of the Deutsche Bundesbank</td><td>Deutsche Bundesbank</td></tr><tr><td>1985</td><td>MORKMON</td><td>De Nederlandsche Bank</td></tr></table>

Source: Acosta and Cherrier (2021), Bank of Finland (1972), Goutsmedt et al. (2024), Barten (1991), Courbis (1991), Rancan (2020), Sato (1991), Zonzilos (2004), Helliwell (2006), Wewel (1991).

Other central banks were early adopters of macroeconometric modelling in the 1960s-early 1970s (see Table 2). In some countries, modelling practices originated in academia, and were then adopted by central banks, in a joint development with academia. At the Bank of Canada, like at the Fed Board, academics were brought in part-time to build a macroeconometric model, delivered in 1969 under the name ‘RDX1’ (for ‘Research Department eXperimental [model] 1’). This was soon followed, in 1971, by RDX2, which, similarly to the FMP/MPS model, featured an extensive description of the financial sector (Duguay and Longworth 1998). Japan followed a similar pathway, with early models being developed in universities, but with the practice soon spreading not only to the Bank of Japan but also to several other policymaking institutions, notably the Economic Planning Agency (Sato 1991). In the United Kingdom, the first macroeconometric model of the British economy had been developed by Klein himself, during the years he had spent in Oxford (1954-1958; Klein 1980). From this early attempt, larger models ensued at various British universities, particularly at the London Business School, which started publishing forecasts from their model in the mid-1960s. The London Business School also played a key role in helping the Treasury with developing their own macroeconometric model, in the late 1960s, and, more broadly, in helping change the view on the usefulness of models in the United Kingdom (Ball and Holly 1991). The Bank of England followed this movement, by acquiring the London Business School model in 1972 and making it its own few years later (Goutsmedt et al. 2024). In Belgium, large-
scale macroeconometric modelling remained mostly an academic endeavour during the 1960s and the
1970s. In the 1970s, some of these university-based models were commissioned and sponsored by the
European Commission; Belgian policymaking institutions (the Planning Commission, then the Banque
Nationale de Belgique) only adopted these models in the 1980s (Evrard 2023; Rancan and Sergi 2024,
chap. 1). In The Netherlands and in Norway, central banks were also ‘late’ adopters of
macroeconometric modelling, embracing the practice mostly in the 1980s. In the Netherlands,
Tinbergen’s modelling work unfolded in the 1950s and the 1960s, almost immediately connecting
academia and the Central Planning Bureau; the Ministry of Finance soon followed this example, whilst
the De Nederlandsche Bank built its in-house model only in the mid-1980s (van Els 2003). Norway
accounts to a similar case: the Ministry of Finance had established, in cooperation with academia, a
tradition of developing and using macroeconometric models for supporting policymaking decisions
much earlier than the central bank (Bjerkholt 1998).

In the countries covered by the literature, there are a few cases in which macroeconometric modelling developed *first* in policymaking institutions (including central banks) and only *later* this practice disseminated to academia.

In France, universities were not a welcoming environment for the development of this practice until the late 1970s. Indeed, in French academia, the status of economics was still one of marginalisation, with no proper degrees or research programmes; moreover, mathematical and statistical economics was only adopted by a small minority within the profession, rather in engineering schools and public administrations (see e.g., Fourcade 2009). The development of macroeconometric models thus unfolded, in the 1960s and the 1970s, outside academic circles, mainly at the French Treasury and the National Institute of Economics and Statistics (see e.g., Courbis 1991). The Banque de France, despite some early ‘small scale’ attempts at macroeconometric models (such as the SIMPLET model in 1972), was not really investing in developing in-house large-scale macroeconometric modelling until 1979: then, with the help of the National Research Center (CNRS) and the University of Paris 10, the Banque de France developed the ‘GAMA’ model (Dutilleul 2025).
In Italy, like in France, academic economists were generally rather sceptical of econometrics and mathematical models. The first sizable macroeconometric model of the Italian economy was built by the Banca d'Italia: commissioned as early as 1964 by the Governor Guido Carli (a firm believer in the relevance of this new practice), the 'M1BI' was completed in 1970. The work of Banca d'Italia 'Servizio Studi' (Research Department) then spurred a dynamic of emulation across Italian academics, leading to the development of macroeconometric models at University of Bologna and at University of Ancona (Rancan and Sergi 2024, chap. 1).

In both the Italian and the French case, the FMP/MPS experience in the United States played a pivotal role for the introduction of large-scale macroeconometric modelling. In France, one of the main models of the 1970s-1980s (the 'METRIC' model), was developed under the supervision of George de Ménil—himself a former contributor to the FMP/MPS model in the United States (Goutsmedt, Renault, and Sergi 2021; Rancan and Sergi 2024, chap. 1). Modigliani, one of the main coordinators of the FMP/MPS model, came several times in Rome to consult on the ongoing work on M1B1. Although the resulting model did not follow exactly the blueprint of the FMP/MPS model, a fruitful dialogue was established (Rancan 2020).

These examples are illustrative of a general convergence of modelling experiences across central banks: as this modelling practice spread in various national contexts, international networks of specialists arose, creating spaces for discussing modelling practices (from theoretical specifications, to the choice of data, or coding standards).<fnref n="50" /> Modellers based in the United States often played a pivotal role in such networks. This mirrored a broader phenomenon, the internationalisation/Americanisation of academic economics, starting from the 1970s: that is, the establishment of international networks and cooperation to a much larger scale than before, bringing to the circulation of economists, economic ideas and theories, modelling practices, and the alignment of methodological and professional standards on those prevalent in the United States.<fnref n="51" />

<footnote n="50">50 As mentioned above, Klein's Project Link constituted probably the most extensive of such networks.</footnote>

<footnote n="51">51 On the specific role of large-scale macroeconometric modelling in this movement, see notably Bodkin et al. (1991) for a first-hand account and Goutsmedt et al. (2021) and Rancan and Sergi (2024, chap. 4) for a historical perspective.</footnote>
Despite this phenomenon, building up to a convergence towards international standards for macroeconometric modelling in central banks, we have also highlighted above the diversity of national cases. And yet, there is not, at the moment, any historical work covering extensively and comparing the various national experiences with macroeconometric models.<fnref n="52" />

## 3.2 Making Space for Macroeconometric Models

Since the early works of Klein, the core ambition of macroeconometric modellers is to provide both economic forecasts of the ongoing economic conditions and to quantify the possible economic effects of different policy decisions. But what has then been the role of such models within central banks, from the late 1960s to the end of the 1980s? What were the actual *uses* of these models within central banks?

Again, there is a variety of specificities, related to the individual national cases. We could say though that the literature points at one general dynamic: macroeconometric modelling constituted a vehicle to assert the relevance of economists' expertise within central banks; *however*, this expertise was challenged, and sometimes marginalised, by alternative forms of expertise and knowledge.

In the case of the Fed Board, the FMP/MPS model had to come to terms both with other approaches to economic analysis and with ‘traditionalist’ views of an older generation of policymakers, which valued practical experience of the business and banking world over economists’ expertise. As documented by Acosta and Cherrier (2021), the 1960s at the Fed Board coincided with a ‘rift’ between economists (especially those working within the Division of Research and Statistics; DRS), and the policymakers (including chairmen and members of the Federal Open Market Committee). William McChesney Martin (Chairman from 1951 to 1970), for instance, ‘led the group who felt that the Federal Reserve policy had to remain an art rather than a science’ and that the ability to read ‘the tone and feel’ of the markets was more crucial than economic statistics and models (Maisel in Acosta and Cherrier 2021, 333).<fnref n="53" /> At the same time, however, Martin also encouraged the DRS to develop more quantitative economic analysis, and he supported a hiring policy for younger economists trained in econometrics and macroeconometric modelling. Yet, within the DRS, the connection with institutionalist economics was

<footnote n="52">52 See Bodkin et al. (1991) or Morgan and Butter (2003) for attempts in this direction.</footnote>

<footnote n="53">53 Lawyers constituted a third group providing a competing expertise within the Fed (Conti-Brown 2016, chap. 3).</footnote>
rather strong (ibid., 337), and not yet fully in favor of developing large-scale macroeconometric modelling. In practice, economists' contribution to the policymaking process resided, in this era, mostly in providing 'projections' (the word 'forecast' was avoided) of relevant future variables. From June 1964, DRS projections were collected and circulated to the Federal Open Market Committee members in booklets with a green cover (hence their nickname, 'greenbooks'), soon accompanied by 'bluebooks' (also produced by the DRS), which outlined more precisely monetary policy parameters (interest rates, reserve measures, etc.) and the projected outcome of three policy scenarios (A, B, and C). Greenbooks and bluebooks initially relied, on the one hand, on data and statistics elaborated by the DRS (in line with the tradition outlined in Section 2); on the other hand, projections resulted from 'purely judgmental' reasoning, by DRS 'experts' in each market and sector (ibid., 343). From 1968, forecasts produced with the FMP/MPS model started being combined with such judgmental forecasts. This meant that, although knowledge produced with large-scale macroeconometric modelling had entered the policymaking process, it still was not the only, nor the dominant way of producing economic expertise and support policy decisions. Actually, large-scale macroeconometric modelling even experienced a clear set-back, as it failed to correctly predict the consequences of Johnson's tax surcharge implemented in 1968. This 'debacle' made chairman Martin willing to dismiss altogether economic analysis presented in bluebooks, as representative of 'statisticalitis ... a disease that could kill us all' (Martin quoted in Acosta and Cherrier 2021, 344). The following chairman, Arthur Burns, although he did not endorse this extreme scepticism, did have little faith in large-scale macroeconometric modelling as a useful technique. Large-scale macroeconometric modelling was largely sidelined in the following decades, at least when it came to the policymaking process (that is, the drafting and discussion of bluebooks), although this practice continued to serve as a platform for DRS economists to produce policy work within the division.<fnref n="54" />

Yet, during the 1960s and through the 1980s, challenges to the FMP/MPS model were also coming from outside the Fed Board. Attacks came even from within the Federal Reserve System: e.g., the Federal

<footnote n="54">54 As mentioned earlier, the practice of large-scale macroeconometric modelling did survive and actually prosper throughout the 1970s and even the 1980s, especially outside the United States, and not only as a policymaking-related practice but also as a flourishing private consulting business (see e.g., Pedro G. Duarte and Sergi 2023).</footnote>
Reserve Bank of St. Louis had developed an alternative modelling strategy, based on single-equation testing specific hypotheses, which aimed at challenging the FMP/MPS model, both on empirical grounds and on theoretical ones (Rancan 2019).<fnref n="55" /> Moreover, academic criticisms against large-scale macroeconomic models raged in the 1970s, particularly in the United States. Some of these criticisms aimed at contesting the relevance of specific theoretical mechanisms embedded within the FMP/MPS, such as the Phillips curve, or the term-structure of interest rates (Delcey and Sergi 2023). Other criticisms, such as the ‘Lucas critique’ (Lucas 1976), were more ‘systematic’, putting into question the overarching structure and methodology of such models.<fnref n="56" />

In other central banks, the upper echelons were sometimes supportive of large-scale macroeconometric modelling. Carli (Banca d'Italia governor from 1960 to 1975) is a case in point: unlike Martin at the Fed, Carli personally initiated the construction of a macroeconometric model, akin of the one in development at the Fed Board; it was also Carli who invited Modigliani in Rome to provide advice and guidance about the model. Yet, Carli's faith in this practice did not entail that he envisioned relying entirely on the model to conduct monetary policy. As documented by Rancan (2020), Carli made the model public, advertising it personally, in conferences before various audiences, sending out copies, and encouraging media coverage. This publicity was intended to leverage the model (and the associated activities of the whole Research Division) as ‘a tool to defend the Bank’s monetary action against policy pressures and criticisms, emphasising their scientific foundation. The model should have traced a boundary between the technical and political power’ (Rancan 2020, 28). Yet, the model remained rather a qualitative tool (providing ‘mental discipline’ and a ‘rational framework’ for thinking about monetary policy). This also limited the model’s actual use ‘for the official show of the Annual Report, and for domestic and foreign public relations use ... [but] when it came to policy, models were pushed aside ... and the telephone was used’ (De Cecco in Rancan 2020, 21).

<footnote n="55">55 This methodology was inspired by Milton Friedman's empirical methodology of 'naïve models'. See e.g., Chao (2019), Orozco Espinel (2022).</footnote>

<footnote n="56">56 On the ‘Lucas Critique’ and its impact on large-scale macroeconometric modelling, see e.g., Hoover (1994) and Goutsmedt et al. (2019).</footnote>
Similar tensions appeared in other central banks. Very often, central banks leveraged models in their conflicts with Treasuries—a tense relationship, in many countries, insofar as most central banks were not yet independent, i.e. they formally had to enforce and operationalise government monetary policy decisions. At the Bank of England, the adoption of a large-scale macroeconometric model was mainly conceived as a way to compete with the Treasury's model. The purpose was thus to produce an equivalent counter-expertise, that could be leveraged within policy meetings between the two institutions (Goutsmedt et al. 2024). Yet, the final say on monetary policy belonged to the Treasury, and the Bank of England was to operationalise its decisions: for this purpose, the large-scale macroeconometric model was of practically no use.<fnref n="57" /> Moreover, contrary to the Bank of Italy's use of the model in the public debate, the Bank of England was informally forbidden by the Treasury to publish alternative forecasts produced with its model. Thus, large-scale macroeconometric modelling at the Bank of England was largely kept behind curtains.

