I use data from the National Football League (NFL) to analyze the impact of minimum salaries on an employee’s firm tenure, an employee’s career length, and an employer’s distribution of employee experience. The NFL has a salary structure in which the minimum salary a player can receive increases with the player’s years of experience. Salary schedules similar to the NFL’s exist in public education, Secret Service, Internal Revenue Service, other federal government agencies, the Episcopalian church, and unionized industries. Even though the magnitude of the salaries in the NFL differs from other industries, this study provides insight to the impact of this type of salary structure firm tenure, career length, and the experience distribution. In the first essay, I analyze the impact of minimum salaries on firm tenure and career length for six positional groups in the NFL, defensive backs, defensive linemen, linebackers, running backs, tight ends, and wide receivers. A major advantage of using NFL data is that I am able to control for a player’s productivity. I find statistically significant evidence that minimum salaries shorten firm tenure and career length when they require teams to increase a player’s base salary from year t to year t+1 or a player’s total compensation from year t to year t+1. In the second essay, I analyze the impact of minimum salaries on the experience distribution. I exploit the fact that the NFL’s minimum salary schedule causes the relative minimum price between two experience levels to change over time. This provides teams with an incentive to substitute away from the experience level whose relative minimum price becomes more expensive. I find evidence that when relative minimum prices change, the experience distribution changes.

This dissertation is a historically comparative study of adult mortality between Taiwan and the United States throughout the 20th century. The 20th century was characterized by the largest rise in life expectancy at birth and the most rapid decrease in mortality in recorded human history. This dissertation aims not only to examine and compare the trends and levels of life expectancy in Taiwan and the United States over an extended period of time, but also to evaluate the extent to which smoking behavior and obesity play an important role in the recent levels of adult mortality in the United States. I used logistic models of mortality to examine and compare the trends and levels of life expectancy in Taiwan from 1906 to 2008 and in the United States from 1933 to 2007. Second, I re-estimated life expectancy by introducing smoking-attributable mortality to further compare the levels of life expectancy between the two countries. Third, I estimated event history models to investigate whether and how smoking behavior and obesity are related to mortality in the United States in the 1990 to 2006 and the 2000 to 2006 periods. At the end of the 20th century, the level of life expectancy at birth for females in the U.S. was higher than in Taiwan, but they were close. In this century, however, the level of life expectancy at birth in Taiwan has increased to a higher level than in the U.S. The levels of male life expectancy at birth for the two countries are similar in this century, but there were significant differences in the 20th century. The great improvements in juvenile, background and senescent mortality rates in Taiwan may be used to explain this correspondence of life expectancy between the two countries today. Besides, higher smoking-attributed mortality can also serve as another possible reason for the stagnant levels of life expectancy in the U.S. Finally, smoking-related and obesity-related mortality have become progressively more important as predictors of adult mortality in the U.S. in past decades.

This thesis explores the concepts and measurements of chronic poverty, with application to Kazakhstan. A rigorous analysis of different approaches in the measurement of poverty and chronic poverty is presented in this study. Five matching techniques have been applied for the construction of unintended panel data based on KHBS 2001-2009. The substantial test of reliability, representativeness and robustness of the constructed panel data has examined. The attrition biases of the longitudinal data have been studied rigorously. The appropriate equivalence scale has been determined through regression analysis to the Kazakhstan HBS. The sensitivity of conventional and chronic poverty measures to various poverty lines and equivalence scales studied in this thesis. The stochastic dominance analysis of per adult equivalent consumption expenditures has been presented. The chronic poverty measures and determinants of chronically and transient poor have been estimated. It illustrates that the main correlates of chronic poverty are education, employment status of the head of household, household composition, the ownership of assets such as a dwelling other than main dwelling, a car, access to water in the house and location. The correlates of transient poverty are similar to chronic poverty; however some of them have opposite signs, for example the ethnicity of the head of household, household compositions, an ownership of a dwelling other than main dwelling, location in urban area and repayments of loan in 2008. The Oaxaca-Blinder decomposition analysis of the gap in consumption expenditures between chronically and transient poor, chronically poor and non-poor explains the differences through returns to endowments. Poverty transitions analysis illustrate improvement in poverty dynamics in later period of the study in 2006-2009. Long durations of poverty prevail among singles with children and couples with children. Poverty exit rates are higher than poverty entry rates for the whole period of 2001-2009. The multivariate hazard regression models are estimated to examine differences in people's experience of poverty over a period of time. For individuals who enter poverty, the total span of time that they spend in poverty consequently depends on both the chances of exit from poverty and the chances of re-entry to poverty. The results confirm the negative duration dependence of the hazards of poverty exit and re-entry for longer lengths of state. The only factor significantly positive influence on poverty exit is a location in Almaty. Many correlates of the model estimation have the same signs for the hazard rate of poverty exit and re-entries. These facts mean that these factors are common for transient poor, who are moving in and out poverty in given period of time. As defined before the existence of children under age six will increase the hazard rate of poverty re-entry.

