The purpose of this study was to examine the longitudinal impacts of the Science Writing Heuristic (SWH) approach on student science achievement measured by the Iowa Test of Basic Skills (ITBS). A number of studies have reported positive impact of an inquiry-based instruction on student achievement, critical thinking skills, reasoning skills, attitude toward science, etc. So far, studies have focused on exploring how an intervention affects student achievement using teacher/researcher-generated measurement. Only a few studies have attempted to explore the long-term impacts of an intervention on student science achievement measured by standardized tests. The students' science and reading ITBS data was collected from 2000 to 2011 from a school district which had adopted the SWH approach as the main approach in science classrooms since 2002. The data consisted of 12,350 data points from 3,039 students. The multilevel model for change with discontinuity in elevation and slope technique was used to analyze changes in student science achievement growth trajectories prior and after adopting the SWH approach. The results showed that the SWH approach positively impacted students by initially raising science achievement scores. The initial impact was maintained and gradually increased when students were continuously exposed to the SWH approach. Disadvantaged students who were at risk of having low science achievement had bigger benefits from experience with the SWH approach. As a result, existing problematic achievement gaps were narrowed down. Moreover, students who started experience with the SWH approach as early as elementary school seemed to have better science achievement growth compared to students who started experiencing with the SWH approach only in high school. The results found in this study not only confirmed the positive impacts of the SWH approach on student achievement, but also demonstrated additive impacts found when students had longitudinal experiences with the approach. By engaging in the argument-based classrooms where teachers value students' prior knowledge, encourage students to take control of their learning, and provide non-threatening environment for students to developing big ideas through negotiation, student's achievement can be enhanced. The results also started to shed some light on sustainability of the SWH approach within the school district.

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The increase in right wing populist parties in Europe combined with the sudden influx of asylum applicants has given rise to the debate regarding immigration both politically and within research. This paper sets out to examine the relation between asylum seeker group size and people’s attitudes towards immigration. Based on group threat theory and ethnic competition theory we hypothesize that countries´ increases in asylum seekers is correlated with decreases in attitudinal support for immigration. We test this hypothesis using cross- national time series survey data from the Eurobarometer from 2014 to 2017 and conducting a multilevel analysis. Despite the extensive theoretical arguments that strengthen the hypothesis, we find no evidence that the group size of asylum seekers is related to attitudes towards immigration from outside EU.

Vehicles being driven for work purposes represent a large proportion of road collision and deaths in the workplace. These observations mean that people driving for work can impose a large burden on organisations and on society. In addition, previous studies identified a fleet driver effect for which there was greater collision risk for those who drive for work compared to the general driving population, even after controlling for exposure. This accentuates the need for both organisational and government policy makers to take steps to reduce the impact of these collisions. No single intervention has been found to solve issues around work-related road safety therefore a range of initiatives have been directed towards the risks associated with drivers, vehicles, journeys and organisations. Many of the interventions, however, lack robust evidence to support their use. The aim of this thesis is to assess organisational interventions to improve work-related road safety by using econometric models on real-world data. The data represents driving claims made between 2005 and 2012 by employees of a large UK company, with a fleet of approximately 35,000 vehicles. The drivers were employed in a variety of roles such as working in technical positions at customer sites or making sales visits. The company has applied a range of strategies to road safety resulting in annual claim reductions of 7.7% compared to only a 4.5% reduction in collisions nationally. The company s data are used to undertake three studies which focused on driver training, manager training and claim segmentation. Statistical models were employed to investigate the effect of two different driver training courses on the frequency of claims while controlling for other factors. The results indicated that driver training courses significantly reduced both the total number of claims and the claim types targeted by the training. The impacts of the interventions were also adjusted for the effects of non-random driver selection and other safety improvements initiated by the company or other agencies. An important finding of this work was that randomly inflated pre-training events accounted for between a third and a quarter of the observed reduction in claims following training. The second study evaluated the impact of management training on claims using multilevel models which allowed for correlation between observations. The study could not confirm that this training was an effective safety intervention. This null result provides an incentive to re-evaluate the implementation of the scheme. The final study identified homogeneous claim segments using statistical models and the impact of training was evaluated on these segments. Such claims were estimated to be reduced by between 32% to 55% following existing driver training courses. This thesis has helped close important gaps and contributed to knowledge in terms of both intervention methodology and the understanding of the effectiveness of work-related road safety interventions. The results, which are already being applied in the case study organisation, demonstrated that training employees in either safe and fuel efficient driving, or low speed manoeuvring, reduced vehicle insurance claims. Further work is necessary to verify the safety value of manager training including gathering detailed information on interactions between managers and drivers.