The arrival of Margaret Thatcher at 10 Downing Street in 1979 further altered the relationship between the government and the Treasury on the one side, and the Bank on the other. For the first time since inflation had soared in the late 1960s, the Bank was confronted with politicians who pushed for a new monetary policy doctrine (James 2020, 71).<fnref n="58" /> In the next section, we discuss how this debate played out on a conceptual level. In terms of methodology though, this debate highlights the relevance, in the Bank of England's case, of alternative forms of economic expertise to large-scale macroeconometric modelling. Indeed, economists at the Bank devised a series of smaller, narrower models, studying specifically monetary issues (Goutsmedt et al. 2024). Special advisor Charles Goodhart suggested that the Bank should fund the development and the estimation of a monetary model by James Davidson and David Hendry at the London School of Economics. For Peter Brierley, from the Bank's staff, this model would 'facilitate an evaluation of policy issues within a specifically monetarist framework' and the results could be 'compared with those produced by the Bank and Treasury large structural models, which basically

<footnote n="57">57 Additionally, the operationalisation of monetary policy went through the Markets division, which was thus more central in the Bank of England than the Economics division where the model was developed.</footnote>

<footnote n="58">58 In March 1980 the government launched the Medium Term Financial Strategy (MTFS). The strategy specified money supply targets for monetary policy. In doing so, they explicitly relied on key monetarist assumptions (Best 2020, 603–4) and on the idea that such ‘control of the money supply will over a period of years reduce the rate of inflation’ (James 2020, 70).</footnote>
reflected a more Keynesian approach.' It was, in the end, these works on small monetary models, rather
than large-scale modelling, that the Bank pushed forward in its debate with the Treasury and, also, in his
publications disseminated to external audiences.

By the end of the 1970s, economists had built thus some space for them and their economic expertise inside central banks. Although this started in the early twentieth century with the development of statistics and studies (cf. 2.), macroeconometric modelling emerging in the 1960s-1970s marked a further step: that is, a closer cooperation between central banks and academic economists in building 'boundary objects'. Despite some resistances and push-backs, both these practices (statistics and macroeconometric modelling) continued then to gain space inside central banks throughout the following decades. This was fuelled, in the 1980s and 1990s, by the convergence of central bankers and academic economists towards a common 'cognitive infrastructure' in thinking about monetary policy.

4. Rethinking Monetary Policy

In 2005, a conference organised by the British ‘Government Economic Service’ (Arestis 2007) addressed the question: ‘Is there a new consensus in monetary policy?’ Charles Bean—then chief economist at the Bank of England—responded affirmatively, noting:

[J]ust as there has been a degree of convergence in macroeconomic thought over the last decade
with the development of the New Keynesian synthesis, so there has also been convergence in
beliefs about the proper scope of monetary policy and the appropriate institutional framework
for the conduct of that policy (Bean 2007, 1).

Almost three decades had been necessary to achieve this 'convergence of beliefs' between central
bankers, economists within central banks, and academic economists. In this section, we characterise this
'convergence of belief' as the coproduction of a 'cognitive infrastructure', shared across these different
actors (4.1). The 'convergence' actually started with a growing gap and controversies (1970s-1980s), in
the wake of stagflation and of increased critical scrutiny of central banks' activities, exacerbated by the
monetarist episode (4.2). The convergence happening in the 1990s constituted thus the decisive decade for strengthening the role and place of economists within central banks (4.3).

## 4.1. The Coproduction of a Cognitive Infrastructure

In ‘Do Economists Make Policies?’, Hirschman and Berman (2014) distinguish three channels of economists’ influence on policy decisions: the ‘professional authority’ that academic credentials in economics confer to experts, the strategic positions taken by economists in policymaking institutions, and the ‘cognitive infrastructure’ (cf. 1.). The latter designates an economic ‘style of reasoning’ that determines which problems are important or relevant, and how to solve them, as well as a set of ‘policy devices’ that help to make policy decisions. A style of reasoning relies on a series of concepts: i.e. theories and technical notions that demarcate experts from laymen (e.g., in our case, rational expectations, credibility, time-consistency). Concepts contribute to an expert-framing of problems (for instance, ‘inflation is the result of agents’ expectations’), inducing specific policy solutions (‘inflation is controlled by managing agents’ expectations’). Policy devices are those ‘tools’ operationalizing a style of reasoning, that is, facilitating the transition from ‘thinking’ about a problem to actually ‘acting’ to solve it.<fnref n="59" /> Such ‘tools’ are of different nature: models (such as described in 3.) are one example; yet, as we will see in this section, this also includes statistical indicators or other measures (such as monetary aggregates, M1 or M3, or the output-gap), rules-of-thumb (e.g., the Taylor rule), and communication strategies (e.g., inflation targeting).

In the late 1990s, as Bean testified above, it had become apparent that central bankers, economists within central banks, and academic economists shared the same cognitive infrastructure. Previously, central bankers were often criticising how economists (outside or inside central banks) thought about economic problems and the way to address them, pushing back on economists’ style of reasoning as irrelevant and disconnected from the practical realities of policymaking (cf. 3.2).<fnref n="60" /> The new cognitive infrastructure of

<footnote n="59">59 On the ‘translation of economic ideas into an actionable policy framework embedded in policy devices’, see e.g., Thiemann (2024, 14).</footnote>

<footnote n="60">60 Such criticisms tend to resurface, including in recent times–e.g., Christine Lagarde’s comment on economists as a ‘tribal clique’ (https://www.weforum.org/podcasts/agenda-dialogues/episodes/davos-2024-town-hall-lagarde-how-to-trust-economics/; retrieved 30/05/2025).</footnote>
the 1990s was, however, neither the result of some linear process where central bankers embraced academic economic theories, nor an alignment of academic economists on central bankers' style of reasoning. Rather, this process represents a 'coproduction', wherein the boundary between science and policymaking became increasingly blurred (Hoppe 2005; Jasanoff 2010).

This coproduction is the outcome of the dialogue between academic economists and central banks, which was fostered by three factors.

First, central banks in Western countries found themselves under increased public scrutiny, as they endorsed a more crucial role in fighting stagflation.<fnref n="61" /> Academic economists became more involved with discussions and critiques of monetary policy; for instance, in the US, as in other countries, debates emerged regarding the Fed's decision to raise interest rates in response to the first oil shock in 1973-1974 (Goutsmedt 2021). As a result, academic economists increasingly represented a new and influential audience that central bankers had to engage with and consider seriously (see below, with the monetarist case).

Second, central banks personnel and academic economists had, increasingly, a similar educational background—to the extent that we observe a wider circulation of individuals from academic to central bank career paths, at all levels (including the upper echelons). More policymakers in central banks held academic qualifications such as PhDs in economics; similarly, central bank staff was increasingly hired in the ranks of economics PhDs.<fnref n="62" /> As a result of this transformation (cf. 5.), academic economists and central bank personnel increasingly ‘spoke the same language’, broadening the space for dialogue.

Third, central banks and academia collaboratively established new venues to facilitate ongoing exchanges: central banks created advisory panels to consult with academic economists on monetary policy, organised joint conferences that brought academic economists and central bankers together (e.g.,

<footnote n="61">61 As Singleton (2011, 203) puts it, ‘The Great Inflation and Disinflation restored central banks to a vital place in the economic policy community’. See also Wansleben (2022). On the economic history of the 1970s and the stagflation, see e.g. Blinder (2022) and Chélini and Warlouzet (2017).</footnote>

<footnote n="62">62 This process extends beyond central banks. As they became central institutions for economic policy in a new context of financialization after the 1970s (Krippner 2005; Wansleben 2022), banks and financial institutions also started to hire economists able to analyse (and forecast) monetary policy decisions (Hall 1992, 102–3).</footnote>
the Jackson Hole economic symposium),<fnref n="63" /> and launched visiting programs designed to attract prestigious academic economists.

## 4.2. The Influence of Monetarism: Mind the Gap

Historians and political scientists analysing the role of monetarists have argued about the preeminence of their ideas in reshaping the conduct of monetary policy in the 1970s and the early 1980s. According to this view, monetarism, an intellectual movement gaining prominence in North American academia in the 1960s, ‘provided a template and a legitimizing framework for a new economic strategy that prioritized neoliberal, anti-inflationary policies over employment or growth objectives’ (McNamara 1997, 5–6).<fnref n="64" /> More recent scholarship has documented that the ‘conversion’ of Western central banks to monetarism was far from straightforward (Best 2020; Clift 2019). In this section, we adopt this latter perspective; more generally, we argue that, during this period, academic economists and central bankers were still far from sharing a cognitive infrastructure. The dialogue between the two groups was rather marked by conflict, also mirroring the controversies within academia—ignited, during the 1970s and early 1980s, by reactions against monetarism. Monetarist ideas certainly influenced central bankers’ thinking in response to the pressures of stagflation; however, there was also significant resistance, rejection, and rapid abandonment of monetarist frameworks, particularly at the Fed and the Bank of England, where these ideas initially took roots.

Monetarism is not a monolithic approach, and important distinctions exist within it (Snowdon and Vane 2005, chap. 4). However, three fundamental principles can be highlighted. First, monetary policy plays a decisive role in determining fluctuations in output and inflation; managing the economy is thus better achieved through monetary policy than through fiscal policy (M. Friedman and Schwartz 1963; De Long 2000). Second, as Milton Friedman argued in his 1968 American Economic Association presidential address (M. Friedman 1968), neither monetary policy nor macroeconomic policy in general

<footnote n="63">63 See e.g., Zech (2024). This later fostered the emergence of proper communities of ‘Fedwatchers’ or ‘ECBwatchers’.</footnote>

<footnote n="64">64 See also Hall (1992) and Fourcade-Gourinchas and Babb (2002) for similar views on monetarism. On the origins of monetarism, see e.g., Tavlas (2023).</footnote>
can permanently reduce unemployment.<fnref n="65" /> There exists an equilibrium (or ‘natural’) rate of unemployment, which macroeconomic policy can affect in the short run, but which is determined by structural factors in the long run. In other words, monetary policy is neutral in the long run, i.e., it cannot permanently reduce unemployment below its equilibrium rate. Third, monetary policy should follow rules rather than be guided by discretionary reactions to specific events. Already in his *Program for Monetary Stability*, Friedman (1960) proposed a rule that would ensure stable growth of the money supply. This rule became a core tenet of monetarist in the 1970s, following Friedman (1968) and its sharp critique of discretionary monetary policy: Friedman argued that monetary authorities should avoid attempting to control a natural rate of interest or unemployment, as such interventions could lead to destabilising consequences (Forder 2018).

What was the influence of monetarism on central banks and monetary policy with respect to these three core principles?

With respect to the first principle, beginning in the 1970s, monetary policy did, indeed, take precedence over fiscal policy in many Western countries. While monetarist ideas likely contributed to this realignment, they were not the dominant factor shaping the shift in policy priorities. This shift was driven also by criticisms of the inherent link between fiscal policy and the electoral cycle (Buchanan and Wagner 1977; Nordhaus 1975), and by persistently high inflation rates, which placed immense political pressure, both from governments and the public opinion, on central banks to take action. Furthermore, the collapse of the Bretton Woods system and the accelerating financialization of the global economy transformed the ways in which macroeconomic policies impacted economic stability.<fnref n="66" /> In this changing landscape, monetary policy came to be regarded as a more effective tool for managing economic stability than fiscal measures.

Regarding the second principle—the long run neutrality of monetary policy and the concept of an
equilibrium rate of unemployment—monetarism’s influence has been slow and indirect. Indeed, this
sort of framing of monetary policy has been part of the central bankers’ cognitive infrastructure solely

<footnote n="65">65 Note that the primacy of Friedman in developing these ideas has been questioned (Forder 2014).</footnote>

<footnote n="66">66 On how financialization impacted the conduct of macroeconomic policies, see e.g. Hall (1993), Braun et al. (2021), and Wansleben (2022).</footnote>
since the 1990s (Arbogast, Van Doorslaer, and Vermeiren 2024). Although the ideas of an equilibrium
rate of unemployment and long-run neutrality of monetary policy were discussed among central bank
economists, it took time for these ideas to be fully integrated, for instance, in central banks'
macroeconometric models.<fnref n="67" /> But, in order to achieve this integration, the original concepts devised by
Friedman underwent a substantial transformation, as they were translated into different frameworks,
more compatible with other economic theories—particularly, Keynesian economics (Goutsmedt and
Rubin 2018) and new Classical economics (Hoover 1988). This is illustrated by the change in
vocabulary: the term ‘natural rate of unemployment’ became synonym with the term ‘NAIRU’ (‘non-
accelerating inflation rate of unemployment’), developed by Keynesian economists Modigliani and
Papademos (1975) and Tobin (1976).<fnref n="68" />

The third principle—monetary policy should follow rules—contributed more directly to the 1980s
debates surrounding the instruments of monetary policy, particularly in the United States and in the
United Kingdom. However, the influence monetarists gained over central banks’ thinking on this point
was largely due to their ability to reach out beyond scholarly circles, to politics. In the United States, this
influence first manifested through congressional pressure on the Fed. A peculiar alliance of populist
representatives and other members of Congress sympathetic to monetarist ideas pushed for the public
disclosure of monetary targets. This effort culminated in the passage of House Concurrent Resolution
133, which required Federal Reserve officials to report on their ‘objectives and plans with respect to the
ranges of growth or diminution of monetary and credit aggregates’ (Kettl 1986, 144–45).<fnref n="69" /> Friedman
described this resolution as ‘the most important [...] change in the structure for the formulation of
monetary policy’ since the 1935 Banking Act (ibid. 146).<fnref n="70" />

Nevertheless, the pivotal shift toward rule-based policy in the United States came with the so-called
‘Volcker shock’. After being appointed in August 1979 by President Carter, Paul Volcker, the new

<footnote n="67">67 See Rancan (2022) for the Fed and Goutsmedt et al. (2024) for the BoE.</footnote>

<footnote n="68">68 On the history of the use of these two concepts, see Backhouse et al. (2023).</footnote>

<footnote n="69">69 Similar targets had been adopted in Germany in 1974 and in France in 1976 (Kettl 1986, 144).</footnote>

<footnote n="70">70 U.S. Congress, Senate, Committee on Banking, Housing, and Urban Affairs, *Second Meeting on the Conduct of Monetary Policy*, hearings, 94th Cong., 1st sess., 1975, 34. Someone close to monetarists thinking about policy like Robert Lucas also saw an ‘encouraging example’ provided by Resolution 133 (Lucas 1980).</footnote>
Federal Reserve chairman, announced, in October 1979, that the Fed would adhere to a strict target for the growth of $M1. This decision was not a strict endorsement of monetarism, but rather a political move that demonstrated the Fed's commitment to combating inflation (Hetzel 2008, chap. 13; Krippner 2007).

