Mental health of children with gender and sexual minority parents: a review and future directions

This article reviews the literature between 2015 and 2022 on mental health disparities between children with gender and sexual minority parents and children with different-sex parents. Although most studies indicate that children with gender and sexual minority parents do not experience more mental health problems than children with different-sex parents, the results are mixed and depend on the underlying sample. The review highlights important shortcomings that characterize this literature, including cross-sectional survey samples, correlational methods, lack of diversity by country, and a lack of research on children with transgender and bisexual parents. Therefore, substantial caution is warranted when attempting to arrive at an overall conclusion based on the current state of the literature. Suggestions are provided that can guide academic work when studying mental health outcomes of children with gender and sexual minority parents in the future

Identifying Politically Connected Firms: A Machine Learning Approach

This article introduces machine learning techniques to identify politically connected firms. By assembling information from publicly available sources and the Orbis company database, we constructed a novel firm population dataset from Czechia in which various forms of political connections can be determined. The data about firms' connections are unique and comprehensive. They include political donations by the firm, having members of managerial boards who donated to a political party, and having members of boards who ran for political office. The results indicate that over 85% of firms with political connections can be accurately identified by the proposed algorithms. The model obtains this high accuracy by using only firm-level financial and industry indicators that are widely available in most countries. These findings suggest that machine learning algorithms could be used by public institutions to improve the identification of politically connected firms with potentially large conflicts of interest

Doing Genders: Partner’s Gender and Labor Market Behavior

Partnered men and women show consistently gendered patterns of labor market behavior. We test whether not only a person’s own gender, but also their partner’s gender shapes hours worked. We use Dutch administrative population data on almost 5,000 persons who had both male and female partners, whose hours worked we observe monthly over 15 years. We argue that this provides a unique setting to assess the relevance of partner’s gender for labor market behavior. Using two-way fixed effects and fixed-effects individual slopes models, we find that both men and women tend to work more hours when partnered with a female partner compared to a male partner. These results align with our hypothesis that a partner’s gender influences labor market behavior. For women, we conclude that this finding may be (partly) explained by marital and motherhood status. Additionally, we discovered that women decrease their hours worked to a lesser extent when caring for a child if they have a female partner. Finally, we found that for men, the positive association between own and partner’s hours worked is weaker when one has a female partner, indicating a higher degree of specialization within these couples

Ability of detecting and willingness to share fake news

By conducting large-scale surveys in Germany and the United Kingdom, we investigate the individual-level determinants of the ability to detect fake news and the inclination to share it. We distinguish between deliberate and accidental sharing of fake news. We document that accidental sharing is much more common than deliberate sharing. Furthermore, our results indicate that older, male, high-income, and politically left-leaning respondents better detect fake news. We also find that accidental sharing decreases with age and is more prevalent among right-leaning respondents. Deliberate sharing of fake news is more prevalent among younger respondents in the United Kingdom. Finally, our results imply that respondents have a good assessment of their ability to detect fake news: those we identified as accidental sharers were also more likely to have admitted to having shared fake news

Does It Matter When Your Smartest Peers Leave Your Class? Evidence from Hungary

Elite schools in Hungary cherry pick high achieving students from general primary schools. The geographical coverage of elite schools has remained unchanged since 1999, when the establishment of new elite schools stopped. We exploit this geographical variation and estimate the impact of high achieving peers leaving the class on student achievement, behaviour, and aspirations for higher education. Our estimates indicate moderate but heterogeneous effects on those left behind in general primary schools

Identity and inequality misperceptions, demographic determinants and efficacy of corrective measures

By conducting two waves of large-scale surveys in the United Kingdom and Germany, we investigate the determinants of identity and inequality misperceptions. We first show that people substantially overestimate the share of immigrants, Muslims, people under the poverty line, and the income share of the richest. Moreover, women, lower-income, and lower-educated respondents generally have higher misperceptions. Only income share misperceptions are associated more with people who place themselves on the left of the political spectrum. In contrast, the other three misperceptions are more prevalent among those who place themselves to the right. We then attempt to correct misperceptions by conducting a classic controlled experiment. Specifically, we randomly assign respondents into a treatment group informed about their initial misperceptions and a control group left uninformed. Our results indicate that information treatments had some corrective effects on misperceptions in Germany but were ineffective in the United Kingdom. Moreover, information treatments in Germany were more effective for men, centrists, and highly educated respondents. There is also no evidence of spill-over effects: correcting one misperception does not have corrective effects for the other misperceptions

The effect of modular education on school dropout

Modular education refers to the division of conventional courses into smaller components or modules. Each module enables students to obtain a partial certificate that can be combined into a qualification. This article evaluates whether modular education, which is widely used in secondary and tertiary education, has been effective in reducing school dropout. For this purpose, the study exploits a policy change in the Flemish Community of Belgium, which recently introduced modular education for some programmes. Using a difference‐in‐differences framework with diverse adoption dates per school, the results indicate that modular education may significantly reduce school dropout by 2.5 percentage points, with the largest effects on foreign origin students. Therefore, modular education is likely to be an effective policy to tackle school dropout and reduce the ethnic attainment gap. Additionally, students enrolled in modular education are more likely to be employed and to incur higher earnings on the labour market