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The econometrics of knowledge
Gonçalo Pereira dos Santos
Central Banks as power-houses of scientific breakthroughs
Dissertation presented as partial requirement for obtaining
the Master’s degree in Information Management
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MEGI
2022 Title: The econometrics of knowledge
Subtitle: Central Banks as power-houses of scientific breakthroughs Gonçalo Pereira dos Santos
MGI
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ii NOVA Information Management School
Instituto Superior de Estatística e Gestão de Informação Universidade Nova de Lisboa
THE ECONOMETRICS OF KNOWLEDGE
CENTRAL BANKS AS POWER-HOUSES OF SCIENTIFIC BREAKTHROUGHS
by
Gonçalo Pereira dos Santos
Dissertation presented as partial requirement for obtaining the Master’s degree in Information Management, with a specialization in Knowledge Management and Business Intelligence.
Advisor: Bruno Damásio, PhD Co Advisor: Sandro Mendonça, DPhil
May 2022
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ACKNOWLEDGMENTS
A special thank you to both Bruno Damásio and Sandro Mendonça for the guidance during this journey. The swift and always insightful feedback was crucial for the accomplishment of this work.
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ABSTRACT
Central Banks can be seen as knowledge-based institutions imbedded in a learning economy that, due to their purpose and modus operandi, play a central role on the economic landscape all over the world, either regarding the analysis of past events, as well as by their impact on future changes due to their decisions. Their roles, purpose and objectives reflect the way they look at the economy and the way they see themselves as part of this construct. Therefore, the knowledge they produce, and publish, is a fruitful source to analyze the way Central Banks position themselves on this learning economy. An analysis of these publications, throughout the years and regarding a variety of journals, across several different countries, will be performed on this dissertation. Central Bank’s importance within the Knowledge-Based economy will be analysed through Bibliometric methods, while Markov Chains will allow us to check the transition probability from a state to another, thus leading to an understanding of the impact that systemic changes have on the focus that Central Banks have on their different objectives. Additionally, a sentiment analysis performed over the titles and abstracts of their publications over the past 40 years allowed us to perceive the inexistent difference in behaviors overs more core or peripheral countries Central Banks.
KEYWORDS
Central Banks; learning economy; knowledge-based organizations; Markov-Chains; scientometrics
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INDEX
1. INTRODUCTION ... 5
2. CENTRAL BANKS ... 7
2.1. A brief historical overview across systemic changes ... 7
2.2. Purpose over time ... 8
2.3. Communication via publications ... 9
3. KNOWLEDGE-BASED ECONOMY ... 11
4. METHODOLOGY ... 14
4.1. INFORMETRICS / SCIENTOMETRICS ... 14
4.2. MARKOV CHAINS ... 15
4.3. EXPLORATORY DATA ANALYSIS ... 15
5. INTERACTION BETWEEN MACRO-ECONOMIC INDICATORS AND CENTRAL BANK’S PUBLISHING BEHAVIOR ... 27
5.1. Regarding the Eurosystem ... 30
5.2. Central vs Peripheral Euro Countries ... 32
6. SENTIMENT ANALYSIS... 37
7. MARKOV CHAIN ANALYSIS ... 43
7.1. Publications Analysis ... 43
7.2. Citations Analysis ... 48
8. CONCLUSION ... 53
9. BIBLIOGRAPHY... 55
10. APPENDIX ... 59
10.1. Appendix 1 ... 59
10.2. Appendix 2 ... 60
10.3. Appendix 3 ... 61
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LIST OF FIGURES
Figure 1 - Total number of citations, authors, publications and distinct journals, average h-index,
from 1980 onwards ... 16
Figure 2 - Central Banks total citations and publications relationship ... 18
Figure 3 - Number of publications per journal quartile ... 20
Figure 4 - Number of publications distribution per journal’s quartile, economic field ... 22
Figure 5 - Number of publications distribution per journal’s quartile, sociology field... 23
Figure 6 - Total number of publications per H-index rating distribution by region ... 25
Figure 7 - Wordcloud based on the publication Titles ... 25
Figure 8 - Wordcloud based on the publication Abstracts ... 26
Figure 9 - Central Banks’ scientific publications trendline (1980-2017) ... 27
Figure 10 - Gross Domestic Product trendline (1980-2017) ... 28
Figure 11 - Unemployment rate (1980-2017) ... 28
Figure 12 - Exports of goods and services (1980-2017) ... 29
Figure 13 - Gross capital (1980-2017) ... 29
Figure 14 - Gini index (1980-2017) ... 30
Figure 15 - Eurosystem Central Banks’ scientific publications trendline (1980-2017) ... 30
Figure 16 - Eurosystem Gross Domestic Product trendline (1980-2017) ... 31
Figure 17 - Eurosystem unemployment rate (1980-2017)... 31
Figure 18 - Eurosystem exports of goods and services (1980-2017) ... 31
Figure 19 - Eurosystem gross capital (1980-2017) ... 32
Figure 20 - Eurosystem Gini index (1980-2017) ... 32
Figure 21 - Eurosystem Central Banks’, in peripheral countries, scientific publications trendline (1980-2017) ... 32
Figure 22 - Eurosystem Central Banks’, in non-peripheral countries, scientific publications trendline (1980-2017) ... 33
Figure 23 - Eurosystem's peripheral countries Gross Domestic Product trendline (1980-2017) ... 33
Figure 24 - Eurosystem's non-peripheral countries Gross Domestic Product trendline (1980- 2017) ... 33
Figure 25 - Eurosystem, peripheral countries, unemployment rate (1980-2017) ... 34
Figure 26 - Eurosystem, non-peripheral countries, unemployment rate (1980-2017)………34
Figure 27 - Eurosystem, peripheral countries, exports of goods and services (1980-2017)... 35
Figure 28 - Eurosystem, non-peripheral countries, exports of goods and services (1980-2017) ... 35
Figure 29 - Eurosystem, peripheral countries, gross capital (1980-2017) ... 35
Figure 30 - Eurosystem, non-peripheral countries, gross capital (1980-2017) ... 35
Figure 31 - Eurosystem , peripheral countries, Gini index (1980-2017) ... 36
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Figure 32 - Eurosystem, non-peripheral countries, Gini index (1980-2017) ... 36
Figure 33 - Title sentiment analysis - BING method ... 37
Figure 34 - Title sentiment analysis - AFFIN method ... 38
Figure 35 - Abstract sentiment analysis - BING method ... 39
Figure 36 - Abstract sentiment analysis - AFFIN method... 39
Figure 37 - Peripheral countries Central Banks' title sentiment analysis - BING method ... 40
Figure 38 - Peripheral countries Central Banks' abstract sentiment analysis - BING method .... 41
Figure 39 - Non-peripheral countries Central Banks' title sentiment analysis - BING method ... 41
Figure 40 - Non-peripheral countries Central Banks' abstracts sentiment analysis - BING method ... 42
Figure 41 - Peripheral countries Central Banks' transition Matrix before 2008 ... 43
Figure 42 - Peripheral countries Central Banks' transition Matrix after 2008 ... 43