In the United Kingdom, monetarism did not dominate academic circles either, but it gained influence through political channels as the Conservative Party, under Margaret Thatcher's leadership, gradually adopted its principles (Smith 1987). The Tories were particularly attracted to the 'discipline' offered by strict monetary targets for controlling the growth of the money supply (Hall 1993, 287). Although explicit monetary targets were initially introduced under the Labour government of James Callaghan in 1977, the Conservatives sought to implement more coercive targets when they came to power. In March 1980, the government established a strict target for the growth of £M3.<fnref n="71" /> However, officials within the Bank of England were hesitant to fully endorse this approach, as they viewed the relationship between inflation and £M3 as too unstable (Goutsmedt et al. 2024). In their opposition, they invoked 'Goodhart's Law', articulated by their special advisor on monetary policy, Charles Goodhart: 'any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes' (Goodhart 1983).

In other European countries in Western Europe, monetarist principles also experienced ups and downs. As hinted by James (2012, 95), the Committee of Governors<fnref n="72" /> was mostly reluctant to endorse any form of monetarism; however, some European countries were more inclined to experiment with these principles. Germany and the Bundesbank adopted an explicit monetary target as soon as 1974 (P. A. Johnson 1998). In France, by contrast, the push-back of the Banque de France against monetarist ideas was stark (Monnet 2015; 2018).<fnref n="73" />

<footnote n="71">71 The Bank, at the time, was not operationally independent from the government.</footnote>

<footnote n="72">72 Established in 1964, this meeting gathered all governors or presidents of the central banks of the European Economic Community. On the evolution of European monetary institutions, including different venues gathering European central bankers, see e.g., James (2012).</footnote>

<footnote n="73">73 About monetarism in Belgium and the Netherlands, see notably Harmsma (2024) and Jones (2005); in Italy, see Ventresca (2023). Japan also adopted a monetary target in 1978, although its actual monetarist nature is contested—see notably Ito (1989).</footnote>
Whenever monetarists appeared to win a victory with the adoption of strict monetary growth targets, this success was generally short-lived. As hinted earlier, the adoption of these targets in both the United States and in the United Kingdom did not reflect the establishment of a new paradigm or a consensus among economists and central bankers. Whether in academia or central banks, many economists continued to support discretionary policies. On the policy front, the early 1980s witnessed a ‘hollowing out’ of monetarism (Clift 2019). While monetary policies in the United Kingdom and in the United States achieved some ‘bloody successes’ (rapidly reducing inflation at the cost of significant unemployment increases), they also faced ‘quiet failures’ (Best 2020): the instability of the relationship between inflation and various monetary aggregates in the early 1980s undermined the credibility of monetary targeting (Clift 2019; Smith 1987, 150). In October 1982, the Federal Reserve abandoned M1 targeting, effectively ending this monetarist ‘experiment’ (Best 2022). In the United Kingdom, discretionary policy returned as early as June 1980 when interest rates were lowered despite £M3 exceeding its target (Clift 2019).

What was left of monetarism? Debates around monetarism had started to shape the common cognitive infrastructure of academic economists and central bankers, particularly by drawing attention to a set of new concepts (e.g., equilibrium rate of unemployment) and policy devices (e.g., policy rules and explicit quantifiable targets). Yet, this occurred through a complex and rather uneven process, marked by conflicts, push-backs, and turnarounds. Thus, monetarists had a limited direct influence in the emergence, in the 1990s, of the common cognitive infrastructure.

### 4.3. Closing the Gap between Macroeconomists and Central Bankers

What was the shared cognitive infrastructure that emerged in the 1990s? It involved first and foremost a new style of reasoning regarding the control of inflation. Inflation was now understood as arising from economic fluctuations, triggered by ‘shocks’, that pushed the economy out of its long-term trend of growth; this trend is characterised by a given level of ‘potential output’, an equilibrium rate of unemployment and an equilibrium interest rate. The role of monetary policy was to maintain inflation at a stable and moderate level, which is a necessary condition for the economy to run at its ‘potential’. In order to achieve this, monetary policy has notably to achieve a sustained capacity of influencing
expectations about the future formed by economic agents (households, firms). Indeed, in this way of reasoning about the economy, one pivotal idea is that economic agents make plans (about consumption, investment, savings, etc.) *today*, but *taking into account* what they *expect* will be the economic conditions *tomorrow* (academic economists would say that agents make ‘intertemporal plans’, based on ‘forward-looking’ expectations). It is thus imperative, to steer both the current and the future economic conditions, to ‘anchor’ inflation expectations at a low level. This was the most important novelty in the way central bankers think of the policy problem they are facing, and how to address it.<fnref n="74" />

This particular style of reasoning results in a set of policy devices that would enable central banks to develop the ability to anchor agents’ expectations. The organising principle to this is to establish the *credibility* of the central bank: that is, economic agents should believe in the central bank’s commitment to maintain inflation at a low level. On the one hand, building credibility relies on various policy devices that make what central banks *do* (their policy) credible for agents: this entails notably the operational independence of central banks, their reliance on a transparent communication about their decision-making, notably through inflation targeting (i.e. the commitment to attain a target inflation level, and to justify any deviations from this level). On the other hand, this credibility results from the *legitimacy* of the central bank, through the recognition by the public of its expertise in analysing economic conditions (*cf*. 5.).

Two actors have participated in the coproduction of this cognitive infrastructure: central bankers and academic economists. But not only just *any* academic economists: those participating most actively in this co-construction process were *macroeconomists* (that is, economists working within a *specific* subfield of economics), and they were following a *specific* theoretical and methodological approach, later labelled the ‘new neoclassical synthesis’ (or ‘new Keynesian synthesis’). In this respect, the history of the relation between central banks and economists in the 1990s is actually the history of the relation between central banks and macroeconomists of the ‘new neoclassical synthesis’. The emergence of this ‘special relation’

<footnote n="74">74 For further insights, details and critical perspectives about this style of reasoning, the reader could turn to the literature produced by economists and central bankers (see e.g. Issing et al. 2001; B. M. Friedman 2003; Blinder 2004), various textbooks tackling the subject (see e.g. Drazen 2002), and political economy articles (see e.g., Braun 2015; Walter and Wansleben 2019).</footnote>
resulted in a ‘macroeconomic’ cognitive infrastructure for monetary policy; it also entailed the marginalisation of economists from other subfields—for instance, those working on financial economics—and of those working within other theoretical or methodological frameworks.<fnref n="75" /> In order to understand better the stakes of this ‘coproduction’, one should thus turn, first, to the specificities of the new neoclassical synthesis approach to macroeconomics.<fnref n="76" />

In the 1990s, macroeconomists celebrated the avenement of the new neoclassical synthesis as the emergence of a new ‘scientific consensus’.<fnref n="77" /> The term ‘new neoclassical synthesis’ itself was popularised by Marvin Goodfriend and Robert King, two macroeconomists affiliated with the University of Virginia and the Federal Reserve Bank of Richmond. They first mention the label in an article, presented at a workshop at the Bank of England, and published in 1997. Goodfriend and King (1997, 231) contrasted the ‘common portray’ of macroeconomics as a field ‘in intellectual disarray’—plagued by ‘persistent disagreements’—with the ‘last decade’ trends in macroeconomics, of moving towards a ‘new neoclassical synthesis’.

For Goodfriend and King (ibid., 232), the ‘new neoclassical synthesis’ consists in:

[...] the systematic application of intertemporal optimization and rational expectations as stressed by Robert Lucas. In the synthesis, these ideas are applied to the pricing and output decisions at the heart of Keynesian models, new and old, as well as to the consumption, investment, and factor supply decisions that are at the heart of classical and [real business cycle] models.

Disentangling the elements of Goodfriend and King's summary and extending it to the subsequent literature, one could characterise the new neoclassical synthesis as the combination of five principles:

<footnote n="75">75 See e.g., Fligstein et al. (2017) and Thiemann (2022).</footnote>

<footnote n="76">76 What follows draws from an abundant literature on the history of macroeconomics: see Cherrier et al. (Forthcoming) for a summary.</footnote>

<footnote n="77">77 Note that the term ‘synthesis’ is not simply a synonym for ‘consensus’, but rather a reference to the idea of a 1960s ‘neoclassical synthesis’ in macroeconomics (Pedro G. Duarte and De Vroey 2013). This storytelling is recounted in more detail, and analysed critically, by Sergi (2020).</footnote>
(1) macroeconomics aims at analysing fluctuations ('business cycles'), i.e. co-mouvements in aggregate time-series (consumption, investment, output, prices, etc.) around a trend, as indeed argued by Lucas (1977);

(2) macroeconomic analysis starts with the characterisation of individual behaviour for different classes of 'representative agents' (households, firms). All agents are characterised by 'rational' behaviour. This entails solving an infinite-horizon optimisation problem under some constraint (e.g., maximising utility from consumption under a budget constraint). This approach to macroeconomics has been a key emphasis of Lucas and his co-authors (what has been labelled the 'new classical' approach to macroeconomics);

(3) macroeconomic fluctuations are understood as responses to 'shocks' (exogenous disturbances). This interpretation was crucial in the 'real business cycle' approach (Kydland and Prescott 1982). In the new neoclassical synthesis, shocks pertain either to the 'real' side of the economy (e.g., technological shocks, changing productivity) or the 'nominal' side (affecting, for instance, interest rates or prices). Shocks entail fluctuations insofar as they disturb the intertemporal equilibrium: that is, they force agents to revise their optimal plans;

(4) several economic variables are characterised by 'rigidities': as a result, it is impossible for agents to immediately 'jump' to their new optimal plan. There are both 'real' rigidities (such as the delay, for firms, in adjusting production capacities) and 'nominal' rigidities (such as the delay in adjusting nominal prices or wages). Rigidities generate temporary 'output gaps', that is, levels of output (and the related levels of consumption and investment) that are different from the intertemporal general equilibrium level. Insistence on 'rigidities' is the legacy of what Goodfriend and King call the 'Keynesian models', as embodied by an 'old' generation and a 'new' generation emerging in the 1980s-1990s (Mankiw and Romer 1991);

(5) monetary policy plays an active role in determining aggregate output and stabilising the economy, throughout the nominal interest rate.<fnref n="78" />

<footnote n="78">78 These five principles will then form the theoretical core underlying the development of the 'dynamic stochastic general equilibrium' (DSGE) models, which were developed largely in central banks in the early 2000s (cf 5.2).</footnote>
The new synthesis would notably enhance an easier path at ‘employing’ macroeconomics for policymaking, especially in the domain of monetary policy (Goodfriend and King 1997, 231). From their perspective, the new synthesis supported a set of new conclusions about the role of monetary policy, notably that there is ‘little long-run trade-off between inflation and real activity’, that inflation has significant economic costs, and that credibility is the central concept for understanding the operation of monetary policy (ibid., 232). Additionally, these ideas were deemed ‘consistent with the public statements of central bankers from a wide range of countries’ (ibid.). Further contributions to this line of work would later designate the new synthesis as the ‘Science of Monetary Policy’ (Clarida, Galí, and Gertler 1999); Michael Woodford, in his summary of *Interest and Prices* (2003), also highlighted this objective of ‘reconciling central bankers’ understanding of what they do with the way that monetary policy is conceived in theoretical monetary economics’.

Another development in macroeconomics played an important role in shaping the common cognitive infrastructure emerging in the 1990s: ‘new political macroeconomics’ (Galvão de Almeida 2021), sometimes also labelled ‘new political economics’ or ‘new political economy’. This literature sought to understand ‘how political constraints may explain the choice of policies (and thus economic outcomes) that differ from optimal policies’ (Drazen 2002, 7). A key illustration of this is the time-consistency problem, popularised by Kydland and Prescott (1977), which argued that policies deemed optimal at time *t* may no longer be optimal at time *t+s*, due to policymakers’ incentives to exploit short-term gains by misleading economic agents. This dynamic, however, ultimately undermines policy credibility, as rational agents anticipate these incentives, rendering the optimal policy unachievable.

The time-consistency problem spurred new political macroeconomics analysis of issues such as constraining central banks' discretion, focusing on the importance of credibility and reputation (Barro and Gordon 1983a; 1983b). This literature also explored mechanisms for insulating monetary policy from political pressures, such as selecting central bankers with specific attributes, or formalising the delegation of authority to independent central banks (Rogoff 1985). This literature also investigated empirically the relationship between central bank independence and successful management of inflation (Alesina and Summers 1993). Although initially developed in the United States, the new political
macroeconomics gained wider popularity in Europe during the 1990s (Goutsmedt and Truc 2023): indeed, the tools and concepts introduced by this literature appeared particularly useful for examining European-specific issues, such as systems for stabilising exchange rates, rules for fostering macroeconomic convergence, and conditions for establishing a monetary union.<fnref n="79" />

Finally, this new literature also reignited interest in the 1970s stagflation. While the focus on explaining the causes of stagflation had diminished in the mid-1980s, a fresh set of explanations emerged in the 1990s, centering largely on the alleged missteps of central banks’ during that period (Goutsmedt 2021). These new interpretations reshaped the understanding of stagflation and became deeply embedded in central bank discourse.

During the 1990s, central bankers exhibited a convergence toward a more unified style of economic reasoning. This trend was not fully independent of the academic dynamics described above. However, it was primarily enabled by significant economic and institutional transformations that had taken place since the 1970s. We thus now turn to these changes, taking place inside central banks, before illustrating how they contributed to closing the gap with academia.

Changing economic circumstances have been a powerful driver in reshaping central bankers’ understanding of relevant economic issues and mechanisms, and thus of the policy stakes they were facing. The end of the Bretton Woods system and rising financialisation strengthened central banks’ relationship to financial markets.<fnref n="80" /> The effectiveness of monetary policy—notably in controlling inflation—was thus understood, increasingly, as dependent on the ability to influence the behaviour of financial actors, both at home and, most importantly, abroad (see e.g., Braun 2015; Krippner 2007). In the European context, the emergence of the European Monetary System (then the Exchange Rate Mechanism) bound central banks of the European Economic Community to coordinate their policy interventions, and, more broadly, to think about the international spillover effects of their monetary

<footnote n="79">79 About the links between this literature and the debates about the design of the future ECB, see e.g., James (2012, 270–72).</footnote>

<footnote n="80">80 On the transformations of the international monetary system, see Helleiner (1996) and Daunton (2023). On the link between financialisation and monetary policy, see e.g., Krippner (2007), Holmes (2013), Braun (2018) and Wansleben (2022).</footnote>
policy.<fnref n="81" /> In developing countries, the potentially destabilising effects of developed countries monetary policies, channelled by emerging global financial markets, became a key aspect of the reflection about the role of central banks.<fnref n="82" /> Moreover, after the fall of the Soviet Union, new central banks were called to manage the ensuing economic transformations of the countries of the former Eastern bloc, on the model of Western central banks' actions (J. Johnson 2016). During this same period, many central banks lost their traditional roles in financial supervision and regulation, refocusing their activities primarily on monetary policy and inflation control (Goodhart and Schoenmaker 1995; Wansleben 2022, chap. 5).

