How Interdisciplinary Research Affects Tenure Decision at Elite Economics Departments: Evidence from 2000-2024

How Interdisciplinary Research Affects Tenure Decision at Elite Economics Departments: Evidence from 2000-2024 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article How Interdisciplinary Research Affects Tenure Decision at Elite Economics Departments: Evidence from 2000-2024 Yilin Wang, Terri van Gevelt This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8560476/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Interdisciplinary research (IDR) has gained prominence for addressing complex societal challenges, yet its impact on academic tenure in economics remains unclear. This study examined how IDR influences tenure decisions in elite North American economics departments, using propensity score matching on curriculum vitae data from 553 tenure-track faculty at top 50 universities (2000–2024). Conducting IDR showed no significant effect on tenure success. However, other factors substantially influenced outcomes: Hispanic/Latino scholars faced dramatically reduced odds of tenure acceptance; each additional year between bachelor's and PhD decreased the likelihood by 10%; and T5 journal publications significantly increased the odds. While IDR does not disadvantage economists, systemic biases persist with respect to ethnicity, educational trajectory, journal prestige, and institutional hierarchy. These findings reveal that elite departments maintain implicit hierarchical structures that limit diversity and innovation in scholarship. Interdisciplinary research tenure top universities T5 journal academic hierarchy elite economics departments Figures Figure 1 Figure 2 Background Interdisciplinary research (IDR), integrating knowledge, theories, and methodologies from multiple disciplines, has emerged as a critical approach to addressing complex societal challenges that transcend single-disciplinary boundaries (Aboelela et al., 2007 ). Sá ( 2008 ) reported that prestigious institutions have established incentive grants to encourage researchers to invest in interdisciplinary areas. Within a decade, the top 1% of most-cited academic papers have consistently exhibited higher levels of interdisciplinarity across disciplines (Chen et al., 2015 ). However, when conducting IDR, scholars may encounter epistemic, structural, and affective tensions (Turner et al., 2015 ). Engaging with diverse disciplines or methodologies can increase uncertainty about publication success. It heightens the insecurity of IDR researchers seeking academic tenure, a permanent position that confers job security and scholarly autonomy (Shaw and Lazear, 2008 ), as tenure decisions often prioritize traditional disciplinary contributions. For instance, a qualitative study that interviewed senior tenured scholars revealed stark disciplinary divides in attitudes toward IDR: while science, technology, engineering, and mathematics (STEM) research leaders actively encouraged untenured researchers to pursue interdisciplinary projects, those in the economics department perceived such work as less valuable in tenure evaluations (Mäkinen et al., 2025 ). Hence, early-career economists may face a dilemma: pursuing IDR may yield transformative societal impacts, but it could influence publication outputs in core economic journals, which are critical for tenure decisions. Hence, the current study examined whether IDR influences academic promotion among tenure-track economists. Literature Review on tenure decisions and interdisciplinary research (IDR) in Economics Tenure represents a pivotal milestone for scholars across the social sciences, offering two foundational benefits: job security and academic freedom. In economics departments, the pursuit of tenure is uniquely intense, shaped by the discipline’s competitive norms and institutional structures. Economics is distinguished by a hierarchical job market that prioritizes institutional pedigree and publication records in high-impact journals (Burris, 2004 ). Unlike other social sciences departments, which reward fieldwork or theoretical innovation, economics emphasizes empirical rigor and a narrow set of high-status publication outlets. This creates a ‘tournament’ culture in which early-career scholars face disproportionate pressure to outperform their peers to secure tenure (Oyer, 2006). Current Policy on Tenure Decisions Before the 1990s, the evaluation of faculty work was conducted with little transparency, often accompanied by vague and inconsistent policies that could be susceptible to bias in favor of specific groups, such as White men or individuals with special personal networks (Stewart and Valian, 2018 ). This lack of transparency was challenged by neoliberal logic within higher education institutions in the 1990s, which placed greater emphasis on rigor in tenure evaluations. Slaughter and Leslie ( 2001 ) argued that this transformation to the current tenure decision process can be explained by various political and economic contributors, such as the mitigation of external funding and the influence of marketing competition logic in the traditional non-economic fields (e.g., academia, government). Within neoliberal capitalism, top universities in North America have adopted objective measures to assess scholars’ academic productivity, as quantifiable contributions are believed to reduce prejudice and inequality (Mickey et al., 2023 ). Despite existing gender inequality (e.g., Antecol et al., 2018 ) and authorship order based on scholars’ surnames (e.g., Huang, 2015 ), this strategy is relatively more transparent than that in most of the world. Today, faculty members in top economics departments are audited annually by their academic committees. Scholarly output, often reflected in publications in top-tier journals, is a key indicator in tenure decisions. Flaws of neoliberal capitalism in economic departments However, this merit-based system still has limitations with respect to academic outcomes. Top universities in North America are under pressure to boost their international ranking by increasing the number of published articles in high-status journals, which could be an indicator for attaining more funding resources (Spooner, 2020 ). This proliferation of publications has narrowed economists’ research scope, leading them to focus more on publishing articles for economic gain and prestige than on genuine academic ambition (Acker and Wagner, 2019 ). In addition, this free-market neoliberal capitalism may fail to yield research productivity. For example, Backes-Gellner and Schlinghoff ( 2004 ) compared U.S. economists with German economists and reported that the U.S. tenure policy drives a significant increase in publications before tenure, but the output of publications has seen a dramatic decline during the post-tenure phase. The Tyranny of the top five in the economic department In the economic domain at North American Universities, tenure decisions are conventionally aligned with metric-based standards. The metric of research productivity strongly emphasizes publishing in a group of highly prestigious journals, commonly referred to as the ‘top five’ (T5) (American Economic Review, Quarterly Journal of Economics, Journal of Political Economy, Econometrica, and Review of Economic Studies). This system creates strong incentives for early-career economists to focus on securing T5 publications, thus deciding their career trajectories. However, concerns have been raised about the long-term effects of this structure on research innovation and systemic imbalances within the discipline of economics. While the emphasis on T5 publications provides a clear benchmark for evaluation, it also introduces distortions in research: the scope of publications in these journals remains minimal, and young researchers find it even harder to secure successful acceptance in these journals. Heckman and Moktan ( 2024 ) refers to this as the ‘tyranny of the top five’. According to Heckman and Moktan ( 2024 ), the publications on T5 have been strongly predictive of tenure outcomes at the top 35 U.S. economics departments. This finding aligns with a pattern analysis by Coupé et al. (2004) of 1,000 economists over three decades, which shows that tenure promotion and mobility to high-tier universities are highly sensitive to publication output, particularly in T5 outlets. Through econometric analysis and survey data, they argue that overreliance on T5 publications for screening can distort research incentives, prioritizing careerism over creativity. The Reputation of IDR in Economics Since current merit-based policies in North American economics departments favor disciplinary insularity, they may limit the scope of research output. In response to this issue, IDR may serve as a complement, adding standards to tenure decision-making. However, compared with the consensus on the value of top-tier economic journals such as T5, there is ongoing debate about whether IDR should be taken seriously within elite North American economics departments. Historical Skepticism Economic research has long been characterized by a strong disciplinary identity rooted in neoclassical economics and quantitative modeling. Given this tradition, some authority figures in the economics department typically equate prestige with adherence to these traditional paradigms. For instance, Fourcade et al. (2015) found that economists view their discipline as a ‘superior science’ because they perceive IDR as lacking the mathematical precision or theoretical coherence. This sentiment is reinforced by tenure and promotion criteria that prioritize publications in a narrow set of high-impact economics journals (Heckman and Moktan, 2024 ). IDR, which often requires collaboration with non-economists or publication in interdisciplinary outlets, has historically been perceived as a risky career strategy for early-career scholars (Schläpfer, 2010 ). Systematic Barriers to IDR The reputation of IDR is inextricably tied to publication norms. Top economics journals rarely publish work co-authored with non-economists or employing non-economic methodologies, because journal reputation metrics discount contributions from an interdisciplinary perspective (Schläpfer, 2010 ). Several studies also highlight obstacles that limit the adoption and impact of IDR in economics. For instance, the editorial boards of top economic journals play a key role in placing hurdles on IDR in economics. Ductor and Visser (2021) found that editorial boards remain dominated by researchers from a limited range of institutions, who exhibit a preference for mono-disciplinary research while limiting IDR’s visibility. This aligns with another study demonstrating that economics has historically exhibited strong disciplinary insularity, borrowing less from other fields than others borrow from economics (Angrist et al., 2020 ). Furthermore, tensions arise for scholars within a disciplinary domain when pursuing interdisciplinarity. This could make the tenure and promotion process less favorable to IDR, as it is difficult for the research committee to formulate standardized criteria for evaluating IDR performance. Furthermore, elite departments exhibit contradictory stances toward IDR. Institutions such as MIT and Harvard have launched interdisciplinary initiatives (e.g., behavioral economics labs, climate econometrics consortia), indicating a shift toward valuing IDR’s academic impact (Townsend & Zhang, 2021). However, these efforts often exist alongside rigid tenure criteria that disadvantage interdisciplinary scholars. Additionally, gender disparities may influence IDR’s reputation: women in economics are more likely to pursue interdisciplinary collaborations but face greater scrutiny for diverging from traditional research paths (Sarsons et al., 2021 ). In conclusion, while IDR's reputation in top economics departments reflects growing recognition, persistent biases continue to hinder young researchers' ambitions and motivation to succeed academically in IDR. However, there remains a lack of empirical evidence on the long-term career outcomes of interdisciplinary economists. Therefore, the current study aims to determine whether the risks associated with publishing IDR are diminishing within elite economic institutions. Research Questions Does IDR Influence Tenure Success? As noted, researchers in tenure-track positions may still prioritize core-economics publications (e.g., the ‘T5’) in pursuit of tenure promotion. However, there is no empirical