Exit Rates Research Articles

Minimum wage and self-employed business owners: Evidence from South Korea

This study examines the influences of minimum wage on self-employment exits, using recent changes in the minimum wage level in South Korea. Using the cross-industry variation on the impact of the minimum wage—the proportion of workers whose wages are below the minimum wage in the upcoming year—combined with individual longitudinal data, I estimate the model of self-employment exits. Overall, the estimates show that the minimum wage hike has no significant impact on self-employed workers. However, it increases the likelihood of the business closing for the self-employed who hire employees. The results imply that a ten percent increase in the minimum wage raises the exit probability by 2.6 percentage points, which is 30.9 % of the average exit rate for those with employees. Moreover, the exits are significantly associated with the transition to non-employment.

The stickiness of pandemic-driven disenrollment from public schools

The extent to which pandemic-induced public school enrollment declines will persist is unclear. Student-level data from Michigan through fall 2021 yields three relevant findings. First, relative to pre-pandemic trends, fall 2021 enrollment had partially recovered for low-income, Black, and Hispanic students, but had declined further for non-low-income, White, and Asian students. Second, annual public school exit rates remained elevated for elementary students and accelerated further for middle school students. Third, public school exit is sticky and varies by chosen alternative. Only 21 percent of those who left for private schools in fall 2020 had returned by fall 2021, while 50 percent of those who left for homeschooling had returned. These findings suggest that pandemic-driven public school enrollment declines may persist, and more so among higher income families.

Firm performance and markets: survival analysis of medium and large manufacturing enterprises in Indonesia

AbstractThis study identifies the effect of firm performance, especially efficiency, on firm survival. This study applies efficiency calculations using a translog model based on both time-invariant and time-varying production functions and the Ackerberg–Caves–Frazer (ACF) model to overcome the endogeneity problem in the estimation of the production function. The data used are firm-level data, which are medium and large manufacturing company censuses with an observation period from 1995 to 2015. This study used two estimation techniques: the Cox proportional hazard model and Poisson regression. I estimate the Cox regression with firm-level data, whereas the Poisson regression is estimated with aggregate data for 2-digit ISIC. Estimates at the aggregate 2-digit ISIC level are intended to not only see the effect of efficiency on companies that survive but also on companies that enter and exit. Firm-level evidence shows that a company’s efficiency reduces the hazard ratio or increases its survival time. Moreover, consistent with firm-level results, the aggregate-level estimation shows that efficiency increases the chances of survival and entry of companies into Indonesia and reduces the rate of company exit from the Indonesian market. This shows that a company's level of technical efficiency makes an important contribution to the survival of manufacturing companies in Indonesia.

Long-term care use, hospitalizations and mortality during COVID-19 in Finland and Sweden: A nationwide register-based study in 2020.

To describe long-term care (LTC) use in Finland and Sweden in 2020, by reporting residential entry and exit patterns including hospital admissions and mortality, compared with the 2018-2019 period and community-living individuals. From national registers in Finland and Sweden, all individuals 70+ were included. Using the Finnish and Swedish study populations in January 2018 as the standard population, we reported changes in sex- and age-standardized monthly rates of entry into and exit from LTC facilities, mortality and hospital admission among LTC residents and community-living individuals in 2020. Around 850,000 Finns and 1.4 million Swedes 70+ were included. LTC use decreased in both countries from 2018 to 2020. In the first wave (March/April 2020), Finland experienced a decrease in LTC entry rates and an increase in LTC exit rates, both more marked than Sweden. This was largely due to short-term movements. Mortality rates peaked in April and December 2020 for LTC residents in Finland, while mortality peaked for both community-living individuals and LTC residents in Sweden. A decrease in hospital admissions from LTC facilities occurred in April 2020 and was less marked in Finland versus Sweden. During the first wave of the pandemic mortality was consistently higher in Sweden. We also found a larger decrease in LTC use and, among LTC residents, a smaller decrease in hospital admissions in Finland than in Sweden. This study calls for assessing the health consequences of the differences observed between these two Scandinavian countries as part of the lessons from the COVID-19 pandemic.

