Archivio istituzionale della Ricerca - Bocconi
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Trend analysis of hourly rainfall in the Mediterranean: a case study of the Basilicata Region, Southern Italy (2001–2024)
No full textThis study examines recent trends in sub-daily rainfall extremes across the Basilicata region of southern Italy – , a Mediterranean climate-change hot spot, – using high-resolution hourly data from 32 well-distributed stations, covering years 2001–-2024. A comprehensive set of fixed-threshold and percentile-based indices was applied to describe the occurrence, intensity and spatial variability of short-duration rainfall. Trend analyses were conducted using the Mann–-Kendall test and Theil–-Sen slope estimator, with adjustments for autocorrelation (TFPW) and multiple testing (Benjamini–-Hochberg False Discovery Rate, BH-FDR). Preliminary results indicate widespread upward tendencies in both frequency and intensity of sub-daily rainfall extremes, particularly for events exceeding the 95th and 99th percentiles, with over 80% of stations showing positive trends, most evident in summer and autumn. After BH-FDR correction, no individual station exhibited statistically significant changes; however, the complementary Field Significance Test (FST) revealed spatially coherent regional signals, with summer intensification and winter decline. Comparisons among physiographic zones (Kruskal–-Wallis test) showed stronger trends in mountainous and high-hilly sectors, confirming elevation as a key control on short-duration rainfall variability. Overall, moderate extremes (95th percentile) have intensified, while the most severe events (99th–99.9th percentiles) remain stationary. These results align with broader Mediterranean evidence suggesting a seasonal redistribution of precipitation toward the warm period. The integrative integrated statistical framework adopted here effectively distinguishes genuine climatic signals from natural variability, offering robust guidance for hydrological risk assessment and climate adaptation planning in Mediterranean environments
The Antin IP Acquisition of Hippocrates: Scaling-up the business and refinancing the capital structure - TEACHING NOTES
No full textThe objective of this case study is to analyse the investment and financing strategy implemented by Antin Infrastructure Partners (‘Antin’) in its acquisition and development of Hippocrates Holding (‘Hippocrates’), the largest independent pharmacy platform in Italy. The case, describing the deal that took place in February 2021, requires practical application of technical notions about capital structure optimization and debt sustainability analysis. It offers students the opportunity to gain practical exposure to financial engineering in support of strategic growth, as well as a thorough understanding of how different financing solutions can impact a company’s operational flexibility and risk profile
Kernel Density Estimators in Large Dimensions
No full textThis paper studies Kernel Density Estimation for a high-dimensional distribution . Traditional approaches have focused on the limit of large number of data points and fixed dimension . We analyze instead the regime where both the number of data points and their dimensionality grow with a fixed ratio . Our study reveals three distinct statistical regimes for the kernel-based estimate of the density , depending on the bandwidth : a classical regime for large bandwidth where the Central Limit Theorem (CLT) holds, which is akin to the one found in traditional approaches. Below a certain value of the bandwidth, , we find that the CLT breaks down. The statistics of for a fixed drawn from is given by a heavy-tailed distribution (an alpha-stable distribution). In particular below a value , we find that is governed by extreme value statistics: only a few points in the database matter and give the dominant contribution to the density estimator. We provide a detailed analysis for high-dimensional multivariate Gaussian data. We show that the optimal bandwidth threshold based on Kullback-Leibler divergence lies in the new statistical regime identified in this paper. As known by practitioners, when decreasing the bandwidth a Kernel-estimated estimated changes from a smooth curve to a collections of peaks centred on the data points. Our findings reveal that this general phenomenon is related to sharp transitions between phases characterized by different statistical properties, and offer new insights for Kernel density estimation in high-dimensional settings
Three Essays on Digital Platforms, Start-up Accelerators and Venture Capital Firms
No full textIn this thesis, I present three chapters related to my two areas of research: digital platforms (first chapter) and entrepreneurial finance (second and third chapters).