evidence demonstrating whether IDR significantly affects tenure outcomes. To date, we have found only anecdotal claims that increasing IDR in the economics department might hinder tenure promotion, with no empirical evidence (Mallaband et al., 2017 ). Therefore, the current project primarily established a dataset that addresses tenure outcomes and the number of IDR publications before tenure. Given that a limited number of universities offer tenure-track positions, we focused on the top 50 universities in North America that provide graduate economics courses. Do Socio-Demographics Confound IDR's Impact Potential disparities in tenure attainment across socio-demographic groups raise critical questions about whether factors such as gender, age, and ethnicity interact with IDR to shape tenure promotion outcomes. Empirical evidence suggests that systematic biases still exist against women and scholars from minority backgrounds, despite established policies such as the tenure-clock stop for maternal (e.g., Antecol et al., 2018 ; Sarsons et al., 2021 ). In China, institutional age restrictions (e.g., requiring candidates to be under 35 years old) also exclude older scholars seeking tenure-track positions (Tian et al., 2016 ). The temporal constraints of the tenure clock add another layer of complexity. Publication delays, which are common in peer-reviewed journals, disproportionately affect early-career economists who are often racing to meet deadlines (Conley et al., 2011 ). Especially since COVID-19, the peer-review timeline has been further delayed due to a lack of reviewer participation (Nicholas et al., 2023 ). Such delays may exacerbate inequalities: women, older scholars, and minority scholars risk their careers in chasing the ‘publish or perish’ timeline, thereby complicating assessments of IDR’s impact on tenure success. This interplay may underscore the need to distinguish IDR’s independent effects from the structural inequities that shape academic careers. Hence, this study rigorously controlled for sociodemographic variables to determine whether IDR inherently disadvantages researchers or reflects preexisting biases in tenure evaluation systems. Do Other Factors Moderate IDR’s Influence? Beyond socio-demographic information, other factors, such as authorship, university reputation, and journal rank, may also contribute to tenure success. For instance, prior studies have shown that the order of authors on the reference list can influence tenure promotion at the top 5–10 universities in the US (Einav and Yariv, 2006 ). However, this effect became insignificant when the researchers expanded their dataset to the top 35 universities. This suggests that institutional ranking may moderate the role of authorship hierarchy, with elite universities potentially placing greater emphasis on collaborative contributions. Furthermore, although the impact factor and journal reputation could significantly improve tenure success (e.g., Heckman & Moktan, 2024 ), uncertainties persist regarding IDR-focused journals: whether their prestige confers advantages comparable to those of discipline-specific top-tier journals remains unexplored. This gap is critical, as academic committees often rely on journal rankings (Bajo et al., 2020; Schimanski & Alperin, 2018 ), yet traditional metrics may undervalue interdisciplinary work. The present study, therefore, investigates the potential confounding effects of three covariates. By studying these factors, we aim to clarify how IDR contributions are evaluated in tenure decisions in the economics department. Hypothesis Based on the proposed research questions, we developed the following three hypotheses: H1: Research types (core-economic vs. IDR) will significantly influence the outcome of tenure success. Scholars with higher IDR are less likely to achieve tenure. H2: The socio-demographic factors, including gender, ethnicity, and age, will significantly confound the influence of research type on tenure success. H3: Other covariates comprising the alphabetical order of scholars’ surname, university rank, and journal prestige will significantly moderate IDR’s impact on tenure outcomes. Methods, Data, and Sample To investigate whether publishing interdisciplinary research influences tenure promotion outcomes, we compiled a dataset from the curricula vitae (CVs) of tenure-track faculty in economics departments at the top 50 North American universities from 2000 to 2024. The ranking of academic departments is based on U.S. News & World Report rankings, widely regarded as among the most authoritative sources (U.S. News & World Report, 2024). This timeframe was chosen to align with post-1990 reforms that standardized tenure evaluation processes (Stewart & Valian, 2018 ), ensuring consistency in institutional policies during the study period. The CVs provided comprehensive data on scholars’ publication histories, including journal types (disciplinary vs. interdisciplinary), co-authorship networks, journal impact factors, and demographic variables (e.g., gender, age, ethnicity). Using this dataset, we evaluated the relationship between interdisciplinary publication strategies and tenure success while controlling for co-authorship patterns, journal prestige, and demographic factors. Critically, this study examined whether interdisciplinary publication strategies enhance or hinder tenure progression. Data Search Strategy The dataset for this study was compiled by systematically retrieving historical faculty information from the economics departments of the top 50 universities in North America. To ensure access to the earliest available data, we relied on the Wayback Machine (WM), a digital archiving service operated by the U.S.-based non-profit Internet Archive ( www.archive.org ). The WM preserves historical snapshots of websites, enabling researchers to trace changes in online content over time (Help Center, 2025). Its reliability as a tool for social science research has been empirically validated (Murphy et al., 2007), making it well-suited for reconstructing career timelines. We focused on webpage versions dated after 1999, as this timeframe aligns with documented shifts toward merit-based and transparent tenure practices in U.S. academia (Stewart & Valian, 2018 ). Faculty data collection began with the download of CVs from departmental websites. For scholars whose CVs were not accessible, we gathered career information from personal academic websites linked through faculty directory pages. The coding process emphasized four key career markers: the completion years of bachelor’s and doctoral degrees, the start years of tenure-track positions, and the years in which tenure decisions (both granted and denied) were finalized. Publication records were also documented, including paper titles and journal names. A significant challenge arose in verifying authorship conventions specific to economics, where alphabetical surname ordering typically supersedes contribution-based sequencing (Einav & Yariv, 2006 ). Furthermore, given research indicating that surname initials significantly impact citation counts, with early-alphabet initials (e.g., ABC) conferring advantages over later ones (e.g., XYZ) (Huang, 2015 ), we analyzed this factor. Specifically, we extracted all economists' surnames and initial letters, ordered them alphabetically, and categorized them into four groups based on ascending quartiles. This resulted in the first quartile ('A' to 'F') representing the earliest-alphabet initials, and the fourth quartile ('S' to 'Z') representing the latest-alphabet initials. Operationalizing Tenure Construction A primary challenge in operationalizing tenure status arises from underreporting denied tenure decisions in publicly available CVs, as scholars rarely document unsuccessful promotions. To mitigate sample selection bias, particularly the risk of conflating voluntary departures (e.g., to industry or governmental roles) with tenure denials, we employed three criteria by Sarsons et al. ( 2021 ). First, individuals transitioning to non-academic roles (e.g., industry or government positions) after more than four years as assistant professors were classified as having denied tenure. Second, scholars departing for institutions outside North America after seven years (the typical tenure-clock window) were similarly categorized, since international academic promotion systems differ significantly from those in North America, and prolonged investment in a regional academic career reduces the likelihood of voluntary relocation. Third, downward mobility in both departmental and university rankings (e.g., moving to an institution ranked five positions lower) was interpreted as evidence of tenure denial. This ranking criterion accounts for disciplinary preferences: some scholars prioritize departmental specialization over institutional prestige, potentially accepting positions at lower-ranked universities without incurring career setbacks. We excluded adjunct or visiting professors, individuals granted tenure before 2000, and teaching-focused faculty without research obligations, as their career trajectories do not align with standardized tenure-track promotion criteria. After applying these filters, the final sample comprised 553 tenure-track scholars in economics at the top 50 North American institutions, of whom 441 achieved tenure, and 112 were classified as denied tenure. Categorizing Research Type and Journal Impacts We classified economists’ published papers in non-economics journals as ‘interdisciplinary research’. We first reviewed the stated aims and scope on each journal’s official website to determine journal categorisation. However, this approach proved insufficient, as most journals, including top-tier economics journals like the Journal of Political Economy, explicitly welcome submissions from diverse domains. Despite such broad editorial statements, economists generally agree that specific journals (e.g., top economics journals) remain predominantly single-disciplinary in practice, even if their stated scope appears interdisciplinary. To resolve this ambiguity, we adopted the methodological protocol developed by Combes and Linnemer (2020), which synthesizes journal classifications from the Web of Science (WoS) and the EconLit database. Their algorithm identifies core economics journals by analyzing their specialization patterns relative to economic subfields. By weighting WoS and EconLit classifications, Combes and Linnemer distinguish between core economic journals and those that are interdisciplinary or belong to other disciplines, referred to as ‘interdisciplinary’. Following this framework, we categorised all publications in our dataset as core-economic or interdisciplinary. For journals not listed in Combes and Linnemer’s (2020) tables, we relied on information from their official websites to evaluate their stated aims and scope. As a supplementary measure, we assumed that journals emphasizing adjacent fields, such as finance or business, remained core economics journals. In contrast, those explicitly incorporating disciplines such as psychology and sociology, or those beyond the social sciences (e.g., natural sciences), were classified as interdisciplinary. Journal Prestige To evaluate scholarly impact, we categorize journals into two tiers: (1) publications in the Top 5 (T5) economic journals and (2) all others. This binary classification reflects the consensus among economists regarding the role of T5 publications ( American Economic Review , Econometrica , Journal of Political Economy , Quarterly Journal of Economics , and Review of Economic Studies ) in tenure decisions, relative to other economics journals. As Heckman and Moktan ( 2024 ) emphasize, the ‘tyranny of the Top Five’ reflects an institutional obsession in which publishing in these journals is widely perceived as a prerequisite for tenure promotion. This approach aligns with norms in top economic departments by prioritizing clarity and pragmatism over rankings based on ambiguous standards. Defining Other Covariates To collect other covariates relevant to the person’s demographic information, we refer to tenure-track economists’ CVs and personal websites, which are linked to departmental officials. However, although gender can be inferred from the department website's gender pronouns, most individuals did not disclose their age or ethnicity, and only a few indicated their nationality on their CVs or personal websites. Therefore, to infer their ethnic background, we used their surname origin, which can be found on www.ancestry.com/learn/factscon ( Last Name Meanings and Origins . 