|
on Sociology of Economics |
| By: | Brodeur, Abel; Kattan, Lamis; Musumeci, Marco |
| Abstract: | Graduating economics PhDs face intense competition when seeking faculty or research positions at universities and research institutions. We examine the relationship between statistically significant results, arguably used as indicators of research quality in a competitive academic market, and academic hiring outcomes. We start by investigating the determinants of academic success by analyzing 604 job market papers (JMPs) from 2018-2019 to 2020- 2021. We then turn to the practice of p-hacking focusing on 150 empirical JMPs. We find evidence that marginally significant results in JMPs are associated with higher academic placement likelihoods. During the COVID-19 pandemic, a tighter job market strengthened this relationship without altering the p-hacking behavior of PhD candidates, suggesting that our results reflect a recruitment bias by academic employers. We also find evidence of publication bias, suggesting that recruiters may use statistical significance to gauge candidates' potential for future publications, thus influencing recruitment decisions. Overall, our findings provide insights into the dynamics of the academic job market and the factors influencing career trajectories in academia. |
| Keywords: | Academic job market, p-Hacking, Publication bias, Research credibility |
| JEL: | B41 C13 C40 C93 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:i4rdps:141 |
| By: | Luis Eduardo San Martin (World Bank); Maria Ruth Jones (World Bank); Maria Reyes Retana (World Bank); Benjamin B. Daniels (World Bank, DIME); Kristoffer Bjarkefur (The World Bank, DIME/LSMS) |
| Abstract: | The challenge of reproducing economics research has gained increased attention with the growing advocacy for open science in the field. Economics journals and research institutions are quickly adopting reproducibility guidelines, requiring authors to provide code and data for reproducing results and ensuring the trustworthiness of their findings. Presented by the Development Impact Analytics team of the World Bank, this session delves into the intricacies of achieving reproducibility in Stata. Since the launch of the World Bank's Reproducible Research Repository, the team has conducted reproducibility verifications and curated reproducibility packages for almost a hundred working papers from diverse research teams in the organization, building up a valuable and novel experience into addressing common issues that break reproducibility in Stata analyses. The session will present an overview of the workflows and tools the team has developed in response to identified reproducibility challenges in typical Stata works, covering key topics such as controlling the versions of external dependencies and appropriately handling randomness in Stata code. The presentation will include practical strategies for enhancing the transparency and reliability of Stata-based research. |
| Date: | 2024–08–04 |
| URL: | https://d.repec.org/n?u=RePEc:boc:usug24:15 |
| By: | Casamonti, Matilde (PwC Middle East); Zinovyeva, Natalia (University of Warwick) |
| Abstract: | We analyze the impact of evaluator and candidate gender on the language used in academic evaluations using data on 295, 000 evaluation reports for applicants seeking professorial promotion across all academic fields in Italy. In this context, candidates are assessed by a national-level committee composed of five randomly selected evaluators from the corresponding field. We observe that the language used in evaluation reports varies significantly with applicants’ productivity and professional ties to evaluators, but we find no indication that the language of the assessments depends on the gender of either the candidates or the evaluators. |
| Keywords: | Academic Evaluations ; Women in Academia ; Gendered Language JEL Codes: I23 ; J16 ; J71 ; M51 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1513 |
| By: | Patricia Laurens (LISIS - Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Université Gustave Eiffel, UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University)); Christian Le Bas (ESDES - ESDES, Lyon Business School - UCLy - UCLy - UCLy (Lyon Catholic University), UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University)); Linh-Chi Vo (ESDES - ESDES, Lyon Business School - UCLy - UCLy - UCLy (Lyon Catholic University), UR CONFLUENCE : Sciences et Humanités (EA 1598) - UCLy - UCLy (Lyon Catholic University)) |
| Abstract: | In the perspective of institutional theory, business education is an institutional field, in which two major institutional forces are accreditations and rankings. In this context, French business schools (BS) have adopted an isomorphic response by starting to engage in research and publishing in academic journals. Studies have discussed their research as a new institutional trajectory. However, what remains unknown is how they differ from each other in such research dynamics. To bring new insights to the discussion, this quantitative study examines, over the period of 2008-2018, the evolution of research of French BS by systematically comparing the 'best' schools with other schools in all analyses. The results indicate a strong isomorphism in terms of publication quantity and productivity, scale of research collaboration and the internationalisation of research. However, these schools are heterogeneous in terms research quality and scale of international research collaboration, reflecting the diversity in their research strategy. |
| Keywords: | Business schools, Academic research, Isomorphism, Institutional theory, France |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04666299 |
| By: | Tom Coupé (University of Canterbury) |
| Abstract: | In this paper, I analyse ChatGPT’s opinion on economic issues by repeatedly prompting ChatGPT with questions from different surveys that have been used to assess the opinion of the economics profession. I find that ChatGPT 3.5 is a one-handed economist with strong opinions, while ChatGPT4o is much more of an ‘average’ economist. I further find little evidence that the widespread use of ChatGPT4o could reduce the gap between what the general public thinks about economic issues and the economics’ profession views on those issues, that ChatGPT4o is about equally likely to prefer professors’ financial advice and the financial advice from popular books, and that ChatGPT4o is more likely to agree with less/nonmainstream views about the economics profession than the economics profession. |
| Keywords: | ChatGPT, Economic Opinion, Economists' Consensus, Public Policy, Artificial Intelligence |
| JEL: | C83 A11 D80 D83 |
| Date: | 2024–08–01 |
| URL: | https://d.repec.org/n?u=RePEc:cbt:econwp:24/13 |