In the wake of these changes, central banks grew more concerned with the importance of the ‘credibility’ of their decisions. More broadly, governments and international organisations started pushing for a change in the institutional setting within which central banks operated, paving the way to the ‘independence’ of central banks. Such independence was clearly understood as a way to enhance ‘credibility’. Many Western central banks were indeed granted at least operational independence in the 1990s (see e.g., McNamara 2002).<fnref n="83" /> Inflation-targeting rapidly became a crucial policy device for newly independent central banks, serving both to structure communication with the public and to manage expectations (see e.g. Blinder 2004; Braun 2015; Best 2019).<fnref n="84" /> Inflation-targeting involves the public announcement of a target for inflation over a specified time horizon. Price stability therefore becomes the central objective of the central bank adopting inflation targeting, requiring transparent communication about the instruments used to achieve the target.

This new style of economic reasoning developed within central banks (‘credibility’, ‘targets’, ‘independence’, etc.) mirrored the ideas developed by macroeconomists of the new neoclassical synthesis. Macroeconomists like Goodfriend and King or Woodford seem thus right in highlighting the

<footnote n="81">81 On the role of central banks in the process of European economic and monetary integration, see Mourlon-Druol (2012) and James (2012).</footnote>

<footnote n="82">82 Spectacular economic and financial crises have erupted in Latin America, since the 1980s, and in South-East Asia, at the end of the 1990s. Currency crises and debt crises often constituted the triggers of such episodes, leading central banks in these countries to rethink their operations: see, among others, Boughton (2001), Guzman et al. (2016), Babb (2018).</footnote>

<footnote n="83">83 For a longer perspective about conceptions of ‘independence’, see e.g., Do Vale (2021).</footnote>

<footnote n="84">84 Inflation targeting was first adopted by New Zealand in 1990, followed by Canada in 1991 and the United Kingdom in 1992. See Bernanke and Mishkin (1997, tbl. 1) for the different operational aspects of central banks’ inflation targeting in the 1990s.</footnote>
overlapping between the new synthesis in academic macroeconomics and the new ‘consensus’ within central banks. The point of this section was to highlight that this overlap is not a simple coincidence, but the result of a coproduction process, involving economists outside and inside central banks, as well as policymakers.

One visible driver of this coproduction is the ‘double participation’ in academia *and* central banks of various economists who were instrumental in shaping the new neoclassical synthesis. Besides those already cited (Goodfriend, King), it’s worth mentioning at least three others, working within the Federal Reserve System: John B. Taylor, whose famous ‘rule’ (Taylor 1993) became a key policy device in contemporary central banking; and Jeffrey Fuhrer and George Moore, whose early formulations of a ‘three equation model’ (Fuhrer and Moore 1995) precedes Clarida et al. (1999).

Beyond individual trajectories, collective dynamics were at work, notably thanks to new venues, collaboratively established by central banks and academic macroeconomists. Let’s take, for instance, the case of the Bank of England. It adopted inflation targeting in 1992. This shift required the Bank of England to publish quarterly inflation reports, subjecting it to increased transparency and accountability to both the Treasury and the public. Simultaneously, debates about monetary policy frameworks, central bank independence, accountability, and inflation targeting became central topics in the Bank of England’s internal research (Acosta et al. 2024, 17–18). The working papers and academic articles produced by the staff and executives reflected a growing emphasis on legitimising the Bank’s new policy framework, often engaging directly with the political economy literature. For instance, Briault et al. (1997) reviewed the various theoretical justifications for central bank independence, aligning them with the Bank of England’s focus on transparency and accountability. This was presented at a conference organised by the Bank of Japan on the ‘operational and institutional frameworks for effective monetary policy’ (Kuroda 1997). The Bank of England’s efforts during the 1990s culminated in a 1999 symposium in London on ‘Monetary Policy Frameworks’ (Mahadeva and Sterne 2000).

Going beyond case studies, Figure 1 takes a more quantitative look at this coproduction process. As shown by the common trend in different panels, key concepts elaborated during this period—such as ‘central bank independence’ or ‘credibility’—came to represent a sizable share of academic publications
in macroeconomics.<fnref n="85" /> Symmetrically, as shown in Figure 2, central bank governors and other policymakers more frequently featured, in their public speaking, either technical language (borrowed from academia), or direct reference to academic macroeconomists.<fnref n="86" />

<figure><img src="image_2.png" /><figcaption>Figure 2 - Proportion of central banks' speeches mentioning academic concepts</figcaption></figure>

<footnote n="85">85 The corpus consists of articles indexed in Web of Science, with a macroeconomics JEL code—extracted thanks to the Econlit database. It was compiled by Goutsmedt and Truc (2025). Mentions of ‘central bank(s) independence’ also include variations such as ‘independence of central bank’, while occurrences of ‘central bank’ encompass related expressions such as ‘central banks’ or ‘central banking’.</footnote>

<footnote n="86">86 Mentions of the terms were identified through a full-text search of central banks' speeches collected by Campiglio et al. (2025).</footnote>
<figure><img src="image_3.png" /></figure>

The coproduction of a common cognitive infrastructure by academic macroeconomists and central bankers, as highlighted in this section, was also enabled by a more general phenomenon. During this period central banks progressively became *producers* of academic research in macroeconomics as well, thus directly participating in the transformation of macroeconomics.

## 5. Contributing to Academic Research

By the end of the 1990s, statistics, macroeconomic models, and the common framing of monetary policy with academia were now all established traditions of economic knowledge produced within banks. The world of central banks of the 1990s-2000s has witnessed one major novelty: the creation of a new central bank, the European Central Bank (ECB). The ECB started its operation on June 1, 1998, taking over the (short) legacy of the European Monetary Institute (established in January 1994) and, most importantly, the long tradition of European monetary cooperation. The ECB took charge of the emission of the euro (which entered in circulation on January 1st, 2002) and, thus, of conducting the monetary policy of the (then) second-largest economic area in the world in terms of GDP. The ECB, as the latest created central bank in the twentieth century, was also molded on the cognitive infrastructure discussed in the previous
section: an independent institution, committed to a mission of controlling inflation, and adopting hitherto inflation targeting as an operational framework to anchor expectations.

Building the credibility of the youngest central bank in the world, taking over from the more established national central banks of the eurozone countries, represented a challenge. How did the ECB legitimate its monetary policy decisions? Sociologists Mudge and Vauchez argue that this was made possible by the adoption of specific arrangements regarding academic research, transforming the ECB in a ‘hyperscientised’ central bank (Mudge and Vauchez 2016), ‘acting more like scientific or academic research center, and less like public, political or government institution’ (Mudge and Vauchez 2018, 249). Mudge and Vauchez’s work belongs to a relatively large literature in social sciences, characterising this novelty as the process of the ‘scientisation’ of central banks.

This section scrutinises the literature on ‘scientisation’, highlighting that the most novel aspect of this phenomenon is, indeed, the increasing pace of contributions to academic research produced by central banks (5.1). This ‘contributory’ scientisation represents a distinctive characteristic of the 2000s and 2010s; there, the feedback effect from central banks’ production of knowledge to academia’s production of knowledge reached a much larger scale, compared to the periods covered in the previous sections. Finally, we provide a more in-depth insight into one example of the type of economic knowledge produced by central banks in this period, namely the development and dissemination of Dynamic Stochastic General Equilibrium (DSGE) models (5.2).

## 5.1 The Scientisation of Central Banks: Contributing to Science

‘Scientisation’ is a term proposed by Martin Marcussen (2006; 2009) to describe central banks’ evolution.<fnref n="87" /> ‘Scientisation’ characterises, in Marcussen’s work, the increasing reliance of central banks on ‘science’ and, most specifically, on science produced within central banks. This is the main novelty of what Marcussen calls ‘the fifth age’ of central banking, that is, the period, starting in the early 2000s, during which ‘central bankers gain legitimacy and authority by basing their views on and applying the

<footnote n="87">87 For a complete survey of the related literature on ‘scientisation’ of central banks, see Goutsmedt and Sergi (2025). Note also that this literature has important connections to studies about other policymaking institutions, notably international organisations.</footnote>
language of science', marking a shift of power to 'those who master the discourse of science' (Marcussen 2009, 377). This entails that monetary policy leaves the realm of 'politics', to become 'apolitical'—a 'technical' or 'scientific' issue that should be addressed by economists and central bank economists 'mastering' the relevant scientific knowledge.

This aspect of the transformation of central banks echoes, in Marcussen's framework, the broader 'rationalization process' of modern societies, emphasised notably by Max Weber: 'explicit, abstract, calculable rules and procedures' replace 'sentiments, traditions and rules of thumb' (Marcussen 2009, 375). Yet, the scientization of central banks takes this process further, since it also turns central bankers into 'scientists in their own right' (Marcussen, 2006, 90), also contributing to science—rather than just applying science. In short, one of the characteristics of scientization is to blur the distinction between 'science consumers' and 'science producers' (Marcussen, 2009, 370).

Goutsmedt and Sergi (2025) and Goutsmedt et al. (2025) proposed a reinterpretation for the concept of 'scientization', distinguishing between three different dimensions:

- 'policymaking scientisation': to conduct monetary policy, central bankers rely increasingly on the use of scientific knowledge and expertise;

- 'legitimising scientisation': in order to legitimise the conduct of monetary policy, central bankers rely increasingly on scientific discourse. Appealing and referring to science becomes a 'communication strategy' devised to build credibility and authority vis-a-vis the public, and, simultaneously, to shelter monetary policy decision from political controversies;

- 'contributory scientisation': central banks actively contribute to the relevant science (here, economics).

Distinguishing these three dimensions of scientization allows us to better grasp the actual novelty of the 2000s in the long-lasting, evolving relationship between academia and central banks. The use of 'scientific' knowledge to support policymaking is not such a novelty: the collection of data and statistical analysis conducted within central banks (cf. 2.) or the building of large-scale models (cf. 3.) had been increasingly pervasive within central banks well-before the 2000s. Similarly, legitimizing scientisation has been more and more recurrent since the 1980s: as discussed in Section 4, leveraging academic
literature and scientific concepts to defend its policy (or to dismiss criticisms) played for instance a
pivotal role in the monetarist episode. The new trend since the 2000s is the increasing propensity of
central banks to contribute more and more to academic research, and for economists working inside
central banks to think and act more and more like economists working in universities.

Again, this does not mean that, before the 1990s-2000s, there were no individual central banks (or no
individuals within central banks) contributing to academic research. By contrast, contributory
scientisation is the purposeful result of *institutional, collective* strategies (or, in short ‘research policies’),
whose aim is to increase central banks’ staff inclination to (and opportunities for) making contributions
to academic research and meeting the professional standards that also apply to academic economists.
Depending on the central banks considered, these strategies entailed various institutional arrangements:
creating dedicated spaces, within the institution, almost entirely devoted to this ends (‘research
departments’, with their own full-time staff and material or financial resources, as the ECB’s ‘DG
Research’); reshaping hiring and promotion policies, including by creating specific career pathways that
emphasize meeting certain levels of qualification for hiring (such as holding a PhD in economics or
having a track-record of academic publications); investing material, financial, or symbolic resources in
promoting economic knowledge produced within the institution, for instance by creating working
paper series, publishing books, or organising conferences.

Overall, the rise of these institutional arrangements can be observed qualitatively, at a fine-grained level, when analysing specific cases.<fnref n="88" /> When adopting a more general perspective, the literature on scientisation often relies on quantitative indicators, relating either to the characteristics of central banks’ staff or to research outputs.

The first type of indicators show an increase in central banks' staff dedicated to research. Claveau and
Dion (2018) estimate the number of 'staff research economists' in the Federal Reserve System. In 1993,
an internal report recorded 360 economists; in 2017, Claveau and Dion identified 808 economists,
corresponding to an average annual growth rate of more than 3%.⁸⁹ Moreover, a strong educational
background in economics (typically, having completed a PhD training) has now become the norm in

<footnote n="88">88 See Mudge and Vauchez (2016) for the ECB, Dutilleul (2025) for the Banque de France, Acosta et al. (2024) for the Bank of England and Costa and Marçal (2024) for the Banco do Portugal.</footnote>
central bank hiring for this type of position. Also, ‘hybrid’ careers (from academia to central banking, and back to academia) are no longer exceptions, reflecting the alignment in professional standards between the two worlds.<fnref n="90" /> Yet, these characteristics do not yet provide a clear advantage for accessing the upper echelons of central banking: other professional credentials (in-house central bank career, government offices, corporate executive functions, etc.) still open the way to a seat in monetary policy committees and governors’ offices (Dogan and Lebaron 2025).

The second type of indicators focuses on research outputs, drawing specific attention to the publication of articles, authored or co-authored by central bank staff, in peer-review journals aimed at an academic audience. Claveau and Dion (2018) found that during the 2006-2015 period, 42,2% of articles published in these journals had at least one author working at a central bank—compared to 14,7% during the 1976-1985 period. The Federal Reserve System was a precursor in this direction, displaying a significant investment in academic research well before the 2000s, but many central banks followed then.