Figure 43 - Non-Peripheral countries Central Banks' transition Matrix before 2008 ... 44
Figure 44 - Non-Peripheral countries Central Banks' transition Matrix after 2008 ... 45
Figure 45 - Eurosystem Central Banks' transition Matrix between 1980 and 2017 ... 45
Figure 46 - Non-Peripheral countries Central Banks' transition Matrix between 1980 and 2017 ... ……….46
Figure 47 - Peripheral countries Central Banks' transition Matrix between 1980 and 2017 ... 47
Figure 48 - Eurosystem Central Banks' transition Matrix between 1980 and 2008 ... 47
Figure 49 - Eurosystem Central Banks' transition Matrix after 2008 ... 47
Figure 50 - Eurosystem Central Banks' transition Matrix regarding citations ... 48
Figure 51 - Eurosystem Central Banks' transition Matrix regarding citations before 2008 ... 49
Figure 52 - Eurosystem Central Banks' transition Matrix regarding citations after 2008 ... 49
Figure 53 - Peripheral Central Banks' transition Matrix regarding citations between 1980 and 2014 ... 50
Figure 54 - Peripheral Central Banks' transition Matrix regarding citations before 2008 ... 50
Figure 55 - Peripheral Central Banks' transition Matrix regarding citations after 2008 ... 50
Figure 56 - Non- Peripheral Central Banks' transition Matrix regarding citations between 1980 and 2014 ... 51
Figure 57 - Non- Peripheral Central Banks' transition Matrix regarding citations before 2008 . 51 Figure 58 - Non- Peripheral Central Banks' transition Matrix regarding citations after 2008 .... 52
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LIST OF TABLES
Table 1 - Number of Central Banks per Region ... 16
Table 2 - Overview on Central Bank’s publications variables ... 17
Table 3 - Total Number of Central Banks publications per region ... 19
Table 4 - Total Number of publications distribution per journal quartile ... 19
Table 5 - Total Number of publications distribution per journal’s quartile, economic field ... 20
Table 6 - Total Number of publications distribution per journal’s quartile, sociology field ... 22
Table 7 - Total Number of Authors per Region, and distribution of institutional and external authors from total ... 24
Table 8 - Average, minimum and maximum h-index per region ... 24
Table 9 - Top 10 used JEL codes distribution from total (%) ... 26
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LIST OF ABBREVIATIONS AND ACRONYMS
GDP Gross Domestic Product JEL Journal of Economic Literature
PIGS Group of countries including Portugal, Italy, Greece and Spain SNA System of National Accounts
U.S United States
WDI The World Bank’s World Development Indicators
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1. INTRODUCTION
Since their creation around the XVII century, Central Banks have an important role in the economic system, even when reflecting the purpose changes that they went through over the years, changes that made their influence swing across different topics.
Central Banks’ main focus has been the definition of monetary policies and the assurance of financial stability. This focus has to be accounted for when analyzing Central Banks via their functions, even when some of those functions do not have a specific objective attached.
The understanding of Central Banks functions and focus through history is crucial in order to see how they influence and are influenced by different systemic phenomena. Thus, a brief historical overview will be performed in this dissertation, considering Central Banks’ role, purpose and objectives over time, and how historical changes made an impact on their mission and objectives of “monetary policy”,
“financial stability” and “payment system” (Central Bank Governance Group, 2009).
As it will be discussed, it is possible to see that macroeconomic events affect Central Banks’ purpose, decisions and importance throughout time. This time factor, on the other hand, should be considered since the purpose changes due to the passage of time and the events that occur, so the correlation of this two factors is key to understand the Central Banks’ behavior.
It is not only the outside-in influence that will be analyzed during this thesis, but also the way that Central Banks interact with the outside world, i.e., it is not only the outside world that impacts their evolution, Central Banks’ decisions also impact the outside world. One way Central Banks use to communicate (after analyzing the outside world) is their publications/research, which are a part of that influence. Thus, analyzing their publishing behavior, across time and accounting for specific macroeconomic events like the 2008 economic crisis, presents itself as an ideal solution to understand this interactions.
Central Banks are part of a Knowledge Based Economy, as they produce, distribute and utilize knowledge and information in order to pursue their goals and maintain their relevance in the economic landscape while increasing their productivity and focusing on economic growth. They are, in fact, perceived as a Knowledge Based Organization, which means that research plays a big part on the various duties that a Central Bank executes, as is visible by the investment and resources allocated to this activity. Through knowledge and information, Central Banks are best prepared for the dynamic and constant changes of the overall economy (see Castellaci et al., 2005, and Caraça et al., 2009).
This knowledge proliferation element is a central point of this work. We propose to understand if Central Banks adapt to the external changes in the economic system they themselves integrate. Thus, we will focus our research into understanding if, around a structurally changing event as the 2008 crisis, Central Banks adapt their focus and move away from what can be perceived as a non-core task – scientific publications of their research -, or, on the other hand, they keep this as an important task, in which case we would expect to see no changes in behavior around that period of time, strengthening the perception of Central Banks as power-houses of scientific breakthrough.
6 To achieve this purpose, information on the year of publication, the journal and respective field of knowledge, the quartile of the journal, the authors, title, abstract, keywords, JEL and number of citations for a set of Central Bank’s publications from 1927 to 2017, will be used.
The decision to choose the 2008 crisis is related to two factors. On one hand, the amount of publications authored by Central Banks has been growing over time. On the other hand, an analysis on a few macroeconomic indicators, such as GDP, unemployment and Exports of Goods and Services, reinforce the perception that the years after 2008 were a cut-off point from apparently stable indicators. Having the timeframe decided, it is pertinent to define the regions of analysis. There is the perception that the effects were not the same for different countries, even those belonging to the same currency system, as the Eurosystem. An analysis of the same indicators, splitting the dataset by sub-regions (peripheral and non-peripheral countries), will be performed.