Pension policies and early retirement: New evidence from a counterfactual analysis in Iran

AbstractCompared to the global average, the exit rate of old-aged Iranian labourers is significantly higher than that of middle-aged, raising the hypothesis that social security generosity pulls older workers into early retirement. We used a unique individual dataset of Iran’s Social Security Organization (ISSO), including 267, 000 newly retired in 2016 and 2018, to assess the impact of ISSO’s pension policies on employees’ retirement age. In a counterfactual evaluation design, this study first estimated the implicit tax on work continuation and then applied the Heckman two-stage selection model. The findings show that ISSO’s retirement rules determining the age of exit and benefit eligibilities significantly increase the retirement probability and simultaneously decline the retirement age. Moreover, the implicit tax on work continuation, which reflects ISSO’s benefit formula, has a significant positive effect on retirement probability. The replacement rate also has a significant negative impact on retirement age. The retirement probability in hazardous jobs is higher than in normal ones, while exemptions significantly fall the outflow age of hazardous job holders. To maintain the scheme’s sustainability, reforms have to target an increase in the statutory retirement age, a reduction in the accrual rate, the calculation of reference salary for more extended periods, and the decline of the exemption coefficient for hazardous jobs.

An Analysis of Safe Parking Programs: Identifying Program Features and Outcomes of an Emerging Homelessness Intervention

As vehicular homelessness increases in the United States, safe parking programs have proliferated. Yet little research exists on this emerging homelessness intervention. This three-year, mixed-methods study analyzed one of the largest safe parking programs in operation: the Jewish Family Service of San Diego Safe Parking Program (JFS SPP). Through analysis of quantitative data and interviews with 349 clients and 15 staff, this study yielded three major findings. First, JFS SPP has a 40% positive exit rate, with younger clients, women, veterans, and families more likely to exit into housing. Second, JFS SPP is preferred over shelters by persons who have used both services. This preference is especially important for older clients and clients with disabilities for whom safe parking is a safety net. Finally, increasing access to lots and services would benefit all clients, including families, seniors, and individuals with nontraditional schedules. Findings support policy recommendations for safe parking programs.

Can Personnel Policy Improve Teacher Quality? The Role of Evaluation and the Impact of Exiting Low-Performing Teachers

Abstract Historically, teacher evaluation systems have identified few teachers as low-performing and needing improvement. In 2012, at the beginning of a national reform movement, Chicago Public Schools implemented its overhauled evaluation system, which incorporated multiple measures of teaching practice and dismissal plans for low-rated teachers. We find that the reform increased the exit rate of low-rated tenured teachers by 50 percent. At the same time, the teachers who replaced the exited teachers were significantly higher-performing. Ultimately, the accountability function of the reformed teacher evaluation policy resulted in higher teaching quality. However, the policy impact was limited because very few teachers received low ratings under the reformed system. Policy simulation results suggest that the available teacher labor supply is likely sufficient to set a higher standard for satisfactory teaching.

Abstract A024: Ploidy as a predictive biomarker for gemcitabine sensitivity in triple-negative breast cancers

Abstract The polyploid giant cancer cell (PGCC) state is a common response of cancer cells to various stressors including chemotherapy, irradiation, hypoxia and viral infection. Upon stress, PGCCs adopt an endoreplication in which the genome replicates, mitosis is omitted, and cells grow in size, causing drug resistance. How accessible endoreplication is to a cell, therefore, directly translates to its resistance to therapy. In this study, we hypothesized that endoreplication and PGCC state are more accessible to cancer cells that already have a higher ploidy content prior to therapy. To test this hypothesis, we developed a comprehensive three-tier framework consisting of i) computational, ii) in-vitro and iii) in silico components. First, we designed a set of ordinary differential equations (ODEs) to mathematically model how cells enter and exit the PGCC state in response to a given stressor. We engineered how this in silico approach interacts with in vitro experiments into a broadly applicable software solution called CLONEID. The software uses computer vision to monitor phenotypic changes in cell and nuclear size from standard bright-field microscopy and classify cells into PGCC and non-PGCC states. We used CLONEID to test various therapeutic agents for their ability to select for a stable near-tetraploid (4N) population in a set of near-diploid (2N) cell lines. Through spontaneous cell fusions, we also obtained tetraploid breast cancer cells matched with their parental lines. Altogether, this framework enabled us to i) monitor the PGCC state experimentally in ii) two sets of matched isogenic cell lines with 2N and 4N DNA content to iii) model the successful entry and exit rates to and from the endoreplication state, respectively. As the first application of this framework, we tested the ability of our 2N and 4N TNBC lines (SUM159 and MDA-MB-231) to access the PGCC state upon treatment with 18 chemotherapy agents. Among those drugs, we observed that only gemcitabine caused continued cell growth without cell division in both tetraploid SUM159 and MDA-MB-231 cells whereas near-diploid parental lines were hypersensitive to the treatment. Consequently, tetraploid cancer cells continued to safely grow in the presence of gemcitabine. Furthermore, these PGCCs re-entered the proliferative cell cycle and grew in cell number when treatment is terminated. Gemcitabine-based chemotherapy is a standard treatment for patients with TNBC although its efficacy is limited mainly due to drug resistance. We expect our findings and three-component framework strategy to help stratify the TNBC patient population by their response to gemcitabine. In addition, our mathematical modelling approach has the promising potential to inform personalized dose optimization and to effectively decrease administered gemcitabine dose for a subset of patients, which would alleviate severe therapy-associated side effects and co-morbidities. Citation Format: Vural Tagal, Jackson Cole, Daria Miroshnychenko, Andriy Marusyk, Noemi Andor. Ploidy as a predictive biomarker for gemcitabine sensitivity in triple-negative breast cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A024.

