This paper documents and studies the gender gap in performance among associate lawyers in the United States. Unlike other high-skilled professions, the legal profession assesses performance using transparent measures that are widely used and comparable across firms: the number of hours billed to clients and the amount of new client revenue generated. We find clear evidence of a gender gap in annual performance with respect to both measures. Male lawyers bill ten percent more hours and bring in more than twice the new client revenue than do female lawyers. We demonstrate that the differential impact across genders in the presence of young children and differences in aspirations to become a law firm partner account for a large share of the difference in performance. We also show that accounting for performance has important consequences for gender gaps in lawyers' earnings and subsequent promotion. Whereas individual and firm characteristics explain up to 50 percent of the earnings gap, the inclusion of performance measures explains a substantial share of the remainder. Performance measures also explain a sizeable share of the gender gap in promotion.
As argued in Acquisti et al. (2016), the proliferation of databases containing consumer information has led to exponential growth of the literature on the economics of privacy. Mungan (2017) contributes to the literature on privacy by focusing on publishers' incentives to gather and disseminate individuals' information. More specifically, the paper studies the possibility of allowing individuals to prevent the dissemination of information by exercising conditional privacy rights in exchange of a fee. In this Comment, I provide what I think are the major contributions and limitations of the analysis in the paper. In particular, I point out crucial conditions that might make conditional privacy rights problematic.
Which decision rules are the most efficient? Which are the best in terms of maximin, or maximax? We study these questions for the case of a group of individuals faced with a choice from a set of alternatives. First, we show that the set of optimal decision rules is well-defined, particularly simple and well-known: the class of scoring rules. Second, we provide the optimal decision rules for the three different ideals of justice under consideration: utilitarianism (efficiency), maximin, and maximax. We show that plurality, arguably the most widely used voting system, is optimal in terms of maximax, while the best way to achieve maximin is by means of negative voting, and the optimal utilitarian decision rule depends on the culture of the society. We then provide the mapping between cultures and optimal decision rules.
A standard assumption in the economics of law enforcement is that the probability of a violator being punished depends only on the resources devoted to enforcement. However, it is often true that the productivity of enforcement resources decreases with the number of violators. In this paper, an individual who violates the law provides a positive externality for other offenders because the probability of being punished decreases with the number of individuals violating the law. This externality explains the existence of correlation between individuals' decisions to break a law. The model evaluates the implications when determining the socially optimal enforcement expenditure, focusing specifically on the case of neighborhood crime. In particular, using a parametrized functional form, I show that neighborhood externalities will enhance or impede enforcement, depending on the crime rate.
Using an ideal setting from a major food safety crisis, we estimate a full demand model for the unsafe product and its substitutes and recover consumers' preference parameters. Counterfactual exercises quantify the relevance of different mechanisms (changes in safety perceptions, idiosyncratic tastes, nutritional characteristics, and prices) driving consumers' response.
We find that consumers' reaction is limited by their taste for the product and its nutritional characteristics. Due to the costs associated with switching away from the affected product, the decline in demand following a product-harm crisis tends to understate the true weight of such events in consumers' utility. Indeed, we find that a large fraction of consumers are unresponsive to the crisis even when they significantly downgrade their product safety perception. For an accurate assessment of the crisis, managerial strategies should therefore account for how different demand drivers bind consumers' substitution patterns.
This article studies a model with two lawyers opposing each other in a case where the outcome of the trial depends on the lawyers' talents and effort choices. The trial outcome provides an implicit incentive because it is informative about the lawyers' talents. Regardless of the functional form used to model the binary trial outcome, the implicit incentive is shown to be characterized by three components, namely the ex ante uncertainty over the lawyers' talents, the sensitivity of the trial outcome to the attorneys' talents, and the variance of the noise in the trial outcome, which is endogenous. Their interplay with the attorneys' effort levels and the merits of the case affects the informativeness of the trial outcome on the lawyers' talents, thereby creating strategic interactions.
"The Demand for Gender-Stereotyped TV Content " joint with Friman Sánchez (work in progress)
Persistent traditional gender roles appear to affect men and women of all education levels. One source is likely to be the high prevalence of gender stereotyped Media content, which influences individuals from early on in life. Although TVs and Media companies in several countries have signed self-regulation agreements that commit them not to show this type of contents, these agreements do not seem fully effective. High-demand for sensitive content can be a clear disincentive for TV programmers to fulfill the self-enforcement agreements. We are designing a methodololgy to collect and analyze data for demand estimation of gender-stereotyped TV content using consumption data by representative households in Spain. Detailed consumption data allows the identification of taste for specific contents within TV shows, and therefore, not related to unobserved show characteristics. The accurate catalogation of large scale multimedia content is currently feasible thanks to the use of machine learning algorithms and the improvement of computer processing capabilities. Furthermore, it permits the quantification of multimedia content dimensions that previously needed qualitative or subjective evaluation on a case-by-case analysis.