2025), and verified this information against their profile picture. To comply with the ethnicities category, we adopted the questionnaire developed by Elsevier Inclusion & Diversity center (2023) to classify six major ethnicities among the observed scholars. These six categories are: Caucasian, Hispanic/Latino, Black African, Middle Eastern/North African, East Asian, and South Asian. To address potential age-related confounders, we adopted career progression timelines as more reliable indicators than chronological age, with two considerations. First, publicly available professional profiles (e.g., LinkedIn and Wikipedia) rarely disclose birthdates, whereas educational milestones and employment records are more readily accessible. Second, the only data that implicated their age was from their career timelines on their respective CVs. Therefore, we focused on a single career timeline for critically reflecting on scholars’ age trajectories: the foundational training period from the conferral of a bachelor's degree to PhD completion. Since most people begin college around the same age, the time between BA and PhD may reflect relative age differences among economists, with longer intervals indicating older age at the start of their academic careers and shorter intervals indicating younger age. The descriptions of all covariates for the matched sample are shown in Table 1 . Table 1 Descriptions of Covariates in the Dataset Covariate Description Gender 1 = Male; 2 = Female Ethnicity 1 = Caucasian White; 2 = Hispanic/Latino; 3 = Black; 4 = Middle East/North Africa; 5 = Eastern Asian; 6 = South Asian Age BA_to_PHD = Period from bachelor’s degree to PhD conferment University Rank Elite = Top 5 Economic Departments; Leading = Economic departments ranked from 6 to 15; Strong = Economic departments = ranked from 16 to 30; Good = Economic departments ranked from 31 to 50 Surname Initials 1 = Surname Initials start from A to F; 2 = Surname Initials start from G to L; 3 = Surname Initials start from M to R; 4 = Surname Initials start from S to Z Journal Prestige non-T5 = Journal_rank0; T5 = Journal_rank1 -----------------------------------------Insert Table 1 Here------------------------------------------ Results Statistical Analyses Considering that the current study is based on retrospective observation, the statistical method, namely, propensity score matching (PSM), could allow us to identify whether conducting interdisciplinary research would influence the outcome of tenure success by balancing two groups (economic vs. interdisciplinary research), given a set of collected covariates (Rosenbaum & Rubin, 1983). By adopting this approach, we can simulate a pseudo-random assignment to infer the effect of research type and tenure success. Among all PSM methods, we selected full matching , which uses all available cases in the sample by grouping them into matched clusters containing at least one case from the IDR group and one from the core-economic group. There are two reasons for using this method over alternatives (e.g., nearest-neighbor matching). First, the full matching method focuses on the entire sample without excluding any cases; second, it improves statistical power in the current study, as the sample size is relatively small and the number of observations for the control group (N = 441) substantially exceeds that of the treatment group (N = 11)). Using PSM with full matching, we matched the treatment group (interdisciplinary research) and the control group (core-economic research) in a dataset with 553 observations. Six covariates described in Table 1 were used for matching. The analysis employed full matching with the MatchIt R package (Ho et al., 2011), yielding control and treated samples of 57 individuals each. Figure 1 illustrates the study’s research flow. -----------------------------------------Insert Fig. 1 Here----------------------------------------- The matching performance was assessed using Standardized Mean Differences (SMDs) and variance ratios (VRs), along with visualization. This matching yielded a good balance, as most covariate SMDs were below the cutoff of 0.2, whereas most VRs were within the acceptable range of 0.8–1.25 (Austin, 2009 ). Table 2 summarizes the descriptive statistics and standardized mean differences (SMDs) of the covariates used. Figure 2 (a) and Fig. 2 (b) illustrate that the matched treated and control samples are reasonable. Table 2 Balance Statistics Before and After Full Matching Unmatched Sample Matched Sample Treated Control SMD Treated Control SMD N 441 112 57 57 Journal_rank0 0.5789 0.4395 0.2817 0.4141 0.4519 0.0764 Journal_rank1 0.4211 0.5605 0.2817 0.5859 0.5481 0.0764 Gender_female 0.2982 0.2440 0.1224 0.1899 0.2500 0.1355 Gende_male 0.7018 0.7560 0.1224 0.8101 0.7500 0.1355 Surname_Initials1 0.2456 0.3044 0.1320 0.2911 0.2982 0.0158 Surname_Initials2 0.2456 0.2399 0.0133 0.3128 0.2423 0.1646 Surname_Initials3 0.2807 0.2278 0.1217 0.2477 0.2321 0.0359 Surname_Initials4 0.2281 0.2278 0.0006 0.1483 0.2274 0.1887 Elite 0.0526 0.1169 0.2324 0.1664 0.1102 0.2031 Leading 0.1754 0.2016 0.0670 0.1844 0.1987 0.0366 Strong 0.2105 0.3226 0.2555 0.2477 0.3135 0.1499 Good 0.5614 0.3589 0.4150 0.4014 0.3776 0.0489 Ethnicity1 0.6316 0.6431 0.0241 0.5895 0.6325 0.0894 Ethnicity2 0.0175 0.0202 0.0192 0.0778 0.0196 0.4276 Ethnicity3 0.0175 0.0141 0.0275 0.0127 0.0168 0.0330 Ethnicity4 0.0877 0.1069 0.0646 0.0452 0.1062 0.2060 Ethnicity5 0.1579 0.1492 0.0241 0.2260 0.1551 0.1969 Ethnicity6 0.0877 0.0665 0.0795 0.0488 0.0698 0.0789 BA_to_PHD 7.1123 7.2550 0.0715 7.1425 7.2250 0.0413 Note. SMD = Standardized Mean Difference. Balance improved substantially after full matching, with most SMD values below the 0.25 threshold. -----------------------------------------Insert Fig. 2 Here----------------------------------------- Effects of Interdisciplinary Research on Tenure Success After obtaining the matched samples, we conducted a logistic regression analysis to assess the causal relationship between research type and tenure success outcomes for all economists in the top 50 North American economic departments. The study revealed that five variables significantly predicted tenure outcomes: While no significant effect of performing IDR was found ( p = .27), those identifying with a Latino or Hispanic background ) was associated with sharply reduced odds of tenure (OR = 0.05, 95% CI [0.01, 0.19], z = − 4.42, p < .001) and each additional year between the bachelor’s and Ph.D. degrees corresponded to a 10% reduction in the odds of tenure (OR = 0.90, 95% CI [0.81, 0.99], z = − 2.05, p = .041). In contrast, those with T5 publications (OR = 3.60, 95% CI [2.14, 6.05], z = 4.78, p < .001) are at higher odds of getting tenure compared to those who have no T5 publications. The alphabetical order of surname initials also mattered: authors whose surnames start from letter ‘G’ to ‘L’ had about one-third the odds of tenure compared with those beginning between ‘A’ to ‘F’ (OR = 0.33, 95% CI [0.17, 0.64], z = − 3.40, p = .001). Finally, faculty members who started their career at economic institutions ranked between 6 and 15 are less likely to be tenured than those from the top five economic departments (OR = 0.37, 95% CI [0.14, 0.96], z = − 1.99, p = .047). The model also demonstrated a significant fit, with χ² (15) = 71.35, p < .001, and an Akaike Information Criterion (AIC) of 524.36, indicating good explanatory value. ------------------------------------------Insert Table 2 Here----------------------------------------- Discussion The current study initially used empirical evidence to examine how interdisciplinary research (IDR) affects tenure outcomes in top economics departments. After controlling for other covariates over the last two decades, we found no effect of IDR on tenure success in top economics departments in North America. However, other covariates, including ethnicity, age, journal prestige, surname initials, and the University’s rank, were associated with the tenure outcome. This finding suggests that, although the growing number of IDR publications may mitigate bias against interdisciplinary researchers in economics, top research institutions still harbor implicit stereotypes about economists’ identities. Our findings did not support the first hypothesis: scholars producing IDR were not less likely to be promoted to tenure than their counterparts who published core economic articles. This is consistent with the recent trend in the elite economic academy, where the value of IDR has gained more endorsement (e.g., Townsend & Zhang, 2021). However, the dataset obtained in the current study indicates a disproportionate number of articles published in core economic journals (N = 2778) relative to those published in interdisciplinary journals (N = 419). This implies that, among economists at top research institutions, there has yet to be a departure from disciplinary purity. While universities publicly encourage IDR innovation, they often unconsciously prioritize single-disciplinary research (Turner et al., 2015 ). Past research has also revealed that, despite increasing research funding, the number of publications in disciplinary journals (e.g., the Canadian Journal of Agricultural Economics) has not increased significantly, suggesting that institutional incentives fail to translate into scholarly recognition (Hamermesh, 2018 ). The publication of IDR remains in short supply in leading economics departments in North America. Regarding H2, our findings indicate that ethnicity and age impact tenure success. Hispanic/Latino individuals are less likely to receive tenure promotions. This aligns with the theory of implicit racial bias, which refers to unconscious attitudes or stereotypes influencing people’s judgment and decision-making. Research consistently demonstrates how such biases disadvantage underrepresented groups in academia in North America (Urrieta Jr. et al., 2015 ). Among Hispanic scholars, prior studies have reported that they face systemic barriers to promotion and retention relative to their White peers in academic medicine (Fang et al., 2000 ; Kaplan et al., 2018 ). Our study accordingly demonstrated this barrier for the Hispanic/Latino group. These outcomes may stem from two aspects rooted in implicit biases. First, faculty from minority groups often lack access to mentorship and professional networks critical for navigating career progression (Sapeg, 2020). Without this support, early-career economists with minority backgrounds may miss the opportunities to meet tenure benchmarks. Second, Hispanic researchers are disproportionately burdened by diversity service obligations that divert time from their professional development (Zambrana et al., 2023 ). Additionally, although age was not directly collected in our sample dataset, a prolonged bachelor 's-to-PhD gap often correlates with older candidates, particularly compared to peers who transitioned directly to graduate school. This suggests that older candidates may face systemic disadvantages despite meeting formal criteria alone. Although North American academia notably lacks formal age restrictions for tenure eligibility, in contrast to institutionalized age ceilings such as China's 35-year policy (Tian et al., 2016 ), our finding reveals an implicit age bias in these ‘ostensibly transparent’ systems. The findings also support H3, revealing a pattern related to journal and university prestige: individuals with publications in T5 journals are more likely to receive tenure promotions, and scholars affiliated with Top 5 universities are also more likely to be offered tenure. This finding aligns with recent research indicating that T5 publications carry significant weight in tenure decisions at top economic departments (Heckman & Moktan, 2024 ). However, contrary to anecdotes suggesting that obtaining tenure at top universities is difficult, our study shows that scholars are more likely to secure tenure when at one of the top five universities. Moreover, the number of tenured professors (N = 441) almost quadrupled that of the untenured scholars (N = 112). This disparity reflects the baseline competitiveness of tenure-track candidates, many of whom graduated from prestigious academic backgrounds. For instance, research shows that most faculty who obtained their PhDs from a small set of highly prestigious institutions (e.g., Harvard, MIT) disproportionately earned their bachelor’s