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Fear of Novelty: A Model of Scientific Discovery with Strategic Uncertainty
Abstract
This paper analyzes the production of fundamental research as a coordination game played by scholars. In the model, scholars decide to adopt a new idea only if they believe that a critical mass of peers is following a similar research strategy. If researchers observe only a noisy idiosyncratic signal of the true scientific potential of a new idea, we show that the game presents a single threshold equilibrium. In this environment, fundamental research proceeds with large structural breaks followed by long periods of time in which new ideas are unsuccessful. The likelihood of a new idea emerging depends on various parameters, including the rewards of working in the old paradigm, the critical mass of researchers required to create a new school of thought and scholars' ability to properly assess the scientific value of new ideas. (JEL O31, C72, A14)
... This pursuit adheres to the principle of "no free lunch". Owing to the inherent tension between accumulating academic accomplishments and fostering innovation, scientists grapple with the delicate task of balancing conventional and pioneering research fields [3]. Diverse strategies employed in the process of topic selection yield markedly distinct outcomes, impacting both personal development [4][5][6]and scientific progress [7]. ...
The selection of research topics by scientists can be viewed as an exploration process conducted by individuals with cognitive limitations traversing a complex cognitive landscape influenced by both individual and social factors. While existing theoretical investigations have provided valuable insights, the intricate and multifaceted nature of modern science hinders the implementation of empirical experiments. This study leverages advancements in Geographic Information System (GIS) techniques to investigate the patterns and dynamic mechanisms of topic-transition among scientists. By constructing the knowledge space across 6 large-scale disciplines, we depict the trajectories of scientists' topic transitions within this space, measuring the flow and distance of research regions across different sub-spaces. Our findings reveal a predominantly conservative pattern of topic transition at the individual level, with scientists primarily exploring local knowledge spaces. Furthermore, simulation modeling analysis identifies research intensity, driven by the concentration of scientists within a specific region, as the key facilitator of topic transition. Conversely, the knowledge distance between fields serves as a significant barrier to exploration. Notably, despite potential opportunities for breakthrough discoveries at the intersection of subfields, empirical evidence suggests that these opportunities do not exert a strong pull on scientists, leading them to favor familiar research areas. Our study provides valuable insights into the exploration dynamics of scientific knowledge production, highlighting the influence of individual cognition, social factors, and the intrinsic structure of the knowledge landscape itself. These findings offer a framework for understanding and potentially shaping the course of scientific progress.
... This pursuit adheres to the principle of "no free lunch". Owing to the inherent tension between accumulating academic accomplishments and fostering innovation, scientists grapple with the delicate task of balancing conventional and pioneering research fields [3]. Diverse strategies employed in the process of topic selection yield markedly distinct outcomes, impacting both personal development [4][5][6]and scientific progress [7]. ...
The selection of research topics by scientists can be viewed as an exploration process conducted by individuals with cognitive limitations traversing a complex cognitive landscape influenced by both individual and social factors. While existing theoretical investigations have provided valuable insights, the intricate and multifaceted nature of modern science hinders the implementation of empirical experiments. This study leverages advancements in deep learning techniques to investigate the patterns and dynamic mechanisms of topic-transition among scientists. By constructing the knowledge space across 6 large-scale disciplines, we depict the trajectories of scientists' topic transitions within this space, measuring the flow and distance of research regions across different sub-spaces. Our findings reveal a predominantly conservative pattern of topic transition at the individual level, with scientists primarily exploring local knowledge spaces. Furthermore, simulation modeling analysis identifies research intensity, driven by the concentration of scientists within a specific region, as the key facilitator of topic transition. Conversely, the knowledge distance between fields serves as a significant barrier to exploration. Notably, despite potential opportunities for breakthrough discoveries at the intersection of subfields, empirical evidence suggests that these opportunities do not exert a strong pull on scientists, leading them to favor familiar research areas. Our study provides valuable insights into the exploration dynamics of scientific knowledge production, highlighting the influence of individual cognition, social factors, and the intrinsic structure of the knowledge landscape itself. These findings offer a framework for understanding and potentially shaping the course of scientific progress.
... Perhaps it will. In academic works, people usually fear novelty for a while, as discussed by (Besancenot and Vranceanu (2015). These authors point out that progress in the advancement of knowledge typically proceeds in stages. ...
