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Which Governance Mechanisms Promote Efficiency in Reaching Poor Clients? Evidence from Rated Microfinance Institutions
No full textThis paper evaluates the effectiveness of several governance mechanisms on microfinance institutions' (MFI) performance. We first define performance as efficiency in reaching many poor clients. Following the literature on efficiency in banks, we estimate a stochastic cost frontier and measure output by the number of clients. Therefore, we capture the cost minimisation goal and the goal of serving many poor clients, both of which are pursued by MFIs. We next explore the impact of measurable governance mechanisms on the individual efficiency coefficients. The results show that efficiency increases with a board size of up to nine members and decreases after that. MFIs in which the CEO chairs the board and those with a larger proportion of insiders are less efficient. The evidence also suggests that donors' presence on the board is not beneficial. We do not find consistent evidence for the effect of competition, and we find weak evidence that MFIs in countries with mature regulatory environments reach fewer clients, while MFIs regulated by an independent banking authority are more efficient
A governance perspective on moral character development
No full textThis short contribution extends Smith et al.'s "Moral Moments Model" by adding a governance lens. We contend that compliance-based control systems (CBCSs) confine moral agency through rigid rules and narrow discretion, whereas virtue-based control systems (VBCSs) purposefully preserve uncertainty to nurture moral judgment and character. Using Structured Ethical Debriefings (SEBs) as an illustration, we show how institutionalized debriefings can rekindle moral moments by embedding reflection on ethically charged incidents even within highly regulated environments. Two propositions follow: (1) well-designed governance mechanisms can spark moral moments in either system; and (2) cultivating moral character is a critical challenge not only for individuals but also for organizations-especially for corporate citizens striving to shoulder genuine social responsibility.Dieser Kurzbeitrag erweitert das "Moral Moments Model" von Smith et al. um eine Governance-Perspektive. Wir argumentieren, dass Compliance-basierte Kontrollsysteme (CBCSs) die moralische Handlungsfähigkeit durch starre Regeln und geringe Ermessensspielräume einschränken, während Tugend-basierte Kontrollsysteme (VBCSs) Ungewissheit bewusst bewahren, um moralisches Urteilsvermögen und Charakterbildung zu fördern. Am Beispiel von Structured Ethical Debriefings (SEBs) zeigen wir, wie institutionalisierte Nachbesprechungen moralische Momente neu entfachen können, indem sie die Reflexion über ethisch aufgeladene Ereignisse selbst in stark regulierten Umgebungen verankern. Daraus folgen zwei Thesen: (1) Gut gestaltete Governance-Mechanismen können in beiden Systemtypen moralische Momente auslösen. (2) Moralische Charakterbildung ist eine wichtige Herausforderung nicht nur auf der Ebene von Individuen, sondern auch auf der Ebene von Organisationen - insbesondere für Unternehmen, die als Corporate Citizens gesellschaftliche Verantwortung übernehmen wollen
Unveiling the path to innovation: Exploring the roles of big data analytics management capabilities, strategic agility, and strategic alignment
No full textBig data are known to improve operational efficiency, competitiveness, and performance. Despite these unprecedented benefits, the understanding of how big data transform organizational processes remains limited. To address this gap, this research empirically investigates how big data analytics management capabilities (BDAMC) influence innovation performance. This study bases its assumptions on the dynamic capability and knowledge-based views. A PLS-SEM analysis of 199 firms reveals that establishing BDAMC is essential for fostering organizations' innovation performance. This study advances knowledge by demonstrating that BDAMC enhances organizations' strategic agility, which subsequently boosts innovation performance. Moreover, the empirical findings reveal that developing BDAMC is crucial for achieving strategic alignment, which in turn reinforces innovation performance. These unique findings hold significant practical value for managers and consultants seeking to leverage big data-related systems within organizations
Is it Time to Put a Moratorium on List Experiments for Domestic Violence Elicitation?
