Evaluating the impacts of different inclusion policies to reduce inequality: three Essays

Inequality remains at the forefront of social organization and economic policy debates, emphasizing the urgency for targeted interventions to promote equity and social mobility. According to Chancel et al. (2022), the richest 10% of the global population currently earns 52% of global income, whereas the poorest half obtains merely 8.5%. In practical terms, this translates into stark yearly earnings disparities—an individual in the top 10% of the global income distribution makes on average USD 122,100 per year, contrasted with just USD 2,800 for someone in the poorest half. Such figures highlight the need for evidence-based policies that can mitigate persistent inequality. A broad literature points to policies that boost educational equity, promote social mobility, and tackle discrimination as key policies to reducing inequality (OECD, 2012; D’Addio,2007). However, more empirical evidence is needed on what makes these policies both efective and cost-efficient (D’Addio, 2007; Biasi, 2023). In this dissertation, I address this gap by investigating how targeted programs can shape individual trajectories and social outcomes in two distinct contexts: (i) disadvantaged students in Colombia, a middle-income country known for pronounced inequality, and (ii) socioeconomically disadvantaged individuals with mental health conditions who have been convicted in the United States, a high-income country grappling with significant social and racial disparities. The dissertation comprises three essays that employ impact evaluation methods to shed light on the mechanisms and outcomes of inclusion policies. The first two essays draw on a randomized controlled trial (RCT) that assesses the e"ects of a mentoring program for low-income high-school students in Bogotá-Colombia. The first essay focuses on the mentees, measuring improvements in academic outcomes and aspirations. The second essay pivots to the mentors, measuring how mentoring influences their beliefs and prosocial behavior through experiments that capture changes in attitudes and social preferences. The third essay employs a staggered di"erence-in-di"erences design to explore the causal effect of diversion policies on crime. Specifically, I examine the establishment of 339 mental health courts (MHCs) across US counties from 1980 to 2021 as a natural experiment. Using crime and arrest data from the FBI’s Uniform Crime Reports (UCR) alongside a newly collected dataset on MHCs, I test whether these specialized courts can reduce crime by reducing recidivism rates among individuals with mental health conditions.