Released less than five months ago, ChatGPT became the center of attention of scholars worldwide. This artificial intelligence (AI) language model has over 100 million subscribers worldwide, generating many discussions concerning its accuracy, advantages, and threats to science and education. Its accuracy in law, linguistics, mathematics, and medicine has already been evaluated. Most results suggest that ChatGPT could generate a passing grade in these domains. However, its performance in sports science and psychology has yet to be tested. The large amount of information in this general area may yield more accurate performance. Still, specific subjects in the field, with controversial research findings, can lead to significant errors, which teachers and researchers could quickly spot. In this study, ChatGPT was tested on its accuracy on exercise addiction, a sports science and psychology subject associated with more than 1,000 publications. ChatGPT gave several correct answers to 20 questions but failed the test with 45%. Its performance was like in other already tested subjects. However, when prompted to write a general introductory editorial on AI's role in sports, ChatGPT performed well. Plagiarism detectors could not identify the AI-originated text, but AI detectors did. Therefore, it can be concluded that the system does a relatively good job on general issues but needs further development in more specific areas. Students and scholars cannot rely on ChatGPT to do their job. Still, future versions could yield dilemmas of originality since the system does not provide information for its source(s) of information.
... Perhaps it will. In academic works, people usually fear novelty for a while, as discussed by (Besancenot and Vranceanu (2015). These authors point out that progress in the advancement of knowledge typically proceeds in stages. ...
Released less than fve months ago, ChatGPT became the center of attention of scholars worldwide. This artifcial intelligence (AI) language model has over 100 million subscribers worldwide, generating many discussions concerning its accuracy, advantages, and threats to science and education. Its accuracy in law, linguistics, mathematics, and medicine has already been evaluated. Most results suggest that ChatGPT could generate a passing grade in these domains. However, its performance in sports science and psychology has yet to be tested. The large amount of information in this general area may yield more accurate performance. Still, specifc subjects in the feld, with controversial research fndings, can lead to signifcant errors, which teachers and researchers could quickly spot. In this study, ChatGPT was tested on its accuracy on exercise addiction, a sports science and psychology subject associated with more than 1,000 publications. ChatGPT gave several correct answers to 20 questions but failed the test with 45%. Its performance was like in other already tested subjects. However, when prompted to write a general introductory editorial on AI’s role in sports, ChatGPT performed well. Plagiarism detectors could not identify the AI-originated text, but AI detectors did. Therefore, it can be concluded that the system does a relatively good job on general issues but needs further development in more specifc areas. Students and scholars cannot rely on ChatGPT to do their job. Still, future versions could yield dilemmas of originality since the system does not provide information for its source(s) of information. Keywords: artifcial intelligence; computers, information; language model; plagiarism.
... Perhaps it will. In academic works, people usually fear novelty for a while, as discussed by (Besancenot and Vranceanu (2015). These authors point out that progress in the advancement of knowledge typically proceeds in stages. ...
Released less than three months ago, ChatGPT became the center of attention of scholars around the world. This artificial intelligence (AI) language model has over 100 million subscribers worldwide and generates many discussions concerning its accuracy, advantages, and threats to science and education. Its accuracy in law, linguistics, mathematics, and medicine has already been evaluated. Most results suggest that ChatGPT could generate a passing grade in these domains. Its performance in combined subjects or social sciences has yet to be tested. The large amount of information in this general area may yield more accurate performance. Still, specific subjects in the field, with controversial research findings, can lead to significant errors, which teachers and researchers could quickly spot. In this study, ChatGPT was tested on its accuracy on exercise addiction, a subject in sports sciences and psychology associated with more than 1,000 publications. ChatGPT gave several correct answers to 20 questions but failed the test with 45%. Its performance was like in other already tested subjects. However, when prompted to write a general introductory editorial on AI’s role in sports, ChatGPT performed well. Plagiarism detectors could not identify the AI-originated text, but AI detectors did. Therefore, it can be concluded that the system does a relatively good job on general issues but needs further development in more specific areas. Students and scholars cannot rely on ChatGPT to do their job. Still, future versions could yield dilemmas of originality since the system does not provide information for its source(s) of information.
... This focus on impact in science policy has recently been decried by many, including Alberts (2013) and Osterloh and Frey (2015). For the theory of knowledge production implies that science policy decisions should be guided by not just the influence of scientific work but also what kind of science is being pursued -novel or conventional (Kuhn 1962;Besancenot and Vranceanu 2015). ...
