Costas Meghir Publications

Positive assortative matching refers to the tendency of individuals with similar characteristics to form partnerships. Measuring the extent to which assortative matching differs between two economies is challenging when the marginal distributions of the sorting characteristic (e.g., education) change for either or both sexes. We show how the use of different measures can generate different conclusions. We provide an axiomatic characterization for the odds ratio, normalized trace, and likelihood ratio and provide a structural economic interpretation of the odds ratio. We use our approach to show that marital sorting by education substantially changed between the 1950s and the 1970s cohorts.

Caregiving is a service provided for children with the primary objective of taking care of them and ensuring that they are safe and have opportunities to learn and develop positive relationships with their caregivers and peers while their parents are away. Caregiving takes the forms of home-based care, centre-based care, school-based care, family child care and family, friend, and neighbour (FFN) care. The paper utilises preliminary findings on school attendance from a randomised controlled trial on the effects of a preschool intervention on child learning and women’s economic empowerment in Tharaka Nithi County in school-based care. The research sought to test whether a preschool-based intervention in a rural setting in Kenya influences child development and women’s labour market participation in a cost-effective manner. The project examines the impact of allowing three-year-old children to attend preschool versus the regular pre-primary education programming, which allows children aged 4 years and above to attend preschool. Implementation of the intervention started in January 2024 in 60 intervention schools where five three-year-old children were admitted to a playgroup (PG) in the pre-primary one (PP1) class. Twelve mentors and sixty caregivers were recruited and trained alongside sixty PP1 teachers from the sampled preschools to implement an adapted PP1 curriculum. The twelve mentors coached teachers weekly on the implementation of the curriculum in the five schools assigned to them. This paper presents preliminary findings on preschool attendance for the PG and PP1 children based on weekly attendance data from term one and term two of the 2024 school calendar year on the day the mentors visited the school. Findings reveal that school attendance was low during school openings, midterm breaks, and the last weeks before the schools closed. Public holidays, as well as extracurricular activities coupled with children being sent home for school levies, also contributed to children not attending school regularly. The findings further show that the attendance rate in term one was slightly higher than in term two.

Using city-level crime data for six major U.S. cities from Jan 21 to May 30 2020, we document an approximately 20% average reduction in reported crimes during March, simultaneous with sharp economic downturn and heightened social distancing restrictions. We also decompose trends by crime type and location. Our key findings are:

• Since the steep 20% crime drop in March, overall rates have steadily risen but remain below pre-pandemic levels on average.
• Crimes committed in commercial and street settings (as opposed to residential areas) account for most of the drop in crimes.
• Violent crimes decline in similar proportion to nonviolent crimes.
• Though larcenies fall by one-third, other kinds of theft like burglary and auto theft rise.

Caveats to our findings include the possibility of simultaneous changes in reporting and policing activities.

The onset of the Covid-19 pandemic has led to a dramatic reduction in employment and hours worked in the US economy. The decline can be measured using conventional data sources such as the Current Population Survey and in the number of individuals filing for unemployment. However, given the unprecedented pace of the ongoing changes to labor market conditions, detailed, up-to-date, high frequency data on wages, employment, and hours of work is needed. Such data can provide insights into how firms and workers have been affected by the pandemic so far, and how those effects differ by type of firm and worker wage level. It can also be used to detail – in real time – the state of the labor market.