This thesis consists of three essays that examine issues on university attendance behavior, factorsof university completion, and the labor market value of a university diploma in Sweden. Essay [I] analyzes how the rapid expansion of higher education that increased the geographicalaccessibility to higher education in the 1990s affected university enrollment decisions amongvarious socioeconomic groups of young adults in Sweden. The empirical findings show that theprobability of enrollment in university education increases with accessibility to universityeducation. The results also indicate that accessibility adds to the likelihood of attending auniversity within the region of residence. Access to higher education more locally seems to havedecreased the social distance to higher education, meaning that the option of attending highereducation, as compared to entering the local labor market after upper secondary school, hasbecome a more common and a more natural alternative for more socioeconomic groups insociety. Essay [II] compares the performance of students in universities built before and after the largedecentralization and expansion of the higher educational system in Sweden, starting in the late1970s. Two outcome measures are used: (i) whether or not the student has obtained a degreewithin seven years after she initiated her studies; and (ii) whether or not she obtained 120 creditpoints (the requirement for most undergraduate degrees) within seven years. Controlling forseveral background variables as well as GPA scores in a binomial probit model, we show thatstudents at old universities are about 5 percentage points more likely to get a degree and about 9percentage points more likely to obtain 120 credit points. However, in an extended bivariatemodel where we consider selection on unobservables into university type, we cannot reject thepossibility of no difference in performance between the two university types. Essay [III] analyzes the labor market value of a university diploma (sheepskin) in Sweden. Incontrast to previous studies, this study only focuses on Swedish university students who havethree years of full time university education or more − where some have obtained a universitydegree, others not. The results show that for male students, the wage premium of possessing adegree, i.e. the sheepskin effect, is roughly 5-8 percent. For women, it is about 6-7 percent forthose who have completed four years of fulltime or more. For students who attended a moreprestigious university in the metropolitan areas in Sweden and majored in the natural sciences, asheepskin effect of roughly 13 percent for men and 22 percent for women is traced. However,this result did not hold among students who attended. Keywords: Higher education, university enrollment; university choice; accessibility; universitycompletion; selection bias; propensity score matching, sheepskin, human capital.

Background: Empirical studies in psychiatric research and other fields often show substantially high refusal and drop-out rates. Non-participation and drop-out may introduce a bias whose magnitude depends on how strongly its determinants are related to the respective parameter of interest. Methods: When most information is missing, the standard approach is to estimate each respondent’s probability of participating and assign each respondent a weight that is inversely proportional to this probability. This paper contains a review of the major ideas and principles regarding the computation of statistical weights and the analysis of weighted data. Results: A short software review for weighted data is provided and the use of statistical weights is illustrated through data from the EDSP (Early Developmental Stages of Psychopathology) Study. The results show that disregarding different sampling and response probabilities can have a major impact on estimated odds ratios. Conclusions: The benefit of using statistical weights in reducing sampling bias should be balanced against increased variances in the weighted parameter estimates.

Charles University in Prague Faculty of Social Sciences Institute of Economic Studies DISSERTATION THESIS ABSTRACT Essays on Natural Resource Richness, Economic Growth and Institutional Quality Author: Ayaz Zeynalov Supervisor: Doc. Roman Horvath, Ph.D Academic Year: 2016/2017 Abstract This dissertation consists of three empirical papers on natural resource, economic growth and institutional quality. The first paper analyzes possible publication bias and the reason for contradictory findings in the natural resource literature, the second paper examines the effect of natural resource exports on manufacturing performance in the 15 former Soviet Union countries, and the last addresses whether similarities in country income size and at the institutional level encourage increased amounts of bilateral trade between countries. An introductory chapter puts these three papers into perspective. In the first paper, I analyze 43 studies providing 605 different regression specifica- tions and found that approximately 40% report a negative and statistically significant effect, another 40% report no effect, and the remaining 20% report a positive and statistically significant effect of natural resources on economic growth. The findings show that including interaction between natural resources and institutional quality, controlling...