degrees from elite universities (Jones and Sloan, 2021 ). This suggests a notable convergence between the origins of B.A. and PhD programs globally. Accordingly, the ‘PhD circle’ in academic economics (Klein, 2005) might be another explanation. It was reported that 80% to 90% of faculty members at elite economics departments obtained their Ph. D.s from the top 35 universities in the U.S. This insularity may reinforce a monocentric cultural pyramid within the top economics departments. Consequently, for scholars already embedded in this elite network, obtaining tenure might be less a question of capability but more a matter of time. In addition, our study indicates that scholars' surname initials exhibit a complex pattern in their relationship with tenure outcomes. The surname initial starting from ‘A’ to ‘F’ has benefits in receiving tenure compared to those whose surname begins between letter ‘G’ and ‘L’, which is consistent with previous research showing that alphabetical order influences the citation count (e.g., Huang, 2015 ) and tenure success (e.g., Einav & Yariv, 2006 ). However, the letters appearing earlier in the alphabet did not show any significant benefits compared to those at the end of the alphabet (e.g., XYZ). This finding implies that there might be a serial position effect (Fischer, 1966), which is also applicable to the recall of an author’s name in the reference list. Whereas the surname initials showing up at the beginning or end of the alphabet easily impress the scholars who are looking for citations, those in the middle could be somehow neglected. Implications of the Current Research The Hierarchy of Elite Economics The neoliberal economic paradigm, which gradually gained prominence in the late 20th century, posits that free-market principles, wherein meritocratic competition is prioritized, can eventually diminish systemic biases such as racism, ageism, and sexism (Harvey, 2005 ). However, our findings reveal a significant discrepancy with this idealized assumption: the hierarchical structure persists in elite economic departments. We could conclude this with the “double T5 hierarchy”: scholars who begin their careers at the top 5 financial institutions and publish in the most prestigious journals (T5) are favored in tenure decisions, reinforcing a cycle of institutional privilege. Diversity Considerations While diversity issues were not the central focus of our study, our findings raise critical questions about the interplay between IDR and systemic inequities in the academic field. The significantly fewer publications in IDR reflect the current tenure policies that still favor the disciplinary culture. Thus, as Fitzgerald et al. (2018) suggested, universities should acknowledge the value of interdisciplinary collaboration in tenure and review processes. Additionally, although prior studies have documented a persistent gender gap in tenure promotion rates (e.g., Antecol et al., 2018 ; Mickey et al., 2023 ), our study found no significant gender effect on tenure success. This nonconformity may reflect progress linked to equity-focused reforms in academia, such as the adoption of transparent tenure-track policies in North America grounded in merit-based principles (Stewart and Valian, 2018 ). However, the total number of tenured male professors (N = 415) is three times that of tenured female professors (N = 138), indicating an asymmetric distribution that reflects ongoing disparities in women’s representation. This imbalance might be due to systemic bias against female professionals, such as tenure-clock pressures exacerbated by caregiving responsibilities (Mickey et al., 2023 ). Limitations and Future Direction Our study still has some limitations. First, the research focuses exclusively on North American Universities, which constrains the generalizability of findings to other regions worldwide. Furthermore, the dataset used in this study may not fully capture the career outcomes of tenured and untenured economists. Because faculty websites often lag in updating personal information, we may omit some individuals who have transitioned to new roles. Moreover, propensity score matching (PSM) is not equal to the real experiment in terms of yielding causal interpretations. Sainai (2012) reported that the effects of unmeasured or unobserved confounders cannot be fully accounted for without real assignment and manipulation under PSM. Regarding future direction, prospective studies could replicate our study across universities in other regions to examine whether implicit bias against IDR persists globally in economics departments. Additionally, qualitative interviews with tenure committee members at top economics departments can be conducted to investigate institutional attitudes toward IDR and to elucidate how biases manifest in the evaluative process. Finally, prospective research should also be concerned about whether the current academic promotion system disadvantages the population who are usually neglected in the policy research, such as the non-tenure-track faculty mothers (Beck, 2025 ) References Aboelela SW, Larson E, Bakken S, Carrasquillo O, Formicola A, Glied SA, Haas J, Gebbie KM (2007) Defining Interdisciplinary Research: Conclusions from a Critical Review of the Literature. Health Serv Res 42:329–346. https://doi.org/10.1111/j.1475-6773.2006.00621.x Acker S, Wagner A (2019) Feminist scholars working around the neoliberal university. Gend Educ 31:62–81. https://doi.org/10.1080/09540253.2017.1296117 Angrist J, Azoulay P, Ellison G, Hill R, Lu SF (2020) Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship. J Econ Lit 58:3–52. https://doi.org/10.1257/jel.20181508 Antecol H, Bedard K, Stearns J (2018) Equal but Inequitable: Who Benefits from Gender-Neutral Tenure Clock Stopping Policies? 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Energy Res Social Sci 25:9–18. https://doi.org/10.1016/j.erss.2016.11.001 McFadden P, Neill RD, Mallett J, Manthorpe J, Gillen P, Moriarty J, Currie D, Schroder H, Ravalier J, Nicholl P, Ross J (2022) Mental well-being and quality of working life in UK social workers before and during the COVID-19 pandemic: A propensity score matching study. Br J Social Work 52:2814–2833. https://doi.org/10.1093/bjsw/bcab198 Mickey EL, Misra J, Clark D (2023) The persistence of neoliberal logics in faculty evaluations amidst Covid-19: Recalibrating toward equity. Gend Work Organ 30:638–656. https://doi.org/10.1111/gwao.12817 Nicholas D, Herman E, Rodríguez-Bravo B, Watkinson A, Boukacem-Zeghmouri C, Świgoń M, Abrizah A, Sims D, Xu J, Clark D, Serbina G, Jamali HR, Tenopir C, Allard S (2023) Peer review: the attitudes and behaviours of Covid-19 pandemic-era early career researchers. https://doi.org/10.3145/epi.2023.may.06 . EPI e320306 Rosenbaum PR, Rubin DB n.d. The central role of the propensity score in observational studies for causal effects Sá CM (2008) Interdisciplinary strategies’ in U.S. research universities. High Educ 55:537–552. https://doi.org/10.1007/s10734-007-9073-5 Sarsons H, Gërxhani K, Reuben E, Schram A (2021) Gender Differences in Recognition for Group Work. J Polit Econ 129:101–147. https://doi.org/10.1086/711401 Schimanski LA, Alperin JP (2018) The evaluation of scholarship in academic promotion and tenure processes: Past, present, and future. F1000Res 7:1605. https://doi.org/10.12688/f1000research.16493.1 Schläpfer F, Implications for Environmental Economic Research (2010) GAIA - Ecol Perspect Sci Soc 19:140–145. https://doi.org/10.14512/gaia.19.2.13 . How Much Does Journal Reputation Tell Us About the Academic Interest and Relevance of Economic Research? Empirical Analysis and Shaw K, Lazear EP (2008) Tenure and output. Labour Econ 15:704–723. https://doi.org/10.1016/j.labeco.2007.08.004 Slaughter S, Leslie LL (2001) Expanding and Elaborating the Concept of Academic Capitalism. Organization 8:154–161. https://doi.org/10.1177/1350508401082003 Spooner M (2020) Technologies of Governance in Context: Four Global Windows Into Neoliberalism and Audit Culture in Higher Education. Qualitative Inq 26:743–747. https://doi.org/10.1177/1077800419878750 Stewart AJ, Valian V (2018) An Inclusive Academy: Achieving Diversity and Excellence. The MIT Press. https://doi.org/10.7551/mitpress/9766.001.0001 Tian M, Su Y, Ru X (2016) Perish or Publish in China: Pressures on Young Chinese Scholars to Publish in Internationally Indexed Journals. Publications 4:9. https://doi.org/10.3390/publications4020009 Townsend RM, Zhang NX n.d. Innovative financial designs utilizing homomorphic encryption and multiparty computation Turner VK, Benessaiah K, Warren S, Iwaniec D (2015) Essential tensions in interdisciplinary scholarship: navigating challenges in affect, epistemologies, and structure in environment–society research centers. High Educ 70:649–665. https://doi.org/10.1007/s10734-015-9859-9 Urrieta L Jr, Méndez,Lina, Rodríguez E (2015) A moving target: a critical race analysis of Latina/o faculty experiences, perspectives, and reflections on the tenure and promotion process. Int J Qualitative Stud Educ 28:1149–1168. https://doi.org/10.1080/09518398.2014.974715 Zambrana RE, Carvajal,Diana, Townsend J (2023) Institutional penalty: mentoring, service, perceived discrimination and its impacts on the health and academic careers of Latino faculty. Ethnic Racial Stud 46:1132–1157. https://doi.org/10.1080/01419870.2022.2160651 Additional Declarations The authors declare no competing interests. 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12:40:11","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":123832,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8560476/v1/31b87a9ae787e0026c6b5c8e.html"},{"id":100147395,"identity":"c4edfa7a-31cd-416d-9b2e-9f611e8798f3","added_by":"auto","created_at":"2026-01-13 12:40:10","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68959,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8560476/v1/a342d2cdaa6ea311bff02f42.jpeg"},{"id":100147405,"identity":"5b74ce97-1512-481e-9633-75d26ec8ba4a","added_by":"auto","created_at":"2026-01-13 12:40:11","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":107686,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8560476/v1/3159c450409335cdbf09a18d.jpeg"},{"id":100147458,"identity":"7d723181-992f-42a0-b824-b0222e7c01b1","added_by":"auto","created_at":"2026-01-13 12:40:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1040787,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8560476/v1/52e7ec04-420c-4262-8f0c-b7a4ac1ad3f3.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eHow Interdisciplinary Research Affects Tenure Decision at Elite Economics Departments: Evidence from 2000-2024\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eInterdisciplinary research (IDR), integrating knowledge, theories, and methodologies from multiple disciplines, has emerged as a critical approach to addressing complex societal challenges that transcend single-disciplinary boundaries (Aboelela et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). S\u0026aacute; (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) reported that prestigious institutions have established incentive grants to encourage researchers to invest in interdisciplinary areas. Within a decade, the top 1% of most-cited academic papers have consistently exhibited higher levels of interdisciplinarity across disciplines (Chen et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, when conducting IDR, scholars may encounter epistemic, structural, and affective tensions (Turner et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Engaging with diverse disciplines or methodologies can increase uncertainty about publication success. It heightens the insecurity of IDR researchers seeking academic tenure, a permanent position that confers job security and scholarly autonomy (Shaw and Lazear, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), as tenure decisions often prioritize traditional disciplinary contributions. For instance, a qualitative study that interviewed senior tenured scholars revealed stark disciplinary divides in attitudes toward IDR: while science, technology, engineering, and mathematics (STEM) research leaders actively encouraged untenured researchers to pursue interdisciplinary projects, those in the economics department perceived such work as less valuable in tenure evaluations (M\u0026auml;kinen et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Hence, early-career economists may face a dilemma: pursuing IDR may yield transformative societal impacts, but it could influence publication outputs in core economic journals, which are critical for tenure decisions. Hence, the current study examined whether IDR influences academic promotion among tenure-track economists.