With this analysis basis, we will now look at the impact of systemic changes on the Central Banks publishing behavior, as well as the quality of those publications. After this overall analysis, we will focus on analyzing the correlation between these bibliometric indicators and the chosen macroeconomic indicators, in order to look for a visible impact between each group of metrics. In addition to this analysis, as we are using a crisis as a cut-off point, sentiment analysis on the titles and abstracts will shine a light over the possibility of the content (aside from the quantity and quality) of the research changed in tone to reflect the negative events at the time. Finally, in order to achieve our proposed main goal, Markov Chains analysis will be performed considering the number of publications and citations as states from which we will analyze the likelihood of behavioral changes in the 1980 to 2017 period.
This analysis will strengthen our understanding of the possible impact an event like the 2008 crisis, with the socioeconomical impacts that are still under discussion and analysis due to its importance, may have affected Central Banks in this specific task – scientific publications.
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2. CENTRAL BANKS
2.1.
A BRIEF HISTORICAL OVERVIEW ACROSS SYSTEMIC CHANGESCentral Banks play a central role on the general world economic landscape. Their creation goes back to the XVII century when their purpose was to finance war, like the cases of the Bank of England and the Banque de France (Goodhart, 2010) - banks that emerged after the Glorious Revolution of 1688, and the French Revolution that ended in 1799, respectively. Later, other banks were created with the purpose of bringing some order to the issuance of banknotes, to fund conduits for the government, while also others were previously large commercial banks that were given monopoly rights to issue banknotes. The number of Central Banks grew from 18 in 1900 to 161 in 1990 (Criste & Lupu, 2014), due to their multiple origins and their increasing importance over time, during such period in which the majority of Central Banks were created as public policy agencies for central banking functions, i.e., were created as Central Banks from the start (Central Bank Governance Group, 2009).
Central Banks reason for establishment and functions shifted through history (Eijffinger et al., 2002), but maintain the constant of defining the monetary policies and playing a central role on assuring financial stability. One example of said shift is the view that the Central Bank’s main purpose was lending of last resort, related to financial stability (a microeconomic purpose) (Goodhart, 2010), and later, as Giannini (2010) points out on his extensive historical analysis, the focus on the issuance of money, that was of main importance due to the “dematerialization” of money that elicited more the need for monetary stability (a macroeconomic purpose). Ultimately, the role of a Central Bank is not fixed through time. A specific example of this changes is the Bank of England, previously pointed out as one of the first ones to be created with the purpose to finance war, and which role changed also due to the focus that was put on the social welfare instead of the shareholder’s profits (Ugolini, 2017).
We will briefly focus on these roles and purposes later on this chapter. This brief overview on the historical evolution of Central Banks is key to understand the impact time and systemic changes have on their purpose and role.
Following the Central Bank’s role changes, the dynamics of the economic behavior brings attention to the focus that may be put into the role of monetary policy, one of Central Banks focuses. This dynamic is visible through the stages of the Great Inflation (in the 1970s), the so-called Great Moderation that followed, and the Great Recession more lately (Best & Hur, 2019). Analyzing these periods alongside the monetary policies established, as well as the learning and the volatility of these periods, have proven to be of most importance in trying to justify these macroeconomic changes through time (Best & Hur, 2019).
From a brief analysis of the historical changes that Central Banks have been through, it is clear that they influence, as well as are influenced by, systemic phenomena. Because of this, Goodhart (2010) refers three periods where the financial stability allowed for a more stable approach of central banks: “(a) the Victorian era, say 1840s until 1914; (b) the decades of government control, 1930s until the end of the 1960s, and the triumph of the markets, 1980s until 2007” (Goodhart, 2010, p. 1).
This periods stability were interrupted by the 1914-1931/33 period that “was a confused inter- regnum including WWI, followed by a failed attempt to re-establish the Gold Standard” (Goodhart, 2010, p. 1), and the 1970s period that “was another confused inter-regnum between the
subservience of monetary policies to government control, and the establishment of a free market system, with the Central Bank following a regime of inflation targetry.” (Goodhart, 2010, p. 1) By analyzing this pattern, it is safe to assume that the 2008 crisis may be referred to as another “inter- regnum” period that will allow for a fourth epoch that may permit a new approach, even though, as
8 Goodhart (2010, p. 1) points out “the achievement of a new consensus on their appropriate behavior and operations may well be as messy and confused, as in the two previous inter-regnums”.
2.2.
PURPOSE OVER TIMEUntil 2007, the credibility of Central Banks was growing steadily due to their positive results and ability to reduce inflation. After 2007 it changed, now being pressured to go beyond their previous framework to better fit into the new economic demands (Criste & Lupu, 2014). The 2008 crisis brought along some still unanswered questions related to “the future of payment systems, the development of macroprudential regulation, the possible disappearance of cash, as well as the status of monetary policy in a world with very low equilibrium interest rates.” (Ugolini, 2017, p.2). Ugolini (2017) goes on to state that these questions lie on two main issues, the relationship between
monetary and fiscal authorities (prior to 2007 the point of view was that the Central Banks should be fully autonomous) and the legitimacy that Central Banks have to be the main organizations entrusted with guaranteeing the financial and monetary stability (related to their position between being totally integrated by the government or externalized to the private sector).
After the 2008 crisis the role and actions of Central Banks were severely criticized by the general population. Until recently (pre-Covid 19 phenomenon), the economic figures have shown that the economy was growing somewhat steadily on most European countries and North America, although the same could not be stated regarding Central and South America countries.
Due to its natural volatility, it seems of most relevance to analyze Central Banks’ role, intervention and respective ongoing studies throughout the years and its impact on macro-economic events by cross checking the effect their studies have on the efficiency of their functions. This leads us to questioning what will be the role, purpose and objectives of Central Banks in the future and how did past historical changes affect the path of Central Banks in what concerns their mission.
