Work on different days of the week is not equally desirable to workers. The same is true for work performed at different times of the day. Undesirable work times are more common among less educated workers, young and quite old workers, minorities, and immigrants. There are substantial cross-country differences in patterns of work timing, with work in lower-income countries distributed more evenly across the week. Policies to affect the timing of work are few, but they do alter outcomes.

Labour market discrimination is widespread and raises ethical, societal, and efficiency concerns. It not only results in the unfair treatment of individuals with comparable skills, but also imposes broader costs on society by eroding trust and weakening cohesion. Moreover, discrimination limits the full potential of the working-age population by excluding talent or trapping people in roles below their abilities. These effects are amplified by feedback loops: fewer opportunities lower labour market participation and productivity, while the harm discrimination inflicts on mental and physical health further reduces economic output.

In the past 25 years, the Chilean labour market has observed a modernisation in terms of its transition to a service economy, but also in terms of its institutional robustness. It has seen a consistent growth in the labour force, driven by women’s entrance in the labour market, and a sustained increase in earnings from salaried work. However, it faces obstacles to drive growth through labour productivity and to ensure that growth translates to better socioeconomic outcomes for workers as a large low-productivity segment persists, also driving informality. These obstacles include lengthy permits, human capital deficits, low R&D investment, as well as slow technological adoption. Solving these issues requires coherent policy making beyond employment and labour policy.

Brain drain refers to the selective emigration of highly educated people, who often have stronger incentives to migrate and face fewer barriers. At first glance, this seems to be an adverse situation: losing doctors, engineers or teachers could hinder development. However, migration can also be beneficial by spurring investment in skills, fueling remittances, fostering innovation, business links, and transfers of knowledge and norms. The net impact depends on the skills involved and the context, creating an opportunity for policies that transform emigration into a driver of development.

The Portuguese labour market has stabilised after the 2010–2013 sovereign debt crisis, which pushed unemployment to a historic 18.5%. By 2025, the rate of unemployment has exhibited low-record levels reaching 5.9%. Long-term unemployment has declined, and the female employment rate reached historical values. Yet, several structural imbalances persist. Productivity levels remain low compared to European peers, and wages continue to struggle to keep pace with the cost of living.

How do minimum wage policies interact with labour tax evasion? In many transition economies, two features stand out: a large spike in the wage distribution at the minimum wage and widespread use of “envelope wages”—undeclared cash paid in addition to official earnings. This spike can be explained by the over-representation of tax-evading employers among minimum wage payers. In such a context, raising the minimum wage may serve as an enforcement tool by compelling evading firms to convert part of the undeclared pay into formal wages in order to comply with the legal minimum.

While Mexico has improved the education of its labor force, maintained a stable macroeconomic environment, and been friendly to international trade, its labor market still faces many challenges. In particular, Mexico has difficulty creating high-paying jobs: the share of informal employment has remained stagnant for the last 20 years, and, by 2025, remains above 50%. These problems are particularly poignant in southern Mexico.

It is common practice to incorporate additional covariates in empirical economics. In the context of regression discontinuity (RD) designs, covariate adjustment plays multiple roles, making it essential to understand its impact on analysis and conclusions. Typically implemented via local least squares regressions, covariate adjustment can serve three main distinct purposes: (i) improving the efficiency of RD average causal effect estimators, (ii) learning about heterogeneous RD policy effects, and (iii) changing the RD parameter of interest.