## 5.2 Central Banks’ Contribution to Macroeconomics: DSGE Modelling

From the mid-2000s, central banks all over the world established a new modelling practice—DSGE models (see Table 3)—replacing large-scale macroeconometric models that they had developed since the 1970s (cf. 2).<fnref n="91" /> Although this practice also played a role in central banks policy routines (especially forecasting), DSGE modelling constitutes, foremost, an important contribution of central banks to the academic literature in macroeconomics. DSGE modelling is thus a key example of contributory scientisation: theoretical ingredients for this class of models proceeded from the academic developments of the new neoclassical synthesis. However, the actual DSGE modelling practice, particularly with respect to its empirical and computational implementation, was the original outcome of modelling

<footnote n="89">89 Similarly, Mudge and Vauchez (2016) document the rapid and sustained growth of the number of ‘visitors’ to the ECB, facilitated by postgraduate, internship and fellowship programmes.</footnote>

<footnote n="90">90 See Goutsmedt et al. (2025). Note that circulation of personnel across central banks (as well as between central banks and various international organisations) is also a significant trend.</footnote>

<footnote n="91">91 The involvement of central banks in DSGE modelling starts precisely with various attempts, made in the 1990s, of moving away from large-scale macroeconometric models. These older models did not match the cognitive infrastructure prevalent in central banks in the 1990s. One early attempt at creating new models, integrating some of the five distinctive elements of the new neoclassical synthesis, is the Reserve Bank of New Zealand model (Hunt, Rose, and Scott 2000).</footnote>
activities developed inside central banks. Moreover, the dissemination of DSGE models in academia (and therefore, their establishment as the 'mainstream' in academic macroeconomics) resulted, in a significant proportion, from central banks' staff sustained publication activities (cf. 5.1).

<table><caption>**Table 3. DSGE Models in Central Banks**</caption><thead><tr><td>Institution</td><td>Model Name</td><td>Year</td></tr></thead><tbody><tr><td>European Central Bank</td><td>NAWM</td><td>2003</td></tr><tr><td>Federal Reserve Board</td><td>SIGMA</td><td>2005</td></tr><tr><td>Bank of England</td><td>BEQM</td><td>2005</td></tr><tr><td>Czech National Bank</td><td>New Model or G3</td><td>2005</td></tr><tr><td>Bank of Canada</td><td>ToTEM</td><td>2006</td></tr><tr><td>Norges Bank</td><td>NEMO</td><td>2006</td></tr><tr><td>Bank of Finland</td><td>AINO</td><td>2006</td></tr><tr><td>Banco de España</td><td>BEMOD</td><td>2006</td></tr><tr><td>Banco central de Chile</td><td>MAS</td><td>2006</td></tr><tr><td>Sveriges Riksbank</td><td>RAMSES</td><td>2007</td></tr><tr><td>Bank of Thailand</td><td>BOT-DSGE</td><td>2007</td></tr><tr><td>Swiss National Bank</td><td>DSGE-CH</td><td>2007</td></tr><tr><td>Banco Central de Reserva del Perú</td><td>MEGA-D</td><td>2008</td></tr><tr><td>Banco Central do Brasil</td><td>SAMBA</td><td>2008</td></tr><tr><td>Banco de la República (Colombia)</td><td>PATACON</td><td>2008</td></tr><tr><td>Reserve Bank of Australia</td><td>&lt;NA&gt;</td><td>2008</td></tr><tr><td>Banco do Portugal</td><td>PESSOA</td><td>2008</td></tr><tr><td>South Africa Reserve Bank</td><td>&lt;NA&gt;</td><td>2008</td></tr></tbody></table>
<table><tr><td>Reserve Bank of New Zealand</td><td>KITT</td><td>2009</td></tr><tr><td>Banco de España</td><td>MEDEA</td><td>2009</td></tr><tr><td>Banque centrale du Luxembourg</td><td>LOLA</td><td>2009</td></tr><tr><td>Bangko Sentral ng Pilipinas</td><td>&lt;NA&gt;</td><td>2009</td></tr><tr><td>Federal Reserve Board</td><td>EDO</td><td>2010</td></tr><tr><td>Bank of Japan</td><td>M-JEM</td><td>2010</td></tr><tr><td>European Central Bank</td><td>EAGLE</td><td>2010</td></tr><tr><td>Bank of England</td><td>COMPASS</td><td>2011</td></tr><tr><td>Federal Reserve Bank of Chicago</td><td>&lt;NA&gt;</td><td>2012</td></tr><tr><td>Bank of Israel</td><td>MOISE</td><td>2012</td></tr><tr><td>Banco de España and Deutsche Bundesbank</td><td>FiMOD</td><td>2012</td></tr><tr><td>Federal Reserve Bank of New York</td><td>&lt;NA&gt;</td><td>2013</td></tr><tr><td>Sveriges Riksbank</td><td>RAMSES II</td><td>2013</td></tr><tr><td>Danmarks Nationalbank</td><td>&lt;NA&gt;</td><td>2013</td></tr><tr><td>Bank of Canada</td><td>ToTEM II</td><td>2013</td></tr><tr><td>Swiss National Bank</td><td>&lt;NA&gt;</td><td>2014</td></tr><tr><td>Reserve Bank of New Zealand</td><td>NZSIM</td><td>2015</td></tr><tr><td>Norges Bank</td><td>NEMO II</td><td>2017</td></tr></table>

Source: this is a non-exhaustive list of DSGE models developed in central banks for policy purposes. It is based on previous work by Sergi (2020), Yagihashi (2020), and Cherrier et al. (2023).
A DSGE model combines the theoretical insights of the new neoclassical synthesis into a single modelling framework. This is often summarised by the ‘three-equations’ structure inspired from Fuhrer and Moore (1995) and Clarida et al. (1999):<fnref n="92" />

$$x_t = E_t(x_{t+1}) + 1/\sigma[R_t - E_t(\pi_{t+1})] + \epsilon_t^d \quad (1)$$

$$\pi_t = \beta E_t(\pi_{t+1}) + \theta x_t + \epsilon_t^p \quad (2)$$

$$R_t = \rho_1 R_{t-1} + \rho_2(\pi_t - \bar{\pi}) + \rho_3 x_t + \epsilon_m^m \quad (3)$$

Equations (1) sets the equilibrium on the goods market (and so, the level of the output gap $x$ at any date $t$); equation (2) describes the evolution of aggregate prices (the rate of inflation $\pi$); and equation (3) describes the central bank decision about the level of the nominal interest rate ($R$). The dynamics of the economy consists of both stochastic shocks ($\epsilon$) and, for (1) and (2), of equilibrium conditions resulting from agents’ optimal intertemporal plans about consumption, employment, pricing, production, etc., given their rational expectations at the current period ($E_t$) for future values of the variables and some parameters (the aggregate price rigidity parameter $\theta$, the intertemporal elasticity of consumption $\sigma$). Equation (3) describes the ‘monetary policy rule’ followed by central banks, in the style of Taylor’s (1993) rule: that is, a reaction function to the size of the current output gap, of the difference between the current rate of inflation and the target rate ($\bar{\pi}$).

Beyond this theoretical structure, DSGE models typically consist of two additional features: a distinctive solution algorithm, embedded in a particular software (named ‘Dynare’), and an equally distinctive econometric technique, Bayesian estimation. These two ‘technical features’ became two cornerstones of DSGE modelling, both for works developed within central banks and for academic contributions to macroeconomics.

A solution algorithm for DSGE models was originally developed in the 1990s, by Jean-Pierre Laffargue, Raouf Boucekkine, and Michel Julliard.<fnref n="93" /> This allows for tractability of DSGE models, that is, the possibility of solving the model (determining the intertemporal equilibrium values), using a reasonable amount of computational resources. This feature is particularly essential for formulating large-scale

<footnote n="92">92 These three equations are reduced forms, derived from the underlying intertemporal optimisation problem of economic agents in the model.</footnote>

<footnote n="93">93 See Cherrier et al. (2023) for a more detailed history of the algorithm.</footnote>
DSGE models ('large' meaning here, of comparable descriptive detail as the models in operation since the 1970s). Indeed, the mathematical problem implicit in the three equations above is of recursive nature: rational expectations entail that current values (t) of economic choice variables depend on all future realisations (t+n) of all other economic variables. The dimensionality of this mathematical problem has posed a substantial challenge for solving and simulating rational expectations models in the 1980s and in the 1990s (Cherrier, Saïdi, and Sergi 2023). Juillard also developed a user-friendly interface to implement the algorithm, which soon started to circulate as a Matlab package, under the name 'Dynare' (for 'Dynamic Rational Expectations'). The development of Dynare was oriented, from the start, towards providing central banks and other policymaking institutions with a new tool, allowing them to develop large-scale models integrating rational expectations. Indeed, this work has been sponsored and advertised, in the 1990s, by such institutions, including the French Treasury, the IMF, and the European Commission.

Bayesian estimation methods, introduced by Smets and Wouters (2003) and Eichenbaum et al. (2005), solved a long-standing difficulty for rational expectations models in matching data. In the early development of rational expectations models, with the so-called 'real business cycle' models (Kydland and Prescott 1982), the most popular strategy adopted was 'calibration': that is, models' parameters were attributed values following modellers' 'best judgement' (drawing from microeconomic data, when available, or other diverse forms of evidence); then, the dynamic of endogenous variables were simulated; finally, these simulation results were compared with the observed pattern of relevant variables. Calibration spurred controversies and was overall seen as an inferior solution with respect to the estimation of parameters with traditional econometric techniques (see e.g. Hoover 1995). Moreover, the ability to match the data with calibrated models was also controversial—and, consequently, the relevance of such models for forecasting, in the context of policymaking routines—was doubtful. The rise of Bayesian estimation as a solution to such problems is notably related to the work conducted at the ECB by Frank Smets and Raf Wouters. In their effort to build a new, DSGE-type model for the ECB, Smets and Wouters (2003) implemented Bayesian estimation and proved that such approach could fit data satisfyingly and, henceforth, that DSGE models could be adopted as a tool for central banks.
Both the work on Dynare and on Bayesian estimation took place within a network of central bank economists, with also significant involvement by some academic economists. In 1998, an annual ‘Central Bank Macroeconomic Modelling Workshop’ was established (at the initiative of Douglas Laxton, a modeller from IMF) and met annually in a different central bank.<fnref n="94" /> This networking initiative proved crucial, in the early 2000s, for the three teams building the first large-scale DSGE models: besides Smets and Wouters’ team at the ECB, the Fed Reserve Board created SIGMA (Erceg, Guerrieri, and Gust 2006) and the IMF produced the GEM model—as a collaboration between Laxton and New York Fed economist Paolo Pesenti (Bayoumi and Laxton 2004; Laxton and Pesenti 2003). Moreover, it was during a workshop held at the Bank of Finland in 2002, that Dynare’ creator, Michel Juillard, was approached to integrate Bayesian estimation techniques into Dynare (Cherrier, Saïdi, and Sergi 2023; 2025). The Norges Bank funded the project, and Dynare 3.0 (released in 2004) came to integrate, in one single piece of software, all the technical features enabling the development of large-scale DSGE models. Moreover, several central banks established a new initiative, named ‘DSGE-net’, which funded Dynare.<fnref n="95" /> These financial resources ensured the continuous development and maintenance of the software, which had become a ‘digital commons’ for both the central banking and the academic community (Cherrier, Saïdi, and Sergi 2025).

Central banks’ staff heavily capitalised on these developments of DSGE modelling practices for academic publication. Table 4 shows most recurrent authors’ affiliations, in more than 2600 journal articles on DSGE, published between 1998 and 2021: authors are, overwhelmingly, affiliated with central banks.<fnref n="96" />

<caption>**Table 4. Authors’ affiliation for academic articles about DSGE models**</caption>

<footnote n="94">⁹⁴ See http://www.douglaslaxton.org/id38.html [retrieved 03/05/2025].</footnote>

<footnote n="95">⁹⁵ For ‘International Network for DSGE Modelling, Monetary and Fiscal Policy’. See https://www.dsge.net/ [retrieved 03/05/2025].</footnote>

<footnote n="96">⁹⁶ Data comes from the Scopus database. We conducted a search for titles and abstracts containing the terms ‘DSGE’ or ‘Dynamic Stochastic General Equilibrium’. For each paper, we recorded all unique institutional affiliations—that is, if multiple co-authors were affiliated with the same institution (e.g., the European Central Bank), the institution was counted only once per paper. Based on this method, we identified, for instance, 79 papers that included at least one author affiliated with the ECB. Additionally, all individual Federal Reserve Banks were aggregated into a single entity for the purpose of this analysis.</footnote>
<table><thead><tr><td>Articles' Affiliations</td><td>Occurrences</td><td>Rank</td></tr></thead><tbody><tr><td>Federal Reserve Banks</td><td>127</td><td>1</td></tr><tr><td>European Central Bank</td><td>79</td><td>2</td></tr><tr><td>Cardiff University</td><td>64</td><td>3</td></tr><tr><td>International Monetary Fund</td><td>60</td><td>4</td></tr><tr><td>Federal Reserve Board</td><td>56</td><td>5</td></tr><tr><td>University of Pennsylvania</td><td>53</td><td>6</td></tr><tr><td>Bank of England</td><td>49</td><td>7</td></tr><tr><td>Sveriges Riksbank</td><td>41</td><td>8</td></tr><tr><td>University of Pretoria</td><td>29</td><td>9</td></tr><tr><td>Banque de France</td><td>28</td><td>10</td></tr><tr><td>Deutsche Bundesbank</td><td>28</td><td>11</td></tr><tr><td>European Commission</td><td>28</td><td>12</td></tr><tr><td>Bank of Italy</td><td>26</td><td>13</td></tr></tbody></table>

## 6. Recent Challenges to Economists and Economic Knowledge in Central Banks

The ‘Great Financial Crisis’ and the ensuing ‘Great Recession’ yielded, along its financial and economic consequences, a critical, severe scrutiny of economics by the public. In his popular opinion column in the *New York Times*, economist Paul Krugman (2012) summarised three main criticisms addressed to his profession, and particularly to macroeconomists of the new neoclassical synthesis. First, they were unable to foresee the crisis and, most importantly, to even foresee the possibility of an event of such magnitude. Second, they were unable to understand the mechanisms that led from the 2008 Lehman
Brothers’ collapse to the Great Recession. Finally, they were not in the position of devising (or advising about) relevant policy responses to the crisis.

These criticisms were felt upon by central banks which faced similarly harsh judgment: after all, as recounted in the two previous sections, central bank economists and academic macroeconomists of the new neoclassical synthesis had developed a shared understanding of the pre-2008 world, of the role of central banks and of monetary policy; and, in turn, central bank economists had actively contributed in fuelling the academic macroeconomic mainstream that had come under such a severe attack.