In the first chapter, I explore advertising on social media platforms, which surged in recent years due to platforms’ ability to capture user attention and broker this attention to advertisers. I develop a two-sided model with heterogeneous users, who differ in product preferences and annoyance from ads, and heterogeneous advertisers, who vary in product type and quality, located on an infinite plane. Advertisers choose whether to join the platform and their targeting reach, while the platform sets prices and users decide whether to participate and to click on ads. I analyze two cases: one with full user participation driven by a high standalone benefit, and one with partial participation when there is no standalone benefit. In both cases, improvements in attention brokering ability raise advertising prices and yet lead to greater advertiser entry, which reduces average ad quality and relevance. Under partial participation, users who are most annoyed by ads exit, leading the platform to raise prices further to account for the negative externalities of ads. The welfare analysis shows that platform profits and advertiser surplus always increase with attention brokering; user welfare follows an inverted-U shape when the standalone benefit is high but increases monotonically otherwise. A regulator focused on users would restrict brokering only when the standalone benefit is high; one maximizing the welfare of all platform participants would choose intermediate brokering under high standalone benefit and full brokering otherwise.
In the second chapter, I examine start-up accelerators and the role of similarity among start-ups within their cohorts. While similarity can improve post-acceleration performance through exposure to relevant knowledge, it can also intensify competition and reduce the benefits of acceleration. I hypothesize and show in the data an inverted U-shaped relationship between start-ups’ business similarity and their post-acceleration performance. Using data on 2,225 start-ups across 129 cohorts from 8 U.S. accelerators (2005-2018), I find that performance initially rises with similarity but falls beyond a certain point. Decomposing business similarity into technology and market similarity suggests that the interaction of these two dimensions contribute to the observed inverted-U: while higher similarity on either dimension has a positive impact on performance, high similarity along both dimensions vanishes these beneficial effects. These results offer guidance for accelerator managers designing cohorts and for start-ups evaluating accelerators.
In the third chapter, I employ machine learning methods to isolate and quantify the persistent effect (if any) of general partners on performance across multiple funds. Analyzing a panel dataset of 29,021 quarterly observations covering 722 funds managed by 811 general partners (1997-2022), I document statistically significant albeit modest effects of general partners on performance persistence. These magnitudes are substantially smaller than those reported in the literature, highlighting the limited external validity of traditional methods for the task at hand. Moreover, the general partner effect consistently exceeds that of venture capital firms, suggesting that individual-level analyses provide greater insights than firm-level ones. These results indicate that most of the variation in venture capital performance is not attributable to the organizational characteristics of venture capital firms and can be explained only partially by the individuals managing them
Methodologies for complex health economic modeling
No full textMaking effective decisions in health and medicine is crucial, as each decision affects the well-being of others. Making cost-effective decisions in health and medicine is even more critical as economic resources are not infinite. Health economic modeling refers to the process of evaluating the costs and effects of healthcare interventions. Decision analytic models are mathematical tools to account for and model the uncertainty around each decision, and to determine the best decision after collecting different sources of evidence. There are different open challenges and interesting problems related to statistical techniques to analyze complex and realistic evidence sources, as well as the uncertainty surrounding decision-making. In this thesis, we focus on the development of various Bayesian methodologies in complex and realistic frameworks within the context of health economic modeling.
In the first chapter, we provide an extensive introduction to the context of health economic modeling and cost-effective analysis, and outline the open challenges we will address throughout the thesis.
In Chapter 2, we define Inverse target trial emulation, a novel Bayesian methodology to generate realistic observational data. The central idea of this methodology is to start with an initial (preliminary) Randomized Clinical Trial (RCT) and use the initial information to generate different types of observational data in various contexts and under different assumptions. Target trial emulation (TTE) is a methodology that links an observational dataset to a targeted RCT, emulating experimental data by solving all the different forms of bias in observational data. In this context, we reverse this process, aiming to simulate (not only emulate) observational data from an initial trial. This methodology proves to be very useful for performing different forms of sensitivity analysis, research prioritization, and testing of the robustness of the methods typically employed to analyze observational data.
In the third and fourth chapters, we focus our attention on VoI (Value of Information) analysis in complex and realistic scenarios. Given an underlying health-economic decision model, VoI analysis is a technique to quantify the expected benefit that may result from reducing uncertainty in the economic model. In particular, the Expected Value of Sample Information (EVSI) is a measure that estimates the expected benefit of performing additional data to reduce the uncertainty in the parameters of the underlying health economic model.
