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During recent decades, economists' interest in gender-related issues has risen. Researchers aim to show how economic theory can be applied to gender related topics such as peer effect, labor market outcomes, and education. This dissertation aims to contribute to our understandings of the interaction, inequality and sources of differences across genders, and it consists of three empirical papers in the research area of gender economics. The aim of the first paper ("Separating gender composition effect from peer effects in education") is to demonstrate the importance of considering endogenous peer effects in order to identify gender composition effect. This fact is analytically illustrated by employing Manski's (1993) linear-in-means model. The paper derives an innovative solution to the simultaneous identification of endogenous and exogenous peer effects: gender composition effect of interest is estimated from auxiliary reduced-form estimates after identifying the endogenous peer effect by using Graham (2008) variance restriction method. The paper applies this methodology to two different data sets from American and Italian schools. The motivation of the second paper ("Gender differences in vulnerability to an economic crisis") is to analyze the different effect of recent economic crisis on the labor market outcome of men and women. Using triple differences method (before-after crisis, harder-milder hit sectors, men-women) the paper used British data at the occupation level and shows that men suffer more than women in terms of probability of losing their job. Several explanations for the findings are proposed. The third paper ("Gender gap in educational outcome") is concerned with a controversial academic debate on the existence, degree and origin of the gender gap in test scores. The existence of a gap both in mean scores and the variability around the mean is documented and analyzed. The origins of the gap are investigated by looking at wide range of possible explanations.

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).

ObjectivesThis paper estimates associations between long-term exposure to ambient particulate air pollution and 13 self-reported health outcomes including poor general health, chronic illness, experiencing long-running difficulties with breathing, and experiencing frequent periods of confusion or memory loss. It examines the extent to which these associations are explained by confounding factors.
ApproachLongitudinally-linked Census data from the Northern Ireland Longitudinal Study linked to data on annual average particulate (PM2.5) concentrations at the 1km grid-square level over the period 2002-2010, exploiting complete residential histories, are used. The paper controls for potentially confounding factors at the neighbourhood, household and individual level, including for prior health, in a multivariate regression framework. Robustness to the presence of remaining unobserved confounders is assessed in two extensions, first by assuming selection on unobservables is proportional to selection on observables, and second through inclusion of an extensive set of fixed effects in the model.
ResultsThere are strong statistical associations between long-term exposure to ambient particulate pollution and all 13 health outcomes measured by the 2011 Northern Ireland Census. Most of these estimated associations survive conditioning on an extensive set of observable controls. Of these, however, only two associations – with chronic illness and with long-running breathing difficulties, where we might expect the strongest causal effects – survive further analysis designed to elicit robustness to selection on unobservables. The estimated magnitudes of these remaining effects are non-trivial. For example, a 5 µg/m3 difference in particulate exposure averaged over 9 years has a similar magnitude effect on the probability of reporting long-running breathing difficulties as the difference between those aged in their 20s and those in their 40s.
ConclusionsThis study provides evidence of substantial effects of long-term exposure to ambient particulates on the probabilities of experiencing chronic illness and long-running breathing difficulties. These are qualitatively robust to both observed and unobserved confounders. Associations between particulate exposure and other health outcomes in the study are shown to reflect confounders.

ObjectivesThis paper links prescriptions data for the Northern Ireland population with data from the Northern Ireland Longitudinal Study and localized ambient air pollution data from 2002 onwards to estimate the association between long-term exposure to ambient air pollutant from fine particulates (PM2.5) and Parkinson's Disease (PD).
ApproachCox Proportional Hazards models are used to examine the impact of air pollution on PD, first unconditionally, and then conditioning on a rich set of observable individual, family and contextual characteristics. Long-term exposure to PM2.5 is defined as exposure averaged over the previous 5 years. Onset of PD is proxied by first receipt of a prescription for PD medication. Estimates are presented in the form of hazard ratios for the effect of long-term PM2.5 exposure on the risk of PD onset.
ResultsThere is a non-trivial magnitude and statistically significant unconditional association between long-term exposure to ambient PM2.5 pollution and receiving a prescription for PD, with those exposed to higher levels of pollution more likely to receive a prescription for PD. This estimated association disappears (becomes insignificantly different from zero), however, when the model accounts for confounding variables at household, individual and geographical levels.
ConclusionsThis study contributes to an emerging literature examining the association between ambient PM2.5 pollution and onset of PD. Despite finding an unconditional association, we find no evidence for an association once individual, family and contextual characteristics are controlled for, at least in the relatively low-pollution context of Northern Ireland.

This paper links localised annual average ambient air pollution data to a population database of births in Northern Ireland between 2011 and 2017 to investigate the relationship between particulate matter (PM) 2.5 exposure during pregnancy and a range of birth outcomes, with a focus on birth weight.
Linear regression analysis is used to estimate the effect of exposure to PM 2.5 during pregnancy on commonly studied markers of infant health (birth weight, preterm birth), less commonly studied markers such as Apgar scores, and markers of placental health which potentially represent a mechanism through which pollution might negatively affect newborns. In addition to maternal characteristics and weather conditions, detailed adjustment is made for area of residence. Moreover, comparisons of birth outcomes are drawn amongst siblings born at different times and subject to different levels of in utero exposure, permitting adjustment for mother-specific factors common to siblings.
Most birth outcomes exhibit a strong unadjusted association with PM 2.5 exposure that conforms with expectations. For birth weight, the negative effect of PM 2.5 weakens slightly after adjusting for differences in maternal characteristics and weather, but weakens much further after adjusting additionally for area of residence. After adjustment, being born to mothers in the middling (6-10 micrograms per cubic metre) and highest (10-16 micrograms per cubic metre) categories of exposure is associated with a 12 gram and 32 gram reduction in mean birth weight, respectively, compared to being born into the lowest (3-6 micrograms per cubic metre) category. However, after adjusting additionally for mother-specific factors, these effects become statistically no different from zero. This holds for other outcomes, including measures of placental health.
We find little evidence that exposure to PM 2.5 is related to worse infant health once we adjust as fully as possible for omitted variable bias. We conclude that the association between PM 2.5 and birth outcomes in this population at least partly reflects unmeasured characteristics of families.