In this final section, we suggest that the Great Financial Crisis did challenge the relationship between economists, economic knowledge, and central banks; but, ultimately, this relationship became even stronger: central banks had been asking their economists to provide new perspectives—new styles of reasoning, new policy devices—to make sense of the post-2008 economic circumstances and for supporting new policy needs. This entailed two distinctive effects, on academic economics (6.1) and another on economic knowledge produced within central banks (6.2).

## 6.1 Looking for New Perspectives

The Great Financial Crisis questioned what we have termed the ‘cognitive infrastructure’ coproduced by central banks and academic economists in the 1990s (cf. 4.1). On the one hand, the crisis uncovered some biases in the style of reasoning prevalent before the crisis (that is, in the way of determining which problems are important or relevant, and how to solve them). On the other hand, the crisis exposed the irrelevance, in the mutated economic conditions, of existing policy devices (tools allowing us to move from ‘thinking’ to ‘acting’).

An example of the first element is provided by Fligstein et al. (2017). The authors highlight how, in the United States, the Federal Open Market Committee failed to ‘recognise the impending collapse of the financial system and its broader consequences’, *because* of its way of ‘seeing’ the world. The ‘framing effect’ of the new neoclassical synthesis ‘blinded’ the Fed, insofar as, among other shortcomings, this framework ‘overwhelmingly brackets the real economy from the financial system’ (Fligstein, Stuart
Brundage, and Schultz 2017, 887).<fnref n="97" /> Indeed, new neoclassical synthesis macroeconomics neglected the role of financial markets and of the banking system in determining aggregate fluctuations in output, employment, and prices.<fnref n="98" />

An example of the second element (the shortcomings of existing policy devices) pertains to the role played by economists in implementation of Quantitative Easing (QE) policies by central banks during the crisis.<fnref n="99" /> Acosta et al. (2024) and Cassar (2023) documented, for instance, the case of the Bank of England's QE implementation. Policymakers soon realised the irrelevance of existing analytical tools (particularly, of macroeconomic models based on the new neoclassical synthesis) when the interest rate reached the 'zero lower bound'. This entailed a difficulty in understanding the mechanisms at work with this type of policy, but, most importantly, in conceiving the concrete operationalisation of QE (e.g., the amount, structure, and maturity of asset purchase). As a policymaker recalls, 'operational design was done in a rush [...] It was a breakdown of communication. The economists had done some economic analysis but hadn't thought about how you might implement [it] in the market.' (Acosta et al. 2024, 28) As a result, policymakers 'essentially knocked up the QE plan ('That's how it will work, end of story') in about three days' (ibid.), thus without relying on expertise produced by in-house economists. After the start of the QE, the Bank initiated new research to provide a rationale for the policy, and an assessment of its actual effects (ibid., 29-30).

Despite these shortcomings, the cognitive infrastructure prevalent before the crisis did not entirely collapse. Actually, the prevailing style of reasoning about monetary policy—the necessity for central banks to be independent, the need to build their credibility, notably by prioritising price stability and using inflation targeting, etc.—remained largely uncontested. Nonetheless, central banks have been 'layering new elements onto the old' (J. Johnson, Arel-Bundock, and Portniaguine 2019, 547), gradually transforming their style of reasoning to incorporate the imperatives of maintaining financial stability

<footnote n="97">97 Other relevant shortcomings, for these circumstances, in the style of reasoning of the new neoclassical synthesis include: the concept of equilibrium (which exclude the possibility of large fluctuations), the idea of business cycles as driven by shocks (exogenous to the functioning of the economy), the idea of rationality (marginalising thus the possibility of panics, mimetic behaviours, etc.).</footnote>

<footnote n="98">98 For instance, few pre-2008 DSGE models included a representation of these sectors (see e.g. Caballero 2010).</footnote>

<footnote n="99">99 For a presentation and discussion of QE, see notably Benford et al. (2009).</footnote>
and developing macroprudential regulation.<fnref n="100" /> However, this transformation is not without contradictions. Central banks' additional objectives, such as financial stability, increase the likelihood of new policy trade-offs (Goutsmedt and Fontan 2024) and require new types of expertise (cf. 6.2).

Similarly to the style of reasoning forged in the 1990s, DSGE models maintained an important role after the crisis, both in central banking and in academia. As illustrated by Table 3 and 4 (cf. 5.2), central banks around the world continued, after 2008, to produce in-house DSGE models; in the meantime, central bank staff pursued their research publication activities based on DSGE modelling. There have been various interpretations about the reasons for this resilience of DSGE models. For instance, it has been suggested that central banks had already invested, in the pre-crisis years, such a significant amount of material and symbolic resources, making these models ‘too embedded to fail’ (Mudge and Vauchez 2018).<fnref n="101" />

However, these analyses, emphasising the permanence of new neoclassical synthesis macroeconomics and DSGE modelling, often understudy the elements of change within DSGE modelling. Actually, the consensus in academic macroeconomics has been on the move since the crisis. Public criticisms, such as those summarised by Krugman (2012), have been obviously one driver for this movement; yet, given central bank economists' have been also fostering new developments, especially with the intention of meeting the demands for new perspectives coming from policymakers.

One substantial part of these new developments simply consisted in the extension and amendment of the DSGE modelling framework. This included notably a more detailed integration of financial markets and the banking sector, as well as fleshing out their linkages with the real economy. This constituted an attempt at explaining the underlying mechanisms of the Great Financial Crisis.<fnref n="102" /> The inclusion of financial markets and the banking sector in DSGE models was the most notable element of a general shift of macroeconomics towards studying these topics, as highlighted by Glandon et al. (2023)'s quantitative analysis of publications in macroeconomics. A related novelty has been the more detailed account given

<footnote n="100">100 On the transformations of central banks objectives and communication following the financial crisis, see e.g. Moschella (2024).</footnote>

<footnote n="101">101 An alternative explanation pertains to the ‘gatekeeping’ role of mainstream economists, which prevents alternative frameworks from emerging and gaining recognition within the profession (see e.g., Helgadóttir and Ban 2021).</footnote>

<footnote n="102">102 See for instance Iacoviello and Neri (2010) and Boissay et al. (2016).</footnote>
to alternative channels of monetary policy, trying thus to provide a rationale to QE: literature on monetary policy at the ‘zero-lower-bound’ flourished.<fnref n="103" /> Another substantial trend has been the exploration of new hypotheses about economic agents’ behaviour, amending several distinctive elements of the new neoclassical synthesis (such as rational expectations, the homogeneity of economic agents, intertemporal optimisation). Examples of this trend include a literature on ‘heterogeneous agents’, and another importing into macroeconomics some insights from behavioural economics. Both strains of research have their own roots in distinct intellectual and modelling traditions, often at odds with the new neoclassical synthesis (Cherrier, Duarte, and Saïdi 2023; Passard and Sergi 2024). And yet, some of ideas from behavioural and heterogeneous agents macroeconomics could be integrated into DSGE models, creating new avatars of the new neoclassical synthesis (see e.g., De Grauwe 2011; Grauwe and Ji 2019; Kaplan, Moll, and Violante 2018).

Other approaches to economics, departing more radically from the new neoclassical synthesis, have also gained further space in academia, taking advantage of the criticisms against the ‘mainstream’. Some of these have been trying to make their way into central banks, and gained some institutional support within the institution: a good example is agent-based modelling (see Axtell and Farmer 2025 for a survey), which became part of a new research programme of the Bank of England in the early 2010s, despite being also met with resistance and criticism both within and outside the institution (Plassard 2020).<fnref n="104" />

## 6.2 Strengthening Central Banks’ Expertise?

Yes, the use of DSGE modelling was seriously challenged by the Great Financial Crisis. Indeed, the work of economists within central banks came under intense criticism, as existing models failed to anticipate or adequately explain the unfolding crisis and its consequences. Yet, if anything, the crisis ultimately

<footnote n="103">103 See for instance Bhattarai and Neely (2022) for a survey, and Harrison (2012) and Hohberg et al. (2019) for two examples produced by central bank economists.</footnote>

<footnote n="104">104 Beyond models, other ideas or concepts previously at the margins had entered the style of reasoning of central bankers: one example is Minsky’s ‘paradox of tranquillity’ (and the related concept of financial instability); see for instance Yellen (2009).</footnote>
strengthened central banks' reliance on economic expertise, insofar as new missions emerged, requiring specialised knowledge and analytical tools.

To support this statement, let's turn to the usual indicators to assess scientisation (both, in its 'policymaking' and 'contributory' dimensions; cf. 5.1).<fnref n="105" /> The crisis triggered a temporary slowdown in academic publications for some central banks, such as the Bank of England (Goutsmedt et al. 2025), though this was not the case for others, like the ECB (Mudge and Vauchez 2016). Overall, since 2008, central banks have continued to increase their academic publication output. Similarly, there is no evidence of a slowdown in the recruitment of PhD economists across most central banks (Dogan and Lebaron 2025; Goutsmedt et al. 2025). Finally, appointments of economists with strong academic credentials to top leadership positions also continued uninterrupted—with figures such as Janet Yellen at the Fed, Mario Draghi at the ECB, and Mark Carney at the Bank of England exemplifying this trend. One reason for this strengthened role of economic expertise lies in the institutional transformations of central banks after the Great Financial Crisis. As they were entrusted with new responsibilities (including financial supervision and regulation) and requested of dealing with emerging issues (such as climate change and inequality), central banks were compelled to develop new policy toolkits—which, in turn, called for novel forms of expertise.<fnref n="106" /> Macroprudential policies offer a useful illustration of this shift. ‘Macroprudential policies’ designate various regulatory frameworks designed to monitor and mitigate systemic risks within the financial system. To implement such policies, central banks need to collect extensive financial data, construct models, and, ultimately, produce credible policy recommendations (Thiemann 2024).<fnref n="107" /> This long process was made possible by a new alliance (featuring central banks, the BIS, and academic economists), whose aims was to bridge the ‘gap’ between

<footnote n="105">105 Regarding what Goutsmedt and Sergi (2025) refer to as ‘legitimising scientisation’—that is, the strategic use of economic expertise to justify policy decisions and deflect criticisms—we may ask to what extent central banks have altered their communication strategies. Indeed, in the wake of the crisis, executives at the Bank of England reduced the technicality of their discourse (Goutsmedt et al. 2025), while the ECB has broadened its communication efforts to appear more responsive to ‘public contestation’ (Moschella, Pinto, and Martocchia Diodati 2020).</footnote>

<footnote n="106">106 On the debates about the new missions of central banks, see e.g. Tucker (2018) and Johnson et al. (2019). On the issue of monetary policy and inequality, see Fontan et al. (2016).</footnote>

<footnote n="107">107 On the development of new models for macroprudential regulation, see also Coombs (2020).</footnote>
macroeconomics and financial economics and to conceptualize ‘the financial system’s cyclical fragilities and potential impact on the macroeconomy’ (Thiemann and Priester 2024, 3).

Importantly, the development of these new tools involved a different kind of economic knowledge, than that which had previously dominated in central banks. It called for economists with profiles distinct from the typical new neoclassical synthesis macroeconomists who were predominant in the 2000s. But as Thiemann (2024, chap. 3) explains, it also differed from traditional financial economics, which largely relied on a ‘micro-prudential’ perspective and the ‘market efficiency’ hypothesis.

Central banks’ new involvement in climate change mitigation illustrates a similar trend. In recent years, several central banks have adopted a more proactive stance, and taken responsibilities in this domain.<fnref n="108" /> At the international level, this shift has led to the creation of the Network for Greening the Financial System (NGFS) in 2017—a coalition of central banks and financial supervisory authorities, aimed at stimulating debates on green finance and developing new solutions. Regarding expertise, for instance, the NGFS has issued a guide to assist central banks in building ‘climate scenario analysis’, assessing material risks to financial stability.<fnref n="109" /> Beyond relying on scenario analysis—a standard expert technique used by the Intergovernmental Panel on Climate Change (Borie et al. 2021)—central banks have also developed new models to evaluate the financial risks posed by climate change.<fnref n="110" /> This includes the adaptation of stress-test models to incorporate climate-related risks, resulting in the emergence of ‘climate stress testing’. In this case, unlike what Thiemann (2024) observed for macroprudential policies, the development of these new tools has been driven by competing forms of expertise, originating outside central banks, particularly from private finance professionals and green think tanks (see e.g., Quorning 2024).

While the focus has thus far been primarily on financial stability concerns, the development of new climate-related expertise within central banks is not limited to this domain. The resurgence of inflation

<footnote n="108">108 On central banks’ new discourse and responsibilities regarding climate change mitigation, see e.g. Langley and Morris (2020), Deyris (2023), and Rosa (2025). See also Best et. al (2025) for a survey.</footnote>

<footnote n="109">109 https://www.ngfs.net/system/files/import/ngfs/medias/documents/ngfs_guidescenario_analysis_final.pdf
(retrieved 13/05/2025).</footnote>

<footnote n="110">110 Economists have not entirely disregarded scenario techniques in the twentieth century (see e.g. Lenel 2023; see also Evrard, forthcoming); however, they remain a relatively uncommon tool.</footnote>
since 2021, in the context of ongoing climate change, has introduced new policy trade-offs—notably the tension between raising interest rates and maintaining adequate funding for the energy transition (see e.g. Goutsmedt and Fontan 2024; Best et al. 2025). Central bankers and economists within central banks are increasingly adjusting their style of reasoning by conceptualizing price stability through the lens of climate-related risks, including the impact on prices of the dependence on fossil fuels, the acceleration of the energy transition, and climate-induced catastrophic events (see e.g. Angeli et al. 2022; Schnabel 2022). This evolving style of reasoning underscores the need to integrate climate risks into macroeconomic modelling, particularly within DSGE models (Chen et al. 2021)—which remains relatively uncommon to date.

Beyond the development of analytical tools, climate change also necessitates institutional reorganization within central banks to ensure that climate concerns are seriously addressed—or at least to appear to be prioritised. Just as transformations in data collection (cf. 1.), model development (cf. 2.) and academic publishing (cf. 5.1) signalled shifts in the role of economists within central banks, organisational restructuring can symbolise a broader institutional commitment to transform expertise related to climate issues. For instance, in January 2021, the ECB established a ‘Climate Change Centre’ coordinating activities ‘on climate change and sustainable finance’.<fnref n="111" /> Such organisational transformation will likely lead to the recruitment of increasing numbers of experts with backgrounds in climate science. In turn, this may facilitate the development of new tools, but also provoke epistemic tensions with more established forms of expertise—particularly those associated with macroeconomics or financial economics.

