Archivio istituzionale della Ricerca - Bocconi
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Making subsidies work: rules versus discretion
Get PDFWe estimate the employment effects of a large program of public investment subsidies to private firms that ranked applicants on a score reflecting both objective rules and local politicians' discretion. Leveraging the rationing of funds as an ideal Regression Discontinuity Design, we characterize the heterogeneity of treatment effects and cost‐per‐new‐job across inframarginal firms and estimate the cost‐effectiveness of subsidies under factual and counterfactual allocations. Firms ranking high on objective rules and firms preferred by local politicians generated larger employment growth on average, but the latter did so at a higher cost per job. We estimate that relying only on objective criteria would reduce the cost per job by 11%, while relying only on political discretion would increase such cost by 42%
The bidirectional link between left ventricular hypertrophy and chronic kidney disease. A cross lagged analysis
No full textBackground:Heart failure (HF) is known to reduce glomerular filtration rate (GFR), while chronic kidney disease (CKD) significantly increases the risk of left ventricular hypertrophy (LVH) and HF. Although these connections have been explored in separate studies, comprehensive research examining the mutual links between CKD and LVH progression is lacking.Methods:Our study investigates the longitudinal relationship between estimated GFR (eGFR) and left ventricular mass index (LVMI) in a cohort of 106 CKD patients across stages G1-5. Using a cross-lagged model, we paired each predictor (eGFR or LVMI) with subsequent outcome measurements, adjusting for previous values to ensure accuracy. Over a three-year follow-up period, we analyzed 257 paired LVMI and eGFR measurements.Results:At baseline, the median eGFR was 54 ml/min/1.73 m2, and the LVMI was 134 ± 48 g/m2, with a 62% prevalence of LVH. Our adjusted models revealed that a decrease in eGFR by 1 ml/min/1.73 m2 predicted an increase in LVMI of 1.12 g/m2 (95% CI: 0.71-1.54, P < 0.001). In contrast, high LVMI did not predict a reduction in eGFR over time. This analysis highlights a significant risk of LVH worsening due to GFR loss, while the reverse risk does not achieve statistical significance.Conclusions:Although these observational analyses cannot establish causality, they suggest that the risk of cardiomyopathy driven by kidney disease in stable CKD patients may be more substantial than the risk of CKD progression driven by heart disease. This insight underscores the importance of monitoring kidney function to manage cardiovascular risk in CKD patients
Algorithmic Collusion in EU Competition Law: Decoding the Puzzle
Get PDFThis thesis explores the phenomenon of algorithmic collusion, a term used to describe scenarios where pricing algorithms facilitate, enable, or even autonomously engage in explicit or tacit collusive behavior. In recent years, this issue has drawn significant attention within the global antitrust community, as highlighted by the extensive body of research stemming from Ezrachi and Stucke’s seminal work, Virtual Competition (2016).
The debate surrounding algorithmic collusion is driven by three main concerns. First, pricing algorithms may indirectly foster human collusion by enhancing market transparency, simplifying coordination, and easing enforcement. Second, algorithms can act as tools for firms to implement collusive strategies, making such behavior more stable and less detectable. Third, and most critically, AI-driven algorithms might independently learn to collude without explicit programming, raising the question of whether firms should bear responsibility for unintended collusive outcomes.
Against this backdrop, this research seeks to “decode the puzzle” of algorithmic collusion, focusing on its compatibility with the EU antitrust legal framework, specifically Article 101 TFEU on agreements and concerted practices. The study is structured around three objectives: (1) categorizing algorithmic collusion based on existing literature, (2) assessing the applicability of Article 101 TFEU to each category, and (3) proposing alternative remedies where Article 101 proves insufficient.
The findings reveal that when pricing algorithms act as tools to support collusive strategies, Article 101 TFEU should apply, and the use of such algorithms may influence the severity of fines. For autonomous algorithmic collusion, which often mimics human behavior, explicit collusion can be addressed under Article 101 through an expansive interpretation of “meeting of minds”. Even when firms do not directly program algorithms to collude, they can still be held liable based on principles of vicarious liability. However, tacit collusion, whether human or algorithmic, remains outside the scope of Article 101 due to the legal acceptance of outcomes driven by interdependence.
