Introduction: The prevalence of bad perceived health status and depression, their sociodemographic determinants (education level, employment status, relative household income, race, age and gender) and the modifying effect of depression on PHS have been investigated among a cohort of young adults using data from the South African National Income Dynamics Study (NIDS) waves 1-5. South Africa is a middle-income country, with very high levels of socioeconomic inequality and a history of apartheid. Both depression and PHS tend to be affected by socio-demographic and environmental factors. Methods: Depression was measured using the CES-D-10 scale and PHS was measured on a 5- point likert scale ranging from excellent to poor. A binary version of PHS was generated which groups the categories excellent, very good and good into good and the categories poor and fair into bad PHS. Descriptive analysis and Mixed Effects Regression analysis were conducted. MER is appropriate for unbalanced panels as this method is robust to irregularly spaced measurements. Results: A high prevalence of depression was found in the study with about 13%-20% of the cohort being depressed at each wave. Surprisingly, a low level of bad PHS has been found in the cohort with less than 5% of the young adults having bad PHS at all waves. Completion of secondary and tertiary education and being employed have been found to significantly lower the odds of being depressed and increase the chances of having good PHS. Africans were significantly more likely to be depressed, as compared to other racial groups. Finally, being depressed was found to reduce the likelihood of good PHS. Discussion: Education level completed and being employed have been found to significantly protect individuals from being depressed and to increase the likelihood of good PHS. In post-apartheid South Africa, the effects of inequalities arising from apartheid social and economic policies are still present with Africans being found more likely to be depressed.

This dissertation consists of three chapters. The first chapter addresses the roles of changes in assisted reproductive technologies, returns to female experience and abortion rates in explaining the historical trend of child adoption. The second chapter assesses the effects of increased income inequality and decreased income mobility on timing of births and marriages and on the single motherhood rates. The third chapter establishes the importance of accounting for marital state in the models of indirect income uncertainty inference. Chapter 1 aims to explain the μ-shaped historical trend of child adoption in the US by emphasizing the role of the changes in the demand side of the market for child adoption. I argue that changes on the demand side such as increasing returns to female human capital and innovations in Assisted Reproductive Technology (ART) have played a major role in shaping the historical adoption trend along with the changes in the supply side, namely, increase in the abortion rates. I present a life-cycle model, in which an agent makes a fertility-timing decision based on the returns to her human capital and age-specific probability of conception. Under the assumption that adoption is an alternative to childbearing, i.e. an agent chooses to adopt after she fails to conceive, the presented model uses historical trends of returns to human capital and success rate of ART to explain changes in adoption trends. According to the model, increasing returns to female human capital were responsible for the delay in childbearing and therefore the increase in the demand for adoption until the 1970s. After 1970, the legalization of abortion decreased the supply of orphans, while innovations in ART decreased the demand by allowing women to have biological children at later ages. Around 1980, the effect of increasing returns to human capital overturned the one of advances in ART, which resulted in a slow recovery of the adoption trend. Chapter 2 studies the dramatic transformation that the typical American family has undergone since the 1950s. Marriage and fertility have been delayed, while single-motherhood rates have increased. The link between these facts emanates from the greater delay in marriage than that in first births. As “the Gap” between the age at first birth and the age at first marriage becomes negative for some women, out-of-wedlock first births increase. In my analyses, I focus on the increase in income inequality and the decrease in income mobility --- observed across two National Longitudinal Survey of Youth (NLSY) cohorts of women --- to account for the above facts using an equilibrium two-sided search framework in which agents make marriage and fertility choices over the life-cycle. Marriage is a commitment device for consumption-sharing, providing spouses with partial insurance against idiosyncratic earnings risk. Agents derive utility from children, but children also involve a risky commitment to future monetary and time costs. According to my model, two observed trends in the income process produce these changes in the respective timings of marriage and fertility. First, the increase in income inequality produces incentives to delay marriage. Since single women tend to face higher income risk than do married women, all else being equal, a decline in marriages when young implies delayed births, which are perceived to be risky. Second, the decrease in income mobility also delays marriage as the insurance value of marriage decreases but accelerates fertility because it becomes less risky to have a child. The model qualitatively matches the observed changes in family formation and quantitatively accounts for a significant portion of the observed changes in marriage and fertility timing between the two NLSY cohorts. In Chapter 3 I aim to add to the indirect income uncertainty inference literature. The currently existing models used to infer earnings uncertainty from consumption decisions of individuals either use married couples as a unit of analysis or treat married individuals as singles. Income pooling and less than perfect correlation of earnings in marital unions provide spouses with marital income insurance. Not accounting for the marital insurance biases the uncertainty estimation results. In this chapter, I demonstrate some properties of the marital insurance bias in a stylized analytical model. In order to access the potential magnitude of the marital bias, I build a structural model which accounts for marital insurance. I then compare the estimation results of the model which accounts for marriage with the results of one that does not after using them on the simulated data set. In addition, I introduce a non-parametric income process in the structural model used for the indirect uncertainty inference. The main advantage of the resulting model is that, unlike the typical models in this area, it can be used on short-term panel data.