A key decision in scientific work is whether to build on novel or well-established ideas. Because exploiting new ideas is often harder than more conventional science, novel work can be especially dependent on interactions with colleagues, the training environment, and ready access to potential collaborators. Location may thus influence the tendency to pursue work that is close to the edge of the scientific frontier in the sense that it builds on recent ideas. We calculate for each nation its position relative to the edge of the scientific frontier by measuring its propensity to build on relatively new ideas in biomedical research. Text analysis of 20+ million publications shows that the United States and South Korea have the highest tendencies for novel science. China has become a leader in favoring newer ideas when working with basic science ideas and research tools, but is still slow to adopt new clinical ideas. Many locations remain far behind the leaders in terms of their tendency to work with novel ideas, indicating that the world is far from flat in this regard.
... Scientific progress depends on the openness of a scientific community to try out new ideas systematically and continuously (5)(6)(7)(8)(34)(35)(36). When new ideas are first born, they are often raw and poorly understood and only develop into transformative ideas (if at all) through revision and debate on their merits. ...
The National Institutes of Health (NIH) plays a critical role in funding scientific endeavors in biomedicine. Funding innovative science is an essential element of the NIH’s mission, but many have questioned the NIH’s ability to fulfill this aim. Based on an analysis of a comprehensive corpus of published biomedical research articles, we measure whether the NIH succeeds in funding work with novel ideas, which we term edge science. We find that edge science is more often NIH funded than less novel science, but with a delay. Papers that build on very recent ideas are NIH funded less often than are papers that build on ideas that have had a chance to mature for at least 7 y. We have three further findings. First, the tendency to fund edge science is mostly limited to basic science. Papers that build on novel clinical ideas are not more often NIH funded than are papers that build on well-established clinical knowledge. Second, novel papers tend to be NIH funded more often because there are more NIH-funded papers in innovative areas of investigation, rather than because the NIH funds innovative papers within research areas. Third, the NIH’s tendency to have funded papers that build on the most recent advances has declined over time. In this regard, NIH funding has become more conservative despite initiatives to increase funding for innovative projects. Given our focus on published papers, the results reflect both the funding preferences of the NIH and the composition of the applications it receives.
... The breakthrough Economist J.M. Keynes said that worldly wisdom teaches that it is better for reputation to fail conventionally than to succeed unconventionally (Keynes, 1937). Novel research methodologies are challenging and often ignored because of fear of rejection by accepted conventions for publication of research which Besancenot and Vranceanu (2015) argue is conventional and a conservative or risk-averse approach to research. Novel research methods do challenge the status quo. ...
Design Science as a research method offers the researcher a viable way of improving the outcome of research for both the researcher and the researched. In Construction and Engineering there is almost always the intention to better understand and then improve processes, materials or outcomes. Using two case studies of research adopting Design Science, one in Engineering and one in Construction, the advantages of the use of Design Science as the research method are highlighted. The desire to improve construction and engineering through a better understanding of “practical wisdom” or domain expertise through use of the concept of phronesis enables the researcher to build solutions that reflect the practices and processes practitioners actually need, enhancing their own knowledge through the collaborative research process and enabling the researcher to better reflect on what the research produced.
Purpose: The edge Factor index provides a new evaluation for journal articles in order to evaluate the novelty and innovation of journal articles. In other words, it determines the novel ideas close to the edge of scientific frontiers, and its results can be used as a complementary tool in planning and making policies to evaluate journals in various scientific fields. Based on this, the purpose of this article is to evaluate the scientific articles of the nuclear technology journals in the INIS database in order to provide a new evaluation of these journals based on the measuring the novelty and innovation of the articles using the Edge Factor index from 2001 to 2020.
Methods: This is application research conducted by scientometric methodology and data mining techniques. The population comprises all nuclear science and technology records from 2001 to 2020, retrieved from the INIS database. The sources of data gathering included Journal Citation Report (J.C.R.) and the International Nuclear Information System (INIS) database, and its specialized thesaurus. Also, in this research in order to reach the goals of the research, a list of selected journals in the field of nuclear science and technology was needed. This list was prepared using the 2020 edition of the journal citation report database. Using the browsing by category in this database, a list of 29 selected journals in the field of nuclear science and technology based on the impact factor along with the data of the other citation indices of the journals, including the Eigen factor, Immediacy Index, and Article Influence Score were extracted. Data was analyzed using Excel 2021 and social science statistical software (SPSS) version 23, and the Shapiro–Wilk test, Pearson Correlation test, and Spearman Correlation test were conducted.