Job Flows Into and Out of Health Care Before and After the COVID-19 Pandemic

Anecdotal evidence suggests that health care employers have faced increased difficulty recruiting and retaining staff in the wake of the COVID-19 pandemic. Empirical research is needed to understand the magnitude and persistence of these changes, and whether they have disproportionate implications for certain types of workers or regions of the country. To quantify the number of workers exiting from and entering into the health care workforce before and after the pandemic and to examine variations over time and across states and worker demographics. This cohort study used US Census Bureau state unemployment insurance data on job-to-job flows in the continental US to construct state-level quarterly exit and entry rates for the health care industry from January 2018 through December 2021 (Arkansas, Mississippi, and Tennessee were omitted due to missing data). An event study design was used to compute quarterly mean adjusted rates of job exit from and entry into the health care sector as defined by the North American Industry Classification System. Data were examined from January to June 2023. The COVID-19 pandemic. The main outcomes were the mean adjusted health care worker exit and entry rates in each quarter by state and by worker demographics (age, gender, race and ethnicity, and education level). In quarter 1 of 2020, there were approximately 18.8 million people (14.6 million females [77.6%]) working in the health care sector in our sample. The exit rate for health care workers increased at the onset of the pandemic, from a baseline quarterly mean of 5.9 percentage points in 2018 to 8.0 (95% CI, 7.7-8.3) percentage points in quarter 1 of 2020. Exit rates remained higher than baseline levels through quarter 4 of 2021, when the health care exit rate was 7.7 (95% CI, 7.4-7.9) percentage points higher than the 2018 baseline. In quarter 1 of 2020, the increase in health care worker exit rates was dominated by an increase in workers exiting to nonemployment (78% increase compared with baseline); in contrast, by quarter 4 of 2021, the exit rate was dominated by workers exiting to employment in non-health care sectors (38% increase compared with baseline). Entry rates into health care also increased in the postpandemic period, from 6.2 percentage points at baseline to 7.7 percentage points (95% CI, 7.4-7.9 percentage points) in the last quarter of 2021, suggesting increased turnover of health care staff. Compared with prepandemic job flows, the share of workers exiting health care after the pandemic who were female was disproportionately larger, and the shares of workers entering health care who were female or Black was disproportionately smaller. Results of this cohort study suggest a substantial and persistent increase in health care workforce turnover after the pandemic, which may have long-lasting implications for workers' willingness to remain in health care jobs. Policymakers and health care organizations may need to act to prevent further losses of experienced staff.