To better analyze this, one should start by focusing on what is usually referred to as the
purpose/objectives of Central Banks. We will do so by starting to briefly describe a compendium of what can be stated as the Guiding principles prior the 2008 crisis (Mishkin, 2000): price stability;
fiscal policy, aligned with monetary policy; time inconsistency must be avoided; monetary policy;
accountability is seen as a basic principle; monetary policy should focus not only on the output but in price fluctuations also; and the statement that most economic crisis are associated with instability.
These guiding principles come from theorizing in monetary economics and must be seen as something that will allow for successful outcomes in Central Banks conduct of monetary policy (Mishkin, 2000). These principles should lead to the realization that “price stability should be the overriding, long-run goal of monetary policy; an explicit nominal anchor should be adopted; a central bank should be goal dependent; a central bank should be instrument independent; a central bank should be accountable; a central bank should stress transparency and communication; a central bank should also have the goal of financial stability” (Mishkin, 2000, p. 3). A work published by the Central Bank Governance Group (2009) shines a light on the role of modern banks pos-2008. In this case, and similarly to what was previously discussed, with a slight change on the weight of each part, the Central Banks are seen primarily as an agency for monetary policy, with functions related to financial stability that are more preeminent during financial crisis. It is important to comment, however, that other functions, and the way they are structured overall, may vary between countries. A difference between ECB’s role and national central banks can be seen by the fact that the first one needs to formulate monetary policy, while the last have responsibilities in supervising the financial system and collecting data for statistical purposes (Eijffinger et al., 2002).
Regarding the objectives, they can be separated into “monetary policy”, “financial stability” and
“payment system” objectives (Central Bank Governance Group, 2009). The first type is usually tied to price stability, and are usually reflected on legal statements of the respective countries, with only a
9 few exceptions where they have the form of extra-statutory statements. It might be interesting to analyze whether the fact that an objective is reflected on the country’s legislation impacts the way it is studied, and what countries address these monetary policies more in their publications. On other words, it might be interesting to see if countries with more focused on extra-statutory statements, like Australia and Brazil, and thus apparently more flexible when it comes to policy changes, publish more or less regarding these topics than more legally grounded countries (like the countries in the Eurosystem). Financial stability objectives are reflected on most of central banks statements, even though “fewer than half of central bank statutes contain objectives relating to financial stability”
(Central Bank Governance Group, 2009, p. 25), and less than a fifth of the 146 central bank laws analyzed by the same study have objectives related to this financial stability. Therefore, it might be interesting to see, even though this objective is not reflected on most country’s legislation, how Central Banks study and publish on this, given the core importance that financial stability plays in the economy. This seems to be where many central banks can focus on, as some state that this can be given a “quantitative representation”, and, thus, is the focus of most research (Central Bank Governance Group, 2009). Finally, the payment system objectives reflect the oversight of payment systems and is heavily legislated, even though the way the objectives are stated is usually very general (Central Bank Governance Group, 2009). These objectives relate to the financial stability ones, as many discussed issues are seen in both objectives, and the existence of research is expected in this case as well. It might be expected that, because of emerging fintech being available, and new payment systems entering the market, the latest years of scientific publications have dived deeper on this issue.
Whilst analyzing Central Banks after the 2008 crisis, Dow (2017, p. 1545) states that the crisis
“exposed the weakness in basing central bank practice on monetary stability addressed through mathematical modelling. When the crisis hit, central banks had no choice but to accept the
interdependencies and complexities belied by the modelling approach.” This lead to the realization that the banks that were too focused on inflation instead of financial stability were worst in dealing with the crisis given that they did not acknowledge the existing interdependencies between the financial and private sectors, central banks and governments that are reflected in the financial stability goals (Dow, 2017). Dow (2017) also shines a light on the importance of Central banks communication and their ability to signal and influence expectations as a way of forward guidance.
As it is now perceivable, Central Banks’ purpose change over time, whilst macroeconomic evolution relates to this change in an apparently significant way.
How Central Banks’ are able to understand this macroeconomic evolution over time is an important object of analysis, without ignoring the fact that as actors in this system they are able to influence in some way that same system. One of the main ways Central Bank communicate with the external world is with the scientific publications they invest resources on.
2.3. C
OMMUNICATION VIA PUBLICATIONSCentral Banks provide information to the public about their objectives and strategy for the monetary policies, their foreseen economic outlook and its impact on future policy decisions (Blinder et al., 2008; Hubert, 2015). Such communication affects the economic landscape and general stakeholders perspectives, and is part of the transparency key feature of Central Banks. This transparency is seen as the lack of problems by the general public to deduce Central Banks’ intentions and future
objectives (Faust & Svensson, 2001), even though the theoretical literature is not yet clear on the right level of transparency to be adopted by the Banks (Blinder et al., 2008). Both transparency and communication are linked (Nicolay & Oliveira, 2019) and is known to positively contribute to expectation management and Central Banks’ goal achievement (Hayo & Neuenkirch, 2018). Central Banks communication is known to shape the general public assumptions on the future, whether they are professional economists or not. By communicating their beliefs, Central Banks indirectly lead the
10 economy to their rational equilibrium by allowing the other economic agents to not having to learn on the go having time to analyze and decide based on the Central Banks available information, information that is believed to be of superior quality (Blinder et al., 2008, Nicolay & Oliveira, 2019).
This assumption on the quality of the information that is communicated is based on the fact that Central banks usually devote more resources than any other private agent, thus making it more knowledgeable of the economic outlook, thus having lower forecast errors while also providing policy signals with these communications. For example, it is known that many financial markets react to the outlook provided by the Central Banks, changing their own views based on that information, even though it must be clear that these communications are not synonym of a commitment (Aizenman et al., 2011, Blinder et al., 2008, Hubert, 2015).
However, one should point out that Central Banks should be careful while communicating about instances where they themselves are not totally clear about (Blinder et al., 2008), making it of most relevance to have a good body of knowledge backing up their conclusions.
Thus, Central Bank “communication and learning are inextricably tied” (Blinder et al., 2008, p. 923), making it important to also perceive Central Banks as learning and knowledge based organizations.
The research they conduct allows them to attain the “conceptual and empirical basis for better policymaking, and for better communication of policies to affected countries and the public”
(Aizenman et al., 2011).
The importance of the communication is perceivable on the fact that it shapes the beliefs that feed the heuristic decision that are made in short term, while also anchoring expectations (Blinder et al., 2008). This heuristic based decision-making was acknowledged by the Bank of England Governor Mervyn King, in 2005, while discussing the moments where a “rational optimizing behavior is … too demanding” (Blinder et al., 2008).