Until now, the EVSI methodology has been applied only to fairly simple data collection exercises. In most cases, it has been used to understand the value of randomized clinical trial (RCT) data, meaning that it measured the value of collecting additional RCTs to reduce uncertainty. In these chapters, relying also on the results from Chapter 1, we design and apply a novel methodology to use EVSI when we plan to collect more complex and realistic data, i.e., data affected by missingness and confounding.
In the final chapter, we develop a Bayesian version of the subpopulation treatment effect pattern plot (STEPP) methodology and apply it to real scenarios. STEPs is a methodology that enables researchers to properly analyze the heterogeneity of treatment effects (HTE) in experimental studies, providing the necessary information to customize treatment for individuals to maximize benefits. STEPP constructs overlapping subpopulations along the continuum of a continuous covariate of interest (e.g., a biomarker), thus improving the precision of the estimated treatment effects within the subgroups. In that chapter, we introduce a Bayesian version of the STEPP method (B-STEPP) and demonstrate that a Bayesian approach enables flexible modeling of the dependence among the relevant parameters, providing good control over the joint distribution of the parameters and their associated uncertainty
Essays in Auditing and ESG Regulation
No full textThe first chapter of this PhD Thesis explores the effect of expanded audit report rules on the client-auditor relation. The fact that in the U.K. these rules were implemented in several stages allows applying difference-in-differences methodology to analyze the consequences of the new reporting regime. We test whether expanded reporting rules create additional tension between companies and their auditors which leads to an increase in auditor turnover rate. Companies might want to minimise the number of the reported KAMs (i.e., risky areas) as some papers show that receiving too many of them can be perceived by the users of financial statements as a bad signal. At the same time, auditors might prefer to report more KAMs in order to provide high audit quality and minimize potential litigation and reputation losses in cases of detected misreporting. Empirical results suggest that, in line with this idea of the opposing interest of companies and their auditors regarding KAM disclosure, the implementation of the new audit reporting regime lead to an increase in the probability of auditor switch. Cross-sectional analyzes give further support to the idea that KAM disclosure increases tension between auditors and their clients as in the post-implementation period the probability of auditor switch is positively associated with the number of reported KAMs. Finally, there is some evidence of a reduction in the number of reported KAMs following auditor switches, which may indicate a new form of successful opinion shopping.
The second chapter investigates how U.S. auditors respond to shifts in litigation risk driven by two Supreme Court rulings—Tellabs (2007) and Janus (2011)—which altered legal standards across federal circuits. These rulings created exogenous variation in auditors’ legal exposure, allowing us to examine adjustments in audit pricing, reporting conservatism, and audit quality. We consistently find that auditors raise their fees in circuits where litigation risk increased following both rulings. However, the evidence for other auditor responses is mixed: while some findings support the expected effects following Tellabs ruling, others are contradictory. For Janus, we find no meaningful evidence of auditor responses beyond fee adjustments.