The Research on Optimization of Online Education Platform Based on Customer Satisfaction

With the application of Internet technology in traditional education, online education has emerged as a teaching and learning form based on the Internet. Since 2010, there has been a surge in investment in online education, with market size and user numbers steadily increasing, and online education platforms flourishing. Chaoxing Learning Platform is a comprehensive mobile application developed by Beijing Chaoxing Company in 2016, covering mobile teaching, learning, reading, and social functions. It is one of the earliest companies in China to engage in the digitization of paper resources and electronic publishing. However, users still encounter the following problems when using Chaoxing Learning Platform or other online learning platforms: low completion rate, poor learning effectiveness, difficult time management, lack of motivation, lack of feedback and guidance, and so on. Therefore, it is necessary to find ways to improve the low completion rate and high exit rate of Chaoxing Learning Platform for its future healthy development. This study takes Chaoxing Learning Platform as the research object, based on customer satisfaction model and technology acceptance model, explores the factors that affect user satisfaction of online education platforms, and is expected to provide useful suggestions and countermeasures for platform optimization, promotion, and improvement of user experience.

The role of entrepreneurial ecosystems in reducing the gender gap of entrepreneurial intention and exit rates

The role of entrepreneurial ecosystems in reducing the gender gap of entrepreneurial intention and exit rates

Employers' requests when advertising for nurses-A national mapping of recruitment advertising for nurses in Sweden.

There is a shortage of nurses and many are leaving the profession. Maintaining sufficient nursing staff is a major healthcare challenge for societies worldwide. Work conditions, job orientation, and career opportunities all factor into nurses' rates of attrition, exit, and turnover. Newly graduated nurses have requested structured introductory and/or mentoring programmes to ease their transition from education to work life and develop the skills and knowledge necessary in their particular work setting. Nurses also seek opportunities to continue learning and developing professionally. To map and describe the content of recruitment advertisements for nurses. Research questions were: 'What qualifications do healthcare employers request when recruiting nurses?' and 'What sorts of professional development do healthcare employers offer nurses? A comprehensive national mapping of recruitment advertisements for nurses in Sweden where all advertisements, N = 450, on 20 of the 21 regional hospital websites were collected. A qualitative and a quantitative content analysis was performed. Personal characteristics dominated requested competence in recruitment advertisements. Employers offered general nursing opportunities with unspecific work content and focused more on recruiting newly registered, rather than experienced, nurses. In only a few advertisements, employers asked for a master's degree. No employer requested nurses with a PhD or research experience. While the World Health Organization stresses the need for a sustainable recruitment and attainment of nurses to secure health care, employers' recruitment of mostly newly graduated nurses and offering little professional development and few career opportunities may be one explanation for the difficulties in securing safe nurse staffing.

From a spark to a sweeping fire: An integrative conceptual review of group turnover and a theoretical exploration of its development.

The phenomenon of group turnover has generated substantial yet disconnected scholarly interests. Despite valuable insights gained from the collective turnover literature as well as parallel research concerning related or coordinated quitting, a holistic understanding of the unique group turnover phenomenon is needed, both to synthesize existing research across multiple domains and disciplines and to kindle new inquiries regarding its dynamic nature and developmental process. To this end, we begin by conducting an integrative review of research relating to group turnover, reinterpreting it by identifying its common pathways as a function of varying triggers, temporal patterns, and departure destinations. We then leverage the groups literature to explicate group turnover's self-reinforcing and dynamic nature and propose a three-dimensional Interdependence, Temporality, and Emergence (ITE) framework that accounts for its developmental process. Using this framework, we develop an illustrative set of propositions regarding how ITE-related group properties affect the extent to which individual departures might escalate into group turnover of a larger scale and faster speed. Our emphasis on groups as a unique unit of reference thus provides an important conceptual refinement and extension for understanding collective turnover-shifting from a static focus on aggregate exit (rates) to a dynamic focus on the often-coordinated, temporally evolving nature of multiple group member quit events. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Does electrification cause industrial development? Grid expansion and firm turnover in Indonesia

I ask whether electrification causes industrial development. I combine newly digitized data from the Indonesian state electricity company with rich manufacturing census data. To understand how electrification can cause industrial development, I shed light on an important economic mechanism — firm turnover. In particular, I study the effect of the extensive margin of electrification (grid expansion) on the extensive margin of industrial development (firm entry and exit). To deal with endogenous grid placement, I use an instrumental variable approach exploiting the location of colonial electric infrastructure and the need for an interconnected grid on the island of Java. I find that electrification causes industrial development by increasing the number of manufacturing firms, manufacturing workers, and manufacturing output. Electrification increases firm entry rates, but also exit rates, and entry accounts for most of the increase in output. This is consistent with electrification lowering entry costs, increasing competition, and forcing unproductive firms to exit more often.