On top of that, on their study, Best and Hur (2019) show that policy makers, such as Central Banks, learn about the economy while everything is happening, in real time, adjusting their policies according to what they learn in the moment and their own beliefs. This statement is of most
importance, given the possible assumption that their beliefs are shaped based on the knowledge that these institutions possess and create over time, shaping their decisions. Such knowledge is
developed and shared, also, through academic studies from which Central banks are a part of, like the ones that are the basis of this dissertation.
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3. KNOWLEDGE-BASED ECONOMY
By reviewing what was previously described, it is now safe to assume that, while pursuing their objectives, Central Banks produce, distribute and utilize knowledge and information. This inserts them on what can be called a knowledge-based economy, which is the type of economy that focus on that 3 usages for knowledge and information, by looking at knowledge as the way to increase productivity and allow economic growth (APEC Economic Committee, 2000). The central role that the knowledge-based economy has is patent on the fact that its creation and development is something that the World Bank and the OEDC cooperate on (Tocan, 2012).
Knowledge evolves over time and can be perceived as operating on an individual or organizational level, the latter being responsible for most new knowledge, i.e., innovation, as result of a collective effort, with some innovation focus being unrelated to what one would initially expect (Castellaci et al., 2005; Mendonça, 2003). Note that knowledge is increasingly becoming an important asset for economic development, taking over the original management models (Yuan, 2017). Mendonça (2003) shows the importance of learning in a non-restrictive way, expanding ones fields of knowledge creation to not only the ones directly related to the product lines. Also, Louçã &
Mendonça (2002) point to cumulative investment and knowledge as the “reasons for continuity” of existence for top organization, based on the evidence found on his study of the top 100 world’s largest firms. Chandler (1994) refers that knowledge allows for organizations to create entry barriers to new firms by building specific organizational capabilities, allowing for continued growth, while, at the same time, this predominant position allows them to keep investing in R&D initiatives, even though this position is disputed by evidence brought by Audretsch (1997) and reinforced by Louçã &
Mendonça (2002).
Hudson (2011) states that there are three ways that make knowledge preeminent in the economy:
knowledge perceived as a commodified output; increase of knowledge on existing commodities;
material commodities and services are more related between each other. This look on knowledge increases its influence on defining development policies. However, one should point out that not all knowledge is valued the same, being necessary to track it and change to a certain knowledge that is perceived as useful for the future, abandoning knowledge that no longer provides a purpose (Hudson, 2011).
The effect of new knowledge on macroeconomic phenomena may be looked at from an evolutionary approach, such may be the discontinuities and disequilibrium that such innovations might create, with effects over time (Castellaci et al., 2005). The outcomes are not the same for different countries, creating two groups of followers and leading countries. Even though follower countries tend to mature at a higher speed then leading countries, via imitation, it is not the same for all, provided the existence of a close link between new knowledge and technological costs, along with social and institutional capabilities (Castellaci et al., 2005).
The awareness of such different leads one to believe that different behaviors will be found when analyzing in detail the link between knowledge creation for different Central Banks according to the countries they account for.
On the other hand, we may look at the impact new studies have on macro-economic policies. For example, look at the change on labor market regulation provided by Siebert (1997) findings on its evolution of unemployment analysis (Martins & Damásio, 2019) as a clear and direct example of how publications may lead to changes in the way institutions, governmental or not, operate. This
particular example is even more peculiar if we look at its fast absorption by policy makers, even though earlier studies (see Blanchard & Jimeno, 1995) found different behaviors for some countries being analyzed, such as Portugal and Spain (Martins & Damásio, 2019). Other example may be the political decisions during the euro crisis (2010-2012), backed by a scientific ground explicit by the
12 presence of Alberto Alesina at an Ecofin meeting (Alesina, 2010) and him being referenced by policy makers directly, as stated by Chowedhury (2012), all while ignoring other scientifically relevant positions against an austerity strategy (Cabral & Louçã, 2019).
As part of this knowledge based economy are the Knowledge-Based Organizations that are seen as a type of organization that is best prepared to face the new challenges that this economic perspective brings along (Stewart, 1998). These organizations’ main role is, according to Nicolescu to use the
“specialized knowledges, obtaining, protection, integration and fructification” (cited in Tocan, 2012, p. 78), and in order to do so the organization obtains, protects and integrates the knowledge that grants them power and competitiveness (Tocan, 2012).
An emphasis on Central Banks as knowledge based organization can be made by looking at the fact that these organization’s characteristics include not only the product or service (most commonly used to measure the knowledge intensity of a company), but also process, purpose and perspective (Zack, 2003). One can say that the more knowledge is associated with the product or service, the most knowledgeable a company is. Central Banks even have research departments, in which they have been investing to improve their capabilities, to assure this achievements of feeding their councils with information and interpretations of economical phenomena to make decisions, better policymaking and communication of policies (Eijffinger et al., 2002; Aizenman et al., 2011). This research also contribute to the increase of credibility and reputation of the central bank, and it is a way to connect the research that is made with the policy-design process as it is all done in-house (Eijffinger et al., 2002).Conversely, this view is not enough, as it focus only on the observable measures. As Itami (1987) stated, the “invisible assets” play a role of at most importance, related to the what, how and why of what the organization does. As the knowledge becomes essential to the economic landscape and social development system (Drucker, 1998), it becomes more and more important to be able to measure its impact and try to see if it can be related to strategic changes of an organization.
Zack (2003), focusing on these intangible aspects, defines the process as the activities within the organization that may or may not be related to producing a product or delivering a service; while the purpose reflects the organization’s mission and strategy; and the perspective relates to the way the exterior world can influence and constrain the decision that are made by the organization. By cross checking these statements with what were previously described as the purpose and objectives of Central Banks, one can safely infer that Central Banks are Knowledge-Based Organizations, from which this knowledge management is used to assist on better decision making, and is produced and distributed, namely, through their publications. Even though it is not a Central Bank, one could point out the change that the World Bank as done to define itself as the “knowledge bank”, in order to acknowledge the key aspect of understanding and managing knowledge to achieve their goal of reducing world poverty, making it more efficient on the use of money to reach that goal.
Let us now focus on the importance of not only managing knowledge but managing the right
knowledge as well as part of the strategic plan of an organization. To be successful in the long run, an organization must align their knowledge with the stated strategy, making knowledge a strategic resource (Zack, 2003).
