There are growing concerns about the impact of pollution on maternal and infant health. In the UK in 2018, 36% of local authorities had levels of PM2.5 where exposure exceeded the annual level recommended by the World Health Organisation at the time. Using a population database of births in Northern Ireland linked to localised geographic information on pollution in mothers' postcodes (zip codes) of residence during pregnancy, we examine whether prenatal exposure to PM2.5 is associated with a comprehensive range of birth outcomes. Overall, we find little evidence that particulate matter is related to worse infant outcomes once we implement a fixed effects approach that accounts for time-invariant factors common to mothers. While reducing pollution remains an urgent public health priority, our results imply that improvements in short-run levels of prenatal PM2.5 exposure are unlikely to be sufficient by themselves to reduce disparities in birth outcomes.

This paper aims to highlight the importance of considering endogenous peer effects, as defined by Manski (1993), in order to identify gender composition effect on education outcome appropriately. Using Manski (1993) linear-in-means model, this paper illustrates that the gender composition effect that is currently estimated in education function is the function of three parameters: social multiplier, gender differences in outcome and gender composition effect (known as a gender peer effect). The appropriate gender peer effect is identified after using Graham's variance restriction method to identify and rule out a social multiplier effect. The findings suggest that a social multiplier plays a crucial role in learning process for Italian secondary and US primary students, although a gender peer effect is not as important as highlighted in previous literatures (Hoxby, 2000; Whitmore, 2005; Lavy and Schlosser, 2011).