nep-sog New Economics Papers
on Sociology of Economics
Issue of 2020‒11‒09
six papers chosen by
Jonas Holmström
Axventure AB

  1. Why are connections to editorial board members of economics journals valuable? By Lorenzo Ductor; Bauke Visser
  2. On the Inuence of Top Journals By Lorenzo Ductor; Sanjeev Goyal; Marco van der Leij; Gustavo Nicolas Paez
  4. Does preregistration improve the credibility of research findings? By Rubin, Mark
  5. Statisticians roll up your sleeves! There’s a crisis to be solved. By Seibold, Heidi; Charlton, Alethea; Boulesteix, Anne-Laure; Hoffmann, Sabine
  6. Historical Data: Where to Find Them, How to Use Them By Paola Giuliano; Andrea Matranga

  1. By: Lorenzo Ductor (Department of Economic Theory and Economic History, University of Granada.); Bauke Visser (Erasmus University Rotterdam and Tinbergen Institute)
    Abstract: Using novel and large-scale data, we estimate the causal effect of being connected to an editorial board member of an economics journal on a department’s or coauthor’s success in publishing in the journal. Prior studies suggests that editors are helping colleagues not themselves and that connections lead to markedly better papers. Instead, we explicitly take into account that authors and editorial board members are not two distinct sets of persons and find that of the overall 27% increase in a department’s annual publication record in a journal, 73% is thanks to the increase in the number of publications by editorial board members themselves. At the individual level, co-authors publish 7% more articles in the journal, excluding the work with the editorial board member. More editorial power, captured by the member’s role in the submission process, and long service on the editorial board lead to substantially larger increases. We analyze various mechanisms. Rather than a marked increase in quality thanks to connections, we find no such increase (nor signs of favoritism). Analysis of individual-level connections suggests that connections act as signals of a coauthor’s quality.
    Keywords: editorial boards, networks, collaboration
    JEL: A11 D71 I26 J44 O30
    Date: 2020–10–20
  2. By: Lorenzo Ductor (Department of Economic Theory and Economic History, University of Granada.); Sanjeev Goyal (Christ's College and Faculty of Economics, Cambridge); Marco van der Leij (University of Amsterdam and Tinbergen Institute.); Gustavo Nicolas Paez (Myanmar Development Institute)
    Abstract: We study the evolution of the influence of journals over the period 1970-2017. In the early 1970's, a number of journals had similar influence. But by 1995, the `Top 5' journals - QJE, AER, RES, Econometrica, and JPE - had acquired a major lead; this dominance persists (with small changes) until 2017. To place these developments in a broader context we also study journal influence in sociology. The trends there have gone the other way - the field journals rose in influence relative to the top general journals, over the same period. We present a model of journals as platforms to help explain the different trajectories of journal influence across time and across disciplines.
    Keywords: research impact, Top 5 journals, academic publishing, citations
    JEL: A14 D85
    Date: 2020–10–15
  3. By: Hossan, Dalowar
    Abstract: The aim of this study is to identify the features of fraudulent journals. Fraudulent and clone journals wasted valuable manuscripts when scholars and authors publish their works in these journals. Fraud journals publish the articles without reviewing process with a high rate of fee while the name and ISSN of clone journals are identical to the original journals. Purposive sampling technique as well as document analysis method have been used to conduct this research. Two clone versions and two fraud journals of the SCOPUS indexing journals have been selected for reviewing their articles. Based on the discussion of this study, researchers found some characteristics of predatory/fraud/ clone journals that will help the scholars to avoid publishing on fake journals.
    Date: 2020–09–29
  4. By: Rubin, Mark (The University of Newcastle, Australia)
    Abstract: Preregistration entails researchers registering their planned research hypotheses, methods, and analyses in a time-stamped document before they undertake their data collection and analyses. This document is then made available with the published research report to allow readers to identify discrepancies between what the researchers originally planned to do and what they actually ended up doing. This historical transparency is supposed to facilitate judgments about the credibility of the research findings. The present article provides a critical review of 17 of the reasons behind this argument. The article covers issues such as HARKing, multiple testing, p-hacking, forking paths, optional stopping, researchers’ biases, selective reporting, test severity, publication bias, and replication rates. It is concluded that preregistration’s historical transparency does not facilitate judgments about the credibility of research findings when researchers provide contemporary transparency in the form of (a) clear rationales for current hypotheses and analytical approaches, (b) public access to research data, materials, and code, and (c) demonstrations of the robustness of research conclusions to alternative interpretations and analytical approaches.
    Date: 2020–09–13
  5. By: Seibold, Heidi; Charlton, Alethea; Boulesteix, Anne-Laure; Hoffmann, Sabine
    Abstract: Statisticians play a key role in almost all scientific research. But are they also the key to solving the reproducibility crisis? Heidi Seibold, Alethea Charlton, Anne-Laure Boulesteix and Sabine Hoffmann urge statisticians to take an active role in promoting more replicable and more credible science.
    Date: 2020–10–23
  6. By: Paola Giuliano; Andrea Matranga
    Abstract: The use of historical data has become a standard tool in economics, serving three main purposes: to examine the influence of the past on current economic outcomes; to use unique natural experiments to test modern economic theories; and to use modern economic theories to refine our understanding of important historical events. In this chapter, we provide a comprehensive analysis of the types of historical data most commonly used in economic research and discuss a variety of issues that they raise, such as the constant change in national and administrative borders; the reshuffling of ethnic groups due to migration, colonialism, natural disasters, and many other forces. We also point out which methodological advances allow economists to overcome or minimize these problems.
    JEL: N0
    Date: 2020–10

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