<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>

[pt] Desde o trabalho seminal de Modigliani e Miller (1961), muito se aprendeu sobre as decisões de endividamento corporativo. Tipicamente, empresas maiores e com uma proporção maior de ativos imobilizados são mais endividadas, e as mais lucrativas possuem endividamento mais baixo (Rajan e Zingales, 1995). Lemmon, Roberts e Zender (2008) mostram, porém, que uma parte substancial do endividamento é determinado por características não observáveis constantes no tempo. A importância dessas características é consistente com a persistência do endividamento das empresas americanas de capital aberto e a sua convergência para alvos que mudam ao longo do tempo. Será que características não observáveis constantes no tempo também são relevantes para o endividamento das empresas brasileiras? Há razões para crer que não. A economia brasileira é marcada por uma alta volatilidade de fatores macroeconômicos como taxas de juros, taxas de câmbio e inflação. Tal volatilidade talvez magnifique fatores conjunturais a um ponto que solape fatores mais estruturais das decisões de endividamento. Nesse caso, a documentada convergência do endividamento alvo das empresas americanas pode simplesmente não existir no Brasil. O objetivo principal desta dissertação é estudar os fatores permanentes e transitórios das decisões de endividamento no Brasil, verificando em que setores da economia os primeiros são mais importantes do que os últimos, e avaliando se as combinações desses fatores transitórios descarta a existência de um endividamento alvo médio para as empresas de capital aberto no Brasil. / [en] Since the seminal work of Modigliani and Miller (1961), much has been learned about corporate debt decisions. Typically, larger firms with a higher proportion of fixed assets are more indebted, and the more profitable have lower indebtedness (Rajan and Zingales, 1995). Lemmon, Roberts and Zender (2008) show, however, that a substantial part of the indebtedness is determined by unobservable characteristics that are constant in time. The importance of these characteristics is consistent with the continued indebtedness of US publicly traded companies and their convergence to targets that change over time. Are non-observable characteristics constant in time also relevant to the indebtedness of Brazilian companies? There are reasons to believe that not. The Brazilian economy is marked by a high volatility of macroeconomic factors such as interest rates, exchange rates and inflation. Such volatility may magnify cyclical factors to a point that overlaps more structural factors of debt decisions. In this case, the documented convergence of the target debt of US companies may simply not exist in Brazil. The main objective of this dissertation is to study the permanent and transitory factors of indebtedness decisions in Brazil, verifying in which sectors of the economy the former are more important than the last, and evaluating if the combinations of these transitory factors rule out the existence of a target debt average for publicly traded companies in Brazil.

The following dissertation contains two related essays. The first essay explores how institutional investor presence impacts investments during the global financial crisis. Using OLS, industry fixed effects, and Heckman 2SLS regression approaches, I explore two ways through which institutional investors could impact investments: liquidity and monitoring. My findings best support monitoring theory. I find that institutional investors monitor capital and R&D levels to maximize crisis period firm value. The second essay is a direct fallout from my first essay. In it, I investigate how institutional investor types influence investments. I ask, do certain types of investors improve liquidity or monitor firm investment behavior during the global financial crisis? My results suggest that long-term, dedicated institutional investors monitor firm investments more than short-term, transient investors. As a result, firms with greater dedicated investor presence perform better during the crisis periods than their peers.

Magister Scientiae - MSc / Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do. There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections. / South Africa

In this study, we will show how Sweden's export is affected by changes in the exchange rate during the years 1962-2011. The regression model is built on the gravity model of trade, and is tested with both OLS and fixed effects. We have collected data from Sweden’s top 30 trading partners according to Statistiska Centralbyrån in April 2017. Three historically important regimes for Swedish exchange rate have been selected to study the short time effects on Swedish export. Those periods are 1970-1975, which is the last years of the Bretton Woods system and when it fell, 1991-1994 which is the period Sweden changed from fixed exchange rate to a floating and 2001-2006 to examine Sweden’s choice of not participate in the European Monetary Union (EMU). When analyzing the result, there is no conclusion on whether the effects of the changes in exchange rates have had a negative or positive impact on the Swedish export. The results vary depending on whether OLS or fixed effects are used. / I den här studien ska vi visa hur Sveriges export påverkats av förändringar i växelkursen under tidsperioden 1962–2011. Den använda regressionsmodellen har sin grund i gravitationsmodellen och testas med OLS och fixa effekter. Studien använder sig av Sveriges 30 största exportländer enligt Statistiska Centralbyrån i april 2017. Tre historiskt viktiga händelser för svensk växelkurs har valts ut för att undersöka de kortsiktiga effekterna på den svenska exporten. Dessa perioder är Bretton Woods systemet (1970–1975), när Sverige bytte från fast till rörlig växelkurs (1991–1994) och perioden 2001–2006 för att studera effekten av Sveriges val att stå utanför EMU. När vi analyserar resultatet finns det ingen slutgiltig slutsats av huruvida förändringar i växelkursen har haft en positiv eller negativ effekt på den svenska exporten. Resultaten varierar beroende på om OLS eller fixa effekter har använts.

