|
on Law and Economics |
| By: | Anna Laura Baraldi (Università della Campania Luigi Vanvitelli); Giovanni Immordino (Università di Napoli Federico II and CSEF); Erasmo Papagni (Università di Napoli Federico II); Marco Stimolo (Università di Siena) |
| Abstract: | Several studies document that women are more honest than men, so an increase in their political representation improves political institutions. However, greater honesty among politicians is an obstacle to mafias’ influence, who may respond by escalating violence. We test this unintended consequence in Italy using Law 215/2012 whereby voters can express two preferences if they are of different genders. A Difference-in- Differences analysis documents an increase in violence probability of 0.6 times its mean (0.031). An alternative Differences-in-Discontinuities design yields similar results. These findings are not driven by the regions most plagued by mafias, and are validated by several robustness checks. |
| Keywords: | Organized Crime, Violence, Gender balance laws. |
| JEL: | C25 D73 D78 I38 K42 |
| Date: | 2023–12–06 |
| URL: | http://d.repec.org/n?u=RePEc:sef:csefwp:698&r=law |
| By: | Wentian Zhang |
| Abstract: | This paper studies the effect of antitrust enforcement on venture capital (VC) investments and VC-backed companies. To establish causality, I exploit the DOJ's decision to close several antitrust field offices in 2013, which reduced the antitrust enforcement in areas near the closed offices. I find that the reduction in antitrust enforcement causes a significant decrease in VC investments in startups located in the affected areas. Furthermore, these affected VC-backed startups exhibit a reduced likelihood of successful exits and diminished innovation performance. These negative results are mainly driven by startups in concentrated industries, where incumbents tend to engage in anticompetitive behaviors more frequently. To mitigate the adverse effect, startups should innovate more to differentiate their products. This paper sheds light on the importance of local antitrust enforcement in fostering competition and innovation. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2312.13564&r=law |
| By: | Aaron Chalfin; Felipe M. Gonçalves |
| Abstract: | We study how public sector workers balance their professional motivations with private economic concerns, focusing on police arrests. Arrests made near the end of an officer's shift typically require overtime work, and officers respond by reducing arrest frequency but increasing arrest quality. Days in which an officer works a second job after their police shift have higher opportunity cost, also reducing late-shift arrests. Combining our estimates in a dynamic model identifies officer preferences over workplace activity and overtime work. Our results indicate that officers' private costs of arrests have a first-order impact on the quantity and quality of enforcement. |
| JEL: | J33 J45 K42 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31985&r=law |
| By: | Johann Laux; Fabian Stephany; Alice Liefgreen |
| Abstract: | The global surge in AI applications is transforming industries, leading to displacement and complementation of existing jobs, while also giving rise to new employment opportunities. Human oversight of AI is an emerging task in which human workers interact with an AI model to improve its performance, safety, and compliance with normative principles. Data annotation, encompassing the labelling of images or annotating of texts, serves as a critical human oversight process, as the quality of a dataset directly influences the quality of AI models trained on it. Therefore, the efficiency of human oversight work stands as an important competitive advantage for AI developers. This paper delves into the foundational economics of human oversight, with a specific focus on the impact of norm design and monetary incentives on data quality and costs. An experimental study involving 307 data annotators examines six groups with varying task instructions (norms) and monetary incentives. Results reveal that annotators provided with clear rules exhibit higher accuracy rates, outperforming those with vague standards by 14%. Similarly, annotators receiving an additional monetary incentive perform significantly better, with the highest accuracy rate recorded in the group working with both clear rules and incentives (87.5% accuracy). However, both groups require more time to complete tasks, with a 31% increase in average task completion time compared to those working with standards and no incentives. These empirical findings underscore the trade-off between data quality and efficiency in data curation, shedding light on the nuanced impact of norm design and incentives on the economics of AI development. The paper contributes experimental insights to discussions on the economical, ethical, and legal considerations of AI technologies. |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2312.14565&r=law |
| By: | Alessandra Fenizia; Raffaele Saggio |
| Abstract: | This paper studies the long-run economic impact of dismissing city councils infiltrated by organized crime. Applying a matched difference-in-differences design to the universe of Italian social security records, we find that city council dismissals (CCDs) increase employment, the number of firms, and industrial real estate prices. The effects are concentrated in Mafia-dominated sectors and in municipalities where fewer incumbents are re-elected. The dismissals generate large economic returns by weakening the Mafia and fostering trust in local institutions. The analysis suggests that CCDs represent an effective intervention for establishing legitimacy and spurring economic activity in areas dominated by organized crime. |
| JEL: | H5 J08 P0 |
| Date: | 2023–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32002&r=law |