This thesis challenges the exclusion of algorithmic tacit collusion from antitrust scrutiny, arguing that algorithms could make tacit collusion more pervasive and effective than human-driven interdependence. As such, the legal treatment of algorithmic tacit collusion warrants reevaluation. To address this, the thesis maps and evaluates existing remedies within and beyond the antitrust framework, while also proposing new approaches. Central to this is the concept of ‘outcome visibility,’ which holds firms accountable for the observable market effects of their algorithms, even when unintentional. By advancing this framework, the thesis contributes to bridging regulatory gaps and ensuring that antitrust law keeps pace with technological advancements
Civic associations, populism, and (un-)civic behavior: evidence from Germany
Get PDFCivic associations are expected to foster civic, pro-social behavior, but this optimistic view is increasingly contested. We argue that populist radical right parties can strategically target and infiltrate associations to diffuse anti-establishment rhetoric and anti-democratic attitudes. We illustrate this phenomenon by examining the relationship between civic associations and compliance with government rules during Germany's first Covid-19 lockdown with a difference-in-differences design. Results show that areas with denser sport, nature, and culture clubs recorded higher mobility under lockdown. We document the infiltration mechanism and the spreading of anti-democratic attitudes within associations, using survey and election data and qualitative evidence including interviews. In doing so, we shed light on a negative effect of social networks and an understudied strategy of challenger populist parties
The effect of fair value accounting on firm public debt–evidence from business combinations under common control
No full textWe analyze the choice allowed to parent firms under IFRS of how to account for a business combination under common control (BCUCC), and provide evidence on the motivation to select fair values and the economic implications of this choice. A BCUCC is a merger of two firms owned by the same parent. Under IFRS, parent firms can use the acquisition method (fair values) to record the BCUCC or use assets' historical cost. We show that parents are likely to choose fair values when they desire to increase the transparency of their financial reports and when they likely need to raise capital. Using propensity-score matching, we find that firms that used fair values are more likely to issue new public debt following the transaction. We also find that the cost of issuing new debt for these firms is 55 basis points lower than that of comparable firms that did not do BCUCCs. Our results suggest that using fair values in BCUCCs can increase transparency and lower firms' cost of debt
Design and features of pricing and payment schemes for health technologies: a scoping review and a proposal for a flexible need-driven classification
No full textPricing and payment schemes have been proposed as possible solutions to the problems of affordability and access to health technologies. This work mapped existing types of pricing and payment schemes, and proposed a new approach for their classification.
Overall, 70 unique types of pricing and payments schemes around different technology types and therapeutic areas have been identified, both theoretical formulations and schemes applied in the real world. The schemes populate the Pay-for-Innovation Observatory, publicly accessible online.
Our proposed approach to categorize available types of pricing and payment schemes is to allow a flexible use of the entire repository of schemes, driven by the specific objective that different stakeholders might have, conscious that schemes can be better defined by using the combination of their key characteristics
Investor memory
No full textWe provide experimental evidence of a positive memory bias which affects individuals' beliefs, decisions to reinvest, and overconfidence in the stock market. Individuals over-remember positive investment outcomes of chosen assets and under-remember negative ones. Based on their memories, subjects form overly optimistic beliefs about their investment, reinvest too much, and become overconfident about their investment ability relative to others. We further provide evidence on motivation driving the memory bias. This positive memory bias offers a cognitive microfoundation for why gains weight more than losses when people learn from experiences. This helps reconciling various stylized facts in investor beliefs and behavior
Generative AI in innovation and marketing processes: a roadmap of research opportunities
Get PDFNowadays, we are witnessing the exponential growth of Generative AI (GenAI), a group of AI models designed to producenew content. This technology is poised to revolutionize marketing research and practice. Since the marketing literatureabout GenAI is still in its infancy, we offer a technical overview of how GenAI models are trained and how they pro-duce content. Following this, we construct a roadmap for future research on GenAI in marketing, divided into two maindomains. The first domain focuses on how firms can harness the potential of GenAI throughout the innovation process.We begin by discussing how GenAI changes consumer behavior and propose research questions at the consumer level.We then connect these emerging consumer insights with corresponding firm marketing strategies, presenting researchquestions at the firm level. The second set of research questions examines the likely consequences of using GenAI toanalyze: (1) the relationship between market-based assets and firm value, and (2) consumer skills, preferences, and rolein marketing processes
Conflitto e incertezza: il sorprendente ruolo della paura nei mercati finanziari
No full textIl conflitto in Ucraina ha generato un aumento dell'incertezza tra gli operatori economici, e la letteratura attesta che tale incertezza ha determinato un incremento della volatilità nei mercati finanziari globali. I dati di questo studio sono stati raccolti tra il 1° marzo e il 30 aprile 2022, impiegando la metodologia Cawi, ottenendo 2.000 risposte, ridotte a 1.729 dopo l'eliminazione dei valori mancanti. L'obiettivo di questa ricerca è verificare se la paura connessa allo scoppio del conflitto in Ucraina sia correlata sia alla fiducia sia alle scelte di investimento che gli operatori compiono sui mercati finanziari. I risultati mostrano che gli individui più intimoriti dall'escalation del conflitto tendono a riporre una maggiore fiducia nei mercati finanziari, ma, al contempo, la paura suscitata dalla guerra riduce la loro propensione a investir
The race for data: utilizing informative or persuasive cues to gain opt-in?
No full textThe EU's General Data Protection Regulation (GDPR) mandates explicit user opt-in consent for data access. It recommends transparency in opt-in requests about data collection, storage, and use, without specifying the format of these requests. Consequently, the GDPR gives firms flexibility in designing opt-in messages. This research uses theory, multiple datasets, and methods to investigate firms’ communication formats for opt-in requests, addressing three questions: 1) how do firms design their opt-in requests? 2) does the chosen format affect consumer response? 3) what drives firms' choices of formats? The analysis of 1,506 re-permission emails from 1,396 firms post-GDPR shows that 26% use only persuasive cues to request data, while 24% blend persuasive and informative cues. Notably, businesses with an offline presence use more persuasive cues compared to purely digital entities. A field experiment rationalizes this behavior showing that informative cues alone did not improve opt-in; a mix of persuasive and informative cues proved more successful. Additionally, firms dependent on personal data utilize persuasive cues more often than firms concerned with reputational risks of GDPR non-compliance. This study offers pivotal insights for regulators, firms, and consumers, revealing variations in how different firms acquire consent and the impact of their strategies on user behavior