This thesis consists of an introductory part and the following four self-contained papers: In Paper [I] we analyze the implications of social identity and self-categorization for optimal redistributive income taxation. A two-type model is supplemented by an assumption that individuals select themselves into social categories, in which norms are formed and education effort choices partly depend on these norms. The results show, among other things, that externality correction by a welfarist government leads to an element of tax progression that serves to reduce the discrepancy between the effort norm and the actual effort chosen by low-productivity individuals in the high-effort group. Furthermore, if the preference for social identity is sufficiently strong, increased wage-inequality leads to higher social welfare through a relaxation of the selection constraint. It may thus be desirable to use publicly provided education to induce more wage-inequality, even if higher wage-inequality increases the intrinsic utility of a potential mimicker. In Paper [II] I employ high quality register data to present new facts about income mobility in Sweden. The focus of the paper is regional differences in mobility, using a novel approach based on a multilevel model. This method is well-suited when regions differ greatly in population size as is the case in Sweden. The maximum likelihood estimates are substantially more precise than those obtained by running separate OLS regressions. I find small regional differences in income mobility when measured in relative terms. Regional differences are large when adopting an absolute measure and focusing on children with below-median parent income. On the national level I find that the association between parent and child income ranks has decreased over time, implying increased mobility. In Paper [III] I study the long term effects of inter-municipal moving during childhood on income using Swedish register data. Due to the richness of the data I am able to control for important sources of selection into moving, such as parent separation, parents' unemployment, education, long run income, and immigration background. I find that children's long run incomes are significantly negatively affected by moving during childhood, and the effect is larger for those who move more often. For children who move once, I also estimate the effect of the timing and the quality of the move. I measure the quality of each neighborhood based on the adult outcomes for individuals who never move. The quality of a move is defined as the difference in quality between the origin and the destination. Given that a family moves, I find that the negative effect of childhood moving on adult income is increasing in age at move. Children benefit economically from the quality of the region they move to only if they move before age 12 (sons) and age 16 (daughters). In Paper [IV] I study the bias of IGE estimates for different missing-data scenarios based on simulated income processes. Using an income process from the income dynamics and risks literature to generate two linked generations’ complete income histories, I use Monte Carlo methods to study the relationship between available data patterns and the bias of the IGE. I find that the traditional approach using the average of the typically available log income observations leads to IGE estimates that are around 40 percent too small. Moreover, I show that the attenuation bias is not reduced by averaging over many father income observations. Using just one income observation for each generation at the optimal age (as discussed in the paper) or using weighted instead of unweighted averages can reduce the bias. In addition, the rank-rank slope is found to be clearly less sensitive to missing data.