Therefore, Knowledge Management is a critical strategy that organizations use to achieve their goals and continuously improve their performances and adapt to external changes. It is a field that has increasingly gained the focus of the organizations’ leaders, who see their employees not only as individuals who will execute specific tasks, but as “knowledge workers and potential problem solvers” (Cavalieri & Seivert, 2005, p. 5). Thus, employees cooperate in the knowledge creation and sharing processes. This processes is important due to the fact that organizations may not develop and be more competitive only due to the learning they do from their mistakes, they should foster an environment in which the employees can develop solutions to existing problems and create new
13 knowledge that will make them more efficient on doing so on a continuous improvement basis (Cavalieri & Seivert, 2005).
Many researchers have studied this by analyzing various organizations regarding their knowledge, for example, by viewing their patents (cfr. Mendonça, 2003; Mendonça et al., 2021); and Eijffinger, de Haan and Koedijk (2002) studied the way the research departments from Central Banks relate to their publications’ quality, albeit some controversy regarding their “small is beautiful” findings (cfr.
Eijffinger et al., 2003, Angelini, 2003). The work being developed right now changes the perspective in a way that focus on Central Banks as the organizations, and the scientific publications as the source. Additionally, this analysis provides us an additional tool to perceive the importance of research and publications.
14
4. METHODOLOGY
Given the changes that socio-economic developments have on the functions and objectives of central banks, an analysis of what has been Central Banks’ main publications throughout the years seem to be of high value, especially if we take into account recent economic changes.
Therefore, we intend to analyze the impact that systemic changes have on the focus that Central Banks put into their different objectives, analyzed via their publications in scientific journals, and the importance of said publications overall.
More specifically, the scientific publications will provide the behavioral measure to check how Central Banks behave across different economic phenomena, seen through the analysis of the different GDP cycles, unemployment, exports, gross capital and Gini index trends.
This dissertation will use a database that includes information regarding Central Bank’s publications from 1927 to 2017. The database includes information on the year of publication, the journal and respective field of knowledge, the quartile of said journal, the authors, title, abstract, keywords, JEL and number of citations.
After an exploratory data analysis, a decision was made in order to consider only the information regarding the years 1980 to 2018, which is the period of time that seemed most relevant either by the fact that it collected most of the publications, but also because from an economic perspective one can perceive cyclical behaviors and it accounts for the last known economic crisis.
This database will be analyzed via text analysis in order to obtain what are the main subjects that are studied by the Central Banks and possible links between them. Given the importance of knowledge management, which implies the distribution of said knowledge, scientometric methods will be applied in order to analyze and conclude on the Central Banks publication impact. Also, due to their nature, and the intent to check whether Central Banks can be proactive and anticipate economical changes, a stochastic analysis of the data will be performed via Markov Chains.
4.1. INFORMETRICS / SCIENTOMETRICS
As previously stated, one way to address the relevance of Central Banks knowledge management and their systemic impact is to evaluate the influence of their publications throughout the years. To do so, one can refer the methods related to informetrics or scientometrics, that will be discussed next.
Given our purpose, we will highlight some of the most relevant indicators used in this field of knowledge, for which we will use some to try to prove the relevance stated above.
Informetrics can be defined as “the study of the application of mathematical methods to the objects of information science” (Nacke, 1979, p. 220), no matter the form or the origin (Egghe & Rousseau, 1988). Scientometrics, although related, can be defined specifically as “the quantitative methods of the research on the development of science as an informational process” (Nalimov & Mulcjenko, 1971, p. 2), being more related to science itself. Therefore, one can state that informetrics, being broader, may include the scientometrics, as well as bibliometrics and webometrics, discussion that we will not focus on here (Egghe, 2005). Scientometrics studies several aspects of science and technology and its evolution (Mendonça et al., 2022), however it is safe to state that the nuclear concept is “citation”, i.e., citing other research links the authors and their ideas, the journals and institutions, making it possible to quantitatively analyze them (Cole and Cole, 1973, Merton, 1973, Mingers & Leydesdorff, 2015, Aizenman et al., 2011). Citations are used to measure the quality and utilization for assessing individual researchers, but also departments or academic journals (Aizenman et al., 2011). When analyzing an author, we analyze all citations, but when analyzing departments or journals a window of three, five or ten years is defined (Mingers & Leydesdorff, 2015). Along with the
15 citations, that can be analyzed via the total number of citations and the citations per paper (cpp), the h-index is perceived as another good indicator (Costas & Bordons, 2007; Glanzel, 2006; Hirsch, 2005;
Mingers, 2008b; Mingers, et al., 2012). Finally, one should mention the rise of mapping and visualization, initiate by Garfield, Sher and Thorpie (1964) with the concept of “historiographs”
(Mingers & Leydesdorff, 2015), and the co-word analysis that checks pairs from titles, abstracts or keywords (Mingers & Leydesdorff, 2015). The research produced by central banks is usually
evaluated by focusing in the publications in refereed journals and the number of citations because of the perception that it is a good indicator it is useful in addressing relevant policy issues (Aizenman et al., 2011). The studies around citation show that they peak about three years after the publication date.
Even though citation plays a central role in scientometrics, it is not above criticism (see Weinstock, 1971; Cozzens, 1989; Day, 2014; Leydesdorff, 1998; Wouters, P., 2014; Chapman, 1989).
4.2. MARKOV CHAINS
Markov Chains are able to verify intra-probability transitions, with respect to past events, within categorical data sequences (Damásio, 2013; Damásio, 2018), with two key features: the outcome is one of a set of discrete states; the outcome depends only on the present state, and not on any past states.
It is possible to describe a Markov Chain as having a set of states, S = {s1,s2,…,sr}, the process starts in one of these states and moves successively from one state to another. If the chain is currently in state si, then it moves to state sj at the next step with a probability denoted by pij (transition probabilities), and this probability does not depend upon which states the chain was in before the current state. The process can remain in the state it is in, and this occurs with probability pii. An initial probability distribution, defined on S, specifies the starting state. Usually this is done by specifying a particular state as the starting state.
In the cases where s > 1 categorical time series (categories) interrelated, and the state of the future events of a category depends not only on its previous state (inter-transition) but also on another series’ previous states (intra-transitions) we get a Multivariate Markov Chain – which “allows intra and inter-probability transitions within and between categorical data sequences to be captured”
(Damásio, 2013, p. 7).