## 7. Concluding Remarks: Paths for Future Research

This book covered a relatively diverse scholarship within social sciences, addressing the evolution of the role and place of economists and economic knowledge within central banks. As we argued, the extant strains of literature document clearly some major trends unfolding along the twentieth century—

<footnote n="111">111 https://www.ecb.europa.eu/press/pr/date/2021/html/ecb.pr210125_1~3fc4ebb4c6.en.html (retrieved 13/05/2025). The Banque de France also created a ‘Climate Change Centre’ in 2021 (https://www.banque-france.fr/en/banque-de-france/engaged-central-bank/climate-change-sustainable-finance; retrieved 13/05/2025).</footnote>
notably, the evolution of central banks towards a closer proximity with academia. However, it is
important to emphasise how the research conducted so far still has substantial blindspots, calling for
further investigation. The purpose of these concluding remarks is to suggest future research paths for
those of our readers (scholars and future scholars in the social sciences) who would be willing to engage
in future research on this topic. These suggestions build upon the general framework developed along
this book—that is, central banks as boundary organisation, navigating in-between the market, the State,
and academia.

Heterogeneous historical trajectories drove each national central bank to develop a distinctive
relationship with, on the one hand, national and international financial and banking actors, and, on the
other hand, with other policymaking institutions and the public. For this reason, one could not expect to
observe the same kind of central banking in (say) Montevideo, London, and in Manila. As obvious as
this sounds, it is an important difference to highlight, insofar as there is now much that we know about
central banking in London, but not much about central banking in Montevideo, in Manila, and in most
countries of emerging economies and of the Global South.<fnref n="112" /> There is, thus, still much to be learned from
addressing these case studies. One should not under-estimate, though, the influence over Global South
central banks of the ‘cognitive infrastructure’ developed within Western central banks: ideas like
‘independence’ of the central bank, or ‘inflation-targeting’, have been definitely held as universal
principles to be adopted by any central bank—as for instance in the countries of the former Soviet bloc
(J. Johnson 2016).<fnref n="113" /> Yet, most central banks in emerging countries or in the Global South are definitely
adapting, resisting, and translating these Western ideas about central banking, building on their own
local history and trajectory. What is mainly missing from the literature is to engage with cases in which
the ‘boundary position’ of the central banks substantially diverges from that observable in most
countries: one could notably think of central banks in economies where the State plays a more
prominent role in organising the economy than in Western capitalist economies. The central bank of the

<footnote n="112">112 Note that this does not mean that Western central banks have been extensively covered by the literature: for instance, almost no coverage has been given to central banking in small European open-economies (such as Austria, Switzerland, Luxemburg, or Ireland).</footnote>

<footnote n="113">113 One could distinguish here two rather different dynamics, one of emulation and one of imposition of Western standards. Both dynamics have been brokered, historically, by international organisations, especially the IMF.</footnote>
People Republic of China represents, in this respect, one main case study that is so far absent from the literature covered in this book.

The different configurations in terms of State/market relationships with the central bank would thus be the main reason for observing heterogeneous roles and places of economists and economic knowledge across different national central banks. To say it otherwise, insofar as central banks are different, they will pick different kinds of economists for participating in their respective operations. However, one should not forget that economists within central banks ‘live a double life’ (‘double participation’; cf. 5.1): besides their job position as a central bank economist, they also rely on credentials rooted in the intellectual and professional standards determined in academia. With respect to this latter set of defining characteristics, central bank economists’ identity tends to converge, all over the world, towards a shared and unique identity, driven by the double process of internationalisation/Americanisation of academic economics (cf 1.). This similarity is clearly visible in career patterns, most particularly the ability of central bank economists to move from one central bank to another.<fnref n="114" /> Now, this global circulation of central bank economists has not been addressed *per se* by the literature; but, most importantly, its *effects* have not been investigated.<fnref n="115" /> It seems obvious that the emergence of an international workforce of like-minded economists could constitute a key driver for integrating and homogenising the type of economic knowledge produced by central banks—and, eventually, forcing more ‘Western’ views over emerging and Global South countries. In short, economic knowledge (e.g., ideas, theories, and models) travel across central banks with economists, and there is thus something to be learned from these travels.

‘What is an economist’ is, however, not set in stone. Despite the internationalisation trend observed, several national intellectual traditions still play more or less significant roles. Moreover, approaches that have been or that are currently marginalised within academia can pick up a new pace—while dominant approaches can experience decline and relegation. Investigating these academic dynamics should be a more central concern in future research about central banks. At least for some important subfields of

<footnote n="114">114 See e.g. Dogan & Lebaron (2025) and Goutsmedt et al. (2025).</footnote>

<footnote n="115">115 Note that this workforce circulates frequently across central banks and other national and international policymaking institutions, but also between central banks and private business, including financial corporations and commercial banks. The increasing role of economists and economic knowledge in financial corporations, and its consequences and debates monetary policy and financial regulation, constitutes another, related topic that has not yet been covered by current research.</footnote>
economics, central banks are now important actors, insofar as their economists are major contributors to the academic literature. Thus, their ability to ‘spin’ the identity and research agenda of economics has to be acknowledged.

All these paths for further research present similar challenges. They would require to balance, as we have tried to do in this book, a comparative, global perspective with the idiosyncratic nature of case studies. Moreover, further research would benefit from adopting, from the onset, a mixed-methods approach, towards which the literature has converged in the past years: that is, a combination of qualitative methods (including, most particularly, the use of archives, oral history and interviews, ethnographic methods) and quantitative methods. This represents a challenge, insofar as access to sources could prove more difficult for some central banks than for others.

Despite these challenges, there are still exciting new opportunities for new research, getting to understand more comprehensively the evolution of the role and place of economists and economic knowledge in central banks around the world.

## References

Abbott, Andrew. 1988. *The System of Professions: An Essay on the Division of Expert Labor*. University of Chicago Press. http://gen.lib.rus.ec/book/index.php?md5=b618808bb9c23fc978f9c5c4d870b7ef.

Abdelal, Rawi. 2009. *Capital Rules - The Construction of Global Finance*. Harvard University Press.

Acosta, Juan, and Beatrice Cherrier. 2021. ‘The Transformation of Economic Analysis at the Board of Governors of the Federal Reserve System During the 1960s’. *Journal of the History of Economic Thought* 43 (3): 323–49. https://doi.org/10.1017/S1053837220000188.

Acosta, Juan, Beatrice Cherrier, François Claveau, Clément Fontan, Aurélien Goutsmedt, and Francesco Sergi. 2024. ‘Six Decades of Economic Research at the Bank of England’. *History of Political Economy* 56 (1): 1–40. https://doi.org/10.1215/00182702-10956544.

Acosta, Juan, and Erich Pinzón-Fuchs. 2019. ‘Peddling Macroeconometric Modeling and Quantitative Policy Analysis: The Early Years of the Ssrc’s Committee on Economic Stability, 1959-1963’. *Economia. History, Methodology, Philosophy* 9 (3): 537–58. https://doi.org/10.4000/oeconomia.6603.

Acosta, Juan, and Goulven Rubin. 2019. ‘Bank Behavior in Large-Scale Macroeconometric Models of the 1960s’. *History of Political Economy* 51 (3): 471–91. https://doi.org/10.1215/00182702-7551876.

Alesina, Alberto, and Lawrence H. Summers. 1993. ‘Central Bank Independence and Macroeconomic
Performance: Some Comparative Evidence'. *Journal of Money, Credit and Banking* 25 (2): 151-62. https://doi.org/10.2307/2077833.

Álvarez, Andrés, Vincent Bignon, Anders Ögren, and Masato Shizume, eds. 2024. *Money Doctors Around the Globe: A Historical Perspective*. 2024th edition. Springer.

Angeletti, Thomas. 2023. *L'invention de l'économie française*. Paris: SciencesPo, les Presses.

Angeli, Marilena, Cassandra Archer, Sandra Batten, Ambrogio Cesa-Bianchi, Lucio D'Aguanno, Alex Haberis, Theresa Löber, Sarah Maxwell, Rana Sajedi, and Michelle van der Merwe. 2022. 'Climate Change: Possible Macroeconomic Implications'. *Bank of England Quarterly Bulletin*. https://search.ebscohost.com/login.aspx?
direct=true&profile=ehost&scope=site&authtype=crawler&jrnI=00055166&AN=16003233
2&h=DeaIJzpZr31x6ULLqPRBGDeScKaHsTOb1mexUiQu5DTsKTy5P9%2F2HRa9Hnu1
Iw6v2EGFqtBBzE9IbiJCi%2FvYCQ%3D%3D&crl=c.

Arbogast, Tobias, Hielke Van Doorslaer, and Mattias Vermeiren. 2024. 'Another Strange Non-Death: The NAIRU and the Ideational Foundations of the Federal Reserve's New Monetary Policy Framework'. *Review of International Political Economy* 31 (3): 805-30. https://doi.org/10.1080/09692290.2023.2250348.

Arestis, Philip, ed. 2007. *Is There a New Consensus in Macroeconomics?* Houndmills, Basingstoke, Hampshire; New York: Palgrave Macmillan.

Arnon, Arie. 2011. *Monetary Theory and Policy from Hume and Smith to Wicksell: Money, Credit, and the Economy*. New York: Cambridge University Press.

Axilrod, Stephen H. 2009. *Inside the Fed: Monetary Policy and Its Management, Martin Through Greenspan to Bernanke*. Cambridge, Mass: MIT Press.

Axtell, Robert L., and J. Doyne Farmer. 2025. 'Agent-Based Modeling in Economics and Finance: Past, Present, and Future'. *Journal of Economic Literature* 63 (1): 197-287. https://doi.org/10.1257/jel.20221319.

Babb, Sarah. 2018. *Managing Mexico: Economists from Nationalism to Neoliberalism*. Princeton: Princeton University Press.

Backhouse, Roger E., and Beatrice Cherrier. 2019. 'The Ordinary Business of Macroeconometric Modeling: Working on the Fed-MIT-Penn Model, 1964-74'. *History of Political Economy* 51 (3): 425-47. https://doi.org/10.1215/00182702-7551852.

Backhouse, Roger, Janes Forder, and Christina Laskaridis. 2023. 'The Natural Rate of Unemployment and the NAIRU'. *European Economic Review* 158.

Bagehot. 1873. *Lombard Street: A Description of the Money Market*. London: Henry S. King & Co.

Ball, J., and Sean Holly. 1991. 'Macroeconometric model-building in the united kingdom'. In *A history of macroeconometric model-building*, edited by Ronald G. Bodkin, Lawrence R. Klein, and Kanta Marwah, 195-230. Aldershot, Hants, England; Brookfield, Vt., USA: Edward Elgar.

Bank of England. 1976. 'The Work of the Economic Intelligence Department'. *Bank of England Quarterly Bulletin* 16 (4): 436-46.

Bank of Finland. 1972. 'A Quarterly Model of the Finnish Economy: By the Project Team of the Research Department'. *Series D* 29 (August).
https://publications.bof.fi/handle/10024/45554.

Barro, Robert J., and David B. Gordon. 1983a. 'A Positive Theory of Monetary Policy in a Natural Rate Model'. *Journal of Political Economy* 91 (4): 589–610.

—. 1983b. 'Rules, Discretion and Reputation in a Model of Monetary Policy'. *Journal of Monetary Economics* 12 (1): 101–21. https://doi.org/10.1016/0304-3932(83)90051-X.

Barten, Anton P. 1991. 'The History of Dutch Macroeconometric Modelling, 1936-86'. In *A history of macroeconometric model-building*, edited by Ronald Bodkin, Lawrence Klein, and Kanta Marwah, 153–94. Edward Elgar Publishing.

Bayoumi, Tamim A., and Douglas Laxton. 2004. *GEM: A New International Macroeconomic Model*. Occasional Paper 239. Washington, D.C: International Monetary Fund.

Bean, Charles. 2007. 'Is There a New Consensus in Monetary Policy'. In *Is There a New Consensus in Macroeconomics?*, by Philip Arestis, 18. Palgrave MacMillan.

Benford, James, Stuart Berry, Kalin Nikolov, Chris Young, and Mark Robson. 2009. 'Quantitative Easing'. *Bank of England. Quarterly Bulletin* 49 (2): 90.

Berman, Elizabeth Popp. 2022. *Thinking Like an Economist: How Efficiency Replaced Equality in U.S. Public Policy*. Princeton University Press. Princeton. https://press.princeton.edu/books/hardcover/9780691167381/thinking-like-an-economist.

Bernanke, Ben S., and Frederic S. Mishkin. 1997. 'Inflation Targeting: A New Framework for Monetary Policy?' *Journal of Economic Perspectives* 11 (2): 97–116.

Best, Jacqueline. 2019. 'The Inflation Game: Targets, Practices and the Social Production of Monetary Credibility'. *New Political Economy* 24 (5): 623–40. https://doi.org/10.1080/13563467.2018.1484714.

—. 2020. 'The Quiet Failures of Early Neoliberalism: From Rational Expectations to Keynesianism in Reverse'. *Review of International Studies* 46 (5): 594–612. https://doi.org/10.1017/S0260210520000169.

—. 2022. 'Uncomfortable Knowledge in Central Banking: Economic Expertise Confronts the Visibility Dilemma'. *Economy and Society* 0 (0): 1–25. https://doi.org/10.1080/03085147.2022.2121066.

Best, Jacqueline, Paterson Paterson Matthew, Ilias Alami, Daniel Bailey, Sarah Bracking, Jeremy Green, Helleiner, Eric, et al. 2025. 'Climate Change Governance by Central Banks in an Era of Interlocking Crises'. *Environmental Politics* 0 (0): 1–27. https://doi.org/10.1080/09644016.2025.2481713.

Bhattarai, Saroj, and Christopher J. Neely. 2022. 'An Analysis of the Literature on International Unconventional Monetary Policy'. *Journal of Economic Literature* 60 (2): 527–97. https://doi.org/10.1257/jel.20201493.