This study examines the pattern of unemployment duration of African immigrants in Sweden as well as the effect of emigration origin, age, gender, level of education and family characteristics on the probability of getting a job upon arrival. The study is based on PLACE-database; the dataset is restricted to individuals born in Africa who immigrated to Sweden during the period of 1994-2008. Results from the Kaplan–Meier estimators and Proportional Hazard Models indicate that unemployment duration and the relative risk of getting a job upon arrival vary according to emigration origin and gender differences. In fact, immigrants from Somalia experience longer unemployment duration than Sub Saharan and North African immigrants. Additionally, African women are more likely to experience longer unemployment duration in comparison to men. Women from Sub Saharan Africa experience shorter unemployment duration in comparison to Somalis and North African ones. On the contrary, there are North African men who experience shorter unemployment duration than men from Sub- Saharan African and Somalia. The results also indicate that the relative risk of leaving unemployment upon arrival also differ by gender and region of emigration. In fact, men experience higher relative risk of leaving unemployment in comparison to women. In addition, the gender gap is found to be much more remarkable among the North African immigrants in comparison to Somalis and Sub Saharan ones. Furthermore, the possibility of leaving unemployment upon arrival decreases with age and childbearing, moreover holding university education increases the relative risk of leaving unemployment upon arrival.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18574号 / 工博第3935号 / 新制||工||1605(附属図書館) / 31474 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 大津 宏康, 教授 河野 広隆, 教授 清野 純史 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第19291号 / 工博第4088号 / 新制||工||1630(附属図書館) / 32293 / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小林 潔司, 教授 大津 宏康, 准教授 松島 格也 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The advancement in data acquiring technology continues to see survival data sets with many covariates. This has posed a new challenge for researchers in identifying important covariates for inference and prediction for a time-to-event response variable. In this dissertation, common Cox proportional hazards model selection techniques and a random survival forest technique were compared using five performance criteria measures. These performance measures were concordance index, integrated area under the curve, and , and R2 . To carry out this exercise, a multicentre clinical trial data set was used. A simulation study was also implemented for this comparison. To develop a Cox proportional model, a training dataset of 75% of the observations was used and the model selection techniques were implemented to select covariates. Full Cox PH models containing all covariates were also incorporated for analysis for both the clinical trial data set and simulations. The clinical trial data set showed that the full model and forward selection technique performed better with the performance metrics employed, though they do not reduce the complexity of the model as much as the Lasso technique does. The simulation studies also showed that the full model performed better than the other techniques, with the Lasso technique overpenalising the model from the simulation with the smaller data set and many covariates. AIC and BIC were less effective in computation than the rest of the variable selection techniques, but effectively reduced model complexity than their counterparts for the simulations. The integrated area under the curve was the performance metric of choice for choosing the final model for analysis on the real data set. This performance metric gave more efficient outcomes unlike the other metrics on all selection techniques. This dissertation hence showed that variable selection techniques differ according to the study design of the research as well as the performance measure used. Hence, to have a good model, it is important to not use a model selection technique in isolation. There is therefore need for further research and publish techniques that work generally well for different study designs to make the process shorter for most researchers.

Indiana University-Purdue University Indianapolis (IUPUI) / Background: Tobacco use is associated with an increased risk of developing Alzheimer's disease (AD). 14% of the incidence of AD is associated with various types of tobacco exposure. Additional real-world evidence is warranted to reveal the association between tobacco use and AD in age/gender-specific subpopulations. Method: In this thesis, the relationships between diagnoses related to tobacco use and diagnoses of AD in gender- and age-specific subgroups were investigated, using health information exchange data. The non-parametric Kaplan-Meier method was used to estimate the incidence of AD. Furthermore, the log-rank test was used to compare incidence between individuals with and without tobacco related diagnoses. In addition, we used semi-parametric Cox models to examine the association between tobacco related diagnoses and diagnoses of AD, while adjusting covariates. Results: Tobacco related diagnosis was associated with increased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 60-74 years (female hazard ratio [HR] =1.26, 95% confidence interval [CI]: 1.07 – 1.48, p-value = 0.005; and male HR =1.33, 95% CI: 1.10 - 1.62, p-value =0.004). Tobacco related diagnosis was associated with decreased risk of developing AD comparing to no tobacco related diagnosis among individuals aged 75-100 years (female HR =0.79, 95% CI: 0.70 - 0.89, p-value =0.001; and male HR =0.90, 95% CI: 0.82 - 0.99, p-value =0.023). Conclusion: Individuals with tobacco related diagnoses were associated with an increased risk of developing AD in older adults aged 60-75 years. Among older adults aged 75-100 years, individuals with tobacco related diagnoses were associated with a decreased risk of developing AD.