Findings: Results indicate that 79,879 articles had been retrieved from the INIS database in nuclear technology, from 2001 to 2020. The findings of measuring articles' vintage revealed that most articles with novel ideas were published in 2018 among the surveyed period. The results of journals' ranking based on measuring Edge Factor revealed that the "Science and Technology of Nuclear Installations" journal was at first. Furthermore, there was no significant correlation between the Edge Factor and the citation-based indexes, including the Impact Factor, Eigen factor, Immediacy Index, and Article Influence Score.
Conclusion: Journals should publish articles that are at the frontier of science in order to science advancement. Using content-based indexes, including the Edge Factor as complementary indexes in journals' evaluation can help to design evaluation and ranking systems that capture not just influence but also what kind of science -novel science or conventional science- is being pursued. So, it is better to use other content-based indexes, including the Edge Factor as complementary indexes in journals' evaluation.
A key decision in scientific work is whether to build on novel or well-established ideas. Because exploiting new ideas is often harder than more conventional science, novel work can be especially dependent on interactions with colleagues, the training environment, and ready access to potential collaborators. Location may thus influence the tendency to pursue work that is close to the edge of the scientific frontier in the sense that it builds on recent ideas. We calculate for each nation its position relative to the edge of the scientific frontier by measuring its propensity to build on relatively new ideas in biomedical research. Text analysis of 20+ million publications shows that the United States and South Korea have the highest tendencies for novel science. China has become a leader in favoring newer ideas when working with basic science ideas and research tools, but is still slow to adopt new clinical ideas. Many locations remain far behind the leaders in terms of their tendency to work with novel ideas, indicating that the world is far from flat in this regard.
The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)—these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists’ incentives to pursue innovative work.
Global games of regime change—coordination games of incomplete information in which a status quo is abandoned once a sufficiently large fraction of agents attack it— have been used to study crises phenomena such as currency attacks, bank runs, debt crises, and political change. We extend the static benchmark examined in the literature by allowing agents to take actions in many periods and to learn about the underlying fundamentals over time. We first provide a simple recursive algorithm for the characterization of monotone equilibria. We then show how the interaction of the knowledge that the regime survived past attacks with the arrival of information over time, or with changes in fundamentals, leads to interesting equilibrium properties. First, multiplicity may obtain under the same conditions on exogenous information that guarantee uniqueness in the static benchmark. Second, fundamentals may predict the eventual fate of the regime but not the timing or the number of attacks. Finally, equilibrium dynamics can alternate between phases of tranquility—where no attack is possible—and phases of distress—where a large attack can occur—even without changes in fundamentals.
In April 2013, all of the major academic publishing houses moved thousands of journal titles to an original hybrid model, under which authors of accepted papers can choose between an expensive open access track and the traditional track available only to subscribers. This paper argues that authors might use publication strategy as a quality signaling device. The imperfect information game between authors and readers presents several types of Perfect Bayesian Equilibria, including a separating equilibrium in which only authors of high quality papers are driven toward the open access track. The publishing house will choose the open-access publication fee that supports the emergence of the highest return equilibrium. Journal structures will evolve over time according to the journals' accessibility - quality profiles.
This chapter examines the contributions that economists have made to the study of science and the types of contributions the profession is positioned to make in the future. Special emphasis is placed on the public nature of knowledge and characteristics of the reward structure that encourage the production and sharing of knowledge. The role that cognitive and noncognitive resources play in discovery is discussed as well as the costs of resources used in research. Different models for the funding of research are presented. The chapter also discusses scientific labor markets and the extreme difficulty encountered in forecasting the demand for and supply of scientists. The chapter closes with a discussion of the relationship of scientific research to economic growth and suggestions for future research.
Preemption games are widely used to model economic problems such as patent races. We introduce private information into these
games and allow for this information to stochastically change over time. This reflects, e.g. how R&D competitors improve their innovations over time and keep these innovations secret before patenting them. The analysis
initially appears intractable because of the complexity of the equilibrium updating of beliefs on opponents' information.
However, we demonstrate the existence of a class of equilibria and calculate these equilibria in closed form. We find that
the expected durations in these equilibria are longer than when players' information is public but, in some cases, shorter
than in the collusive outcome. Hence, R&D secrecy slows down innovation disclosure.
