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The Commercial Paper Funding Facility (CPFF) bought commercial paper from highly rated issuers of U.S. dollar commercial paper during the financial crisis of 2008 to 2009. This is the only study to analyze the accounting characteristics of both financial and non-financial firms participating and not participating in this $738 billion Federal Reserve program. In logistic regressions, CPFF participants and non-participants differed little in solvency or liquidity ratios. Thus, there is little evidence of adverse selection by financial firms. Nevertheless, CPFF participants were significantly more likely to receive capital injections from the TARP bailout, to pose greater systemic risks and be based in North America. JEL Classification: G01, G18, G2, G28 Keywords: ABCP, Asset Backed Commercial Paper, Bailout, Banks, Capital Purchase Program (CPP), Commercial Paper, Commercial Paper Funding Facility (CPFF), Emergency Lending, Federal Reserve, Multinational Firms, Section 13(3), Troubled Asset Relief Program (TARP), U.S. Treasury, Unsecured Commercial Paper, Unusual and Exigent Circumstances, I. Introduction The Federal Reserve, through its Commercial Paper Funding Facility (CPFF), made aggregate purchases of commercial paper of $738.3 billion between October 27, 2008, and February 1, 2010. This [...]

In this paper, we provide a bibliometric overview of publications in economics by authors with affiliations from Serbia. We use the Web of Science database, analyse all the articles published from 1996 onwards, and provide an overview of publications, journals targeted, trends, and the effects of collaboration. We identify the main topics of interest of the published papers. To do this, we use bibliographic mapping and provide the most common terms used in the titles and abstracts of the papers, grouped in clusters. Using these clusters, we present the main interests and focus of the papers in the dataset. The robustness of the conclusions is obtained by extending the analysis to another citation database, the SCImago Journal Rank.

To supplement the quantitative portrait of Ukrainian Economics discipline with the results of gender and author ordering analysis at the level of individual authors, special methods of working with bibliographic data with a predominant share of non-English authors are used. The properties of gender mixing, the likelihood of male and female authors occupying the first position in the authorship list, as well as the arrangements of names are studied.

Understanding how to make the world a better place requires interdisciplinary knowledge. Public policy analysis helps policymakers arrive at informed policy decisions. The policy analysis process involves public problem definition and data collection, stakeholder identification, a rationale for government involvement, evaluation criteria, identification and analysis of policy alternatives, and a recommendation. Economics informs not only the identification of market failures but also how we think about public problems, evaluate relevant research, identify policy alternatives, weigh objective criteria (costs, benefits, equity), and select optimal solutions. Students of policy analysis gain experience through in-class examples of contemporary topics and an iterative policy paper, where each student selects a public problem, conducts research, and writes an analysis. Students become effective consumers and beginning producers of policy analysis.

The gig economy and gig work have grown quickly in recent years and have drawn much attention from researchers in different fields. Because the platform mediated gig economy is a relatively new phenomenon, studies have produced a range of interesting findings; of interest here are the socio‐technical issues that this work has surfaced. This systematic literature review (SLR) provides a snapshot of a range of socio‐technical issues raised in the last 12 years of literature focused on the platform mediated gig economy. Based on a sample of 515 papers gathered from nine databases in multiple disciplines, 132 were coded that specifically studied the gig economy, gig work, and gig workers. Three main socio‐technical themes were identified: (1) the digital workplace, which includes information infrastructure and digital labor that are related to the nature of gig work and the user agency; (2) algorithmic management, which includes platform governance, performance management, information asymmetry, power asymmetry, and system manipulation, relying on a diverse set of technological tools including algorithms and big data analytics; (3) ethical design, as a relevant value set that gig workers expect from the platform, which includes trust, fairness, equality, privacy, and transparency. A social informatics perspective is used to rethink the relationship between gig workers and platforms, extract the socio‐technical issues noted in prior research, and discuss the underexplored aspects of the platform mediated gig economy. The results draw attention to understudied yet critically important socio‐technical issues in the gig economy that suggest short‐ and long‐term opportunities for future research directions. [ABSTRACT FROM AUTHOR]

Caribbean Trade, Integration and Development: Selected Papers and Speeches of Alister Mclntyre. Volume 1: Trade and Integration. Volume 2: Aspects of Human Resources Development and Higher Education. Edited by Andrew [...]

