|
on Sociology of Economics |
| By: | Han, Donggeun; Adom, Enoch; Lambert, Dayton M. |
| Abstract: | Research credibility in agricultural economics is compromised by two interrelated factors: selective reporting and low statistical power. These factors contribute to exaggerated findings that appear more persuasive and garner more citations. This study analyzes 849 articles published in leading U.S. agricultural economics journals between 2018 and 2023, with 48, 962 observations. Two empirical analyses are conducted. The first regresses citation counts on p-values reported in article tables, a proxy for statistical power, article topics, and journal and year fixed effects. The second predicts the time it takes a journal to be cited ‘10’ times, given p-values and statistical power. We hypothesized that citation counts would be negatively associated with p-values (i.e., lower p-value attract more citations), while no specific hypothesis was formed for statistical power, as it is unobservable to readers. The results show that citation counts are strongly influenced by topic novelty and journal prestige, with studies reporting lower p-values receiving more citations, whereas adequately powered studies receive fewer. The misalignment between research rigor and citation counts raises concerns that farmers may adopt recommendations based on less reliable findings, as agricultural extension services may rely on citation metrics when evaluating scientific research. Thus, aligning citation-based evaluations with empirical credibility is important not only for maintaining trust in science but also for informing decisions made by farmers and extension agents. |
| Keywords: | Research Methods/Statistical Methods |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361172 |
| By: | Richard V. Burkhauser; Ji Ma |
| Abstract: | How does academic research inform presidential economic policy? This paper investigates the sources of evidence in the Economic Report of the President from 2010 to 2025. We construct a novel dataset of 4, 140 unique references cited across the Obama, Trump, and Biden administrations to map the evidence base used by the Council of Economic Advisers. Our analysis shows that peer-reviewed articles, comprising 66.62% of all these references, are heavily concentrated in top-tier economics journals. While the specific articles cited change with policy priorities, the hierarchy of journals remains moderately stable across years and administrations. A co-author network analysis reveals a scholarly landscape of distinct intellectual camps. Crucially, a small number of high-centrality scholars act as brokers, connecting these disparate research communities. Together, our findings illuminate the social structure of evidence-based policymaking, demonstrating how journal hierarchies and scholarly networks shape the flow of economic knowledge to the White House. |
| JEL: | A11 H11 I38 J08 N01 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34597 |
| By: | Singhal, Karan (University of Luxembourg, LISER); Sierminska, Eva (Luxembourg Institute of Socio-Economic Research (LISER)) |
| Abstract: | We study the determinants of field specialization among U.S. economics PhD students, focusing on individual, institutional, and contextual factors shaping early research careers. Using data on over 8, 000 dissertations from 2009–2018, we classify each dissertation into one of ten fields using author-reported JEL codes and topic modeling of abstracts. We link dissertations to student gender, program characteristics, and country of origin inferred from surnames and matched to country-level indicators. We find substantial variation in field choice by region of origin. Gender gaps in specialization are not uniform but vary in size and direction across regions, indicating that gender and origin interact in shaping choices. Results are robust to alternative classification methods and to using genetic distance as a continuous measure of origin. Our findings highlight how early specialization in economics reflects inherited context and institutional exposure, with implications for research agendas, job market outcomes, and diversity across subfields. |
| Keywords: | topic modeling, JEL, economics PhD students, field specialization, diversity in economics |
| JEL: | J15 J16 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18348 |
| By: | Dreier, Lukas (University of Jena); Göthner, Maximilian (University of Twente); Lawson, Cornelia (University of Manchester) |
| Abstract: | Academically trained scientists play a pivotal role in innovation by advancing the knowledge frontier across industries, prompting firms to increasingly engage in proactive recruitment. This paper investigates academic scientists’ career transitions into industry by jointly examining two often separately studied mechanisms: scientists’ intentions to leave academia (the supply side) and firms’ recruitment efforts (the demand side). We conceptualize intersectoral mobility as the outcome of how these two mechanisms align or diverge. Using survey data from 469 scientists in Germany linked to follow-up information on their actual career outcomes more than three years later, our results show that exit intentions are the predominant predictor of subsequent transitions into industry jobs. Job offers reinforce the impact of existing exit intentions. By contrast, scientists who receive a job offer but do not intend to leave academia are the least likely to transition to private-sector employment. Implications for firms’ active recruiting strategies and for universities seeking to retain scientific staff are discussed. |
| Keywords: | exit intentions, knowledge transfer, industry transition, career mobility, academic scientists, job offers |
| JEL: | J63 O31 J24 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18347 |