This article engages with problems that are usually opaque: What trajectories do scientific debates assume, when does a scientific community consider a proposition to be a fact, and how can we know that? We develop a strategy for evaluating the state of scientific contestation on issues. The analysis builds from Latour's black box imagery, which we observe in scientific citation networks. We show that as consensus forms, the importance of internal divisions to the overall network structure declines. We consider substantive cases that are now considered facts, such as the carcinogenicity of smoking and the non-carcinogenicity of coffee. We then employ the same analysis to currently contested cases: the suspected carcinogenicity of cellular phones, and the relationship between vaccines and autism. Extracting meaning from the internal structure of scientific knowledge carves a niche for renewed sociological commentary on science, revealing a typology of trajectories that scientific propositions may experience en route to consensus.
Since the work of Thomas Kuhn, the role of social factors in the scientific enterprise has been a major concern in the philosophy and history of science. In particular, conformity effects among scientists have been used to question whether science naturally progresses over time. Using neoclassical economic reasoning, this paper develops a formal model of scientific theory choice which incorporates social factors. Our results demonstrate that the influence of social factors on scientific progress is more complex than previously thought. The patterns of theory choice predicted by the model seem consistent with historical episodes of theory change.
This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
This book was originally published by Macmillan in 1936. It was voted the top Academic Book that Shaped Modern Britain by Academic Book Week (UK) in 2017, and in 2011 was placed on Time Magazine's top 100 non-fiction books written in English since 1923. Reissued with a fresh Introduction by the Nobel-prize winner Paul Krugman and a new Afterword by Keynes’ biographer Robert Skidelsky, this important work is made available to a new generation.
The General Theory of Employment, Interest and Money transformed economics and changed the face of modern macroeconomics. Keynes’ argument is based on the idea that the level of employment is not determined by the price of labour, but by the spending of money. It gave way to an entirely new approach where employment, inflation and the market economy are concerned.
Highly provocative at its time of publication, this book and Keynes’ theories continue to remain the subject of much support and praise, criticism and debate. Economists at any stage in their career will enjoy revisiting this treatise and observing the relevance of Keynes’ work in today’s contemporary climate.
In April 2013, all of the major academic publishing houses moved thousands of journal titles to an original hybrid model, under which authors of accepted papers can choose between an expensive open access (OA) track and the traditional track available only to subscribers. This paper argues that authors might now use a publication strategy as a quality signaling device. The imperfect information game between authors and readers presents several types of Perfect Bayesian Equilibria, including a separating equilibrium in which only authors of high-quality papers are driven toward the open access track. The publishing house should choose an open-access publication fee that supports the emergence of the highest return equilibrium. Journal structures will evolve over time according to the journals’ accessibility and quality profiles.
Most theories in economics and finance predict what people will do, given what they know about the world around them. But what do people know about their environments? The study of information choice seeks to answer this question, explaining why economic players know what they know--and how the information they have affects collective outcomes. Instead of assuming what people do or don't know, information choice asks what people would choose to know. Then it predicts what, given that information, they would choose to do. In this textbook, Laura Veldkamp introduces graduate students in economics and finance to this important new research. The book illustrates how information choice is used to answer questions in monetary economics, portfolio choice theory, business cycle theory, international finance, asset pricing, and other areas. It shows how to build and test applied theory models with information frictions. And it covers recent work on topics such as rational inattention, information markets, and strategic games with heterogeneous information. Illustrates how information choice is used to answer questions in monetary economics, portfolio choice theory, business cycle theory, international finance, asset pricing, and other areas Teaches how to build and test applied theory models with information frictions Covers recent research on topics such as rational inattention, information markets, and strategic games with heterogeneous information.
Scitation is the online home of leading journals and conference proceedings from AIP Publishing and AIP Member Societies
This paper shows how to solve global games applied to macroeconomics and finance. We ascertain the roles of public and private information for the determination of a unique equilibrium, and discuss the informative role of market prices. We examine the impact of public information on social welfare, comparing models with and without complementarities at the aggregate level.
This paper analyses the consequences of young researchers' scientific choice on the dynamics of sciences. We develop a simple two state mean field game model to analyse the competition between two paradigms based on Kuhn's theory of scientific revolution. The dynamics of the model are driven by the scientific choice of young researchers at the beginning of their career. Despite the possibility of multiple equilibria, the model exhibits at least one stable solution in which both para digms coexist. The occurrence of shocks on the parameters may induce the shift from one paradigm to the other. During this shift, researchers' choice is proved to be having a great impact on the evolution of sciences.