Import Uncertainty and Export Dynamics

Abstract A supply chain is only as strong as its weakest link. Firms are constantly managing uncertainties, including unexpected delays in the provision of a critical input that can slow down or halt the production process, possibly making the manufacturer miss a delivery deadline. As most exporters are also importers of intermediate goods, supply chain unreliability related to import processing times at the border could impact downstream export dynamics. The role of unpredictability in border-clearance times for imports in manufacturing firms’ entry, exit, and survival in export markets is investigated using the PPML estimator on a rich dataset built on firm-level information for 48 developing countries over 2006–2014. Uncertainty in the time to clear imported inputs impacts neither the entry nor the exit rate, but translates into lower survival rates for new exporters, reducing the number of firms that continue serving the foreign market beyond their first year of entry. This effect grows larger over time, owing to rising reputational costs to input-importing exporters and is mainly driven by South-North trade, possibly reflecting the time-sensitivity of buyers in developed countries. Results also reveal heterogeneous effects across export industries, and the mediating role of sunk costs of entry in foreign markets, which attenuate the negative effect of uncertainty on survival rates as firms delay exiting the export market.

Supporting and Incentivizing Peer Leaders for an Internet-Based Private Peer Community for Youths With Type 1 Diabetes: Social Network and Directed Content Analysis.

Youths with type 1 diabetes (T1D) frequently experience stigma. Internet-based peer communities can mitigate this through social support but require leaders to catalyze exchange. Whether nurturing potential leaders translates into a central role has not been well studied. Another issue understudied in such communities is lurking, the viewing of exchanges without commenting or posting. We aimed to assess the centrality of the peer leaders we selected, trained, and incentivized within the Canadian Virtual Peer Network (VPN)-T1D. This is a private Facebook (Meta Platforms, Inc) group that we created for persons aged 14 to 24 years with T1D. We specifically sought to (1) compare a quantitative estimate of network centrality between peer leaders and regular members, (2) assess the proportions of network exchanges that were social support oriented, and (3) assess proportions of high engagement (posts, comments, reactions, and votes) and low engagement (lurking) exchanges. We recruited peer leaders and members with T1D from prior study cohorts and clinics. We trained 10 leaders, provided them with a monthly stipend, and encouraged them to post on the private Facebook group we launched on June 21, 2017. We extracted all communications (posts, messages, reactions, polls, votes, and views) that occurred until March 20, 2020. We calculated each member's centrality (80% of higher engagement communications comprising posts, comments, and reactions plus 20% of members with whom they connected). We divided each member's centrality by the highest centrality to compute the relative centrality, and compared the mean values between leaders and members (linear regression). We calculated the proportions of communications that were posts, comments, reactions, and views without reaction. We performed content analysis with a social support framework (informational, emotional, esteem-related, network, and tangible support), applying a maximum of 3 codes per communication. VPN-T1D gained 212 regular members and 10 peer leaders over 33 months; of these 222 members, 26 (11.7%) exited. Peer leaders had 10-fold higher relative centrality than regular members (mean 0.53, SD 0.26 vs mean 0.04, SD 0.05; 0.49 difference; 95% CI 0.44-0.53). Overall, 91.4% (203/222) of the members connected at least once through posts, comments, or reactions. Among the 75,051 communications, there were 5109 (6.81%) posts, comments, and polls, 6233 (8.31%) reactions, and 63,709 (84.9%) views (lurking). Moreover, 54.9% (3430/6253) of codes applied were social support related, 66.4% (2277/3430) of which were informational (eg, insurance and travel preparation), and 20.4% (699/3430) of which were esteem related (eg, relieving blame). Designating, training, and incentivizing peer leaders may stimulate content exchange and creation. Social support was a key VPN-T1D deliverable. Although lurking accounted for a high proportion of the overall activity, even those demonstrating this type of passive participation likely derived benefits, given that the network exit rate was low. RR2-10.2196/18714.

Intellectual monopolies as a new pattern of innovation and technological regime

Abstract Building on Schumpeter Mark I and Mark II, I propose an additional pattern of innovation and technological regime called the intellectual monopoly (IM) to explain the co-habitation of large incumbent firms with high entry and exit rates and provide evidence for pharmaceuticals and information technologies. I associate the IM pattern and technological regime with corporate innovation systems and illustrate that patterns not only evolve after changes in technological regimes but also due to economic, political, and institutional transformations.

