Volume 19, Issue 3

The pervasiveness of law enforcement schemes that prescribe harsher penalties for repeat offenders continues to challenge scholars who seek an economic explanation for criminal justice policies. The current paper formalizes an explanation suggested by Dana, D. (2001. Rethinking the puzzle of escalating penalties for repeat offenders. Yale Law J. 110: 733–783), which is based on the role of the law in educating people about wrongful behavior—the so-called “expressive function” of law. The analysis shows that an escalating structure that imposes a lenient sanction on all first-timers and a harsh sanction on repeaters represents a compromise solution that is (second best) optimal if the fraction of unknowing offenders in the population of potential offenders (as opposed to rational calculators) is sufficiently large.

From 2003 to 2018, all 50 states and the District of Columbia enacted breach notification laws (BNLs) mandating that firms suffering data breaches provide timely notification to affected persons and others about breach incidents and mitigation responses. BNLs were supposed to decrease data breaches and develop a market for data privacy where firms could strike their preferred balance between data security quality and cost. We find no systemic evidence for either supposition. Results from two-way difference-in-difference analyses indicate no decrease in data breach incident counts or magnitudes after BNLs are enacted. Results also indicate no longer-term decrease in data misuse after breaches. These non-effects appear to be precisely estimated nulls that persist for different firms, time-periods, data-breach types, and BNL types. Apparently inconsistent notification standards and inadequate information dissemination to the public may explain BNL ineffectiveness. An alternative federal regime may address these shortcomings and let a national BNL achieve goals state BNLs have apparently failed to meet.

Recent evidence suggests that legal marijuana markets in several U.S. states have decreased violence in Mexican-U.S. border regions. As legal markets for production and distribution displace drug cartel distribution, the violence associated with cartel trafficking and distribution decreases. Prior analysis has not considered an important emerging innovation for drug distribution: online anonymous marketplaces. The increasing volume of drug trade that has occurred on this “Dark Web” could result in reduced drug cartel violence as production and distribution use this substitute network and turn away from the cartel distribution networks. This paper investigates the relationship between border violence and the volume of drug trade that occurs on the Dark Web using a difference in differences model. We examine differences in crime rates at the U.S.-Mexico border and away from the border during the emergence of the Dark Web. Data on Dark Web transactions, users, and markets allows us to measure changes in Dark Web activity and the subsequent impact on crime. We find evidence that the rise in Dark Web marketplaces results in crime reductions at the border of the U.S., relative to non-border counties.

In this article we study collusive strategies and the optimal level of fines when firms face random demand fluctuations. Collusive firms can choose to alternate collusive periods with more competitive periods: such an intermittent strategy can be implemented particularly if demand variability is high. Firms then set competitive prices during recessions to cancel the risk of cartel detection and keep the ability to cartelize for the future. If the maximum fine is too low to fully deter cartels, the antitrust authority can influence the choice of collusive agreement by varying the level of fines according to demand states. If the demand is highly variable, the antitrust authority may induce firms to collude in all demand states (by decreasing the fine during recessions), in order to detect and break up cartels more easily. On the other hand, if the demand variability is low the optimal policy may be to reduce the fine when demand is high.

One of the most vexing problems in privacy policy is identifying consumer harm from unwanted observation; because it is highly subjective and is likely to vary greatly throughout the population, it doesn’t lend itself to easy measurement. Yet, these types of situations increasingly are the focal point of privacy policy discussions, including the Supreme Court’s recent decisions regarding standing and the FTC’s recently announced commercial surveillance rulemaking. The primary approach to attempt to quantify subjective harms has been to measure consumers’ willingness to exchange personal data for money in an experimental setting. This study takes a different tack, using field data to measure actual consumer response to a real-world reduction in the anonymity of online search. In March 2012, Google began to combine user information across platforms. To the extent that Google’s policy change reduced the anonymity associated with Google search, it may have diminished incentives to search sensitive topics. Using Google Trends (GT) data and a difference-in-difference estimator with top non-sensitive search terms as the control group, the results suggest that there was a 3–7 % short-term (1–2 months) reduction in sensitive search (relative to the non-sensitive search control group), as measured by GT. I examine heterogenous treatment effects, and find that the largest measured impact is for health-related search. There is no measured difference in reaction between high- and low-privacy demand states.

This paper analyses possibilities for amending the withdrawal right under the EU consumer law, aiming to reduce the information asymmetry between contracting parties in distance sales and thus increase the number of concluded contracts and the overall contractual surplus. The main findings are that the rules suggested in law and economics theory (the personalized mandatory rules and the mandated-choice model) may not be optimal tools for amending the withdrawal right because they mostly seem to neglect the allocation of risk between contracting parties. Thus, this paper suggests the new ‘risk allocation’ rules as a tool for amending the withdrawal right, focusing on its use in distance sales. If amended in line with those rules, the withdrawal right could deal with information asymmetry problems more efficiently, incentivise contracting parties to enter more distance sales contracts, and increase the overall contractual surplus, especially within the realms of e-commerce. The suggested proposal is conceived – at least for the time being – more as a thought experiment; relevant empirical analysis may follow up at a subsequent phase.