Increasing the “truth per dollar” of money spent on science is one legitimate long-run goal of the economics of science. But before this goal can be achieved, we need to increase our knowledge of the successes and failures of past and current reward structures of science. This essay reviews what economists have learned about the behavior of scientists and the reward structure of science. One important use of such knowledge will be to help policy-makers create a reward structure that is more efficient in the future.
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We describe and contrast three diierent measures of an institu-tion's credit risk. \Insolvency risk" is the conditional probability of default due to deterioration of asset quality if there is no run by short term creditors. \Total credit risk" is the unconditional probability of default, either because of a (short term) creditor run or (long run) asset insolvency. \Illiquidity risk" is the diierence between the two, i.e., the probability of a default due to a run when the institution would otherwise have been solvent. We discuss how the three kinds of risk vary with balance sheet composition. We provide a formula for illiquidity risk and show that it is (i) decreasing in the \liquidity ratio" -the ratio of realizable cash on the balance sheet to short term liabilities; (ii) increasing in the \outside option ratio" -a measure of the opportunity cost of the funds used to roll over short term liabil-ities; and (iii) increasing in the \fundamental risk ratio" -a measure of ex post variance of the asset portfolio. We thank Pete Kyle, Kohei Kawaguchi and Yusuke Narita for their comments as discussants on this paper. We are grateful to Sylvain Chassang, Masazumi Hattori, Chester Spatt, Wei Xiong and workshop and conference participants at many institutions for their comments on earlier versions of this paper; and to Thomas Eisenbach for research assitance on the project. We acknowledge support from the NSF grant #SES-0648806.
Summary This article asserts that any theory or research on fads or fashions in science has to answer three questions clearly and unambiguously. What defines "science"? What defines a "scientific fad" or a "scientific fashion"? What might facilitate the occurrence of scientific fads or fashions so defined? To illustrate this argument, this article critically examines the answers to three questions suggested by Starbuck's article: [Starbuck, W. H. (2009). The constant causes of never-ending faddishness in the behavioral and social sciences. Scandinavian Journal of Management]. The article concludes by discussing the challenges that certain scholars can pose to other scholars who courageously raise the possibility that fads or fashions might hold sway in the behavioral or social sciences.
This paper deals in a Stackelberg differential game with Kuhn (1962) ideas of paradigm depletion and resiliency. Paradigm is considered as potential knowledge, as a stock of ideas that can be harvested to produce science. The results are: (i) paradigm depletion can be optimal, (ii) the optimal editor's shadow price of potential knowledge must be non‐positive, if it is positive, the editor is a keeper of the orthodoxy rather than a scientist, (iii) editor's and/or researcher's impatience is bad for science, and (iv) in equilibrium editor's behavior does not matter for research effort, while only editor's behavior matter for the paradigm.
This paper analyzes the implications of currency crises in a model with unique equilibrium. Starting from a typical multiple equilibria model with self-fulfilling expectations we introduce noisy information, following Morris/Shin (1999). Under certain conditions for the noise parameter, all equilibria but one are eliminated so that we are able to derive comparative statics and subsequent policy devices. We can show that if the a priori expected fundamental state of the economy is good, there is an incentive for the government to disseminate very precise information. However, a high precision of public information increases the danger of an attack if ex-ante expected fundamentals are bad. Moreover, we find that the influence of private information's precision is exactly the reverse.
The General Theory of Employment, Interest, and Money / John Maynard Keynes Note: The University of Adelaide Library eBooks @ Adelaide.
This paper studies the dynamics of fundamental research. We develop a simple model where researchers allocate their effort between improving existing fields and inventing new ones. A key assumption is that scientists derive utility from recognition from other scientists. We show that the economy can be either in a regime where new fields are constantly invented, and then converges to a steady state, or in a cyclical regime where periods of innovation alternate with periods of exploitation. We characterize the cyclicals dynamics of the economy, show that indeterminacy may appear, and establish some comparative statics and welfare implications.
Creditors of a distressed borrower face a coordination problem. Even if the fundamentals are sound, fear of premature foreclosure by others may lead to pre-emptive actions, undermining the project. Recognition of this problem lies behind corporate bankruptcy provisions across the world, and it has been identified as a culprit in international financial crises, but has received scant attention from the literature on debt pricing. Without common knowledge of fundamentals, the incidence of failure is uniquely determined provided that private information is precise enough. This affords a way to price the coordination failure. There are two further conclusions. First, coordination is more difficult to sustain when fundamentals deteriorate. Thus, when fundamentals deteriorate, the onset of crisis can be very swift. Second, ¶transparency¶ in the sense of greater provision of information to the market does not generally mitigate the coordination problem.