Magister Commercii - MCom / There have been many studies focussing on informal sector in South Africa in the last 25 years. This paper adds to the wealth of research that has been conducted in this field. It examines the linkages between the formal sector and informal sector, and how they interact with each other. The study uses probit models and fixed effects models to investigate how variables such as age, education and skill level affect employability and income in the labour market. This paper uses two data sets: wave 1 to wave 5 panel data of the 2008-2016 National Income Dynamics Study (NIDS) to investigate the nature of the formal sector and the informal sector in South Africa. To study the linkages between the firms in the formal and informal sector, it uses the eThekwini Large and Medium Manufacturing Firm Survey dataset collected in 2013/2014.

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I explore the relationship between quality of maternal employment and children’s reading achievement between six to thirteen years of age using data from the Panel Study of Income Dynamics. The hypotheses assert that job quality in terms of level of autonomy, supervisory power, complexity with people, data and things, and family benefits have significant positive effects on children’s reading achievement. The least squares estimates indicate that complexity, power, and autonomy has significant positive effects for children while the effects of family benefits is weak with the exception of the positive effect of union membership for racially disadvantaged groups.

<p>Socioeconomic inequalities in health research comprises the investigation of the pathways through which differential access to resources affects the distribution of morbidity and mortality in the population. Because many of the factors that influence health are cumulative, researchers have incorporated a life course approach into their work by linking socioeconomic conditions in one stage of the life course to health at a later stage. The childhood period has acquired particular significance due to conflicting theories about the relative importance of early life events for health inequalities during adulthood.</p> <p>Using seven waves of the child component of the National Longitudinal Study of Youth (1986-98), I employ generalized linear mixed models to examine the effect of household income on child physical and mental health over the entire childhood period. The results of this dissertation support the hypothesis that household income influences the physical and mental health of children, both concurrently and over time. In generalized linear mixed models, the stable component of household income, that is, the average household income for a given child over the period in which he or she is observed, exerts a strong influence on risk for child chronic health limitation, child anxiety/depression and antisocial behaviour, and to a lesser extent, child medically attended accident or injury. However, the dynamic component of household income, defined as deviations in household income over time from the observed average of that household, is mostly unrelated to child health.</p> <p>These findings have broader implications for life course theory and for the discipline of sociology as health inequalities researchers track the impact of socially significant events over time and reveal the long term processes underlying the social distribution of health.</p> / Doctor of Philosophy (PhD)

Schools, families, and neighborhoods can support the development of happy, healthy children and adolescents. However, a majority of children in the United States also experience adversity in their early lives that can have deleterious effects on their cognitive and socioemotional development. Measuring and modeling early adversity is fundamental to understanding development as it occurs through interactions with schools, families and neighborhoods. As outlined by Bronfenbrenner's bioecological model of human development, proximal and distal forces shape development, and cannot be isolated when relating measures of the developmental context to outcomes for individuals. For schools and other social programs to support students from high adversity backgrounds, the nature and structure of adversity and contextual influences must be measured and modeled in a robust manner. The three distinct papers in this dissertation describe the construction and evaluation of measurements for adversity, family conflict, neighborhood quality, and school safety, along with models that relate these elements to each other and cognitive outcomes in childhood and adolescence. Structural equation modeling is used to investigate the latent variables generated to measure the constructs and the nature of their relationships. The studies use nationally representative data from the Panel Study of Income Dynamics to create and test the theoretically driven models. The first study constructs and tests latent variables aligned with the Adverse Childhood Experiences (ACEs) framework in order to generate a continuous and theoretically coherent measurement of adversity. The second study uses this ACEs measurement along with measures of family conflict and neighborhood quality to generate and test path models informed by the bioecological theory of development. The third study applies these measures of developmental constructs to the study of safety in schools and identifies the differential function of school safety for children with varying levels of adversity to better understand the potential for school-based interventions. Results from these studies indicate the utility of a latent variable approach to measuring adversity, and the viability of path analysis for the study of how ACEs, family conflict and neighborhood quality influence cognitive outcomes. Additionally, results provide evidence for the necessity of varied and networked developmental supports for children from highly adverse beginnings, above those that may be available through reforms to school safety. Taken together, these studies provide a rich portrait of childhood development incorporating multiple contextual influences, and add to our understanding of what schools can and cannot do to support children.