The choice regarding Markov Chains is linked to the fact that they have shown to be useful in
multiple scientific scenarios (e.g., economics (Mehran, 1989; Damásio et al., 2018), finance (Siu et al., 2005), forecasting (Damásio and Nicolau, 2014), the estimation of expected hitting times (Damásio, 2018; Nicolau, 2017)), and the fact that they are capable of modeling complex and non-linear phenomenon, which fit the current scenario (Damásio and Nicolau, 2020; Vasconcelos and Damásio, 2022).
This framework allows us to verify if Central Banks are proactive or reactive to economic changes, by allowing us to check the nonlinear causality between the various variables being considered, such as the volume of publications, citations, the economic cycles (via GDP) and the unemployment rates.
4.3. EXPLORATORY DATA ANALYSIS
The dataset contains information on Central Banks’ publications from 1927 to 2017. In total 40 Central banks are analyzed, being 19 from the Eurosystem, 9 from Non-Eurosystem, 8 from Non- European System of Central Bank, 3 are Non-European and 1 is the European Central Bank.
16
Bank Region Total Nr. of Banks
Eurosystem 19
Non-Eurosystem 9
Non- European System of Central Bank 8
Non-European 3
European Central Bank 1
Table 1: Number of Central Banks per Region
Even though information from 1927 is available, the time that as passed and the low number of records for several years will make us drop these records. Therefore, we will focus our study on the last 40 years (1980 onwards). This choice is also related to the fact that we can see an increasing trend on the publications volume starting around that year (total number of publications from 1927 to 1979 is 70), and, as seen prior, it’s stated by Goodhart (2010) as the start of the epoch known as the triumph of the markets.
To glimpse over the amount of information Central Bank’s distribute via publications, our dataset has a total of 6.845 publications in 956 distinct journals, accounting for a total of 15.474 total authors, 92.628 overall citations and an average H-index of 53.
Figure 1: Total number of citations, authors, publications and distinct journals, average h-index, from 1980 onwards
Below, we can check the distribution of these values by Central Bank, ordered by the number of publications. A first look shows that most publications are done by the European Central Bank, Bank of England and Bank of Italia, accounting for most of the citations and authors as well. Regarding the citations, a first note goes to the Bank of Spain with 9.933 total citations, despite being only the seventh Central Bank with most publications. Analyzing the H-index variable, one can state that the Central Banks with most publications also have high h-index average, with the exception of the Czech National Bank. These variables will be analyzed in more detail in a later stage of this dissertation.
92628
15474
6845
956 53
0 25000 50000 75000
# Citations # Authors # Publications # Journals Avg H-Index
Totals
17
Bank Name # Publications # Citations # Authors Avg H-Index # Journals
European Central Bank 1119 20937 2529 59.5 259
Bank of England 626 11389 1330 67.6 161
Bank of Italia 552 7010 1253 55.2 211
Deutsche Bundesbank 542 6111 1241 52.3 179
De Nederlandsche Bank 477 5596 1085 54.8 155
Bank of Finland 459 5063 1032 56.6 193
Bank of Spain 448 9933 1058 57.4 173
Bank of Greece 396 4623 941 51.5 196
Czech National Bank 387 2056 795 22.5 69
Banco de Portugal 281 3831 696 57.4 134
Oesterreichische Nationalbank 230 2516 524 48.1 127
Sveriges Riksbank 213 3328 481 72.9 93
Bank of Australia 210 1508 444 39.0 89
Narodowy Bank Polski 184 723 413 34.2 94
National Bank of Belgium 127 4279 344 59.4 79
Magyar Nemzeti Bank 54 405 127 46.4 41
Central Bank of Luxembourg 53 394 128 52.9 40
Bank of Russia 51 188 197 27.8 34
Banka Slovenije 39 118 94 33.4 32
Danmarks Nationalbank 38 253 78 45.2 31
Central Bank of Ireland 34 447 74 45.6 26
Swiss National Bank 33 319 43 75.2 19
Croatian National Bank 32 157 67 22.6 25
Bank of Estonia 31 152 69 28.8 24
National Bank of Serbia 27 119 66 26.6 16
Central Bank of Montenegro 25 30 36 3.1 5
National Bank of Romania 24 32 48 15.8 13
Central Bank of Iceland 22 111 35 64.3 18
Central Bank of Argentina 21 99 44 33.8 18
Bank of Latvia 20 29 35 26.3 14
Central Bank of Cyprus 20 191 38 60.6 18
Central Bank of Malta 12 17 14 23.8 12
Národná banka Slovenska 12 16 16 15.8 5
Bank of Lithuania 11 5 20 46.1 9
Bulgarian National Bank 11 23 21 16.2 8
Norges Bank 11 552 22 55.2 9
Bank of Albania 9 64 22 46.9 9
Central Bank (Northern Cyprus) 2 3 6 62.0 1
Central Bank of Egypt 1 1 4 55.0 1
National Bank of Moldova 1 0 4 11.0 1
18 Table 2: Overview on Central Bank’s publications variables
The field of knowledge distribution of the 6845 publications included in the dataset is mainly in the Economics field (5858) and Sociology (934). As previously stated, the publications were signed by 15474 authors (average of 2.26 authors per publication), being 9150 linked with bank institutions, and the rest external to them. Regarding the citations, the dataset contains publications with 0 citations, and the publication most cited accounts 3573 citations. The average number of citations is 13.53.
A graphical relationship between the number of citations and publications is shown below, showing that Central Banks with most publications also account for most of the citations (bar with lighter blue), as is the case of the European Central Bank and Bank of England. Bank of Italy is surpassed by the Bank of Spain in number of citations, despite being the third one with most publications.
Figure 2: Central Banks total citations and publications relationship
To further detail our analysis, several regions were considered. The Eurosystem region accounts for all Central Banks belonging to the Eurosystem; the Non-Eurosystem region has European Central Banks that do not belong to the Eurosystem but belong to the European System of Central Banks; the Non-European region holds the banks who are not European; the European Central Bank, although not a specific region, was set on a specific category due to the high volume of publications and representativeness on the dataset. The region with the highest number of publications is the
Eurosystem (3746, 54.7%), followed by the Non-Eurosystem (1569, 22.9%) and the European Central Bank (1119, 16.3%).