La mesure et l'analyse d'éventuels effets établissement s'inscrivent dans le développement des pratiques d'évaluation des politiques publiques, à travers la construction d'indicateurs quantitatifs. Ainsi, on appelle effet établissement l'impact mesurable des caractéristiques d'une institution donnée sur un indicateur de résultat. Plus précisément, nous utilisons les modèles multiniveaux pour relier les informations dont on dispose au niveau des institutions à des indicateurs de résultat au niveau individuel. Dans un premier chapitre, nous étudions l'effet de caractéristiques des universités sur le salaire de leurs diplômés, en nous inscrivant dans le cadre de l'étude de la relation entre qualité de l'éducation et salaire. Il apparaît que deux éléments semblent jouer, d'une part l'orientation vers la professionnalisation des formations proposées, d'autre part la composition sociale de la population étudiante. Dans un second chapitre, nous discutons de la pertinence d'une modulation des dotations affectées aux universités suivant un critère d'insertion tel qu'il a été retenu par l'autorité de tutelle. En effet, nous avons retenu de la première partie que les caractéristiques propres des étudiants jouent le rôle le plus important. Dès lors, si on intègre les spécificités du marché du travail ainsi que la structure de l'offre de formation des établissements, il est délicat de distinguer un effet propre de l'université, et par conséquent d'envisager de les classer suivant le critère d'insertion considéré. / The question of measurement and analysis of schooling effects takes place in the development of public policy evaluation, through the construction of quantitative indicators. We call schooling effects the measurable influence of an institution's characteristics on an output indicator. More precisely, we use multilevel models to link data we have at the institutionnal level to output indicators at the individual level.In the first chapter, we study the effect of universities characteristics on the earnings of their graduates by considering the analysis of the relation between quality of education and earnings. We find two effects : student get higher wages when they graduate from a more vocationnally oriented university but students graduating from universities where the student population is less favoured get lower wages.In the second chapter, we discuss the relevance of a modulation of the government fundings to universities based on job market integration criteria. We know that the individual characteristics of graduates are the main component affecting their integration. If we take into account the state of the job market, and the composition of the disciplines taught in institutions, it is hard to detect a specific effect of a university, and so to rank them according to such a criteria.In the third chapter, we propose to add to the human capital theory a grasp of social capital. We provide an illustration of this concept in the framework of scientific production by researchers in economics. By building indicators describing the publication habits within the institutions, we extend the question of schooling effects to the field of scientific research.

A Atenção Primária à Saúde - APS é reconhecida como o nível fundamental e porta de entrada do sistema de atenção à saúde, sendo o lugar adequado onde pode ser atendida e resolvida a maior parte dos problemas de saúde. É considerada pela OMS como a principal proposta de modelo assistencial. Essa importância da APS leva a necessidade de pesquisas avaliativas dos seus resultados para adequação e melhoria de políticas e planos de ação delineados em relação à mesma. Pesquisas internacionais e nacionais são realizadas, nas quais indicadores relativos às atividades hospitalares estão sendo empregados com o objetivo de medir resultados como efetividade e acesso da APS. Um desses indicadores, desenvolvido por John Billings da Universidade de Nova York, na década de 90, consiste nas condições pelas quais as internações hospitalares por Condições Sensíveis à Atenção Ambulatorial (CSAA) deveriam ser evitadas caso os serviços da APS fossem efetivos e acessíveis. Utilizando-se o SIH-AIH/2008 e a lista brasileira de Internações por Condições Sensíveis a Atenção Primária, publicada em 2008, a proposta do presente trabalho é a de estudar os cuidados primários à saúde baseando-se nas ICSAA, na área urbana da cidade de Juiz de Fora-MG. Buscou-se responder sobre os efeitos que ocorrem nessas internações a partir das características individuais dos pacientes, das características das Unidades Básicas de Saúde-UBS (infraestrutura, produção e modelos assistenciais) e das condições sócio-econômicas/ambientais das áreas cobertas por UAPS e descobertas (sem UAPS), com a utilização de modelos multiníveis logísticos com intercepto aleatório. Buscou-se conhecer, também, a distribuição espacial das taxas padronizadas por idade das ICSAA nessas áreas e suas associações com as variáveis contextuais, utilizando-se ferramentas da análise espacial. Os resultados do presente trabalho mostraram que a porcentagem de internações por CSAA, foi de 4,1%. Os modelos assistenciais ESF e o Modelo Tradicional, base da organização da atenção primária no Brasil, não apresentaram no município, impacto significativo nas ICSAA, somente na forma de áreas descobertas tendo como referência as áreas cobertas. Também não foram significativas as variáveis de infraestrutura e produção das UAPS. Os efeitos individuais (idade e sexo) nas ICSAA foram significativos, apresentando probabilidades de significância menores que 1%, o mesmo acontecendo com o Índice de Desenvolvimento