\u003c/p\u003e"},{"header":"Literature Review on tenure decisions and interdisciplinary research (IDR) in Economics","content":"\u003cp\u003eTenure represents a pivotal milestone for scholars across the social sciences, offering two foundational benefits: job security and academic freedom. In economics departments, the pursuit of tenure is uniquely intense, shaped by the discipline\u0026rsquo;s competitive norms and institutional structures. Economics is distinguished by a hierarchical job market that prioritizes institutional pedigree and publication records in high-impact journals (Burris, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Unlike other social sciences departments, which reward fieldwork or theoretical innovation, economics emphasizes empirical rigor and a narrow set of high-status publication outlets. This creates a \u0026lsquo;tournament\u0026rsquo; culture in which early-career scholars face disproportionate pressure to outperform their peers to secure tenure (Oyer, 2006).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCurrent Policy on Tenure Decisions\u003c/h2\u003e \u003cp\u003eBefore the 1990s, the evaluation of faculty work was conducted with little transparency, often accompanied by vague and inconsistent policies that could be susceptible to bias in favor of specific groups, such as White men or individuals with special personal networks (Stewart and Valian, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This lack of transparency was challenged by neoliberal logic within higher education institutions in the 1990s, which placed greater emphasis on rigor in tenure evaluations. Slaughter and Leslie (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) argued that this transformation to the current tenure decision process can be explained by various political and economic contributors, such as the mitigation of external funding and the influence of marketing competition logic in the traditional non-economic fields (e.g., academia, government).\u003c/p\u003e \u003cp\u003eWithin neoliberal capitalism, top universities in North America have adopted objective measures to assess scholars\u0026rsquo; academic productivity, as quantifiable contributions are believed to reduce prejudice and inequality (Mickey et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite existing gender inequality (e.g., Antecol et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and authorship order based on scholars\u0026rsquo; surnames (e.g., Huang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), this strategy is relatively more transparent than that in most of the world. Today, faculty members in top economics departments are audited annually by their academic committees. Scholarly output, often reflected in publications in top-tier journals, is a key indicator in tenure decisions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFlaws of neoliberal capitalism in economic departments\u003c/h3\u003e\n\u003cp\u003eHowever, this merit-based system still has limitations with respect to academic outcomes. Top universities in North America are under pressure to boost their international ranking by increasing the number of published articles in high-status journals, which could be an indicator for attaining more funding resources (Spooner, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This proliferation of publications has narrowed economists\u0026rsquo; research scope, leading them to focus more on publishing articles for economic gain and prestige than on genuine academic ambition (Acker and Wagner, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In addition, this free-market neoliberal capitalism may fail to yield research productivity. For example, Backes-Gellner and Schlinghoff (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) compared U.S. economists with German economists and reported that the U.S. tenure policy drives a significant increase in publications before tenure, but the output of publications has seen a dramatic decline during the post-tenure phase.\u003c/p\u003e\n\u003ch3\u003eThe Tyranny of the top five in the economic department\u003c/h3\u003e\n\u003cp\u003eIn the economic domain at North American Universities, tenure decisions are conventionally aligned with metric-based standards. The metric of research productivity strongly emphasizes publishing in a group of highly prestigious journals, commonly referred to as the \u0026lsquo;top five\u0026rsquo; (T5) (American Economic Review, Quarterly Journal of Economics, Journal of Political Economy, Econometrica, and Review of Economic Studies). This system creates strong incentives for early-career economists to focus on securing T5 publications, thus deciding their career trajectories. However, concerns have been raised about the long-term effects of this structure on research innovation and systemic imbalances within the discipline of economics. While the emphasis on T5 publications provides a clear benchmark for evaluation, it also introduces distortions in research: the scope of publications in these journals remains minimal, and young researchers find it even harder to secure successful acceptance in these journals. Heckman and Moktan (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) refers to this as the \u0026lsquo;tyranny of the top five\u0026rsquo;.\u003c/p\u003e \u003cp\u003eAccording to Heckman and Moktan (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the publications on T5 have been strongly predictive of tenure outcomes at the top 35 U.S. economics departments. This finding aligns with a pattern analysis by Coup\u0026eacute; et al. (2004) of 1,000 economists over three decades, which shows that tenure promotion and mobility to high-tier universities are highly sensitive to publication output, particularly in T5 outlets. Through econometric analysis and survey data, they argue that overreliance on T5 publications for screening can distort research incentives, prioritizing careerism over creativity.\u003c/p\u003e\n\u003ch3\u003eThe Reputation of IDR in Economics\u003c/h3\u003e\n\u003cp\u003eSince current merit-based policies in North American economics departments favor disciplinary insularity, they may limit the scope of research output. In response to this issue, IDR may serve as a complement, adding standards to tenure decision-making. However, compared with the consensus on the value of top-tier economic journals such as T5, there is ongoing debate about whether IDR should be taken seriously within elite North American economics departments.\u003c/p\u003e\n\u003ch3\u003eHistorical Skepticism\u003c/h3\u003e\n\u003cp\u003eEconomic research has long been characterized by a strong disciplinary identity rooted in neoclassical economics and quantitative modeling. Given this tradition, some authority figures in the economics department typically equate prestige with adherence to these traditional paradigms. For instance, Fourcade et al. (2015) found that economists view their discipline as a \u0026lsquo;superior science\u0026rsquo; because they perceive IDR as lacking the mathematical precision or theoretical coherence. This sentiment is reinforced by tenure and promotion criteria that prioritize publications in a narrow set of high-impact economics journals (Heckman and Moktan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). IDR, which often requires collaboration with non-economists or publication in interdisciplinary outlets, has historically been perceived as a risky career strategy for early-career scholars (Schl\u0026auml;pfer, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSystematic Barriers to IDR\u003c/h2\u003e \u003cp\u003eThe reputation of IDR is inextricably tied to publication norms. Top economics journals rarely publish work co-authored with non-economists or employing non-economic methodologies, because journal reputation metrics discount contributions from an interdisciplinary perspective (Schl\u0026auml;pfer, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Several studies also highlight obstacles that limit the adoption and impact of IDR in economics. For instance, the editorial boards of top economic journals play a key role in placing hurdles on IDR in economics. Ductor and Visser (2021) found that editorial boards remain dominated by researchers from a limited range of institutions, who exhibit a preference for mono-disciplinary research while limiting IDR\u0026rsquo;s visibility. This aligns with another study demonstrating that economics has historically exhibited strong disciplinary insularity, borrowing less from other fields than others borrow from economics (Angrist et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, tensions arise for scholars within a disciplinary domain when pursuing interdisciplinarity. This could make the tenure and promotion process less favorable to IDR, as it is difficult for the research committee to formulate standardized criteria for evaluating IDR performance.\u003c/p\u003e \u003cp\u003eFurthermore, elite departments exhibit contradictory stances toward IDR. Institutions such as MIT and Harvard have launched interdisciplinary initiatives (e.g., behavioral economics labs, climate econometrics consortia), indicating a shift toward valuing IDR\u0026rsquo;s academic impact (Townsend \u0026amp; Zhang, 2021). However, these efforts often exist alongside rigid tenure criteria that disadvantage interdisciplinary scholars. Additionally, gender disparities may influence IDR\u0026rsquo;s reputation: women in economics are more likely to pursue interdisciplinary collaborations but face greater scrutiny for diverging from traditional research paths (Sarsons et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, while IDR's reputation in top economics departments reflects growing recognition, persistent biases continue to hinder young researchers' ambitions and motivation to succeed academically in IDR. However, there remains a lack of empirical evidence on the long-term career outcomes of interdisciplinary economists. Therefore, the current study aims to determine whether the risks associated with publishing IDR are diminishing within elite economic institutions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eResearch Questions\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDoes IDR Influence Tenure Success?\u003c/h2\u003e \u003cp\u003eAs noted, researchers in tenure-track positions may still prioritize core-economics publications (e.g., the \u0026lsquo;T5\u0026rsquo;) in pursuit of tenure promotion. However, there is no empirical evidence demonstrating whether IDR significantly affects tenure outcomes. To date, we have found only anecdotal claims that increasing IDR in the economics department might hinder tenure promotion, with no empirical evidence (Mallaband et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, the current project primarily established a dataset that addresses tenure outcomes and the number of IDR publications before tenure. Given that a limited number of universities offer tenure-track positions, we focused on the top 50 universities in North America that provide graduate economics courses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDo Socio-Demographics Confound IDR's Impact\u003c/h2\u003e \u003cp\u003ePotential disparities in tenure attainment across socio-demographic groups raise critical questions about whether factors such as gender, age, and ethnicity interact with IDR to shape tenure promotion outcomes. Empirical evidence suggests that systematic biases still exist against women and scholars from minority backgrounds, despite established policies such as the tenure-clock stop for maternal (e.g., Antecol et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sarsons et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In China, institutional age restrictions (e.g., requiring candidates to be under 35 years old) also exclude older scholars seeking tenure-track positions (Tian et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe temporal constraints of the tenure clock add another layer of complexity. Publication delays, which are common in peer-reviewed journals, disproportionately affect early-career economists who are often racing to meet deadlines (Conley et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Especially since COVID-19, the peer-review timeline has been further delayed due to a lack of reviewer participation (Nicholas et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Such delays may exacerbate inequalities: women, older scholars, and minority scholars risk their careers in chasing the \u0026lsquo;publish or perish\u0026rsquo; timeline, thereby complicating assessments of IDR\u0026rsquo;s impact on tenure success. This interplay may underscore the need to distinguish IDR\u0026rsquo;s independent effects from the structural inequities that shape academic careers. Hence, this study rigorously controlled for sociodemographic variables to determine whether IDR inherently disadvantages researchers or reflects preexisting biases in tenure evaluation systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eDo Other Factors Moderate IDR\u0026rsquo;s Influence?