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This paper studies the effect of gender-related provisions in Regional Trade Agreements on under-explored aspects of gender inequality at the plant level, namely the difference in the managerial and ownership status between the two genders. This topic is timely and critical as gender equality considerations are becoming more prominent in new trade agreements, recognizing to different extents that trade policies developed with a gender perspective can help overcome gender inequalities by creating new opportunities for women's equal representation in export jobs and entrepreneurship. We use the World Bank Enterprise Surveys that encompasses data on 195,000 firms in 155 countries in 56 manufacturing and services sectors, and the dataset on gender-related provisions in trade agreements from the World Trade Organization. Our results show that the total number of gender-related provisions in trade agreements, as well their location in articles and in annexes are positively associated with a higher probability of the firm to be owned or managed by a female. This result is robust whether the firm is an exporter, importer, or involved in the global value chain of the sector of interest. When differentiating countries by income level, we find that the positive effect of gender-related provisions in trade agreements on women empowerment holds only for developed countries, pointing out the importance of making South-South agreements more gender friendly.

We examine the effect of media freedom on public expenditure efficiency, using a panel of 158 advanced and developing countries from 1994 to 2016. We find robust evidence that media freedom significantly improves government efficiency, and the effect is strongly complementary to per capita income, level of education, Internet access, and fiscal rules. We further empirically examine the underlying mechanisms and show that the effect of media freedom on efficiency is mainly channeled through reduced corruption, improved transparency and accountability in the public sector, and enhanced electoral competition. These findings underscore the critical role of media freedom in fostering good governance and efficient resource use.

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In credit markets, screening algorithms aim to discriminate between good-type and bad-type borrowers. However, when doing so, they can also discriminate between individuals sharing a protected attribute (e.g., gender, age, racial origin) and the rest of the population. This can be unintentional and originate from the training data set or from the model itself. We show how to formally test the algorithmic fairness of scoring models and how to identify the variables responsible for any lack of fairness. We then use these variables to optimize the fairness-performance tradeoff. Our framework provides guidance on how algorithmic fairness can be monitored by lenders, controlled by their regulators, improved for the benefit of protected groups, while still maintaining a high level of forecasting accuracy. This paper was accepted by Will Cong, finance. Funding: This work was supported by the Autorité de Contrôle Prudentiel et de Résolution (ACPR) Chair in Regulation and Systemic Risk, the Fintech Chair at Dauphine-PSL University, and the French National Research Agency (ANR) [MLEforRisk ANR-21-CE26-0007, Ecodec ANR-11-LABX-0047, and F-STAR ANR-17-CE26-0007-01]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03888 .