Bjerkholt, Olav. 1998. 'Interaction between Model Builders and Policy Makers in the Norwegian Tradition'. *Economic Modelling* 15 (3): 317–39. https://doi.org/10.1016/S0264-9993(98)00015-7.

—. 2014. 'Lawrence R. Klein 1920–2013: Notes on the Early Years'. *Journal of Policy Modeling* 36 (5): 767–84. https://doi.org/10.1016/j.jpolmod.2014.08.001.

Blinder, Alan S. 2004. *The Quiet Revolution - Central Banking Goes Modern*. New Haven: Yale
University Press.

———. 2022. *A Monetary and Fiscal History of the United States, 1961–2021. A Monetary and Fiscal History of the United States, 1961–2021*. Princeton University Press.
https://doi.org/10.1515/9780691238395.

Bodkin, Ronald, Lawrence Klein, and Kanta Marwah, eds. 1991. *A History of Macroeconometric Model-Building*. Edward Elgar.

Bogaard, A. van den. 1999. 'Configuring the Economy: The Emergence of a Modelling Practice in The Netherlands, 1920-1955'. Amsterdam: University of Amsterdam.

Boissay, Frédéric, Fabrice Collard, and Frank Smets. 2016. 'Booms and Banking Crises'. *Journal of Political Economy* 124 (2): 489–538. https://doi.org/10.1086/685475.

Bollard, Alan E. 2016. *A Few Hares to Chase: The Economic Life and Times of Bill Phillips*. Oxford: Oxford University Press USA - OSO.

Bordo, Michael D., and Anna J. Schwartz. 2001. 'From the Exchange Stabilization Fund to the International Monetary Fund'. Working Paper. Working Paper Series. National Bureau of Economic Research. https://doi.org/10.3386/w8100.

———. 2009. *A Retrospective on the Classical Gold Standard, 1821-1931*. University of Chicago Press.

Bordo, Michael D., and Pierre L. Siklos. 2018. 'Central Banks: Evolution and Innovation in Historical Perspective'. In *Sveriges Riksbank and the History of Central Banking*, edited by Rodney Edvinsson, Tor Jacobson, and Daniel Waldenström, 1–25. Cambridge, United Kingdom; New York, NY: Cambridge University Press.

Borie, Maud, Martin Mahony, Noam Obermeister, and Mike Hulme. 2021. 'Knowing Like a Global Expert Organization: Comparative Insights from the Ipcc and Ipbes'. *Global Environmental Change* 68 (May):102261. https://doi.org/10.1016/j.gloenvcha.2021.102261.

Boughton, James M. 2001. *Silent Revolution: The International Monetary Fund, 1979-1989*. Washington, DC: International Monetary Fund.

Braun, Benjamin. 2015. 'Governing the Future: The European Central Bank's Expectation Management During the Great Moderation'. *Economy and Society* 44 (3): 367–91.
https://doi.org/10.1080/03085147.2015.1049447.

———. 2018. 'Central Banking and the Infrastructural Power of Finance: The Case of ECB Support for Repo and Securitization Markets'. *Socio-Economic Review*.
https://doi.org/10.1093/ser/mwy008.

Braun, Benjamin, Arie Krampf, and Steffen Murau. 2021. 'Financial Globalization as Positive Integration: Monetary Technocrats and the Eurodollar Market in the 1970s'. *Review of International Political Economy* 28 (4): 794–819.
https://doi.org/10.1080/09692290.2020.1740291.

Brayton, Flint, Andrew Levin, Ralph Lyon, and John C. Williams. 1997. 'The Evolution of Macro Models at the Federal Reserve Board'. *Carnegie-Rochester Conference Series on Public Policy* 47 (December):43–81.

Briault, Clive, Andrew Haldane, and Mervyn A. King. 1997. 'Independence and Accountability'. In *Towards More Effective Monetary Policy*, 299–340. Springer.

Brisset, Nicolas. 2018. 'Models as Speech Acts: The Telling Case of Financial Models'. *Journal of*
*Economic Methodology* 25 (1): 21–41. https://doi.org/10.1080/1350178X.2018.1419105.

Buchanan, James MacGill, and Richard Edward Wagner. 1977. *Democracy in Deficit: The Political Legacy of Lord Keynes*. New York: Academic Press.

Caballero, Ricardo J. 2010. 'Macroeconomics after the Crisis: Time to Deal with the Pretense-of-Knowledge Syndrome'. *Journal of Economic Perspectives* 24 (4): 85–102.
https://doi.org/10.1257/jep.24.4.85.

Campiglio, Emanuele, Jérôme Deyris, Davide Romelli, and Ginevra Scalisi. 2025. 'Warning Words in a Warming World: Central Bank Communication and Climate Change'. *Grantham Research Institute on Climate Change and the Environment Working Paper* 418.

Carli, Guido. 1995. *Pensieri di un ex governatore*. Pordenone: Edizioni studio tesi.

Cassar, Dylan. 2023. 'Economics as Intervention: Expert Struggles Over Quantitative Easing at the Bank of England'. *Socio-Economic Review*, November, mwad060.
https://doi.org/10.1093/ser/mwad060.

Chélini, Michel-Pierre, and Laurent Warlouzet. 2017. *European inflation in the 1970s*.

Chen, Chuanqi, Dongyang Pan, Zhigang Huang, and Raimund Bleischwitz. 2021. 'Engaging Central Banks in Climate Change? The Mix of Monetary and Climate Policy'. *Energy Economics* 103 (November):105531. https://doi.org/10.1016/j.eneco.2021.105531.

Cherrier, Beatrice, Pedro G. Duarte, and Aurélien Saïdi. 2023. 'Household Heterogeneity in Macroeconomic Models: A Historical Perspective'. *European Economic Review* 158 (September):104497. https://doi.org/10.1016/j.euroecorev.2023.104497.

Cherrier, Beatrice, Pedro G. Duarte, Francesco Sergi, Aurélien Goutsmedt, Aurélien Saïdi, Juan Acosta, and Renault, Matthieu. Forthcoming. *A History of Macroeconomics*. Elements. Cambridge: Cambridge University Press.

Cherrier, Beatrice, Aurélien Saïdi, and Francesco Sergi. 2023. "Write Your Model Almost as You Would on Paper and Dynare Will Take Care of the Rest!" A History of the Dynare Software'. *Economia. History, Methodology, Philosophy*, no. 13–3 (September), 801–48.
https://doi.org/10.4000/oeconomia.16123.

———. 2025. "Write Your Model Almost as You Would on Paper and Michel Will Take Care of the Rest!" Michel Juillard's Contribution to Macroeconomics in Historical Perspective'. SSRN Scholarly Paper. Rochester, NY: Social Science Research Network.
https://doi.org/10.2139/ssrn.5186535.

Christensen, Johan. 2017. *The Power of Economists Within the State*. Stanford, California: Stanford University Press.

———. 2021. 'Expert Knowledge and Policymaking: A Multi-Disciplinary Research Agenda'. *Policy & Politics* 49 (3): 455–71.

Christian, Michel, Sandrine Kott, and Ondrej Matejka, eds. 2018. *Planning in Cold War Europe: Competition, Cooperation, Circulations (1950s-1970s)*. De Gruyter.
https://doi.org/10.1515/9783110534696.

Christiano, Lawrence J., Martin Eichenbaum, and Charles L. Evans. 2005. 'Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy'. *Journal of Political Economy* 113 (1): 1–45.
Chwieroth, Jeffrey M. 2010. *Capital Ideas: The IMF and the Rise of Financial Liberalization*. 1 vols. Princeton (N.J.): Princeton university press.

Clarida, R.H., J. Galí, and M. Gertler. 1999. 'The Science of Monetary Policy—A New Keynesian Perspective'. *Journal of Economic Literature* 37 (4): 1661–1707.

Claveau, François, and Jérémie Dion. 2018. 'Quantifying Central Banks' Scientization: Why and How to Do a Quantified Organizational History of Economics'. *Journal of Economic Methodology* 25 (4): 349–66. https://doi.org/10.1080/1350178X.2018.1529216.

Clift, Ben. 2019. 'The Hollowing Out of Monetarism: The Rise of Rules-Based Monetary Policy-Making in the UK and USA and Problems with the Paradigm Change Framework'. *Comparative European Politics*, April. https://doi.org/10.1057/s41295-019-00186-1.

Coats, Alfred William. 1993. *The Sociology and Professionalization of Economics: British and American Economic Essays*. Hoboken: Routledge.
http://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=242200.

———, ed. 1997. *The Post-1945 Internationalization of Economics*. History of Political Economy, 28.1996, Annual suppl. Durham, NC: Duke Univ. Press.

Conti-Brown, Peter. 2016. *The Power and Independence of the Federal Reserve*. Princeton University Press. http://gen.lib.rus.ec/book/index.php?md5=30bfe3bb4f3ddd0f2a5000559cb67bc5.

Coombs, Nathan. 2020. 'What Do Stress Tests Test? Experimentation, Demonstration, and the Sociotechnical Performance of Regulatory Science'. *The British Journal of Sociology* 71 (3): 520–36.

Coombs, Nathan, and Matthias Thiemann. 2022. 'Recentering Central Banks: Theorizing State-Economy Boundaries as Central Bank Effects'. *Economy and Society*, October, 1–24.
https://doi.org/10.1080/03085147.2022.2118450.

Costa, Ana, and Gonçalo Marçal. 2024. 'Economic Knowledge and Expertise in the Bank of Portugal: An Institutionalist Political Economy Perspective'. *Working Paper*.

Courbis, Raymond. 1991. 'Macroeconometric Modelling in France'. In *A History of Macroeconometric Model-Building*, edited by Ronald G. Bodkin, Lawrence R. Klein, and Kanta Marwah, 231–66. Edward Elgar.

Cruz-e-Silva, Victor, and Felipe Almeida. 2022. 'The Making of Index Numbers in the Early 1920s: A Closer Look at the Fisher-Mitchell Debate'. *History of Political Economy* 54 (4): 655–86.
https://doi.org/10.1215/00182702-9895860.

Daunton, Martin J. 2023. *The Economic Government of the World: 1933-2023*. First American edition.
New York: Farrar Straus and Giroux.

De Grauwe, Paul. 2011. 'Animal Spirits and Monetary Policy'. *Economic Theory* 47 (2): 423–57.
https://doi.org/10.1007/s00199-010-0543-0.

De Long, J. Bradford. 2000. 'The Triumph of Monetarism?' *The Journal of Economic Perspectives*, 83–94.

De Vroey, Michel, and Kevin D. Hoover. 2004. 'Introduction: Seven Decades of the IS-LM Model'. *History of Political Economy* 36:1–11.

Dekker, Erwin. 2021. *Jan Tinbergen (1903-1994) and the Rise of Economic Expertise*. Cambridge: Cambridge University Press.
Delcey, Thomas, and Francesco Sergi. 2023. 'The Efficient Market Hypothesis and Rational Expectations Macroeconomics. How Did They Meet and Live (Happily) Ever After?' *The European Journal of the History of Economic Thought* 30 (1): 86–116.
https://doi.org/10.1080/09672567.2022.2108869.

Desrosières, Alain, and Alain Desrosières. 2011. *The Politics of Large Numbers: A History of Statistical Reasoning*. Translated by Camille Naish. Digital repr. 2011. Cambridge, Mass. London: Harvard University Press.

Deyris, Jérôme. 2023. 'Too Green to Be True? Forging a Climate Consensus at the European Central Bank'. *New Political Economy* 28 (5): 713–30.
https://doi.org/10.1080/13563467.2022.2162869.

Dimand, Robert W. 1998. 'The Quest for an Ideal Index. Irving Fisher and The Making of Index'. In *The Economic Mind in America: Essays in the History of American Economics*, 140–56. London: Routledge.

—. 2010. 'Monetary Economics, History Of'. In *The New Palgrave Dictionary of Economics*, edited by Steven N. Durlauf and Lawrence E. Blume, 189–204. London: Palgrave Macmillan UK. https://doi.org/10.1057/9780230280854_24.

—. 2022. 'The Cowles Commission at the University of Chicago, 1939–1955'. In *The Palgrave Companion to Chicago Economics*, edited by Robert A. Cord, 103–22. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-01775-9_5.

Dogan, Aykiz, and Frédéric Lebaron. 2025. 'Scientisation of Central Bank Governance: A Biographical Analysis of Governors, 2000-2020'. *Finance and Society*.

Dow, J. C. R. 2013. *Inside the Bank of England: Memoirs of Christopher Dow, Chief Economist, 1973-84*. Edited by Graham Hacche and C. T. Taylor. Basingstoke: Palgrave Macmillan.

Drazen, Allan. 2002. *Political Economy in Macroeconomics*. Édition : New Ed. Princeton, N.J: Princeton University Press.

Duarte, Muniz and Loipa. 2023. 'La modélisation macroéconomique en France : une histoire des pratiques de prévision au SEEF et à la DP entre 1950 et 1975'. PhD Thesis, Lyon II: Université Lumière. https://theses.hal.science/tel-04402193.

Duarte, Pedro G., and Michel De Vroey. 2013. 'In Search of Lost Time: The Neoclassical Synthesis'. *B.E Journal of Macroeconomics* 13 (1): 1–31.

Duarte, Pedro G., and Francesco Sergi. 2023. 'Computer Operators and Software Engineers at Data Resources Inc'. *Economia. History, Methodology, Philosophy*, no. 13–3 (September), 723–68.
https://doi.org/10.4000/oeconomia.15635.

Duarte, Pedro Garcia, and Francesco Sergi. 2023. 'Duarte, Computer Operators and Software Engineers at Data Resources Inc'.

Duesenberry, James S., Otto Eckstein, and Gary Fromm. 1960. 'A Simulation of the United States Economy in Recession'. *Econometrica* 28 (4): 749. https://doi.org/10.2307/1907563.

Duguay, Pierre, and David Longworth. 1998. 'Macroeconomic Models and Policy Making at the Bank of Canada'. *Economic Modelling* 15 (3): 357–75. https://doi.org/10.1016/S0264-9993(98)00017-0.

Düppe, Till, and E. Roy Weintraub. 2014. 'Siting the New Economic Science: The Cowles