Households’ entry into non-farm entrepreneurship and the market exit of enterprises in rural Ethiopia

Purpose This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).Design/methodology/approach The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.Findings Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.Practical implications Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.Originality/value Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

A wave-resolving modeling study of rip current variability, rip hazard, and swimmer escape strategies on an embayed beach

Abstract. Drownings due to rip currents are a major threat to beach safety. In this study a high-resolution Boussinesq model with a modified wave-resolving Lagrangian tracking module has been applied to a 2 km long embayed beach, Dadonghai of Sanya, Hainan Island, with the purpose of studying rip current variability, real-time rip hazard identification, and the optimal swimmer escape strategies. The beach stage evolves periodically at the study site and plays an important role in the long-term modulation of the occurrence and strength of rip currents according to the modeling. A series of tests are designed and confirm that rip current strength is closely related to wave properties and tidal levels. Spectral analysis of output time series at specific points shows that the modeled rip currents fluctuate on the orders of 1 and 10 min, which suggests the effects of wave-group-forced infragravity (IG) and very-low-frequency (VLF) motions. Rip hazard levels are defined by combining rip strength and its duration. An attempt to use the GPU-accelerated FUNWAVE-TVD (Total Variation Diminishing version of the Fully Nonlinear Boussinesq Wave Model) embedded with the spectral wave model WAM6-GPU (GPU version of the third-generation spectral wave model WAM Cycle 6) exhibits its capability to evaluate rip hazard levels in real time. One of the differences of the present study from previous works is that the random, wave-resolving tracking of virtual swimmers is performed with 1 m resolution to study beach safety strategies. The results demonstrate that multiple factors contribute to the survival of swimmers caught in the rip currents, including surf-zone bathymetry, rip strength, fine-scale flow patterns, the bather's position, and swimming ability. For weak-to-moderate rip currents and longshore currents, swim onshore consistently seems to be the most successful strategy across all the scenarios in this study. Higher surf-zone exit rates along Dadonghai beach are not favorable for stay afloat action, which puts swimmers at a higher risk of being expelled to deeper water. The effects of wave randomness of incoming wave trains and assignment of wave-following coefficients on Lagrangian tracking are also discussed.

DDEL-05. PHARMACOKINETIC ASSESSMENT OF CONVECTION-ENHANCED DELIVERY OF SMALL MOLECULE DRUGS FOR H3 K27-ALTERED DIFFUSE MIDLINE GLIOMA

Abstract H3 K27-altered diffuse midline gliomas (DMG) are uniformly lethal tumors for which no therapy has been found to be effective. The blood-brain barrier (BBB) restricts uptake and accumulation of systemically administered drugs in the brain. Convection-enhanced delivery (CED) circumvents the BBB by directly infusing therapeutics into the tumor, facilitating homogenous distribution of drugs at high local concentrations with minimal systemic toxicity. However, most drugs given by CED are rapidly cleared from the brain, severely limiting its therapeutic potential. Here, we determine the impact of drug characteristics rather than mechanism of action on compatibility with CED. Various medicinal chemistry prediction models were interrogated to define drug categories predicated on inherent physicochemical properties of the drugs. A panel of FDA-approved drugs with biologically validated activity in DMG were selected for each group: panobinostat/ponatinib, everolimus/topotecan, tolnaftate/tretinoin, and carmofur/eltrombopag. In vivo pharmacokinetic studies of these drugs delivered by CED into the pons of tumor-naïve mice showed that drugs expected to be less likely to undergo active efflux persisted at the site of infusion over prolonged periods of time. Conversely, efflux transporter (ET) substrate drugs were quickly excreted from the brain and readily detectable in the plasma following CED. Based on the observed brain and plasma concentration-time profiles, the brain exit rate constant and clearance out of the brain were much higher for ET substrate drugs compared with ET non-substrates, resulting in a significant increase in the residence time (the time spent by drugs in the brain) in the absence of ET-mediated clearance. These properties were further validated in efficacy studies in DMG animal models. The proclivity of many drugs to be rapidly effluxed from the brain after CED generates a vulnerability that can be exploited for the development of novel therapeutic regimens, such as with pharmacokinetics-informed drug selection or concomitant dosing of ET-inhibiting drugs.