Indiana University-Purdue University Indianapolis (IUPUI) / The counting process is the fundamental of many real-world problems with event data. Poisson process, used as the background intensity of Hawkes process, is the most commonly used point process. The Hawkes process, a self-exciting point process fits to temporal event data, spatial-temporal event data, and event data with covariates. We study the Hawkes process that fits to heterogeneous drug overdose data via a novel semi-parametric approach. The counting process is also related to survival data based on the fact that they both study the occurrences of events over time. We fit a Cox model to temporal event data with a large corpus that is processed into high dimensional covariates. We study the significant features that influence the intensity of events.

Introdução: As técnicas mais comumente empregadas em análise de sobrevida que utilizam dados censurados são o estimador produto limite de Kaplan-Meier (KM) e o modelo de riscos proporcionais de Cox. Estas técnicas têm como suposição que a causa da perda de seguimento seja independente do tempo de sobrevida. Objetivo: O presente estudo visa a analisar o efeito das perdas de seguimento nestas duas técnicas. Material e Métodos: O estudo foi realizado utilizando-se o banco de dados dos pacientes cadastrados no Registro Hospitalar do Hospital do Câncer de São Paulo em 1994. Foram elaborados 28 bancos de dados simulando perdas informativas e não informativas. A perda informativa foi simulada transformando os óbitos em vivos, na proporção de 5 a 50%. A perda não informativa foi simulada através do sorteio de 5 a 50% do total do banco. O estimador de Kaplan-Meier (KM) foi utilizado para estimar a sobrevida acumulada no primeiro, terceiro e quinto ano de seguimento, e o modelo de riscos proporcionais de Cox para estimar as hazard ratio (HR). Todas as estimativas obtidas no KM e as HR's foram comparadas com os resultados do banco de dados original. Resultados: Houve maior proporção de perda nos pacientes com maior escolaridade, admitidos por convênio e particular e os menos graves (estádio I ou II). Quanto maior a proporção de perda informativa, maior a diferença alcançada nas estimativas realizadas pelo KM, verificando-se que a perda de seguimento superior a 15% acarretou diferenças superiores a 20% nas estimativas da probabilidade de sobrevida. As HR's foram menos afetadas, e proporções superiores a 20% de perda de seguimento acarretaram variações de cerca de 10% nas estimativas. Quando as perdas foram não informativas não houve diferenças significativas nas estimativas pelo KM e nas HR's em relação ao banco original. Conclusões: É importante avaliar se as perdas ocorridas em estudos de coorte são informativas ou não, pois se forem podem acarretar distorções principalmente nas estimativas feitas pelo método de KM. / Introduction: The Kaplan Meier product limit estimator (KM) and the Cox proportional hazard (HR) model are the most used tools in survival analysis. These two methods have the key assumption that censoring must be independent from the survival time. Objective: To analyze the consequences of loss to follow up in these two methods. Methods: The study has utilized the data of the Cancer Registry of the patients of Hospital do Cancer in São Paulo of 1994. The informative censure was simulated transforming the death by 5 to 50% into alive. Besides 5 to 50% was spared at random simulating the non-informative censoring. The survival probability and was calculated to the first, third and fifth year of follow –up. All the estimated probabilities and HR’s were compared with the results of the original data. Results: Patients with greater scholars, lower stages and admitted by health plans or private had more losses to follow up. The maximum proportion of accepted loss to follow –up is 10% to 15% when using the KM estimator, and the HR are less affected by the loss to follow-up and one can afford having 20% of it. When the losses were non informative there were no differences between the original probabilities. Conclusions: The possibility of over or under estimated probability must be analyzed in the presence of the losses to follow- up when using the KM and HR in survival analyses.