Research

The COVID-19 pandemic disrupted primary care services worldwide, reducing quality of care. We assess whether information provision and financial incentives to primary care professionals supported quality of care recovering to pre-pandemic levels. Data on 37 quality-of-care indicators from 287 primary care practices (5,250,531 adults) in Catalonia were analysed monthly from 2019 until 2024. Financial incentives were suspended in 2020; 13 indicators were reintegrated into pay-for-performance schemes in 2021, while 24 remained out of the schemes until 2023. Early incentivisation doubled the likelihood of recovery before 2023, with effects varying by indicator type. However, many practices recovered late-incentivised indicators when they were informed only, before financial incentives resumed. Financial incentives accelerated quality-of-care recovery after a system shock, particularly when tailored to indicator types and practice contexts, and complemented by timely information provision.

The relative efficacy of information provision versus financial incentives in improving primary care quality remains a critical, unresolved question. We investigated these two strategies in Catalonia’s public primary care system from 2010 to 2019: an innovative online platform providing real-time quality indicator information, and targeted economic incentives for achieving indicator goals. We conducted an interrupted time series regression analysis on data from 272 primary care practices (5,628,080 patients). Informed indicators showed positive impacts in 75 percent of cases, and incentivized indicators in 64 percent of cases. Both interventions were associated with step reductions in variability and significant trend improvements. Our findings reveal that information provision alone can match or even surpass the impact of financial incentives in improving care quality and reducing practice variability, offering a cost-effective, scalable approach to primary care quality enhancement.

This paper examines how workload affects the provision of care in a large but understudied segment of the healthcare sector – maternity wards. I use detailed patient-level administrative data on childbirth, and exploit quasi-random assignment of unscheduled patients to different staffing ratios. I find that the probability of C-section increases at a decreasing rate with workload. I show that this result is not attributable to patients’ differential sorting across staffing levels. Instead, I find evidence that C-sections are used to alleviate midwives’ workload – they are faster than vaginal births and performed by physicians. I also exploit patient’s civil status to determine whether the effect varies with patient’s bargaining power – single women are on average more likely to be alone in the delivery room. Consistent with induced demand, only single patients are more likely to receive a C-section when admitted at high workload levels.

This paper provides new evidence on the link between patient outcome and physician experience. Using birth certificates data from a large hospital in Italy, I analyze whether cesarean section surgeons who have performed more procedures in the recent past observe an improvement in performance. By using data from the Italian health care system, where patients are not allowed to choose their physician, I lower concerns of potential reverse causality (selective referral). I find evidence indicating a strong learning-by-doing effect: for emergent cases, a one standard deviation increase in recent experience reduces the likelihood of neonatal intensive care unit admission by nearly 3.2 percentage points (13.8 percent) and of being born with a low Apgar Score by about 1.9 percentage points (13.2 percent), all else equal. This effect is not present for the case of elective C-sections.

We study the long-term effects of intergroup contact on nation building by exploiting a national lottery that randomly allocated conscripts to different military areas across Spain. For men born in regions featuring a strong regional identity, we find that being assigned to military service in a region different from one’s region of birth substantially increases self-identification as Spanish and reduces the likelihood of voting for a regionalist party. Moreover, in support of intergroup contact as the main mechanism behind these results, we find that movers are more likely to have friends from another region than nonmovers.

We study the impact of the COVID-19 pandemic on domestic violence in 11 countries with different ex-ante incidence of domestic violence (DV) and lockdown intensity. We use a novel measure of DV incidents that allows us to make cross-country comparisons: a Google search intensity index of DV-related topics. Our difference-in-difference estimates show an increase in DV search intensity after lockdown (31 percent), with larger effects as more people stayed at home (measured with Google Mobility Data). The peak of the increase in DV appears, on average, 7 weeks after the introduction of the lockdown. While we observe that the positive impacts on DV is a widespread phenomenon in developed countries is more than twice as strong as in Latin American countries. We show that the difference in impact correlates with the intensity of compliance with stay-at-home measures in the two groups.

This study examines the challenges of analyzing domestic violence (DV) in Latin America and the Caribbean (LAC) and seeks to improve measurement through two main contributions. First, we collect and describe traditional DV data sources (house- hold surveys and administrative records) across 19 countries. The analysis reveals substantial gaps in data availability, with infrequent and outdated survey efforts in most countries. Nevertheless, surveys confirm high DV prevalence, with at least one in five women reporting victimization in all countries examined, and highlight pervasive underreporting that limits the reliability of administrative crime data. Second, we examine the properties of a novel, high-frequency indicator based on online search behavior: the Google Domestic Violence Index. Using administrative data from eight LAC countries, we find that the index is strongly correlated with calls to DV helplines but shows weaker association with police reports or emergency calls. The evidence suggests that the index captures early-stage, information-seeking behavior and may provide a real-time signal of latent victimization not reflected in official statistics. Our findings underscore the potential of digital data to complement traditional sources and to support more timely, responsive approaches to tracking DV.