The third chapter examines if and how U.S. public companies adjust their ESG practices after receiving penalties for violating ESG-related regulations. We seek to understand whether these firms take steps to improve their ESG standing in order to signal a renewed commitment to ESG principles, rebuild their tainted reputations, and reduce the likelihood of future violations. Consistent with the stated hypotheses, the results indicate that firms with material or repeated violations are more likely to adopt targeted environmental initiatives and experience significant improvements in ESG standing relative to industry peers. Furthermore, we observe greater transparency in ESG reporting, particularly following repeated violations. The findings related to quantitative ESG outcomes — such as waste generation, energy use, or injury rates — are generally weak or statistically insignificant
Socio-Cognitive Drivers of Strategic Decision Making in New Ventures and Privately Held Enterprises
No full textThis dissertation consists of a collection of three essays that examine how socio-cognitive
constructs such as celebrity, emotional attachment, reputation, and status influence strategic
decision making in small and privately held enterprises such as startups, project-based teams,
and family businesses. These non-pecuniary factors not only impact the owners of these firms,
but also influence the members of the founding team and the external evaluators such as
investors when determining how they want to interact with the focal firm. A simple concept
such as a firm or founding team’s reputation will influence the opportunities it has for receiving
outside investment, the firm’s ability to retain members of the founding team, and the
aggressiveness by which the firm defends its intellectual property. Furthermore, because start-
ups and family-owned firms have greater overlap between managers and firm ownership, the
managers of the firm therefore are more likely to make strategic decisions based off of their own
socioemotional influences. This means that these non-pecuniary influences subsequently impact
a firm’s financial performance. For example, Chapter 1 of this dissertation finds that investors
overinvest in celebrity-backed firms despite the fact that celebrity-backed firms experience no
longer-term performance benefit – leading to an inefficient allocation of capital for the investors,
while Chapter 2 shows that the type of external recognition a team receives can lead to
disassembly, despite the overwhelming evidence that repeat collaboration leads to higher
performance. Ultimately, the findings of these studies highlight the importance of integrating
socio-cognitive dimensions into strategic management theories to better predict and interpret
behavior in small and privately held organizations
Democracy, Trust, and Political Orientation: Disentangling Mechanisms Shaping Individuals’ Vaccine Attitudes
No full textContext: In recent decades, many countries experienced a reduction in the quality and functioning of democratic institutions and norms accompanied by rising social distrust and opposing political views. The decline in vaccine confidence might be linked to these trends. This study explores the political factors influencing individual attitudes toward vaccination across 22 upper-middle-income and high-income countries, examining the interaction between political orientation, trust in public health authorities, and levels of democracy. Methods: The authors used the VaxPref database, encompassing demographically representative data from 50,242 respondents collected between July 2022 and June 2023, to conduct an analysis on three levels: pooled sample, democracy groups, and country-specific analyses. Results: The authors found that higher democracy scores generally correlated with lower levels of vaccine skepticism. People in the political center and on the political right expressed more skepticism toward vaccines overall. However, trust in public health authorities emerged as the determinant that explains the largest variation in vaccine attitudes. Conclusions: These findings suggest a greater effectiveness of democratic systems in fostering vaccine confidence and the need to depoliticize vaccination efforts. Building and maintaining trust in scientific information and technical expertise is critical. Blunt measures like vaccination mandates may not sustain long-term confidence, particularly in democratic contexts. Effective interventions should prioritize comprehensive school-based education to promote preventive health behaviors coupled with targeted trust-enhancing communication strategies
Cultural investments and gentrification: An urban transformation study of the city of Milan between 2001 and 2021
No full textThis paper investigates the intersection of cultural investment and urban transformation, using Milan as a case study. It examines whether and how cultural openings correlate with differentiated patterns of gentrification across neighborhoods. By moving beyond isolated case studies, the paper adopts a city-wide, spatialized approach to urban change
Traditional Constitutional Arrangements and the Separation of Powers: A Difficult Relationship in Continental Europe Micro Jurisdictions
No full textThe chapter analyses the impact that the diminutive size of three continental Europe microstates, two monarchies and one republic – namely the two Principalities of Monaco and of Liechtenstein and the Republic of San Marino – has upon their constitutional arrangements, in particular when it comes to the balance of powers between the different branches of government. The main issue with microstates is their need to strike a balance between the maintenance of their traditional institutions on the one hand and the need be receptive the development of the European constitutionalism on the other hand. Their constitutional systems are quite unusual in a comparative perspective, being anchored to a distinctive legal and historical tradition. The transplant of the pillars of European constitutionalism, such as the separation of powers, may be problematic in the sense that it may endanger the traditional institutional arrangements. Microstates are more concerned that normal size states of the preservation of their constitutional identity, because they perceive that a total adjustment to core principles of constitutionalism may cause their system to implode. The chapter will then discuss the criticalities of these traditional institutional arrangements and the recent attempts of reform. In particular, what emerges from the comparison of these three microstates is that they are all characterised by a pivotal institution – the Principe in the two Principalities and the Grand and General Council in San Marino – with respect to whom the system of checks and balances seems to work poorly or just in theory