nÃo hà / O objetivo deste trabalho à estimar a probabilidade de um trabalhador estar empregado no setor informal, condicionadas as suas caracterÃsticas produtivas, considerando a possibilidade de viÃs de seleÃÃo amostral. A amostra se restringe ao CearÃ, e utiliza a Pesquisa Nacional de Amostras por DomicÃlio (PNAD) 2008 para classificar os trabalhadores em formais e informais. De acordo com a hipÃtese da dualidade, os postos de trabalho no setor formal sÃo efetivamente melhores em vÃrias dimensÃes, e a existÃncia de informalidade ocorre porque o nÃmero destes postos à limitado. Se de fato hà segmentaÃÃo no mercado de trabalho e racionamento dos postos de trabalho formais, à importante saber como ocorre à alocaÃÃo de trabalhadores entre os dois setores. Para tanto, à considerada a possibilidade de viÃs de seleÃÃo na escolha entre os setores formal e informal. O viÃs de seleÃÃo ocorre quando uma sÃrie de caracterÃsticas nÃo observÃveis dos indivÃduos pode fazer com que eles acabem trabalhando, por opÃÃo ou necessidade, no setor informal da economia. Ou seja, caracterÃsticas nÃo observÃveis dos indivÃduos, como habilidade, forÃa de vontade, determinaÃÃo, criatividade etc., podem estar determinando a escolha entre trabalhar no mercado formal ou informal. / The aim of this study to estimate the probability of a worker being employed in the informal sector conditioned their productive characteristics, considering the possibility of sample selection bias. The sample is restricted to CearÃ, and uses the National Survey of Household Sample Survey (PNAD) in 2008 to classify workers in formal and informal. According to the dual hypothesis, the jobs in the formal sector are indeed better in many dimensions, and the existence of informality is because the number of these jobs is limited. If indeed there is segmentation in the labor market and rationing of formal jobs, it is important to know how the allocation of workers between the two sectors. For this is considered the possibility of selection bias in the choice between formal and informal sectors. The selection bias occurs when a number of unobservable characteristics of individuals can make them end up working, by choice or necessity, in the informal economy. That is, unobservable characteristics of individuals such as skill, willpower, determination, creativity etc., it may be influencing the choice between working in the formal or informal.

O objetivo desse trabalho é analisar a relação entre o desempenho escolar e os salários dos jovens brasileiros. Examinamos se a qualidade do ensino, mensurada pelas notas obtidas por uma geração nos exames de proficiência realizados pelo Instituto Nacional de Estudos e Pesquisas Anísio Teixeira, o INEP, em seu Estado ao término do ensino médio, afeta os salários a serem recebidos por esta geração quando ela estiver no mercado de trabalho, cinco e seis anos depois, respectivamente com dados do Censo Demográfico de 2000 e da Pesquisa Nacional por Amostra de Domicílios, a PNAD, de 2001. A partir de um modelo de pseudo-painel, corrigimos os problemas de viés de seleção gerados pelas migrações e pelo alto nível educacional da amostra selecionada, através do modelo de Roy (1951) aplicado em Dahl (2001). Os determinantes da proficiência escolar, tais como “background” familiar, a infra-estrutura escolar e o perfil de docentes e diretores também foram analisados. A partir da estimação do modelo em dois estágios, os resultados do primeiro estágio mostram que o desempenho dos alunos em exames de proficiência é positivamente relacionado aos investimentos em educação, como melhor remuneração a professores e diretores, critérios mais rigorosos de seleção desses profissionais, assim como investimentos em infra-estrutura, que melhoram a qualidade da escola. Isso aponta para a existência de uma relação entre os recursos destinados à educação e a qualidade da mesma no Brasil. Adicionalmente, os resultados do segundo estágio do modelo mostram que as notas obtidas por uma geração nos testes de proficiência são significantes para explicar os salários futuros da mesma. Dessa forma o estudo confirma a importância de políticas públicas que invistam na qualidade da escola ao invés de políticas destinadas apenas a aumentar os anos de estudo da população. / The aim of this paper is to examine the relationship between the school performance and the wages of young Brazilians workers. We examine if school quality, measured by test scores of a generation in SAEB at the end of high school, affect the earnings of this generation when they enter the labor force, five and six years later, with sample of Censo (2000) and PNAD (2001). We use a pseudo-panel model to correct the problems of selection bias, created by migrations and by the high education level of the selected sample, through a Roy model (1951) applied in Dahl (2001). The determinants of school performance, like familiar background, school structure, teacher and director profiles also were analyzed. We conclude that school characteristics are responsible for a good performance of students in tests scores, and that the school performance explains the differences of the earnings of young Brazilians workers.