By using panel data from SHARE this thesis shows, that retirement has a negative effect on indicators of physical and mental health. Results from using fixed effects models suggest that retirement leads to 0,85 points increase in chronic diseases, 0,3 points increase in difficulties associated with mobility and 0,07 points increase in body mass index. Also retirement increases the level of depression by 0,5 points. According to the results, the effect of retirement on memory is also negative.

Human migration, the movement of people from one place to another with intention of settling there temporarily or permanently, is an integral part of development of human society. The beginning of the Industrial Revolution in late 18th century has resulted in economic growth and improvement of living standards. Countries, in which was industrialisation most intense attracted most immigrants. Second wave of migration was in second half of 20th century caused by development of communication technologies, which gave opportunities to less developed countries improve their economic development. This diploma thesis is aimed exactly on this period. Its goal is to research the impact of migration on economic growth and find out if the flow of migrants is beneficial for the economy or the exact opposite. The impact is examined by regression analysis on panel data for almost 200 hundred countries from whole world for time period 1955-2004.

This following report estimate the effect of violent crime with juvenile delinquency together with some societal factors with the help of a multiple regression of panel data. The results show that there are some variables that have a significant effect on violent crime. In my conclusion I discuss that the economic situation might contributes to violent crimes initially.

The healthcare labor market has experienced some significant changes in the last half century, including the establishment of Medicare and Medicaid in 1965, the emergence of managed care in the 1980s, and the worldwide mobility of labor encouraged by globalization. Currently, more than 25% of physicians working in the U.S. are foreign-born. The existing body of literature related to the impact of immigration on local wages has to date found conflicting results. The purpose of this research is to evaluate the impact of immigration of foreign physicians on local physician wages. This study employs physician survey data from the AMA Physician Masterfile for the years 1997 through 2007 combined with wage data published by the Bureau of Labor Statistics and data from other government sources. Several econometric models are employed to analyze the wage impacts of immigration, including ordinary least squares, fixed effects, two-stage least squares and a first-difference approach to control for endogenous location choice. The results of this study provide evidence that in the short-run, the impacts of immigration of physicians on area wages is small but positive. In the long run, however, wages adjust and the impact becomes negative and statistically significant, although the magnitude of the impact of a one percentage point increase in the share of immigrant physicians in an area is less than 0.2%. The negative wage effects of immigration tend to be larger for foreign-born physicians educated in the U.S. compared with foreign-born international medical graduates. The study also finds evidence that the negative effects of immigration tend to be offset by outflows of the lowest paid native physicians. Furthermore, physicians tend to locate in areas where wages are already higher, and foreign-born physicians are more likely than their native counterparts to work in larger cities as opposed to rural areas. The research has important policy implications in the presence of current debate over immigration law and healthcare reform and in an era of increasing mobility of labor due to globalization.

This study is based on data regarding the social, economic, and demographic characteristics of 130 countries, and uses fixed effects estimation for the model analysis. It demonstrates that tourism development represents a complex process, which requires the implication of a multitude of stakeholders. Macroeconomic factors, such as GDP per capita growth and economic openness, are having a positive impact because they benefit private ownership and motivate people to open tourism-related businesses. Overall, higher carbon dioxide emissions and worse safety are having a negative effect over tourism development. Human development factors, such as education, are generally beneficial to the long-term tourism growth because they serve as positive externalities. Clustering the initial dataset based on various economic, demographic and social factors brought several new conclusions. Particularly, GDP per capita growth is not an important tourism development factor among developed countries, whereas the dummy variable for the year 2010 is a substantial one. Education and economic freedom are particularly important regressors for post-socialist states. The former is also crucial among African countries and in the Latin American region, where safety has also an essential impact over tourism development. Finally, tourism in small states would benefit the most from lower emissions,whereas in big states the best strategy for the policymaker would be to increase safety measures.