資本資產定價模型 (CAPM) 由Sharp (1964)、Lintner (1965)及Black (1972)發展出後，近年來已被廣泛的應用於衡量證券之預期報酬率與風險間之關係。一般而言，衡量結果之估計有兩個階段，首先由時間序列分析估計出貝它(beta)係數，然後再檢定廠商或投資組合之平均報酬率與貝它係數之關係。 Fama與MacBeth (1973)利用最小平方法估計貝它係數，再將由橫斷面迴歸方法所得出之斜率係數加以平均後，以統計t-test檢定之。然而以最小平方法估計係數，其估計值很容易受離群值之影響，因此本研究考慮以穩健估計 (robust estimator)來避免此一問題。另外，本研究亦將長期資料分析 (longitudinal data analysis) 引入CAPM裡，期望能檢定貝它係數是否能確實有效地衡量出系統性風險。 論文中以台灣股票市場電子業之實證分析來比較上述不同方法對CAPM的結果，資料蒐集期間為1998年9月至2001年12月之月資料。研究結果顯示出，穩健估計相對於最小平方法就CAPM有較佳的解釋力。而長期資料分析模型更用來衡量債券之超額報酬部分，是否會依上、中、下游或公司之不同而不同。 / The Capital Asset Pricing Model (CAPM) of Sharp (1964), Lintner (1965) and Black (1972) has been widely used in measuring the relationship between the expected return on a security and its risk in the recent years. It consists of two stages to estimate the relationship between risk and expected return. The first one is that betas are estimated from time series regressions, and the second is that the relationship between mean returns and betas is tested across firms or portfolios. Fama and MacBeth (1973) first used ordinary least squares (OLS) to estimate beta and took time series averages of the slope coefficients from monthly cross-sectional regressions in such studies. However it is well known that OLS is sensitive to outliers. Therefore, robust estimators are employed to avoid the problems. Furthermore, the longitudinal data analysis is applied to examine whether betas over time and securities are the valid measure of risk in the CAPM. An empirical study is carried out to present the different approaches. We use the data about the Information and Electronic industry in Taiwan stock market during the period from September 1998 to December 2001. For the time series regression analysis, the robust methods lead to more explanatory power than the OLS results. The linear mixed-effect model is used to examine the effects of different streams and companies for the security excess returns in these data.

In this paper, I analyze the effectiveness of state level Earned Income Tax Credit programs on improving of poverty levels. I conducted this analysis for the years 1991 through 2011 using a panel data model with fixed effects. The main independent variables of interest were the state and federal EITC rates, minimum wage, gross state product, population, and unemployment all by state. I determined increases to the state EITC rates provided only a slight decrease to both the overall white below-poverty population and the corresponding white childhood population under 18, while both the overall and the under-18 black population for this category realized moderate decreases in their poverty rates for the same time period. I also provide a comparison of the effectiveness of the state level EITCs and minimum wage at the state level over the same time period on these select demographic groups.

Diabetes is a major risk factor for the development of cataract [3,14,20,22]. In this thesis, we create a model that allows us to understand the incidence of one disease in the context of another; in particular, cataract in the presence of diabetes. The World Health Organization's Vision 2020 blindness-prevention initiative administers surgeries to remove cataracts, the leading cause of blindness worldwide [24]. One of the geographic areas most impacted by cataract-related blindness is Sub-Saharan Africa. In order to plan the number of surgeries to administer, the World Health Organization uses data on cataract prevalence. However, an estimation of the incidence of cataract is more useful than prevalence data for the purpose of resource planning. In 2012, Dray and Williams developed a method for estimating incidence based on prevalence data [5]. Incidence estimates can be further refined by considering associated risk factors such as diabetes. We therefore extend the Dray and Williams model to include diabetes prevalence when calculating cataract incidence estimates. We explore two possible approaches to our model construction, one a detailed extension, and the other, a simplification of that extension. We provide a discussion comparing the two approaches.

Researchers use natural phenomena in a number of disciplines to help explain human behavioral outcomes. Research regarding the potential effects of magnetic fields on animal and human behavior indicates that fields could influence outcomes of interest to social scientists. Tests so far have been limited in scope. This work is a preliminary evaluation of whether the earth’s magnetic field influences human behavior it examines the baseline relationship exhibited between geomagnetic readings and a host of social and political outcomes. The emphasis on breadth of topical coverage in these statistical trials, rather than on depth of development for any one model, means that evidence is only suggestive – but geomagnetic readings frequently covary with social and political variables in a fashion that seems inexplicable in the absence of a causal relationship. The pattern often holds up in more-elaborate statistical models. Analysis provides compelling evidence that geomagnetic variables furnish valuable information to models. Many researchers are already aware of potential causal mechanisms that link human behavior to geomagnetic levels and this evidence provides a compelling case for continuing to develop the line of research with in-depth, focused analysis.