Banco de Portugal Bank of Albania Bank of Australia Bank of England Bank of Estonia Bank of Finland Bank of Greece Bank of Italia Bank of Latvia Bank of Lithuania Bank of Russia Bank of Spain Banka Slovenije Bulgarian National Bank Central Bank (Northern Cyprus) Central Bank of Argentina Central Bank of Cyprus Central Bank of Egypt Central Bank of Iceland Central Bank of Ireland Central Bank of Luxembourg Central Bank of Malta Central Bank of Montenegro Croatian National Bank Czech National Bank Danmarks Nationalbank De Nederlandsche Bank Deutsche Bundesbank European Central Bank Magyar Nemzeti Bank Národná banka Slovenska Narodowy Bank Polski National Bank of Belgium National Bank of Moldova National Bank of Romania National Bank of Serbia Norges Bank Oesterreichische Nationalbank Sveriges Riksbank Swiss National Bank
0 300 600 900
Number of Publications
Central Bank's Citations 0
5000 10000 15000 20000
19
Bank Region Name Bank Region Publications % Distribution
Eurosystem 3746 54.7
Non-Eurosystem 1569 22.9
European Central Bank 1119 16.3
Non-European 232 3.4
Non- European System of Central Bank 179 2.6
Table 3: Total Number of Central Banks publications per region
Regarding the publications and their positioning in the scientific community analyzed via the
quartiles in which the journals they were published on occupy, a detailed analysis is provided below.
In summary, most publications are present in first quartile journals (3063 in total) regarding most of the Central Banks. Regarding second and third quartile journals, there are, respectively, 2192 and 1403 publications.
Central Bank 1st quartile 2nd quartile 3rd quartile 4th quartile
European Central Bank 613 344 189 57
Bank of England 350 183 107 38
Bank of Italia 293 160 87 52
Deutsche Bundesbank 246 185 99 36
Bank of Spain 231 147 58 37
De Nederlandsche Bank 231 165 102 32
Bank of Finland 218 164 86 38
Banco de Portugal 147 98 39 16
Bank of Greece 125 158 105 47
Sveriges Riksbank 125 78 31 6
Oesterreichische Nationalbank 90 81 50 21
National Bank of Belgium 73 30 15 13
Bank of Australia 48 74 78 12
Czech National Bank 47 62 183 106
Narodowy Bank Polski 39 72 58 17
Magyar Nemzeti Bank 34 13 9 3
Central Bank of Luxembourg 26 21 8 4
Danmarks Nationalbank 17 13 4 5
Swiss National Bank 16 16 6 NA
Central Bank of Ireland 14 17 9 2
Banka Slovenije 10 11 15 8
Central Bank of Cyprus 10 7 5 NA
Central Bank of Iceland 10 9 3 1
Central Bank of Argentina 8 5 3 5
National Bank of Serbia 7 14 2 4
Bank of Albania 5 1 2 2
Bank of Estonia 5 10 13 5
Bank of Lithuania 4 4 4 NA
Central Bank of Malta 4 7 1 2
Norges Bank 4 4 5 2
Bank of Latvia 3 9 5 4
Bank of Russia 3 8 9 2
Croatian National Bank 3 5 6 14
20
National Bank of Romania 3 14 3 5
Bulgarian National Bank 1 3 4 3
Table 4: Total Number of publications distribution per journal quartile
Figure 3: Number of publications per journal quartile
The Economic and Sociologic fields account for most of the publications. Therefore, below is the distribution regarding publications made in Economical field journals.
Central Bank 1st quartile 2nd quartile 3rd quartile 4th quartile
European Central Bank 506 284 155 44
Bank of England 300 155 85 33
Bank of Italia 211 121 57 45
Deutsche Bundesbank 194 151 60 32
Bank of Spain 192 116 44 35
De Nederlandsche Bank 183 135 76 25
Bank of Finland 163 136 60 34
Banco de Portugal 118 71 31 13
Sveriges Riksbank 105 62 23 4
National Bank of Belgium 63 25 14 10
Oesterreichische Nationalbank 63 59 40 20
Banco de Portugal Bank of Albania Bank of Australia Bank of England Bank of Estonia Bank of Finland Bank of Greece Bank of Italia Bank of Latvia Bank of Lithuania Bank of Russia Bank of Spain Banka Slovenije Bulgarian National Bank Central Bank of Argentina Central Bank of Cyprus Central Bank of Iceland Central Bank of Ireland Central Bank of Luxembourg Central Bank of Malta Croatian National Bank Czech National Bank Danmarks Nationalbank De Nederlandsche Bank Deutsche Bundesbank European Central Bank Magyar Nemzeti Bank Narodowy Bank Polski National Bank of Belgium National Bank of Romania National Bank of Serbia Norges Bank Oesterreichische Nationalbank Sveriges Riksbank Swiss National Bank
0 200 400 600
Publications Total
Journal quartile 1st quartile 2nd quartile 3rd quartile 4th quartile
21
Bank of Greece 61 116 75 38
Czech National Bank 43 55 172 104
Bank of Australia 38 61 71 10
Magyar Nemzeti Bank 25 10 7 2
Narodowy Bank Polski 24 59 48 17
Central Bank of Luxembourg 22 17 6 4
Danmarks Nationalbank 14 12 4 3
Swiss National Bank 13 13 3 NA
Central Bank of Ireland 10 11 9 2
Central Bank of Cyprus 8 7 1 NA
Bank of Albania 5 1 2 1
Banka Slovenije 5 8 14 6
Bank of Estonia 4 7 11 4
Bank of Lithuania 4 3 3 NA
Central Bank of Argentina 4 4 3 5
Central Bank of Iceland 4 5 1 1
National Bank of Serbia 4 13 2 3
Bank of Latvia 2 7 4 4
Central Bank of Malta 2 4 1 2
Norges Bank 2 4 3 1
Bulgarian National Bank 1 3 4 3
Croatian National Bank 1 5 3 7
National Bank of Romania 1 14 1 3
Bank of Russia NA 8 2 1
Central Bank (Northern Cyprus) NA 2 NA NA
Central Bank of Montenegro NA NA NA 21
Národná banka Slovenska NA NA 5 6
National Bank of Moldova NA 1 NA NA
Table 5: Total Number of publications distribution per journal’s quartile, economic field
