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on Sociology of Economics |
| By: | Manu García; J. Ignacio Conde-Ruiz; Juan-José Ganuza |
| Abstract: | This paper investigates the existence and drivers of gender citation gaps in the five leading journals in economics. Using a comprehensive dataset of 7, 244 articles published between 1999 and 2023, we examine whether female-authored papers are cited more frequently than male-authored ones, and whether this pattern persists after controlling for differences in research topics. We apply Structural Topic Modeling (STM) to abstracts to estimate latent research themes and complement this approach with field classifications based on JEL codes. Our results show that female-authored papers initially display a citation premium—receiving up to 16 log points more citations—but this advantage becomes statistically insignificant once we control for research field composition using either STM topics or JEL codes. These findings suggest that horizontal gender differences in thematic specialization, rather than bias in citation behavior, account for most of the observed citation gap. Our analysis highlights the importance of accounting for field heterogeneity when assessing academic recognition and contributes to ongoing discussions about fairness and diversity in economics publishing. |
| Keywords: | gender gaps, gendered language, machine learning, research fields, structural topic model |
| JEL: | I20 J16 Z13 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1529 |
| By: | Gunseli Berik; Ebru Kongar |
| Abstract: | Macroeconomics is arguably the most male-dominated field within the discipline of economics. Since the mid-1990s, feminist economists have thoroughly and meticulously challenged this field through empirical and theoretical analyses and proposed alternative starting points, frameworks, and models. We evaluate the contributions of five scholars--Nilufer Cagatay, Diane Elson, Caren Grown, Stephanie Seguino, and Elissa Braunstein--who have been influential in the development of feminist macroeconomics as a heterodox project since 1995. Through citation analysis, we examine who is recognizing the macroeconomics-related contributions of these five scholars. We document that the journal articles published by these five are cited primarily by women, in mainstream journals, in disciplines other than economics, and in interdisciplinary journals both in and outside of economics. Our analysis reveals that the impact of the five scholars in heterodox macroeconomics journals is miniscule, and the citations of their works are primarily made by other feminist economists, most of whom are women. |
| Keywords: | Citations; Feminist Economics; Feminist Macroeconomics; Gender |
| JEL: | B54 E11 E12 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:lev:wrkpap:wp_1081 |
| By: | Fabio Bertolotti; Kyle Myers; Wei Yang Tham |
| Abstract: | We develop a method to estimate producers' productivity beliefs when output quantities and input prices are unobservable, and we use it to evaluate the market for science. Our model of researchers' labor supply shows how their willingness to pay for inputs reveals their productivity beliefs. We estimate the model's parameters using data from a nationally representative survey of researchers and find the distribution of productivity to be very skewed. Our counterfactuals indicate that a more efficient allocation of the current budget could be worth billions of dollars. There are substantial gains from developing new ways of identifying talented scientists. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.24916 |
| By: | Chaofeng Wu |
| Abstract: | We propose a framework that recasts scientific novelty not as a single attribute of a paper, but as a reflection of its position within the evolving intellectual landscape. We decompose this position into two orthogonal dimensions: \textit{spatial novelty}, which measures a paper's intellectual distinctiveness from its neighbors, and \textit{temporal novelty}, which captures its engagement with a dynamic research frontier. To operationalize these concepts, we leverage Large Language Models to develop semantic isolation metrics that quantify a paper's location relative to the full-text literature. Applying this framework to a large corpus of economics articles, we uncover a fundamental trade-off: these two dimensions predict systematically different outcomes. Temporal novelty primarily predicts citation counts, whereas spatial novelty predicts disruptive impact. This distinction allows us to construct a typology of semantic neighborhoods, identifying four archetypes associated with distinct and predictable impact profiles. Our findings demonstrate that novelty can be understood as a multidimensional construct whose different forms, reflecting a paper's strategic location, have measurable and fundamentally distinct consequences for scientific progress. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.01211 |