The existence of amenities matters to understanding people’s residential choices. Our theoretical model extends the standard urban model by introducing exogenous amenities to explain population allocation within cities. To estimate the model predictions, we focus on historic amenities using detailed geolocated data for 579 European cities. We analyze how the shape of city centers endowed or not endowed with these amenities is affected. We measure historic amenities with the location of buildings from the Roman, Medieval, and Renaissance-Baroque periods. Our results show that cities with historic buildings in their centers have steeper population density gradients, are more compact and centralized, and have been less affected by the suburbanization processes caused by transportation improvements. Heterogeneity analyses show that the quantity and the quality of historic buildings also matter. Several robustness checks controlling for natural and modern amenities and testing for the spatial scope of these amenities verify our main results.

This paper provides novel evidence of the mental health effects of the Covid-19 outbreak. Between April 2020 and April 2022, we run four waves of a large representative survey in Spain, which we benchmark against a decade of pre-pandemic data. We document a large and sudden deterioration of mental health at the beginning of the pandemic, as the share of people reporting being depressed increased from 16% before the pandemic to 46% in April 2020. This effect is persistent over time, which translates into important and irreversible consequences, such as a surge in suicides. The effect is more pronounced for women, younger individuals and those with unstable incomes. Finally, using mediation analysis, event studies and machine learning techniques, we document the role of the labor market as an important driver of these effects, as women and the young are more exposed to unstable income sources.

Minimum wages have been widely discussed in the literature. The minimum wage impact on employment strongly depends on labor market concentration and the point at which it is located in the income distribution. Therefore, its study essentially involves exploring whether it has been set too far, beyond the competitive market wage. In 2019, the Spanish government decided to raise the minimum wage by 22.3%. This increase is of a previously unseen magnitude. Using rich administrative data, we combine Propensity Score Matching and a Difference-in-Differences model to evaluate the short-run employment effect of this policy. We find that the reform increased the probability of job loss within a range of 0.38 pp. (7.8%) and 0.44 pp. (9.2%) for workers below the new minimum wage, which implies an employment elasticity between 0.3 and 0.4. In addition, our results suggest that the bulk of this effect is concentrated in the group of workers furthest from the new minimum wage. This is the segment of the income distribution that bore the bulk of the employment costs of the minimum wage increase.

This paper empirically tests whether property owners react to the salience of taxes in terms of their consumption of public services. Exploiting a policy change that reduced fares on public transport in various municipalities of the metropolitan area of Barcelona, we find that salience of the tax to finance the fare reduction increases the consumption of public transportation. Our empirical findings support the hypothesis that the salience of taxes may affect the consumption behavior of taxpayers and our main results contribute to previous empirical evidence relating tax salience and consumption behavior regarding public services.

The aim of this paper is to shed light on the effect of Low Emission Zones (LEZs) on traffic. LEZs are areas in which access is restricted for the most polluting vehicles. They have been found to be effective in reducing pollution, while the expected effect on traffic is not clear. Using high-frequency granular data on traffic for the city of Madrid, I analyse whether LEZ schemes are effective in reducing traffic within the area of implementation and whether they generate a displacement effect. Taking advantage of the exogeneity of the implementation timing, I develop a pre/post analysis based on time. Results suggest a reduction in traffic inside the restricted area and a displacement to all the other areas of the city. I find a switch to public transport for commutes directed towards the restricted area and rerouting of trips for destinations outside Madrid Central to be two of the possible mechanisms explaining these results. The reduction in transit inside the restricted area gradually decreases over time and disappears after 7 months. This is consistent with the renewal of the vehicles’ fleet with unrestricted and cleaner vehicles generated by the policy.

We use census data on external assessments in primary and secondary school in the Basque Country (Spain) to estimate learning losses due to the COVID-19 pandemic in March 2021, one year after school closures, which lasted from March to June 2020. Differences-in-differences with student and school-by-grade fixed effects show an average learning loss of 0.045 standard deviations, an effect which is smaller than short-run effects estimated by previous papers, and estimated after 6 months of one of the most successful school reopening campaigns among OECD countries. The effect is larger in Mathematics, moderate in Basque language, and none in Spanish language. Controlling for socioeconomic differences, learning losses are especially large in public schools, and also in private schools with a high percentage of low-performing students. On the other hand, we find a regression to the mean within schools, possibly due to a compressed curriculum during the whole period. Finally, we show that students’ with higher learning losses self-report significantly worse levels of socio-emotional well- being due to the pandemic.