Les principaux facteurs de l'insécurité routière sont connus, et l'enjeu réside aujourd'hui dans la mesure de l'effet d'un facteur, et la hiérarchisation de l'ensemble des causes intervenant dans la survenue de l'accident. Toutefois, les données disponibles concernent généralement que des accidentés. En l'absence de non-accidentés, l'épidémiologiste du risque routier se heurte à une sélection extrême. Une des solutions classiques est d'utiliser des analyses en responsabilité, et de mesurer l'effet causal d'un facteur sur le risque d'être responsable d'un accident. Néanmoins, la validité des analyses en responsabilité repose sur l'hypothèse, discutable, que les non-responsables sont représentatifs des circulants. L'objectif de cette thèse est donc de déterminer si les données disponibles d'accidentés permettent de fournir, via les analyses en responsabilité, des estimations des effets causaux sans biais, et notamment sans un biais de sélection résiduel. Nous montrons dans cette thèse que, dès lors que l'inclusion dépend de la gravité de l'accident, et que le facteur étudié a un impact sur la vitesse, il est impossible d'estimer l'effet causal du facteur sur le risque d'être responsable de l'accident grave sans un biais de sélection résiduel. Ce résultat est tout d'abord démontré de manière formelle, grâce à l'utilisation des modèles causaux structuraux. Ces modèles sont fondés sur une structure graphique, le DAG, qui représente les différentes relations entre les variables. Ce DAG permet la description des variables réellement observées, mais également des variables contrefactuelles, variables observables dans un monde contrefactuel où l'on aurait fixé l'exposition à une certaine valeur. L'effet causal étant défini à partir de ces variables contrefactuelles partiellement observées, c'est la structure du DAG qui permet de déterminer si l'effet causal peut être estimé en fonction des variables observées. Or, la structure du DAG conduisant à la survenue d'un accident grave ne permet pas d'exprimer l'effet causal du facteur étudié sur la responsabilité de l'accident grave en fonction des distributions observées sur les accidentés graves. Conditionner les estimations sur les accidentés graves correspond à ajuster sur une variable du DAG appelée « collider », et ainsi à introduire un biais dit de collision. En générant un modèle relativement simple, nous donnons à nos résultats théoriques une illustration numérique. En effet, lorsque les données ne dépendent pas de la gravité de l'accident, ou que le facteur étudié n'a pas d'effet sur la vitesse, la mesure estimable à partir des analyses en responsabilité est une mesure sans biais de l'effet causal, sous certaines hypothèses de prévalences faibles. Lorsque l'inclusion dépend de la gravité de l'accident, il existe un biais et ce biais induit par les analyses en responsabilité est d'autant plus grand que l'intensité de la relation entre le facteur et la vitesse, et celle entre la vitesse et l'accident est grand. Les schémas d'étude présentés permettent d'approcher des situations où le facteur étudié serait l'alcool ou le cannabis. Dans le cas de l'alcool, il apparait que sous le modèle simple considéré, la mesure d'association estimable serait une sous-estimation de l'effet causal. En revanche, dans le cas du cannabis, la mesure d'association correspondrait à une sur-estimation de l'effet causal. D'autre part, les outils de l'inférence causale nous ont permis de fournir une description formelle de la validité externe et interne, ainsi qu'une description formelle de la mesure d'association estimable via les analyses en responsabilité. Cette question de la validité interne d'une mesure se pose dans d'autres champs d'application que la sécurité routière. Elle se pose notamment dans le cas du paradoxe de l'obésité [etc...] / Many factors associated with the risk and severity of road accidents are now widely considered as causal : alcohol, speed, usage of a mobile phone... Therefore, questions asked by decision-makers now mostly concern the magnitude of their causal effects, as well as the burden of deaths or victims attributable to these various causes of accident. One particularity of road safety epidemiology is that available data generally describe drivers and vehicles involved in road accidents only, or even severe road accidents only. This extreme selection precludes the estimation of causal effects. To circumvent this absence of « control » population of non-crash involved drivers, it is common to use responsibility analysis and to assess the causal effect of a given factor on the risk of being responsible for an accident among involved drivers. The underlying assumption is that non-responsible drivers represent a random sample of the general driving population that was « selected » to crash by circumstances beyond their control and therefore have the same risk factor profile as other drivers on the road at the same time. However, this randomness assumption is questionable. The objective of this thesis is to determine whether available data in road safety allow us to assess causal effects on responsibility without a residual selection bias. We show that a good approximation of causal effect of a given factor on the risk of being responsible is possible only if the inclusion into the dataset does not depend on the severity of the accident, or if the given factor has no effect on speed. This result is shown by using the Structural Causal Model (SCM) framework. The SCM framework is based on a causal graph : the DAG (directed acyclic graph), which represents the relationships among variables. The DAG allows the description of what we observe in the actual world, but also what we would have observed in counterfactual worlds, if we could have intervened and forced the exposure to be set to a given level. Causal effects are then defined by using counterfactual variables, and it is the DAG’s structure which determines whether causal effects are identifiable, or recoverable, and estimable from the distribution of observed variables. However, the assumptions embedded in the DAG which describes the occurence of a severe accident does not ensure that a causal odds ratios is expressible in terms of the observable distribution. Conditioning the estimations on involved drivers in a severe crash correspond to conditioning on a variable in the DAG called « collider », and to create a « collider bias ». We present numerical results to illustrate our theoretical arguments and the magnitude of the bias between the estimable association measure and some causal effects. Under the simple generative model considered, we show that, when the inclusion depends on the severity of the accident, the bias between the estimable association measure and causal effect is larger than the relation between the exposure and speed, or speed and the occurrence of a severe accident is strong. Moreover, the presented designs allow us to describe some situations where the exposure could be alcohol or cannabis intoxication. In the case of alcohol, where alcohol and speed are positively correlated, the estimable associational effect underestimates the causal effect. In the case of cannabis, where cannabis and speed are negatively correlated, the estimable associational effect overestimates the causal effect. On the other hand, we provide a formal definition of internal and external validity, and a counterfactual interpretation of the estimable quantity in the presence of selection bias, when causal effects are not recoverable. This formal interpretation of the estimable quantity in the presence of selection bias is not only useful in the context of responsibility analyses. It is for instance useful to explain the obesity paradox

