Le score de propension s'est progressivement imposé comme l’une des méthodes de référence dans l'analyse des données observationnelles afin de prendre en compte le biais potentiel lié à l’existence de facteurs de confusion dans l'estimation de l'effet du traitement sur le critère de jugement. Parmi les recommandations de bonnes pratiques d'utilisation, le processus de sélection des variables à inclure dans le score final utilisé est essentiel, ainsi que l'évaluation de l'équilibre obtenu sur les covariables après appariement ou pondération sur ce score. Dans l'objectif de prioriser l'inclusion et l'équilibre des variables ayant une relation avec le critère de jugement une nouvelle mesure d'équilibre est proposée dans ce travail de thèse. Une première partie de ce travail a eu pour objectif de développer une mesure globale pondérée permettant d'évaluer l'équilibre global des covariables obtenu après appariement et ainsi d'aider à la sélection d’un modèle de propension le plus parcimonieux possible, en éliminant notamment les variables instrumentales. En effet ces variables ne doivent pas être introduites dans le modèle de score de propension au risque de majorer le biais final d'estimation. Lors des étapes d'évaluation de l'équilibre final obtenu, les différentes mesures d'équilibres disponibles ne prennent le plus souvent pas en compte cette information et concluent souvent à l'intérêt d'inclure une telle variable afin de réduire au maximum le déséquilibre entre les groupes. L'évaluation des performances de cette mesure a dans un premier temps fait appel à des simulations de type Monte Carlo. Dans une seconde partie, une mise en application sur des données réelles issues de la médecine d'urgence a permis de préciser la pratique d'utilisation d'une telle mesure / Propensity score (PS) methods have become increasingly used to analyze observational data and take into account confusion bias in final estimate of treatment effects. The goal of the PS is to balance the distribution of potential confounders across treatment groups. The performance of the PS strongly relies on variable selection in PS construction and balance assessment in PS analysis. Specifically, the choice of the variables to be included in the PS model is of paramount importance. In order to priorize inclusion and balance of variables related to the outcome, a new balance measure was proposed in this thesis. First, a new weighted balance measure was studied to help in construction of PS model and to obtain the most parsimonious model, by excluding instrumental variables known to be related with increasing bias in final treatment estimate. Several balances measures are proposed to assess final balance, but none of them help researchers to not include instrumental variables. We propose a new weighted balance measure that takes into account, for each covariate, its strength of association with the outcome. This measure was evaluated using a simulation study to assess whether minimization of the measure coincided with minimally biased estimates. Secondly, we propose to apply this measure to a real data set from an observational cohort study.

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The present study examines whether the presence of school resource officers (SROs) and their level of involvement in place management activities are associated with higher or lower rates of school-based serious violence. This study uses data from the 2010 School Survey on Crime and Safety (SSOCS) conducted by National Center for Educational Statistics. Propensity score matching is used to create a quasi-experimental design and isolate the influence of SROs and their level of involvement in place management activities on school-based serious violence. The analysis reveals that schools with a school resource officer are associated with higher rates of reported serious violence and those schools with SROs that participate in more place manager duties are also associated with higher rates of reported serious violence. These findings do not support the notion that SROs are acting as effective place managers and through this place management, reducing reported serious violence. Rather, it appears that the presences of a SRO and their execution of place manager duties is associated with an increase in the reporting of serious violence. Policy implications and limitations of the current research are also discussed.

This thesis examines the environmental effect of the European Union Emissions Trading Scheme (EU ETS) in the Czech Republic. Specifically, the impact of the EU ETS on CO2 emissions, carbon-fuel intensity and carbon intensity of production (measured by revenues) is analysed on installation-level financial, environmental and energy data throughout all three phases of the EU ETS over 2005 - 2019. The difference-in-differences approach with propensity score matching is used to infer the causal effect of the regulation. We find no effect of the EU ETS on carbon emissions and carbon intensities in the Czech Republic. This finding holds for various model specifications and different approaches we utilised. In the end, we discuss possible reasons why the EU ETS might not lead to any significant effect in the Czech Republic. JEL Classification O13, F18, Q54, Q58, H23, D22 Keywords EU ETS, environmental regulation, propen- sity score matching, difference-in-differences, the Czech Republic Title The impact of the EU ETS in the Czech Repub- lic