\u003c/h2\u003e \u003cp\u003eBeyond socio-demographic information, other factors, such as authorship, university reputation, and journal rank, may also contribute to tenure success. For instance, prior studies have shown that the order of authors on the reference list can influence tenure promotion at the top 5\u0026ndash;10 universities in the US (Einav and Yariv, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, this effect became insignificant when the researchers expanded their dataset to the top 35 universities. This suggests that institutional ranking may moderate the role of authorship hierarchy, with elite universities potentially placing greater emphasis on collaborative contributions.\u003c/p\u003e \u003cp\u003eFurthermore, although the impact factor and journal reputation could significantly improve tenure success (e.g., Heckman \u0026amp; Moktan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), uncertainties persist regarding IDR-focused journals: whether their prestige confers advantages comparable to those of discipline-specific top-tier journals remains unexplored. This gap is critical, as academic committees often rely on journal rankings (Bajo et al., 2020; Schimanski \u0026amp; Alperin, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), yet traditional metrics may undervalue interdisciplinary work. The present study, therefore, investigates the potential confounding effects of three covariates. By studying these factors, we aim to clarify how IDR contributions are evaluated in tenure decisions in the economics department.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eHypothesis\u003c/h2\u003e \u003cp\u003eBased on the proposed research questions, we developed the following three hypotheses:\u003c/p\u003e \u003cp\u003eH1: Research types (core-economic vs. IDR) will significantly influence the outcome of tenure success. Scholars with higher IDR are less likely to achieve tenure.\u003c/p\u003e \u003cp\u003eH2: The socio-demographic factors, including gender, ethnicity, and age, will significantly confound the influence of research type on tenure success.\u003c/p\u003e \u003cp\u003eH3: Other covariates comprising the alphabetical order of scholars\u0026rsquo; surname, university rank, and journal prestige will significantly moderate IDR\u0026rsquo;s impact on tenure outcomes.\u003c/p\u003e \u003c/div\u003e "},{"header":"Methods, Data, and Sample","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003cp\u003eTo investigate whether publishing interdisciplinary research influences tenure promotion outcomes, we compiled a dataset from the curricula vitae (CVs) of tenure-track faculty in economics departments at the top 50 North American universities from 2000 to 2024. The ranking of academic departments is based on U.S. News \u0026amp; World Report rankings, widely regarded as among the most authoritative sources (U.S. News \u0026amp; World Report, 2024). This timeframe was chosen to align with post-1990 reforms that standardized tenure evaluation processes (Stewart \u0026amp; Valian, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), ensuring consistency in institutional policies during the study period.\u003c/p\u003e \u003cp\u003eThe CVs provided comprehensive data on scholars\u0026rsquo; publication histories, including journal types (disciplinary vs. interdisciplinary), co-authorship networks, journal impact factors, and demographic variables (e.g., gender, age, ethnicity). Using this dataset, we evaluated the relationship between interdisciplinary publication strategies and tenure success while controlling for co-authorship patterns, journal prestige, and demographic factors. Critically, this study examined whether interdisciplinary publication strategies enhance or hinder tenure progression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eData Search Strategy\u003c/h2\u003e \u003cp\u003eThe dataset for this study was compiled by systematically retrieving historical faculty information from the economics departments of the top 50 universities in North America. To ensure access to the earliest available data, we relied on the Wayback Machine (WM), a digital archiving service operated by the U.S.-based non-profit Internet Archive (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.archive.org\" target=\"_blank\"\u003ewww.archive.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.archive.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The WM preserves historical snapshots of websites, enabling researchers to trace changes in online content over time (Help Center, 2025). Its reliability as a tool for social science research has been empirically validated (Murphy et al., 2007), making it well-suited for reconstructing career timelines. We focused on webpage versions dated after 1999, as this timeframe aligns with documented shifts toward merit-based and transparent tenure practices in U.S. academia (Stewart \u0026amp; Valian, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFaculty data collection began with the download of CVs from departmental websites. For scholars whose CVs were not accessible, we gathered career information from personal academic websites linked through faculty directory pages. The coding process emphasized four key career markers: the completion years of bachelor\u0026rsquo;s and doctoral degrees, the start years of tenure-track positions, and the years in which tenure decisions (both granted and denied) were finalized. Publication records were also documented, including paper titles and journal names. A significant challenge arose in verifying authorship conventions specific to economics, where alphabetical surname ordering typically supersedes contribution-based sequencing (Einav \u0026amp; Yariv, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Furthermore, given research indicating that surname initials significantly impact citation counts, with early-alphabet initials (e.g., ABC) conferring advantages over later ones (e.g., XYZ) (Huang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), we analyzed this factor. Specifically, we extracted all economists' surnames and initial letters, ordered them alphabetically, and categorized them into four groups based on ascending quartiles. This resulted in the first quartile ('A' to 'F') representing the earliest-alphabet initials, and the fourth quartile ('S' to 'Z') representing the latest-alphabet initials.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOperationalizing Tenure Construction\u003c/h2\u003e \u003cp\u003eA primary challenge in operationalizing tenure status arises from underreporting denied tenure decisions in publicly available CVs, as scholars rarely document unsuccessful promotions. To mitigate sample selection bias, particularly the risk of conflating voluntary departures (e.g., to industry or governmental roles) with tenure denials, we employed three criteria by Sarsons et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). First, individuals transitioning to non-academic roles (e.g., industry or government positions) after more than four years as assistant professors were classified as having denied tenure. Second, scholars departing for institutions outside North America after seven years (the typical tenure-clock window) were similarly categorized, since international academic promotion systems differ significantly from those in North America, and prolonged investment in a regional academic career reduces the likelihood of voluntary relocation. Third, downward mobility in both departmental and university rankings (e.g., moving to an institution ranked five positions lower) was interpreted as evidence of tenure denial. This ranking criterion accounts for disciplinary preferences: some scholars prioritize departmental specialization over institutional prestige, potentially accepting positions at lower-ranked universities without incurring career setbacks.\u003c/p\u003e \u003cp\u003eWe excluded adjunct or visiting professors, individuals granted tenure before 2000, and teaching-focused faculty without research obligations, as their career trajectories do not align with standardized tenure-track promotion criteria. After applying these filters, the final sample comprised 553 tenure-track scholars in economics at the top 50 North American institutions, of whom 441 achieved tenure, and 112 were classified as denied tenure.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCategorizing Research Type and Journal Impacts\u003c/h2\u003e \u003cp\u003eWe classified economists\u0026rsquo; published papers in non-economics journals as \u0026lsquo;interdisciplinary research\u0026rsquo;. We first reviewed the stated aims and scope on each journal\u0026rsquo;s official website to determine journal categorisation. However, this approach proved insufficient, as most journals, including top-tier economics journals like the Journal of Political Economy, explicitly welcome submissions from diverse domains. Despite such broad editorial statements, economists generally agree that specific journals (e.g., top economics journals) remain predominantly single-disciplinary in practice, even if their stated scope appears interdisciplinary.\u003c/p\u003e \u003cp\u003eTo resolve this ambiguity, we adopted the methodological protocol developed by Combes and Linnemer (2020), which synthesizes journal classifications from the Web of Science (WoS) and the EconLit database. Their algorithm identifies core economics journals by analyzing their specialization patterns relative to economic subfields. By weighting WoS and EconLit classifications, Combes and Linnemer distinguish between core economic journals and those that are interdisciplinary or belong to other disciplines, referred to as \u0026lsquo;interdisciplinary\u0026rsquo;. Following this framework, we categorised all publications in our dataset as core-economic or interdisciplinary. For journals not listed in Combes and Linnemer\u0026rsquo;s (2020) tables, we relied on information from their official websites to evaluate their stated aims and scope. As a supplementary measure, we assumed that journals emphasizing adjacent fields, such as finance or business, remained core economics journals. In contrast, those explicitly incorporating disciplines such as psychology and sociology, or those beyond the social sciences (e.g., natural sciences), were classified as interdisciplinary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eJournal Prestige\u003c/h2\u003e \u003cp\u003eTo evaluate scholarly impact, we categorize journals into two tiers: (1) publications in the \u003cem\u003eTop 5 (T5)\u003c/em\u003e economic journals and (2) all others. This binary classification reflects the consensus among economists regarding the role of T5 publications (\u003cem\u003eAmerican Economic Review\u003c/em\u003e, \u003cem\u003eEconometrica\u003c/em\u003e, \u003cem\u003eJournal of Political Economy\u003c/em\u003e, \u003cem\u003eQuarterly Journal of Economics\u003c/em\u003e, and \u003cem\u003eReview of Economic Studies\u003c/em\u003e) in tenure decisions, relative to other economics journals. As Heckman and Moktan (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) emphasize, the \u0026lsquo;tyranny of the Top Five\u0026rsquo; reflects an institutional obsession in which publishing in these journals is widely perceived as a prerequisite for tenure promotion. This approach aligns with norms in top economic departments by prioritizing clarity and pragmatism over rankings based on ambiguous standards.