The age-cutoff regression discontinuity design (RDD) has emerged as one of the most rigorous quasi-experimental approaches to determining program effects of prekindergarten on literacy and numeracy outcomes for children at kindergarten entry. However, few pre-K meta-analyses have focused attention on validity threats. The current random-effects meta-regression tests the moderating effects of prominent threats to validity, selection bias and sensitivity, on impact estimates generated from age-cutoff regression discontinuity studies from large-scale programs. Results from averaging dependent standardized mean difference effects suggested small positive moderating effects of total attrition and robust 3-month bandwidths on reading effects, but not on math. However, these results were not statistically significant. In contrast, results generated from robust variance estimation yielded a small statistically significant association between total attrition and math effects. These mixed results may warrant further research on prekindergarten evaluation methodology, evaluation estimation methods, and the totality of evidence used to inform policy.

Approved for public release; distribution is unlimited. / This thesis investigates the effect of marital and family status on the performance and job productivity of male U.S. Marine Corps officers. The analysis includes evaluation of fitness reports, retention, and promotion to O-4 and O-5 ranks as performance measures. The primary goal is to examine the existence of any marriage premium on officers' performance and productivity and to investigate potential causal hypotheses. The personnel database used for the analysis includes more than 27,000 male Marine officers who entered the Marine Corps between FY 1980 and 1999. After controlling for selection, estimating fixed effects and using panel data in order to capture timely-varying effects, this study finds that there is a marriage premium for all performance measures. The thesis rejects the explanation that such premiums are due to supervisor favoritism. Moreover, married male officers obtain higher fitness report scores, higher promotion probabilities, and higher retention probabilities than single officers. Each additional year spent in marriage increases fitness report scores and retention probabilities. Having additional non-spousal dependents increase fitness report scores and retention probabilities. On the other hand, being a currently single but "to-be-married" officer yields higher premium, as married officers, for all productivity and performance indicators. This supports selectivity into marriage as a partial explanation of the source of the marriage premium. / Lieutenant Junior Grade, Turkish Navy / First Lieutenant, Turkish Army

If policymakers address water scarcity with the demand-oriented approach, the income elasticity of water demand is of pivotal importance. Its estimates, however, differ considerably. We collect 307 estimates of the income elasticity of water demand reported in 62 studies, codify 31 variables describing the estimation design, and employ Bayesian model averaging to address model uncertainty inherent to any meta-analysis. The studies were published between 1972 and 2015, which means that this meta-analysis covers a longer period of time than two previous meta-analyses on this topic combined. Our results suggest that income elasticity estimates for developed countries do not significantly differ from income elasticity estimates for developing countries and that different estimation techniques do not systematically produce different values of the income elasticity of water demand. We find evidence of publication selection bias in the literature on the income elasticity of water demand with the use of both graphical and regression analysis. We correct the estimates for publication selection bias and estimate the true effect beyond bias, which reaches approximately 0.2. 1

We have considered the problem in which a biased sample is selected from a finite population, and this finite population itself is a random sample from an infinitely large population, called the superpopulation. The parameters of the superpopulation and the finite population are of interest. There is some information about the selection mechanism in that the selection probabilities are linearly related to the measurements. This is typical of establishment surveys where the selection probabilities are taken to be proportional to the previous year's characteristics. When all the selection probabilities are known, as in our problem, inference about the finite population can be made, but inference about the distribution is not so clear. For continuous measurements, one might assume that the the values are normally distributed, but as a practical issue normality can be tenuous. In such a situation a transformation to normality may be useful, but this transformation will destroy the linearity between the selection probabilities and the values. The purpose of this work is to address this issue. In this light we have constructed two models, an ignorable selection model and a nonignorable selection model. We use the Gibbs sampler and the sample importance re-sampling algorithm to fit the nonignorable selection model. We have emphasized estimation of the finite population parameters, although within this framework other quantities can be estimated easily. We have found that our nonignorable selection model can correct the bias due to unequal selection probabilities, and it provides improved precision over the estimates from the ignorable selection model. In addition, we have described the case in which all the selection probabilities are unknown. This is useful because many agencies (e.g., government) tend to hide these selection probabilities when public-used data are constructed. Also, we have given an extensive theoretical discussion on Poisson sampling, an underlying sampling scheme in our models especially useful in the case in which the selection probabilities are unknown.