Even though self-fulfilling currency attacks lead to multiple equilibria when fundamentals are common knowledge, the authors demonstrate the uniqueness of equilibrium when speculators face a small amount of noise in their signals about the fundamentals. This unique equilibrium depends not only on the fundamentals but also on financial variables, such as the quantity of hot money in circulation and the costs of speculative trading. In contrast to multiple equilibrium models, the authors' model allows analysis of policy proposals directed at curtailing currency attacks. Copyright 1998 by American Economic Association.
We report on a two-stage experiment in which i) we first elicit the social network within a section of undergraduate students and ii) we then measure their altruistic attitudes by means of a standard Dictator game. We observe that more socially integrated subjects are also more altruistic, as betweenness centrality and reciprocal degree are positively correlated with the level of giving, even after controlling for framing and social distance, which have been shown to signicantly affect giving in previous studies. Our findings suggest that social distance and social integration are complementary determinants of altruistic behavior.
Since the classic work of Feyerabend and Kuhn, the role of social factors in the scientific enterprise has been a major concern in the philosophy and history of science. In particular, the presence of social factors such as the desire for prestige or pressures to conform to accepted ideas, have been regarded as reasons to question whether science naturally progresses towards more and more accurate approximations of reality. In this paper, we propose a formal model of theory choice which incorporates private and social influences. We provide a characterization of the interaction of social factors with theory choice. Our results demonstrate that the influence of social factors on scientific progress is far more complex than is typically assumed. In particular, we provide conditions under which social influences actually enhance the rate at which a superior theory replaces its inferior predecessor.
L'int�r�t de l'approche par les jeux globaux ("global games'') est pr�cis�ment d'ancrer les anticipations sur des variables exog�nes r�elles. On peut ainsi garder l'aspect auto-r�alisateur des anticipations mais en restaurant l'unicit� de l'�quilibre et donc un meilleur pouvoir pr�dictif du mod�le. Nous illustrons ces m�canismes sur deux exemples. Le premier a trait au choix r�sidentiel d'agents qui ont une pr�f�rence "identitaire''. Le second a trait � la contagion de paniques bancaires d'un pays � un autre. De mani�re plus g�n�rale, tous les jeux qui pr�sentent des compl�mentarit�s strat�giques sont susceptibles d'�tre analys�s au moyen des techniques des "global games''. Il convient toutefois de rappeler que les techniques utilis�es demeurent assez sp�cifiques: l'incertitude strat�gique porte essentiellement sur les croyances de premier degr� des autres acteurs. Or, si de mani�re plus g�n�rale on suppose que cette incertitude peut porter sur des ordres plus �lev�s, les conclusions des mod�les peuvent changer. Ainsi, Weinstein et Yildiz (2004) montrent que dans un oligopole de Cournot, il y a une tr�s grande multiplicit� d'�quilibres si on suppose que l'incertitude porte sur les croyances de niveaux suffisamment �lev�s.
Crises are volatile times when endogenous sources of information are closely monitored. We study the role of information in crises by introducing a financial market in a coordination game with imperfect information. The asset price aggregates dispersed private information acting as a public noisy signal. In contrast to the case with exogenous information, our main result is that uniqueness may not obtain as a perturbation from perfect information: multiplicity is ensured with small noise. In addition, we show that: (a) multiplicity may emerge in the financial price itself; (b) less noise may contribute toward nonfundamental volatility even when the equilibrium is unique; and (c) similar results obtain for a model where individuals observe one another?s actions, highlighting the importance of endogenous information more generally. (JEL D53, D82, D83)
The authors asked the world's leading economists to describe instances in which journals rejected their articles. More than sixty essays, by a broadly diverse group that includes fifteen Nobel Prize winners, indicate that most have suffered publication rejection, often frequently. Indeed, journals have rejected many papers that later became classics. The authors discuss the prize-winners' experiences, other notable cases, and rejections by John Maynard Keynes when he edited the Economic Journal. Finally, they search in economists' almost universal experience of rejection for patterns and lessons about the publication process. Copyright 1994 by American Economic Association.
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