La majorité des personnes utilisatrices de drogues par injection (PUDI) contracteront le virus de l’hépatite C (VHC), les mettant à risque accru de complications hépatiques graves et parfois mortelles. Les comportements les plus risqués pour l’acquisition du VHC incluent le partage de matériel d’injection et l’injection à haute fréquence. Un facteur jusqu’ici négligé dans l’évaluation du risque de VHC est l’aspect dynamique de l’injection, c.-à-d. la manière dont elle varie dans le temps, incluant l’effet des périodes sans injection et celui des changements dans la fréquence d’injection. On reconnaît également l’effet délétère que l’instabilité résidentielle peut avoir sur le risque de VHC, bien que les mécanismes sous-jacents soient mal compris. Cette thèse s’intéresse à l’effet des variations temporelles de l’injection sur le risque de VHC, et à la manière dont la fréquence d’injection évolue en concomitance avec les conditions résidentielles dans le temps, afin d’aider au développement de nouvelles stratégies de prévention du VHC. Les données ont été recueillies entre mars 2011 et juin 2016 dans la Hepatitis Cohort, une cohorte de PUDI suivies trimestriellement à Montréal, au Québec. Une première analyse a évalué l’effet des périodes sans injection de trois mois ou moins sur le risque de VHC sur 916 personnes-années de suivi, par régression de Cox (N=372). Celle-ci suggère que les PUDI présentant des périodes sans injection courtes (3/3 mois sans injection) et sporadiques (1/3 ou 2/3 mois sans injection) sont respectivement 76% et 44% moins à risque de VHC que celles s’injectant de manière persistante (0/3 mois sans injection). Une deuxième analyse a utilisé la modélisation de trajectoires fondée sur le groupement pour identifier cinq types distincts de trajectoires de fréquence d’injection suivies sur une année, lesquels ont ensuite été comparés en termes d’incidence du VHC sur des périodes de suivi allant de 71 à 355 personnes-années (N=386). Les résultats suggèrent que les PUDI dont la fréquence reste élevée (injection fréquente) ou change dans le temps (croissante, décroissante) sont à plus haut risque de VHC que celles s’injectant à basse fréquence (sporadique, peu fréquente). Une dernière analyse a identifié trois types de trajectoires de stabilité résidentielle suivies sur un an (persistance, déclin, amélioration; N=386), lesquels ont été évalués en association avec les trajectoires de fréquence d’injection suivies simultanément. Les résultats suggèrent qu’il existe un lien entre l’amélioration des conditions résidentielles et la diminution de la fréquence d’injection, mais aussi que la probabilité d’injection à fréquence croissante est plus élevée chez les PUDI maintenant des conditions résidentielles stables que celles chez qui elles s’améliorent. Collectivement, les résultats ont de nombreuses implications en termes de prévention du VHC. Cliniquement, l’instabilité de la fréquence d’injection semble être un facteur de risque à monitorer régulièrement. En termes de santé publique, les interventions favorisant l’engagement dans des périodes sans injection ou le maintien d’une basse fréquence d’injection pourraient être prometteuses. Enfin, les stratégies visant l’amélioration des conditions résidentielles pourraient éventuellement aider les PUDI à réduire leur fréquence d’injection, mais être insuffisantes pour maintenir celle-ci à basse fréquence une fois la stabilité atteinte. / The majority of people who inject drugs (PWID) will become infected with hepatitis C virus (HCV), placing them at risk of serious and sometimes fatal liver complications. Injecting behaviours with higher risk of HCV transmission include injecting equipment sharing and high frequency injecting. One factor that has been overlooked when assessing HCV acquisition risk is the dynamic aspect of drug injecting, i.e., how drug injecting varies over time, including the role of injecting cessation episodes and that of changes in injecting frequency. Moreover, there is growing recognition of the deleterious effect unstable housing can have on HCV acquisition risk, although the underlying mechanisms are not yet fully understood. This thesis examines how temporal variations in drug injecting relate to HCV acquisition risk and further explores how housing conditions and injecting frequency evolve together over time, for the purposes of contributing to the development of novel HCV prevention strategies. Data were collected between March 2011 and June 2016 in the Hepatitis Cohort, a prospective cohort study of PWID interviewed and tested for HCV infection at three-monthly intervals in Montréal, Québec. A first analysis examined the effect of injecting cessation episodes of three months or less on the risk of contracting HCV during 916 person-years of follow-up, using Cox regression (N=372). Results suggest that PWID with short injecting cessation episodes (3/3 months without injecting) or sporadic injecting cessation episodes (1/3 or 2/3 months without injecting) are 76% and 44% less at risk of contracting HCV than those with persistent injecting (0/3 months without injecting), respectively. A second analysis used group-based trajectory modeling to identify five distinct types of one-year injecting frequency trajectories and compared these in terms of HCV incidence over follow-up periods ranging from 71 to 355 person-years (N=386). Findings suggest that PWID injecting with consistently high frequencies (frequent) or time-varying frequencies (increasing, decreasing) are at greater HCV acquisition risk compared with those maintaining low injecting frequencies (sporadic, infrequent). Finally, a third analysis identified three types of one-year housing stability trajectories (sustained, declining, improving) and examined their associations with concomitant injecting frequency trajectories (N=386). Findings suggest an association between improving housing stability and decreasing injecting frequency, but also a higher probability of increasing injecting frequency among PWID who maintain housing stability compared to those that improve it. Collectively, these findings have numerous implications for HCV prevention. Clinically, instability in injecting frequency appears to be a risk factor that should be monitored regularly. From a public health perspective, interventions that promote engagement in injecting cessation episodes or maintenance of low injecting frequency may be promising. Finally, strategies aimed to improve housing stability may help PWID to decrease their injecting frequency but may not be sufficient to help them maintain low injecting frequencies once housing stability is achieved.