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDefining Other Covariates\u003c/h2\u003e \u003cp\u003eTo collect other covariates relevant to the person\u0026rsquo;s demographic information, we refer to tenure-track economists\u0026rsquo; CVs and personal websites, which are linked to departmental officials. However, although gender can be inferred from the department website's gender pronouns, most individuals did not disclose their age or ethnicity, and only a few indicated their nationality on their CVs or personal websites. Therefore, to infer their ethnic background, we used their surname origin, which can be found on \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.archive.org\" target=\"_blank\"\u003ewww.ancestry.com/learn/factscon\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.ancestry.com/learn/factscon\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (\u003cem\u003eLast Name Meanings and Origins\u003c/em\u003e. 2025), and verified this information against their profile picture. To comply with the ethnicities category, we adopted the questionnaire developed by Elsevier Inclusion \u0026amp; Diversity center (2023) to classify six major ethnicities among the observed scholars. These six categories are:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e \u003cem\u003eCaucasian, Hispanic/Latino, Black African, Middle Eastern/North African, East Asian, and South Asian.\u003c/em\u003e \u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTo address potential age-related confounders, we adopted career progression timelines as more reliable indicators than chronological age, with two considerations. First, publicly available professional profiles (e.g., LinkedIn and Wikipedia) rarely disclose birthdates, whereas educational milestones and employment records are more readily accessible. Second, the only data that implicated their age was from their career timelines on their respective CVs. Therefore, we focused on a single career timeline for critically reflecting on scholars\u0026rsquo; age trajectories: the foundational training period from the conferral of a bachelor's degree to PhD completion. Since most people begin college around the same age, the time between BA and PhD may reflect relative age differences among economists, with longer intervals indicating older age at the start of their academic careers and shorter intervals indicating younger age. The descriptions of all covariates for the matched sample are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptions of Covariates in the Dataset\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCovariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Male; 2\u0026thinsp;=\u0026thinsp;Female\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Caucasian White; 2\u0026thinsp;=\u0026thinsp;Hispanic/Latino; 3\u0026thinsp;=\u0026thinsp;Black; 4\u0026thinsp;=\u0026thinsp;Middle East/North Africa; 5\u0026thinsp;=\u0026thinsp;Eastern Asian; 6\u0026thinsp;=\u0026thinsp;South Asian\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBA_to_PHD\u0026thinsp;=\u0026thinsp;Period from bachelor\u0026rsquo;s degree to PhD conferment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity Rank\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElite\u0026thinsp;=\u0026thinsp;Top 5 Economic Departments; Leading\u0026thinsp;=\u0026thinsp;Economic departments ranked from 6 to 15; Strong\u0026thinsp;=\u0026thinsp;Economic departments\u0026thinsp;=\u0026thinsp;ranked from 16 to 30; Good\u0026thinsp;=\u0026thinsp;Economic departments ranked from 31 to 50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurname Initials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Surname Initials start from A to F; 2\u0026thinsp;=\u0026thinsp;Surname Initials start from G to L; 3\u0026thinsp;=\u0026thinsp;Surname Initials start from M to R; 4\u0026thinsp;=\u0026thinsp;Surname Initials start from S to Z\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJournal Prestige\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enon-T5\u0026thinsp;=\u0026thinsp;Journal_rank0; T5\u0026thinsp;=\u0026thinsp;Journal_rank1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e-----------------------------------------Insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Here------------------------------------------\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eConsidering that the current study is based on retrospective observation, the statistical method, namely, propensity score matching (PSM), could allow us to identify whether conducting interdisciplinary research would influence the outcome of tenure success by balancing two groups (economic vs. interdisciplinary research), given a set of collected covariates (Rosenbaum \u0026amp; Rubin, 1983). By adopting this approach, we can simulate a pseudo-random assignment to infer the effect of research type and tenure success.\u003c/p\u003e \u003cp\u003eAmong all PSM methods, we selected \u003cem\u003efull matching\u003c/em\u003e, which uses all available cases in the sample by grouping them into matched clusters containing at least one case from the IDR group and one from the core-economic group. There are two reasons for using this method over alternatives (e.g., nearest-neighbor matching). First, the full matching method focuses on the entire sample without excluding any cases; second, it improves statistical power in the current study, as the sample size is relatively small and the number of observations for the control group (N\u0026thinsp;=\u0026thinsp;441) substantially exceeds that of the treatment group (N\u0026thinsp;=\u0026thinsp;11)).\u003c/p\u003e \u003cp\u003eUsing PSM with full matching, we matched the treatment group (interdisciplinary research) and the control group (core-economic research) in a dataset with 553 observations. Six covariates described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were used for matching. The analysis employed full matching with the \u003cem\u003eMatchIt\u003c/em\u003e R package (Ho et al., 2011), yielding control and treated samples of 57 individuals each. Figure\u0026nbsp;1 illustrates the study\u0026rsquo;s research flow.\u003c/p\u003e \u003cp\u003e-----------------------------------------Insert Fig.\u0026nbsp;1 Here-----------------------------------------\u003c/p\u003e \u003cp\u003eThe matching performance was assessed using Standardized Mean Differences (SMDs) and variance ratios (VRs), along with visualization. This matching yielded a good balance, as most covariate SMDs were below the cutoff of 0.2, whereas most VRs were within the acceptable range of 0.8\u0026ndash;1.25 (Austin, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the descriptive statistics and standardized mean differences (SMDs) of the covariates used. Figure\u0026nbsp;2 (a) and Fig.\u0026nbsp;2 (b) illustrate that the matched treated and control samples are reasonable.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBalance Statistics Before and After Full Matching\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnmatched Sample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMatched Sample\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTreated\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJournal_rank0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJournal_rank1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender_female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGende_male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurname_Initials1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurname_Initials2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurname_Initials3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurname_Initials4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1887\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.2555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0330\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1969\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0698\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0789\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBA_to_PHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.1425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.2250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0413\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote. SMD\u0026thinsp;=\u0026thinsp;Standardized Mean Difference. Balance improved substantially after full matching, with most SMD values below the 0.25 threshold.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e-----------------------------------------Insert Fig.\u0026nbsp;2 Here-----------------------------------------\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Interdisciplinary Research on Tenure Success\u003c/h2\u003e \u003cp\u003eAfter obtaining the matched samples, we conducted a logistic regression analysis to assess the causal relationship between research type and tenure success outcomes for all economists in the top 50 North American economic departments. The study revealed that five variables significantly predicted tenure outcomes: While no significant effect of performing IDR was found (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.27), those identifying with a Latino or Hispanic background ) was associated with sharply reduced odds of tenure (OR\u0026thinsp;=\u0026thinsp;0.05, 95% CI [0.01, 0.19], z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;4.42, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and each additional year between the bachelor\u0026rsquo;s and Ph.D. degrees corresponded to a 10% reduction in the odds of tenure (OR\u0026thinsp;=\u0026thinsp;0.90, 95% CI [0.81, 0.99], z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;2.05, p\u0026thinsp;=\u0026thinsp;.041). In contrast, those with T5 publications (OR\u0026thinsp;=\u0026thinsp;3.60, 95% CI [2.14, 6.05], z\u0026thinsp;=\u0026thinsp;4.78, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) are at higher odds of getting tenure compared to those who have no T5 publications. The alphabetical order of surname initials also mattered: authors whose surnames start from letter \u0026lsquo;G\u0026rsquo; to \u0026lsquo;L\u0026rsquo; had about one-third the odds of tenure compared with those beginning between \u0026lsquo;A\u0026rsquo; to \u0026lsquo;F\u0026rsquo; (OR\u0026thinsp;=\u0026thinsp;0.33, 95% CI [0.17, 0.64], z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;3.40, p\u0026thinsp;=\u0026thinsp;.001). Finally, faculty members who started their career at economic institutions ranked between 6 and 15 are less likely to be tenured than those from the top five economic departments (OR\u0026thinsp;=\u0026thinsp;0.37, 95% CI [0.14, 0.96], z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;1.99, p\u0026thinsp;=\u0026thinsp;.047). The model also demonstrated a significant fit, with χ\u0026sup2; (15)\u0026thinsp;=\u0026thinsp;71.35, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, and an Akaike Information Criterion (AIC) of 524.36, indicating good explanatory value.\u003c/p\u003e \u003cp\u003e------------------------------------------Insert Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Here-----------------------------------------\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study initially used empirical evidence to examine how interdisciplinary research (IDR) affects tenure outcomes in top economics departments. After controlling for other covariates over the last two decades, we found no effect of IDR on tenure success in top economics departments in North America. However, other covariates, including ethnicity, age, journal prestige, surname initials, and the University\u0026rsquo;s rank, were associated with the tenure outcome. This finding suggests that, although the growing number of IDR publications may mitigate bias against interdisciplinary researchers in economics, top research institutions still harbor implicit stereotypes about economists\u0026rsquo; identities.