Articles

The privilege or disadvantage of individuals is not determined by a single social identity. The sexual division of labor affects women’s and men’s labor supply, the industries and occupations they enter, their earnings and progress. However, being a racial/ethnic or sexual minority (along with class and age) also influences job opportunities. Evidence shows that minority women’s experiences are unique and jointly determined by their gender and minority status, although the gender effect appears to precede that of minority.

There is little to no consensus in the academic literature over whether centralised, standardised exams are better for students than teacher assessments. While a growing body of evidence from economics highlights bias in teacher assessments, educationalists and psychologists point to the harm caused by high-stakes exam-related stress and argue that exams and teacher assessments generally agree very closely. This lack of academic consensus is reflected in policy: a wide variety of assessment methods are used across (and even within) countries. Policymakers should be aware of the potential for inequalities in non-blind assessments and consider carefully the consequences of relying on a single method of assessment.

The relationship between female labor force participation and economic development is far more complex than often portrayed in both the academic literature and policy debates. Due to various economic and social factors, such as the pattern of growth, education attainment, and social norms, trends in female labor force participation do not conform consistently with the notion of a U-shaped relationship with gross domestic produc (GDP). Despite the initial impact, Covid-19 did not have a lasting negative effect, on average, on women’s participation. At the same time, some countries have made significant progress in increasing participation rates for women, including those who have started from a lower level.

Arguments for increasing gender diversity on corporate boards of directors by gender quotas range from ensuring equal opportunity to improving firm performance. The introduction of gender quotas in a number of countries, mainly in Europe, has increased female representation on boards. Current research does not unambiguously justify gender quotas on grounds of economic efficiency. In many countries, the number of women in top executive positions is limited, and it is not clear from the evidence that quotas lead to a larger pool of female top executives, who, in turn, are the main pipeline for boards of directors. Thus, other supplementary policies may be necessary if politicians want to increase the number of women in senior management positions.

Machine learning (ML) improves economic policy analysis by addressing the complexity of modern data. It complements traditional econometric methods by handling numerous control variables, managing interactions and non-linearities flexibly, and uncovering nuanced differential causal effects. However, careful validation and awareness of limitations such as risk of bias, transparency issues, and data requirements are essential for informed policy recommendations.

Environmental regulations raise production costs at regulated firms, though in most cases the costs are only a small fraction of a firm’s total costs. Productivity tends to fall, and firms may shift new investment and production to locations with less stringent regulation. However, environmental regulations have had enormous benefits in terms of lives saved and illnesses averted, especially through reductions in airborne particulates. The potential health gains may be even greater in developing countries, where pollution levels are high. The benefits to society from environmental regulation hence appear to be much larger than the costs of compliance.

The relationship between technology and employment has always been a source of concern, at least since the first industrial revolution. However, while process innovation can be job-destroying (provided that its direct labor-saving effect is not compensated through market mechanisms), product innovation can imply the emergence of new firms, new sectors, and thus new jobs (provided that its welfare effect dominates the crowding out of old products). Nowadays, the topic is even more relevant because the world economy is undergoing a new technological revolution centred on automation and the diffusion of Artificial Intelligence (AI).

Over the past decades, academics worldwide have conducted experiments with fictitious job applications to measure discrimination in hiring. This discrimination leads to underutilization of labor market potential and higher unemployment rates for individuals from vulnerable groups. Collectively, the insights from the published research suggest that three groups face more discrimination than ethnic minorities: people with disabilities, less physically attractive people, and older people. The discrimination found in Western economies generally persists across countries and is stable over time, although some variation exists.

Artificial intelligence (AI) has streamlined processes, improved workforce allocation, and created new jobs to meet the needs of digitalization and automation. Individuals with AI capital experience greater employment opportunities and higher wages, particularly in high-skilled roles and large firms. Training in AI helps reduce gender-based digital disparities, empowers individuals, and enhances their employability. Policymakers should promote inclusive AI development policies to prevent widening AI-related divides and unemployment, and to ensure equitable opportunities.

The use of anonymous job applications (or blind recruitment) to combat hiring discrimination is gaining attention and interest. Results from field experiments and pilot projects in European countries (France, Germany, the Netherlands, Finland and Sweden are considered here), Canada, and Australia shed light on their potential to reduce some of the discriminatory barriers to hiring for minority and other disadvantaged groups. But although this approach can achieve its primary aims, there are also important cautions to consider.