The outbreak of COVID-19 in 2020 inhibited face-to-face education and constrained exam taking. In many countries worldwide, high-stakes exams happening at the end of the school year determine college admissions. This paper investigates the impact of using historical data of school and high-stakes exams results to train a model to predict high-stakes exams given the available data in the Spring. The most transparent and accurate model turns out to be a linear regression model with high school GPA as the main predictor. Further analysis of the predictions reflect how high-stakes exams relate to GPA in high school for different subgroups in the population. Predicted scores slightly advantage females and low SES individuals, who perform relatively worse in high-stakes exams than in high school. Our preferred model accounts for about 50% of the out-of-sample variation in the high-stakes exam. On average, the student rank using predicted scores differs from the actual rank by almost 17 percentiles. This suggests that either high-stakes exams capture individual skills that are not measured by high school grades or that high-stakes exams are a noisy measure of the same skill.

Worldwide, gang proliferation is fought mostly with tough punishment strategies such as sweeps. In this paper, I study their causal effect on crime for arrested individuals and known peers following a difference-in-differences strategy. I also take advantage of the network structure I retrieved to assess peer effects and identify key players. I perform such an analysis with novel administrative data from the Metropolitan Area of Barcelona, where Latin gangs expanded rapidly and where a stark policy change occurred. Results show significant reductions in crimes of arrested individuals and their peers, particularly in crimes against the person. The areas of the sweeps benefit from improvements in crime, health and education. I further conduct an innovative counterfactual policy exercise comparing sweep outcomes with theoretically predicted crime reductions when removing key players. This exercise indicates that sweeps could have achieved a 50% larger reduction in criminal activity had key players been removed. In this way, a network analysis provides insights on how to improve policy design.

Cross-border medical care, defined as care facilitated by a local health provider under pre-established regional agreements as in the case of EU citizens accessing care within EU countries, has been on the rise. Unlike medical tourism, typically sought by patients through their own volition and paid for out-of-pocket, cross-border medical care is often reimbursable or paid for directly by the responsible government. Yet, because nations vary in the extent of health coverage offered to their residents, these expenditures are often only partially reimbursed. The resulting financial burden for some countries can be large and not reciprocal, straining regional and country-level finances. We analyze the effectiveness of a legislative measure adopted by a Spanish region in January 2012 with the purpose of curbing cross-border medical care. Using a comprehensive administrative dataset of all medical procedures performed in the country between 2008 and 2015, we find that the measure led to a drastic drop in the number of foreigners’ hospitalizations and a reduction of 4.8 million euros/trimester in costs. Finally, the decrease in hospitalizations did not disproportionally affect patients based on their gender, age, or origin; although it fostered a reduction in scheduled hospitalizations, as would be expected.

Bullying is a problem that affects children and teenagers around the world and its repercussions can endure throughout adult life. Its prevalence is, in part, a product of the lack of information and the paucity of studies which analyse the wide-ranging consequences for the individuals involved. The main objective of this research is to study the incidence of bullying on the academic performance of students in education centres in the Madrid Region. The databases used are those of Competency Tests carried out on all 10th grade students in Madrid during the year 2017. These external assessment tests evaluate Spanish language, English language, Mathematics, and Geography and History. Along with these tests, the students, their families, their teachers and head teachers complete comprehensive questionnaires. To analyse all these data, we carry out a multilevel methodological approach to identify the quantitative association of bullying with academic performance and to estimate the probability that performance is affected by the level of bullying that exists in the education centres. The results indicate that bullying has a negative impact on all the competencies evaluated, that the probability of a lower academic performance increases in environments where there is bullying and that bullying can affect students with low or high academic achievement in different ways, depending on what competency is evaluated.

We estimate the labour market and health effects of a long-term unemployment (LTU) subsidy targeted to middle aged disadvantaged workers. In order to do so, we exploit a Spanish reform introduced in July 2012 that increased the age eligibility threshold to receive the subsidy from 52 to 55. Using a within-cohort identification strategy, we show that men ineligible for the subsidy were more likely to leave the labour force. In terms of health outcomes, although we do not report impacts on hospitalizations when considering the whole sample, we do find significant results when we separate the analysis by main diagnosis and gender. More specifically, we show a reduction by 12.9% in hospitalizations due to injuries as well as a drop by 2 percentage points in the probability of a mental health diagnosis for men who were eligible for the LTU subsidy. Our results highlight the role of long-term unemployment benefits as a protecting device for the health (both physical and mental) of middle aged, low educated men who are in a disadvantaged position in the labour market.

This paper analyzes the effect of wealth taxation on mobility and the consequences for tax revenue and wealth inequality. We exploit the unique decentralization of the Spanish wealth tax system in 2011—after which all regions levied positive tax rates except for Madrid—using linked administrative wealth and income tax records. We find that five years after the reform, the stock of wealthy individuals in the region of Madrid increases by 10% relative to other regions, while smaller tax differentials between other regions do not matter for mobility. We rationalize our findings with a theoretical model of evasion and migration, which suggests that evasion is the mechanism most consistent with all of the mobility response being driven by the paraíso fiscal. Combining new subnational wealth inequality series with our estimated elasticities, we show that Madrid’s status as a tax haven reduces the effectiveness of raising tax revenue and exacerbates regional wealth inequalities.