The major goal of this study is to test the direction and strength of the relations of low-income single mothers’ depressive symptoms to their employment and income experiences over a time period following major welfare policy changes in the U.S. (2001 to 2003). The Panel Study of Income Dynamics provided data on 623 low-income, single mothers. The economic characteristics studied were: employment status, hours of work, wages, earnings, a job’s provision of personal control, family income, and welfare receipt. The mental health measure was the K-6 Non-Specific Psychological Distress Scale. The study adds to our understanding of the temporal relations between employment experiences and mental health by testing the social causation, social selection, and interactionist (bidirectional) perspectives. Specifically, this study tested the different perspectives with a wide range of economic indicators, tested mechanisms that may link mental and economic well-being, and combined multiple employment factors to see if patterns emerged that related uniquely to psychological distress. The findings supported social selection as earlier psychological distress predicted future employment, hours, wages, earnings, household income, and welfare receipt. The tested mediator of days of lost work affected by psychological distress indicated an indirect effect of poor mental health predicting diminished job productivity that, in turn, predicted reduced employment, hours, wages, and earnings. Results were similar for subgroups of mothers based on the age of their youngest child or prior welfare history. The single significant finding was that a longer span of welfare receipt predicted worse mental health as compared to mothers who reported a shorter period of welfare receipt. Latent class analysis identified three patterns of employment and welfare receipt across time: a) exchanged earnings for welfare, b) high employment and earnings growth with reduced welfare, and c) moderate employment growth. The groups that exchanged earnings for welfare (about 10% of the sample) evidenced increased psychological distress compared to mothers with high or moderate employment growth. Support for the social selection hypothesis suggests that policies and interventions that help low-income mothers improve their psychological well-being could also enhance their economic well-being. Implications for future research could explore the effects of such policies. / text

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Avec la vague des départs à la retraite amorcée par la génération des baby-boomers, le marché du travail canadien traversera inéluctablement une période de transition. Le vide laissé par ces départs obligera de nombreuses industries à réajuster leur tir afin de ne pas être secouées par de trop fortes turbulences. À cet effet, l’impact des retraites n’aura pas la même ampleur pour chacune des branches d’activité. S’appuyant sur les données longitudinales de l’Enquête sur la dynamique du travail et du revenu de 1993 à 2010, cette recherche analyse les tendances au fil du temps et entre les industries en regard des départs d’emploi de carrière. Une attention particulière est aussi portée aux emplois de transition selon le secteur d’activité, afin de déterminer si cette pratique peut amoindrir les répercussions des départs d’emploi de carrière. Les résultats montrent que l’intensité des départs d’emploi de carrière s’accroit au cours de la période considérée et que d’importantes variations existent entre les travailleurs des diverses catégories d’industries examinées. L’industrie des services professionnels, scientifiques et techniques affiche la plus faible proportion de travailleurs ayant quitté un emploi de carrière (26 %). À l’autre extrémité du spectre, les travailleurs du secteur de l’hébergement et des services de restauration présentent la plus forte probabilité d’effectuer un départ d’emploi de carrière (47 %). Au chapitre des emplois de transition, les travailleurs en provenance l’industrie de la construction montrent la plus forte propension à oeuvrer au sein d’un tel type d’emploi. Si certaines industries se démarquent des autres, cela s’explique surtout en raison du comportement différentiel des travailleurs les plus âgés (55 à 64 ans). / With the Baby-boom generation entering upon a retirement wave, the Canadian labour force will ineluctably go through a transition period. Those departures will leave a vacuum that will force many industries to readjust in order to avoid heavy turbulences. The impact of the retirement wave will not have the same impact for each of the industries. Using longitudinal data from the Survey of Labour and Income Dynamics for years 1993 to 2010, this study analyzes trends over time and across industries regarding workers leaving a career job. A particular attention will also be paid to bridge jobs by industry, in order to determine if this type of work may lessen the effects of the loss of many career jobs. The results show that workers are increasingly leaving career jobs during the period under review and that considerable variations exist between workers of various industries. The industry of Professional, Scientific and Technical Services shows the smallest proportion of workers that have left a career job (26%). Conversely, the highest probability of leaving a career job was recorded among workers of the Accommodation and Food Services industry (47%). Regarding bridge jobs, workers coming from the Construction industry have the greatest propensity to start such a type of work after leaving a career job. If some industries stand out from all the others, this is largely attributable to the distinct behaviour of the eldest workers (55 to 64 years old).