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This dissertation seeks to understand two main issues. The first issue concerns changes in the gender gaps in college attendance and choice of majors between 1960 and 2010. The second main issue concerns changes in the marriage rate in the US since the early twentieth century. The main objective of Chapters 1 and 2 is to answer the following two questions about educational choices: Why do women today invest in a college education at much higher rates than men, whereas fifty years ago men graduated more frequently? And given their high college attendance rates today, why do women continue to select disproportionately into lower-paying majors, with almost no gender convergence along this margin since the mid-1980s? In Chapter 1, I document first that changes in returns to skill over time and gender differences in wage premiums across majors cannot explain the observed gender gaps in educational choices. I then provide reduced-form evidence that two factors help explain the observed gender gaps: first, college degrees provide insurance against very low income for women, especially in case of divorce; second, majors differ substantially in the degree of "work-family flexibility" they offer, such as the size of wage penalties for temporary reductions in labor supply. Based on this reduced-form evidence, in Chapter 2 I construct and estimate a dynamic structural model of marriage, educational choices, and lifetime labor supply. I use the model to analyze the contribution of changes in wages and changes in the marriage market to the observed educational investment patterns over time. I estimate that the insurance value of the college degree for women in case of divorce is equivalent to about 31\% of the college wage premium. I also estimate that the share of women choosing high-return science and business majors would increase from 34\% to 45\% if wage penalties for labor supply reductions were equalized across occupations. Finally, I test the effects of two sets of policies on individuals' choice of major: a differential tuition policy that charges less for science and technical majors, as has been proposed in some states; and interventions intended to improve work-family flexibility. My results show that some family-friendly policies increase the share of women in science and business majors substantially, while others further widen both college gender gaps.Chapter 3, joint work with Maurizio Mazzocco, analyzes changes in U.S. marriage rates over nearly a century. We propose an explanation for these changes in three stages. First, we show that changes in cohort size alone can account for around 50 to 70\% of the variation in marriage rates since the 1930s for both black and white populations. Specifically, increases in cohort size reduce marriage rates, whereas declines in cohort size have the opposite effect. Using plausibly exogenous variation in access to oral contraceptives, and consequently the number of births, across states we provide evidence that the relationship between changes in cohort size and changes in marriage rates is causal. Next, we develop a dynamic search model of the marriage market that qualitatively generates this observed relationship, and derive a testable implication about cohort size's effect on spouses' age differences. Finally, we estimate the model and investigate its consistency with the data. We fail to reject it using the derived implication, and find that it can quantitatively explain much of the observed variation in marriage rates.

Christine Toye,1 Susan Slatyer,2 Su Kitchen,3 Katharine Ingram,4 Mary Bronson,5 Deborah Edwards,6 Welma van Schalkwyk,7 Catherine Pienaar,8 Philippa Wharton,9 Chrianna Bharat,10 Keith D Hill11 1School of Nursing, Midwifery and Paramedicine, Curtin University, Perth, Western Australia 6102, Australia, Centre for Nursing Research, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 2Discipline of Nursing, College of Science, Health, Engineering & Education, Murdoch University, Perth, Western Australia 6150, Australia, Centre for Nursing Research, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 3Clinical Lead and Clinical Nurse Consultant in Falls Management, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 4Consultant Geriatrician, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 5Deputy Nurse Co Director, Medical Division, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 6Occupational Therapy Coordinator, Acute Services Emergency Department, Sir Charles Gardiner Hospital, Perth, Western Australia 6009, Australia; 7Registered Nurse, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 8Project Officer, Nursing Research, Perth Children’s Hospital and Murdoch University, Perth, Western Australia 6009, Australia; 9Project Officer, Centre for Nursing Research, Sir Charles Gairdner Hospital, Perth, Western Australia 6009, Australia; 10National Drug and Alcohol Research Centre, UNSW Sydney, Sydney, New South Wales 2006, Australia; 11Rehabilitation, Ageing and Independent Living (RAIL) Research Centre, Monash University, Frankston, Victoria 3199, AustraliaCorrespondence: Christine ToyeSchool of Nursing, Midwifery and Paramedicine, Curtin University, Perth, Western Australia 6102, AustraliaTel +61 8 9266 1756Email c.toye@curtin.edu.auBackground: Falls remain an important problem for older people in hospital, particularly those with high falls risk. This mixed methods study investigated the association between multiple bed moves and falls during hospitalisation of older patients identified as a fall risk, as well as safety of ward environments, and staff person-centredness and level of inter-professional collaboration.Methods: Patients aged ≥70 years, admitted through the Emergency Department (ED) and identified at high fall risk, who were admitted to four target medical wards, were followed until discharge or transfer to a non-study ward. Hospital administrative data (falls, length of stay [LoS], and bed moves) were collected. Ward environmental safety audits were conducted on the four wards, and staff completed person-centredness of care, and interprofessional collaboration surveys. Staff focus groups and patient interviews provided additional qualitative data about bed moves.Results: From 486 ED tracked admissions, 397 patient records were included in comparisons between those who fell and those who did not [27 fallers/370 non-fallers (mean 84.8 years, SD 7.2; 57.4% female)]. During hospitalisation, patients experienced one to eight bed moves (mean 2.0, SD 1.2). After adjusting for LoS, the number of bed moves after the move to the initial admitting ward was significantly associated with experiencing a fall (OR 1.56, 95% CI 1.11–2.18). Ward environments had relatively few falls hazards identified, and staff surveys indicated components of person-centredness of care and interprofessional collaboration were rated as good overall, and comparable to other reported hospital data. Staff focus groups identified poor communication between discharging and admitting wards, and staff time pressures around bed moves as factors potentially increasing falls risk for involved patients. Patients reported bed moves increased their stress during an already challenging time.Conclusion: Patients who are at high risk for falls admitted to hospital have an increased risk of falling associated with every additional bed move. Strategies are needed to minimise bed moves for patients who are at high risk for falls.Keywords: inpatient, adverse events, older adults, falls, bed moves