Social-IDS, que contempla as condições sociais, econômicas e ambientais das áreas analisadas. A distribuição espacial das taxas padronizadas por idade apresentou padrão aleatório e os testes dos Multiplicadores de Lagrange não foram significativos indicando o modelo de regressão clássico (MQO) como adequado para explicar as taxas em função das variáveis contextuais. Para a análise conjunta das áreas cobertas e descobertas foram fatores de risco: a variável econômica (% dos domicílios com renda até 2 SM), áreas descobertas tendo como referência as áreas cobertas e a região nordeste do município. Para as áreas cobertas as variáveis de produção das UAPS, econômica e a região nordeste apresentaram como fator de risco para as taxas de internação por CSAA. / The Primary Health Care - PHC is recognized as the primary and gateway to the health care system, and the proper place where it can be answered and solved most health problems. It is considered by WHO as the main tender treatment model. This importance of APS leads to the need for evaluative research of their results to adapt and improve policies and action plans outlined in relation to it. International and national surveys are conducted, in which indicators related to hospital activities are being employed with the aim of measuring effectiveness and access to PHC. One of these indicators, developed by John Billings of the University of New York in the 90s, consists of the conditions for which hospitalizations for Ambulatory Care Sensitive Conditions (ACSC) should be avoided if the PHC services were effective and accessible. Using the Brazilian list of ACSC, published in 2008, and SIH-AIH/2008 the purpose of this paper is to study the primary health care based on the hospitalization for ACSC, in the urban area Juiz de Fora-MG city. We tried to answer about the effects that occur in these admissions from the characteristics of individual patients, the characteristics of the Primary Health Care Unit-PHCU (infrastructure, production and care models) and the social conditions of the areas covered (with PHCU) and discoveries (not PHCU), with the use of multilevel logistic models with random intercept. We tried to know, too, the spatial distribution of standardized rates by age in these areas and their associations with contextual variables, using the tools of spatial analysis. The results of this study showed that the percentage of admissions for ACSC was 4.1%. Family Heath Strategy and Traditional models, the base of organization of primary care in Brazil, had no significant impact on the hospitalizations, only when analysed in form to uncovered areas with reference to the areas covered. Nor were significant variables for infrastructure and production of PHCU. The individual effects (age and sex) in ACSC were significant, with significance probabilities less than 1%, as did the Social Development Index-SDI, which includes the social, economic and environmental conditions in these areas examined. The spatial distribution of standardized rates by age showed random pattern and tests of Lagrange multipliers were not significant indicating the classical regression model (OLS) to explain these rates. For the joint analysis of covered and uncovered areas were risk factors: the economic variable (% of households with incomes up to 2 MW), the uncovered areas with reference to the areas covered and the Northeast. For areas covered variables economic, production from PHCU and Northeast were risk factors for admission rates for ACSC.

The purpose of this research was to compare results from two approaches to measuring change over time. The multilevel model (MLM) and latent growth model (LGM) were imposed and the parameter estimates were compared, along with model fit. The study came out of education and used data collected from 191 teachers as part of a professional development intervention in science, which took place over four years. There were missing data as a result of teacher attrition. Teachers reported use of reform-oriented practices (ROP) was used as the outcome, and teacher-level variables were examined for their impact on initial ROP and change in ROP from baseline to one year after the intervention. Change in ROP was examined using a piecewise change model where two linear slopes were modeled. The first slope estimated the change from baseline to T1, or the initial change after the intervention while the second slope estimated the change from T1 to T3, or the secondary change. Parameter estimates obtained from MLM and LGM for a model using the error covariance structure commonly assumed in MLM (i.e., random slopes, homogeneous level-1 variance) were nearly identical. Models with various alternative covariance structures (commonly associated with the LGM framework) were examined, and results were nearly identical. Most of the model fit information was in agreement regarding the best fitting model being the model that assumed the typical MLM error covariance structure with the exception of the standardized root mean square residual (SRMR) fit index. The results from the models demonstrated that ROP increased after participating in the first year of the intervention and this level was sustained, though did not increase significantly in subsequent years. There was more variation in ROP at baseline. This information tells us that the intervention was successful in that after participating in the intervention the teachers' used ROP more frequently. The success of the intervention did not depend on any of the predictors that we assessed, and, as a group, the teachers became more similar in their use of reform-oriented practices over time.