Carlo Migliardo

1. Organised crime, particularly mafia-style activities, poses unique challenges for researchers and policymakers because of its complex and often covert nature. Official crime statistics, typically a...

Purpose: This study quantifies volatility spillovers between WTI and INE, assessing their time-varying nature and INE’s sensitivity to external shocks. It evaluates INE’s integration with global markets and its role as a regional benchmark, offering insights into emerging energy markets’ resilience. Design/methodology/approach: This study examines the volatility spillover dynamics between WTI and Shanghai (INE) crude oil futures launched in 2018 to establish a regional benchmark and stabilize China’s currency. Using high-frequency data, a Multiplicative Error Model (MEM) quantifies spillovers, while a Markov-switching extension captures regime-dependent effects across the pre-pandemic, pandemic (2020–2021), and post-COVID phases. Robustness checks control for geopolitical risks (e.g. US–China tensions) and RMB exchange rate fluctuations. Findings: The results show unidirectional spillovers from WTI to INE, with no reverse effect, highlighting WTI’s dominance. Spillovers intensify during high-volatility regimes, peaking during the pandemic but declining post-COVID. INE demonstrates resilience to geopolitical and currency risks, reflecting its regional focus. The Markov-switching framework confirms regime-dependent spillovers, indicating a structural market shift. Originality/value: This study pioneers the use of MEM with Markov-switching to analyze WTI–INE spillovers, challenging static assumptions in prior research. It provides practical insights for Asian policymakers and investors, clarifying INE’s role as a regionally focused yet globally influenced contract. INE’s insulation from non-energy risks offers novel perspectives on the stability of emerging energy markets, informing risk management in poverty-dependent economies.

In Italy, organized crime poses a significant economic challenge as it reduces productivity and contributes to regional inequalities. This study investigates the influence of mafia activity on firm efficiency, with a specific focus on civil engineering companies. A composite indicator of organized crime was developed to measure its presence at the municipal level, and stochastic frontier models were employed to assess firm efficiency and input misallocation across Italian municipalities. We also estimate an Institutional Quality Indicator (IQI) to account for the impact of local institutional effectiveness on firm performance, with the results showing that higher IQI levels are associated with lower inefficiency. The findings indicate that criminal activities significantly hinder efficiency, especially in areas where organized crime is pervasive. These results underscore the urgent need for strategies to shield firms from organized crime, foster growth, and facilitate regional development.

This study investigates the relationship between European utility companies' compliance with the EU Taxonomy for Sustainable Activities and their overall performance. The EU Taxonomy is a new regulation proposed by the European Commission to promote sustainable finance by 2050. The literature shows that nonfinancial disclosures have a favorable impact on financial performance. However, no research has been conducted to assess the implementation of the EU Taxonomy and its effect on firm performance. Using a sample of European utilities from 2012 to 2022, a difference‐in‐differences (DiD) model was applied to analyze the causal relationship between compliance and performance. Based on institutional and signaling theories, the results show that companies reporting alignment with the Taxonomy exhibit higher market value, profitability, and efficiency than those that do not. This study contributes to firms' transparency and enriches academic discussions by offering insights for policymakers and by improving industry practices.