The Other Side of Assimilation: How Immigrants are Changing American Life

The immigration patterns of the last three decades have profoundly changed nearly every aspect of life in the United States. What do those changes mean for the most established Americans—those whose families have been in the country for multiple generations? The Other Side of Assimilation shows that assimilation is not a one-way street. Jiménez explains how established Americans undergo their own assimilation in response to profound immigration-driven ethnic, racial, political, economic, and cultural shifts.

Co-sponsored with the Center for the Study of International Migration and the Race and Ethnicity Sociology Working Group

The Incidence of Public Subsidies to Private Hospitals under Weak Governance: Evidence from India (joint with Radhika Jain)

Expanding public health insurance and enlisting private agents for service delivery are common policy strategies to meet the goals of universal health coverage, but there is limited evidence from developing countries to inform their design. This paper, joint with Radhika Jain from Harvard School of Public Health, provides quantitative evidence on how insurance design affects program performance and incidence in the context of a government-funded health insurance program that aims to provide free care to 46 million people in Rajasthan, India. We exploit a policy-induced natural experiment, and use administrative claims linked to patient surveys, to provide the first large-scale evidence of private hospital behavior under public health insurance.

Essays in Education and Crime in Colombia

This dissertation contains three essays in applied microeconomics. In the first chapter paper, I test whether the return to college education is the result of human capital accumulation or instead reflects the fact that attending college signals higher ability to employers. The second chapter provides evidence that parental incarceration increases children’s educational attainment. Finally, in the third chapter I derive a new expression that extends the Local Average Treatment Effect concept, to a setting with two sources of unobserved treatment heterogeneity.

"Renal Relationships: Understanding Living Kidney Donor Relationship Patterns"

Abstract: Who do we turn to in times of need? Traditionally, social support research has shown a strong preference to rely on strong ties in these scenarios - often, even when weak ties might be better positioned to help. However, this conclusion has recently been challenged by Small (2017), who argues that people often rely on weak ties for emotional support in stressful times, preferring to avoid more complicated strong ties. This suggests that the types of ties we activate in times of need varies by the situation. In this study, we apply this framework to the study of living donor kidney transplantation (LDKT), effectively asking: How does this behavior differ when the stakes are potentially life and death? Using a variety of primary and secondary datasets, we compare the distribution of LDKT ties to the distribution of ties who would be likely able to help, then seek to explain these relative utilization patterns as a function of medical fundamentals, social/spatial relationships, and qualitative reasoning invoked by survey respondents. Our preliminary findings show that LDKT patterns are primarily driven by social relationship quality, and far less by medical fundamentals such as the potential donors' health or genetic relationship to the patient.

"Can Labor Market Discrimination Explain Racial Disparities in Schooling? Evidence from WWII"

Abstract: Can the racial gap in labor market earnings explain black-white disparities in the schooling of the next generation? To answer this, we exploit the large increase in labor demand in markets that received WWII defense industry contracts. This increase in labor demand combined with a policy that prohibited discrimination by race and ethnicity in the defense industries resulted in significant increases in African American earnings and declines in the racial gap in earnings between 1940 and 1950. This was achieved largely via occupational upgrading among African Americans into semi-skilled professions. In contrast with women, whose progress in the labor market was largely reversed in short order, this occupational upgrading persisted for African Americans. We argue that this persistence is consistent with declines in statistical discrimination. Moreover, we find that in these same labor markets, the next generation of African Americans invested relatively more in their human capital, as measured by greater years of schooling and a decline in the black-white schooling gap. We explore three reasons why reductions in the black white earnings gap might lead to reductions in the black white schooling gap of the next generation. First, this would relax the financial constraint faced by many African American families, allowing their children to remain in school longer. Second, occupational upgrading might have increased the returns to human capital among African Americans. Finally, there may be political responses that result in changes in public funding and provision of schooling and other public goods that affect the human capital accumulation of the next generation of African Americans. We find evidence consistent with the first explanation only. We conclude that efforts to further reduce the racial gap in schooling might consider labor market interventions.

A Century of Educational Inequality in the United States

Abstract: The “income inequality hypothesis” holds that rising income inequality affects the distribution of a wide range of social and economic outcomes. Research highlighting the sharp increase in educational inequality in recent decades has fuelled concerns that rising income inequality has had damaging consequences for equality of educational opportunity, even while other researchers have provided descriptive evidence at odds with the income inequality hypothesis. In this paper we track long-term trends in family income inequalities in college enrollment ("enrollment inequality") using all available nationally representative datasets for cohorts born between 1908 and 1995. We show that the trend in enrollment inequality moved in lockstep with the trend in income inequality over the past century. There is one exception to this general finding: for cohorts at risk of serving in the Vietnam War, enrollment inequality was high while income inequality was low. During this period, enrollment inequality was significantly higher for men than for women. Aside from this singular confounding event, evidence on a century of enrollment inequality establishes a strong association between income inequality and enrollment inequality, providing support for the view that rising income inequality is fundamentally changing the distribution of life chances.
Co-sponsored with the Social Stratification, Inequality and Mobility Working Group

Machine Learning for Causal Inference

Abstract: Given advances in machine learning over the past decades, it is now possible to accurately solve difficult non-parametric prediction problems in a way that is routine and reproducible. In this talk, I'll discuss how these machine learning tools can be rigorously integrated into observational study analyses, and how they interact with classical ideas around randomization, semiparametric modeling, double robustness, etc. When deployed carefully, machine learning enables us to develop statistical estimators that reflect the study design more closely than basic linear regression based methods.

Race, Culture and Health: Conceptual and Methodological Innovations

Abstract: Building a culture of health and achieving health equity requires that we engage cultural processes in a more meaningful way. Cultural processes and systems are commonly referenced in health inequity scholarship but empirical research generally lags behind this conceptual emphasis. I argue that employing a transdisciplinary approach to examining intersections of culture, structure and racism is a valuable analytical tool for understanding the production of social and racial inequities in health. In this talk, I’ll discuss conceptual work advancing the concept of “cultural racism” in relation to racial inequities in health and will also provide an overview of related empirical projects: 1) a laboratory experiment examining the effects of media-based racism on physiological, psychological and behavioral stress responses, 2) a data science project exploring ways to assess chronic exposure to media-based racism and possible links to population health and 3) the use of virtual reality to promote structural competence regarding the structural and cultural roots of racism. In lieu of a deep dive on a single project or paper, the presentation seeks to support a rich conversation about the need for conceptual and methodological innovation in service of better understanding and addressing racial inequities in health.

Diversity, Immigration, and Public Opinion in the U.S.

Abstract: What factors animate public opinion towards immigrants? A substantial literature has tested the impact of individual objective traits like education and job market status on immigration attitudes. In addition, researchers have explored the role of subjective factors like immigrants’ perceived impact on society. However, prior quantitative research has generally overlooked a key aspect: natives’ impressions of who immigrants are. Immigrants in the U.S. are increasingly diverse and evidence suggests that natives prefer certain types of immigrants. Yet, survey questions gauging immigration attitudes often refer to “immigrants” as if they were a single, homogenous group, which makes it hard to interpret survey takers’ answers. To fill this gap, we explore heterogeneity in subjective perceptions of immigrants and assess their attitudinal impacts. We systematically uncover these perceptions by using a Latent Class Analysis approach on a new set of survey items we developed. We find the presence of four different immigrant “archetypes” or multidimensional constellations of immigrant traits. These archetypes are shared across regions, social classes, and partisan lines and more powerfully predict immigration attitudes than typical independent variables used in extant research. Last, we discuss the theoretical and methodological implications of our findings.