No full textUsing data from over 24,000 respondents in the Norwegian Crime Victimization Survey, we conducted a double list experiment to measure domestic violence (DV). Both list experiments revealed a statistically significant decrease in reporting when including a sensitive DV item. This clear violation of the "no design effects" assumption is not only explained by floor effects. One possibility is that the results indicate a "fleeing" behavior whereby respondents try to avoid association with DV. Combined with the inherent power limitations of list experiments in many contexts, these results underscore the need for caution in employing list experiments to measure DV, even in large samples
Deprived children in Ireland: Characterising those who are deprived but not income-poor
No full textThis report examines child deprivation in Ireland. It focuses on children who experience deprivation but are not classified as at-risk-of-poverty (AROP). As a result, they fall outside the official consistent poverty measure, which is a combined measure of AROP and deprivation. The report uses data from the Survey of Income and Living Conditions (SILC) to investigate the composition and characteristics of this group. The report underscores the need for comprehensive policies to improve living standards for vulnerable families
Are hedge funds a hedge for increasing government debt issuance?
No full textThis paper studies the rapid increase since 2019 of Government of Canada (GoC) debt issuance alongside greater hedge fund participation at GoC bond auctions. We find a systematic relationship between GoC debt stock and hedge fund bidding shares at auction. We attribute this to hedge funds' business models, which are based on volume and leverage. We also use bid-level auction data and find that hedge funds are more willing than other investor types to buy bonds at lower auction yields (higher auction prices). These two results i) help explain why GoC auction performance has remained steady despite greater issuance and ii) affirm the importance of hedge funds in supporting Canada's cost-effective debt distribution in recent years. In addition, we conduct a counterfactual analysis of the exit of hedge funds from auction, which further affirms the importance of hedge funds to GoC auction performance. However, the concentration of hedge funds represents a potential vulnerability because hedge funds have a greater flight risk relative to domestic real money investors and thus contribute to a potentially less stable investor base
Interpretable machine learning for earnings forecasts: Leveraging high-dimensional financial statement data
No full textWe predict earnings for forecast horizons of up to five years by using the entire set of Compustat financial statement data as input and providing it to state-of-the-art machine learning models capable of approximating arbitrary functional forms. Our approach improves prediction one year ahead by an average of 11% compared to the traditional linear approach that performs best. This superior performance is consistent across a variety of evaluation metrics as well as different firm subsamples and translates into more profitable investment strategies. Extensive model interpretation reveals that income statement variables, especially different definitions of earnings, are by far the most important predictors. Conversely, we find that while income statement variables decline in relevance, balance sheet information becomes more significant as the forecast horizon extends. Lastly, we show that the influence of interactions and non- linearities on the machine learning forecast is modest, but substantial differences between firm subsamples exist
The Effect of Visual Openness in Meeting Rooms on Team Productivity and Communication Quality: Evidence from a Randomized Controlled Trial
No full textThis study investigates whether a meeting environment's visual openness influences team productivity and communication quality. We conducted a randomized controlled trial with participants assigned to discussions held in a transparent glass meeting room (treatment) or a fully curtained room (control). Team productivity was evaluated based on the quality of participants' policy proposals. Communication quality was assessed using transcript-based indicators such as laugh frequency and topic diversity. We found that groups in visually open meeting rooms received significantly higher proposal ratings and exhibited greater emotional positivity and topic diversity, highlighting that within-session dynamics expose how environmental design affects group interaction
Does Training in AI Affect PhD Students' Careers? Evidence from France
No full textThe rise of Artificial Intelligence (AI) urges us to better understand its impact on the labor market. This paper is the first to analyze the supply of individuals with AI training facing the labor market. We estimate the relationship between AI training and individuals' careers for 35,492 French PhD students in STEM who graduated between 2010 and 2018. To assess the unbiased effect of AI training, we compare the careers of PhD students trained in AI with those of a control sample of similar students with no AI training. We find that AI training is not associated with a higher probability of pursuing a research career after graduation. However, among students who have AI training during the PhD and pursue a research career after graduation, we observe a path dependence in continuing to publish on AI topics and a higher impact of their research. We also observe disciplinary heterogeneity. In Computer Science, AI-trained students are less likely to end up in private research organizations after graduation compared to their non-AI counterparts, while in disciplines other than Computer Science, AI training stimulates patenting activity and mobility abroad after graduation