Abstract The organisation of the 24-h day for hospital nurses in two 12-h shifts has been introduced with value propositions of reduced staffing costs, better quality of care, more efficient work organisation, and increased nurse recruitment and retention. While existing reviews consider the impact of 12-h shifts on nurses’ wellbeing and performance, this discussion paper aims to specifically shed light on whether the current evidence supports the value propositions around 12-h shifts. We found little evidence of the value propositions being realised. Staffing costs are not reduced with 12-h shifts, and outcomes related to productivity and efficiency, including sickness absence and missed nursing care are negatively affected. Nurses working 12-h shifts do not perform more safely than their counterparts working shorter shifts, with evidence pointing to a likely negative effect on safe care due to increased fatigue and sleepiness. In addition, nurses working 12-h shifts may have access to fewer educational opportunities than nurses working shorter shifts. Despite some nurses preferring 12-h shifts, the literature does not indicate that this shift pattern leads to increased recruitment, with studies reporting that nurses working long shifts are more likely to express intention to leave their job. In conclusion, there is little if any support for the value propositions that were advanced when 12-h shifts were introduced. While 12-h shifts might be here to stay, it is important that the limitations, including reduced productivity and efficiency, are recognised and accepted by those in charge of implementing schedules for hospital nurses.

This paper presents a case study that reflects on teaching an economic unit, Cost-benefit analysis (CBA), to a diverse undergraduate student body at the researcher's institution. CBA is an applied economic technique that attempts to assess the economic efficiency of proposed public policies through the systematic prediction of social costs and social benefits. Students in this CBA unit are required to complete an online test, CBA report and a final examination. In the CBA Report, the students perform analytical work to explain the relationships among events, identify options, evaluate choices, and predict the effects of actions. This paper investigates the performance of four different student cohorts from 2019 to 2022. This paper aims to understand the differences in undergraduate students' learning of CBA based on the diversity among students, and in particular whether any specific student demographic (defined by gender, age, course progress level, study load and domestic vs international students) experienced a disproportional impact. The findings are then used to contribute improvement in the teaching and learning of the unit in higher education.

Although experimental evaluations have been labeled the "gold standard" of evidence for policy (U.S. Department of Education, 2003), evaluations without an analysis of costs are not sufficient for policymaking (Monk, 1995; Ross et al., 2007). Funding organizations now require cost-effectiveness data in most evaluations of effects. Yet, there is little guidance on how to integrate research on costs into efficacy or effectiveness evaluations. As a result, research proposals and papers are disjointed in the treatment of costs, implementation, and effects, and studies often miss opportunities to integrate what is learned from the cost component into what is learned about effectiveness. To address this issue, this paper uses common evaluation frameworks to provide guidance for integrating research on costs into the design of field experiments building on the ingredients method (Levin et al., 2018). The goal is to improve study design, resulting in more cohesive, efficient, and higher-quality evaluations.

This paper demonstrates how the innovative application of a Collective Intelligence approach enhanced Local Skills Improvement Planning information for employers, education and skills training organisations and regional economic policy organisations. This took place within a Knowledge Transfer Partnership between a Chamber of Commerce and a University. This aimed to develop and deploy regional business intelligence for enhanced policy and decision-making in enterprise and economic development. The project converged knowledge from several research centres including economics, entrepreneurship and innovation, data science, and Artificial Intelligence. The paper presents a project case study which provides two contributions to applied knowledge. Firstly, it demonstrates how a Collective Intelligence (CI) approach can be applied to achieve rapid results in resolving the real-world problem of local skills information availability. Useful real-time data was gathered from employers in three sectors on skills requirements, supply and training. This was analysed using Artificial Intelligence tools, then shared publicly via an automated Internet portal, providing a scalable model for wider use. Secondly, it explores and evaluates how the knowledge exchange (KE) process can function effectively and quickly in applying CI-based innovation in practical ways which create new value, within a Knowledge Transfer Partnership between a University and Chamber of Commerce.environment.