Book excerpt: In the first chapter we estimate preferences and beliefs of employees on manager gender and quality. If employees do not want to work for female managers, then they would need a wage premium to do so. This would dis-incentivize firm executives to promote or hire females as managers-thus generating glass-ceilings at managerial levels. In order to estimate employee preferences and beliefs, we design and conduct a novel information experiment within a hypothetical job choice survey. In absence of information on manager quality, employees are indifferent between male and female managers. However, given information on manager quality, employees prefer to work for female managers. Hence in the absence of additional information on manager quality, employees believe female managers to be worse in quality. Using a structural model of job choice, we estimate employees are willing to give up 1.3-2.2% of average annual wages to work for female managers, on average. We corroborate the result of negative beliefs regarding female manager quality in an ex-post survey where we directly elicit employee beliefs. The results suggest that glass ceilings for females at the managerial level, driven by discrimination by firm executives-who decide on promotion-could be potentially underestimated.Given that females benefit from toilets in households more than males, the second chapter estimates the impact of increased inheritance rights of females on the presence of a toilet in the household. Daughters being usually married away to the household of the groom, available data do not have all original household characteristics, which determines treatment eligibility. Under generic assumptions, we show that when the treatment is partially observed to the researcher, we can derive a lower bound on the average treatment effect in a difference-in-differences framework. We estimate that the policy increased the probability of the presence of a toilet in the household a woman is married into, by at least 4.3% points. We also uncover heterogeneous treatment effects by the age of the daughter at the time of policy implementation and find the treatment effect to be the largest for the females who were the youngest when the policy was implemented.