\u003c/p\u003e \u003cp\u003eOur findings did not support the first hypothesis: scholars producing IDR were not less likely to be promoted to tenure than their counterparts who published core economic articles. This is consistent with the recent trend in the elite economic academy, where the value of IDR has gained more endorsement (e.g., Townsend \u0026amp; Zhang, 2021). However, the dataset obtained in the current study indicates a disproportionate number of articles published in core economic journals (N\u0026thinsp;=\u0026thinsp;2778) relative to those published in interdisciplinary journals (N\u0026thinsp;=\u0026thinsp;419). This implies that, among economists at top research institutions, there has yet to be a departure from disciplinary purity. While universities publicly encourage IDR innovation, they often unconsciously prioritize single-disciplinary research (Turner et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Past research has also revealed that, despite increasing research funding, the number of publications in disciplinary journals (e.g., the Canadian Journal of Agricultural Economics) has not increased significantly, suggesting that institutional incentives fail to translate into scholarly recognition (Hamermesh, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The publication of IDR remains in short supply in leading economics departments in North America.\u003c/p\u003e \u003cp\u003eRegarding H2, our findings indicate that ethnicity and age impact tenure success. Hispanic/Latino individuals are less likely to receive tenure promotions. This aligns with the theory of implicit racial bias, which refers to unconscious attitudes or stereotypes influencing people\u0026rsquo;s judgment and decision-making. Research consistently demonstrates how such biases disadvantage underrepresented groups in academia in North America (Urrieta Jr. et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Among Hispanic scholars, prior studies have reported that they face systemic barriers to promotion and retention relative to their White peers in academic medicine (Fang et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Kaplan et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Our study accordingly demonstrated this barrier for the Hispanic/Latino group. These outcomes may stem from two aspects rooted in implicit biases. First, faculty from minority groups often lack access to mentorship and professional networks critical for navigating career progression (Sapeg, 2020). Without this support, early-career economists with minority backgrounds may miss the opportunities to meet tenure benchmarks. Second, Hispanic researchers are disproportionately burdened by diversity service obligations that divert time from their professional development (Zambrana et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, although age was not directly collected in our sample dataset, a prolonged bachelor 's-to-PhD gap often correlates with older candidates, particularly compared to peers who transitioned directly to graduate school. This suggests that older candidates may face systemic disadvantages despite meeting formal criteria alone. Although North American academia notably lacks formal age restrictions for tenure eligibility, in contrast to institutionalized age ceilings such as China's 35-year policy (Tian et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), our finding reveals an implicit age bias in these \u0026lsquo;ostensibly transparent\u0026rsquo; systems.\u003c/p\u003e \u003cp\u003eThe findings also support H3, revealing a pattern related to journal and university prestige: individuals with publications in T5 journals are more likely to receive tenure promotions, and scholars affiliated with Top 5 universities are also more likely to be offered tenure. This finding aligns with recent research indicating that T5 publications carry significant weight in tenure decisions at top economic departments (Heckman \u0026amp; Moktan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, contrary to anecdotes suggesting that obtaining tenure at top universities is difficult, our study shows that scholars are more likely to secure tenure when at one of the top five universities. Moreover, the number of tenured professors (N\u0026thinsp;=\u0026thinsp;441) almost quadrupled that of the untenured scholars (N\u0026thinsp;=\u0026thinsp;112). This disparity reflects the baseline competitiveness of tenure-track candidates, many of whom graduated from prestigious academic backgrounds. For instance, research shows that most faculty who obtained their PhDs from a small set of highly prestigious institutions (e.g., Harvard, MIT) disproportionately earned their bachelor\u0026rsquo;s degrees from elite universities (Jones and Sloan, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This suggests a notable convergence between the origins of B.A. and PhD programs globally. Accordingly, the \u0026lsquo;PhD circle\u0026rsquo; in academic economics (Klein, 2005) might be another explanation. It was reported that 80% to 90% of faculty members at elite economics departments obtained their Ph. D.s from the top 35 universities in the U.S. This insularity may reinforce a monocentric cultural pyramid within the top economics departments. Consequently, for scholars already embedded in this elite network, obtaining tenure might be less a question of capability but more a matter of time.\u003c/p\u003e \u003cp\u003eIn addition, our study indicates that scholars' surname initials exhibit a complex pattern in their relationship with tenure outcomes. The surname initial starting from \u0026lsquo;A\u0026rsquo; to \u0026lsquo;F\u0026rsquo; has benefits in receiving tenure compared to those whose surname begins between letter \u0026lsquo;G\u0026rsquo; and \u0026lsquo;L\u0026rsquo;, which is consistent with previous research showing that alphabetical order influences the citation count (e.g., Huang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and tenure success (e.g., Einav \u0026amp; Yariv, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, the letters appearing earlier in the alphabet did not show any significant benefits compared to those at the end of the alphabet (e.g., XYZ). This finding implies that there might be a serial position effect (Fischer, 1966), which is also applicable to the recall of an author\u0026rsquo;s name in the reference list. Whereas the surname initials showing up at the beginning or end of the alphabet easily impress the scholars who are looking for citations, those in the middle could be somehow neglected.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eImplications of the Current Research\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eThe Hierarchy of Elite Economics\u003c/h2\u003e \u003cp\u003eThe neoliberal economic paradigm, which gradually gained prominence in the late 20th century, posits that free-market principles, wherein meritocratic competition is prioritized, can eventually diminish systemic biases such as racism, ageism, and sexism (Harvey, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, our findings reveal a significant discrepancy with this idealized assumption: the hierarchical structure persists in elite economic departments. We could conclude this with the \u0026ldquo;double T5 hierarchy\u0026rdquo;: scholars who begin their careers at the top 5 financial institutions and publish in the most prestigious journals (T5) are favored in tenure decisions, reinforcing a cycle of institutional privilege.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eDiversity Considerations\u003c/h2\u003e \u003cp\u003eWhile diversity issues were not the central focus of our study, our findings raise critical questions about the interplay between IDR and systemic inequities in the academic field. The significantly fewer publications in IDR reflect the current tenure policies that still favor the disciplinary culture. Thus, as Fitzgerald et al. (2018) suggested, universities should acknowledge the value of interdisciplinary collaboration in tenure and review processes.\u003c/p\u003e \u003cp\u003eAdditionally, although prior studies have documented a persistent gender gap in tenure promotion rates (e.g., Antecol et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mickey et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), our study found no significant gender effect on tenure success. This nonconformity may reflect progress linked to equity-focused reforms in academia, such as the adoption of transparent tenure-track policies in North America grounded in merit-based principles (Stewart and Valian, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, the total number of tenured male professors (N\u0026thinsp;=\u0026thinsp;415) is three times that of tenured female professors (N\u0026thinsp;=\u0026thinsp;138), indicating an asymmetric distribution that reflects ongoing disparities in women\u0026rsquo;s representation. This imbalance might be due to systemic bias against female professionals, such as tenure-clock pressures exacerbated by caregiving responsibilities (Mickey et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eLimitations and Future Direction\u003c/h2\u003e \u003cp\u003eOur study still has some limitations. First, the research focuses exclusively on North American Universities, which constrains the generalizability of findings to other regions worldwide. Furthermore, the dataset used in this study may not fully capture the career outcomes of tenured and untenured economists. Because faculty websites often lag in updating personal information, we may omit some individuals who have transitioned to new roles. Moreover, propensity score matching (PSM) is not equal to the real experiment in terms of yielding causal interpretations. Sainai (2012) reported that the effects of unmeasured or unobserved confounders cannot be fully accounted for without real assignment and manipulation under PSM.\u003c/p\u003e \u003cp\u003eRegarding future direction, prospective studies could replicate our study across universities in other regions to examine whether implicit bias against IDR persists globally in economics departments. Additionally, qualitative interviews with tenure committee members at top economics departments can be conducted to investigate institutional attitudes toward IDR and to elucidate how biases manifest in the evaluative process. 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Int J Qualitative Stud Educ 28:1149\u0026ndash;1168. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09518398.2014.974715\u003c/span\u003e\u003cspan address=\"10.1080/09518398.2014.974715\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZambrana RE, Carvajal,Diana, Townsend J (2023) Institutional penalty: mentoring, service, perceived discrimination and its impacts on the health and academic careers of Latino faculty. Ethnic Racial Stud 46:1132\u0026ndash;1157. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01419870.2022.2160651\u003c/span\u003e\u003cspan address=\"10.1080/01419870.2022.2160651\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Singapore Management University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Interdisciplinary research, tenure, top universities, T5 journal, academic hierarchy, elite economics departments","lastPublishedDoi":"10.21203/rs.3.rs-8560476/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8560476/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eInterdisciplinary research (IDR) has gained prominence for addressing complex societal challenges, yet its impact on academic tenure in economics remains unclear. This study examined how IDR influences tenure decisions in elite North American economics departments, using propensity score matching on curriculum vitae data from 553 tenure-track faculty at top 50 universities (2000–2024). Conducting IDR showed no significant effect on tenure success. However, other factors substantially influenced outcomes: Hispanic/Latino scholars faced dramatically reduced odds of tenure acceptance; each additional year between bachelor's and PhD decreased the likelihood by 10%; and T5 journal publications significantly increased the odds. While IDR does not disadvantage economists, systemic biases persist with respect to ethnicity, educational trajectory, journal prestige, and institutional hierarchy. These findings reveal that elite departments maintain implicit hierarchical structures that limit diversity and innovation in scholarship.\u003c/p\u003e","manuscriptTitle":"How Interdisciplinary Research Affects Tenure Decision at Elite Economics Departments: Evidence from 2000-2024","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 12:39:54","doi":"10.21203/rs.3.rs-8560476/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1e04ddfc-3ca3-4d4a-aa1b-5c96ef3f048e","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-13T12:39:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 12:39:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8560476","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8560476","identity":"rs-8560476","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}