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In this study, I examine the employment effects on average earnings and duration to work during a 45 month period, after receiving social assistance (SA) in October 2019, compared to receiving unemployment insurance (UI) the same month. A distinction is made between two treatment groups; receiving SA in addition to UI (treatment I) and receiving SA (treatment II). Using propensity score matching (PSM), I estimate the average treatment effects on the treated on earnings, as well as duration to work by using the Kaplan-Meier survival estimator with the matched observations. I use newly released Swedish administrative micro level data of individuals’ monthly labour market status (BAS) between 2020-2023, from Statistics Sweden. During this thesis process, where Statistics Sweden allowed me data access, I was allowed an additional year of data, for 2019. Results showed that the inflow of SA recipients in October 2019, on average had 25.5 percent lower earnings between November 2019-July 2023, compared to the inflow of UI recipients the same month. In addition, the inflow of SA recipients in October 2019, on average spent 4 months longer in unemployment, compared to those receiving UI the same month. However, results were insignificant when comparing effects between the inflow of those receiving SA in addition to UI in October 2019 with the inflow of UI recipients the same month. Results for this group were insignificant for both employment outcomes; average earnings and duration to work.

In this study, I examine the employment effects on average earnings and duration to work during a 45 month period, after receiving social assistance (SA) in October 2019, compared to receiving unemployment insurance (UI) the same month. A distinction is made between two treatment groups; receiving SA in addition to UI (treatment I) and receiving SA (treatment II). Using propensity score matching (PSM), I estimate the average treatment effects on the treated on earnings, as well as duration to work by using the Kaplan-Meier survival estimator with the matched observations. I use newly released Swedish administrative micro level data of individuals’ monthly labour market status (BAS) between 2020-2023, from Statistics Sweden. During this thesis process, where Statistics Sweden allowed me data access, I was allowed an additional year of data, for 2019. Results showed that the inflow of SA recipients in October 2019, on average had 25.5 percent lower earnings between November 2019-July 2023, compared to the inflow of UI recipients the same month. In addition, the inflow of SA recipients in October 2019, on average spent 4 months longer in unemployment, compared to those receiving UI the same month. However, results were insignificant when comparing effects between the inflow of those receiving SA in addition to UI in October 2019 with the inflow of UI recipients the same month. Results for this group were insignificant for both employment outcomes; average earnings and duration to work.

Heterogeneity in the school education quality plays an important role for those who want to pursue a bachelor's degree in Peru since access to higher education is highly correlated with socioeconomic status. In that sense, an intervention for disadvantaged students took place for the first time in 2022 and was constrained to the assessment of a scholarship called “Beca 18”, the biggest scholarship that the public institution called PRONABEC addresses every year since 2012. The intervention included additional tools for a group of applicants: (i) full-time online classes for 2 to 4 months; (ii) an electronic device with an internet connection; and (iii) the admission exam payment fully covered up to 2 times. The objective of this thesis is to evaluate the effectiveness of this intervention in increasing the likelihood of the treated to access higher education through the 2022 “Beca 18” scholarship process. As the treatment was not randomly assigned, a control group was estimated using the Propensity Score Matching methodology based on individual characteristics. Results showed that there is no statistically significant effect of the intervention in the treated applicants and invite to re-evaluate its design and implementation.

Employing the causal inference methods (matching for binary and continuous treatments), I examined the impact of conservation payments on corn yield. I used the propensity score and covariate distance matching and generalized propensity score methods to manage the problem of selection bias since the enrollment of conservation programs (i.e., receiving conservation payments) is not a randomized experiment. Using USDA Economic Research Service – Agricultural Resource Management Survey (ERS-ARMS) field-level data, I assessed whether receiving conservation payments had harm on corn yield in the Mississippi and Arkansas Delta. The findings from the two binary matchings showed that receiving conservation payments didn’t decrease corn yield. The generalized propensity approach revealed that lower conservation payments received held higher corn yield while higher conservation payments led to lower corn yield.