A hazard model of the probability of medical school dropout in the United Kingdom

From individual level longitudinal data for two entire cohorts of medical students in UK universities, we use multilevel models to analyse the probability that an individual student will drop out of medical school. We find that academic preparedness—both in terms of previous subjects studied and levels of attainment therein—is the major influence on withdrawal by medical students. Additionally, males and more mature students are more likely to withdraw than females or younger students respectively. We find evidence that the factors influencing the decision to transfer course differ from those affecting the decision to drop out for other reasons

Sibling death clustering in India : genuine scarring vs unobserved heterogeneity

Data from a range of environments indicate that the incidence of death is not randomly distributed across families but, rather, that there is a clustering of death among siblings. A natural explanation of this would be that there are (observed or unobserved) differences across families, e.g. in genetic frailty, education or living standards. Another hypothesis that is of considerable interest for both theory and policy is that there is a causal process whereby the death of a child influences the risk of death of the succeeding child in the family. Drawing language from the literature on the economics of unemployment, the causal effect is referred to here as state dependence (or scarring). The paper investigates the extent of state dependence in India, distinguishing this from family level risk factors that are common to siblings. It offers some methodological innovations on previous research. Estimates are obtained for each of three Indian states, which exhibit dramatic differences in socio-economic and demographic variables. The results suggest a significant degree of state dependence in each of the three regions. Eliminating scarring, it is estimated, would reduce the incidence of infant mortality (among children who are born after the first child) by 9.8% in the state of Uttar Pradesh, 6.0% in West Bengal and 5.9% in Kerala

How does the benefit effect vary as unemployment spells lengthen?

SIGLEAvailable from British Library Document Supply Centre- DSC:9261.96(375) / BLDSC - British Library Document Supply CentreGBUnited Kingdo