Past research consistently suggests that single people (i.e. singles) are stigmatized, but do they constitute a stigmatized 'group'? The current research will provide deeper insight into the stigmatization and well-being of singles by understanding the ‘group-y’ nature of singles, and how identification with groups and perceptions of groups map onto discrimination and prejudice. Study 1 will examine the extent to which singles identify as part of a group. Participants will be assigned a novel minimal group identity and then complete measures of group identification for four distinct group memberships (e.g., minimal group, relationship status, sexual orientation, nationality). We hypothesize that single participants' identification with their single group will be lower compared to other identities—including partnered people—although a smaller subset of singles may identify strongly with other singles. We also hypothesize that singles in general will perceive less discrimination towards singles relative to other aspects of their identity. In contrast, Study 2 will examine the extent to which singles are perceived as a group and the extent to which they are perceived as being responsible for their group membership. Participants will complete measures of entitativity and perceptions of responsibility for similar out-group identities as in Study 1 (e.g., single people or people in romantic relationships, sexual or asexual people, etc.). We hypothesize that singles will be rated lower in entitativity than people in romantic relationships and other groups, yet rated higher in responsibility than other groups. Moreover, we hypothesize that prejudice towards singles will be more acceptable than prejudice towards other groups. Throughout both studies, we will use Bayesian sequential analyses in order to efficiently acquire evidence in favor or against our experimental hypotheses. We discuss the importance of group-based theoretical perspectives for understanding the current and future stigmatization and well-being of singles.

Machine learning algorithms create models from training data for the purpose of estimation, prediction and classification. While releasing parametric machine learning models requires the release of the parameters of the model, releasing non-parametric machine learning models requires the release of the training dataset along with the parameters. Indeed , estimation, prediction or classification with non-parametric models computes some form of correlation between new data and the training data. The release of the training dataset creates a risk of breach of privacy. An alternative to the release of the training dataset is the presentation of the non-parametric model as a service. Still, the non-parametric model as a service may leak information about the training dataset. We study how to provide differential privacy guarantees for non-parametric models as a service. This cannot be achieved by perturbation of the output but requires perturbation of the model functions. We show how to apply the perturbation to the model functions of histogram, kernel density estimator, kernel SVM and Gaussian process regression in order to provide (, δ)-differential privacy. We evaluate the trade-off between the privacy guarantee and the error incurred for each of these non-parametric machine learning algorithms on benchmarks and real-world datasets. Our contribution is twofold. We show that functional perturbation is not only pragmatic for releasing machine learning models as a service but also yields higher effectiveness than output perturbation mechanisms for specified privacy parameters. We show the practical step to pertur-bate the model functions of histogram, kernel SVM, Gaussian process regression along with kernel density estimator. We evaluate the tradeoff between the privacy guarantee and the error incurred for each of these non-parametric machine learning algorithms for a real-world dataset as well as a selection of benchmarks.

Many studies consider ethnicity as an equivalent term for the country of birth. This could neglect ethnic heterogeneity within the sending country. Focusing on German-born, Polish-born, and Russian-born immigrants in the 1920 and 1930 U.S. census, I propose an ethnicity variable constructed based on the linguistic origin of the surname using an artificial intelligence algorithm. Employing this ethnicity variable, I study ethnic segregation within each immigrant group defined based on the country of birth. Results suggest the degree of within-group ethnic segregation was high. Specifically, ethnic majorities within each immigrant group generally resided in areas with significantly more compatriots.

Redistricting is the problem of partitioning a set of geographical units into a fixed number of districts, subject to a list of often-vague rules and priorities. In recent years, the use of randomized methods to sample from the vast space of districting plans has been gaining traction in courts of law for identifying partisan gerrymanders, and it is now emerging as a possible analytical tool for legislatures and independent commissions. In this paper, we set up redistricting as a graph partition problem and introduce a new family of Markov chains called Recombination (or ReCom) on the space of graph partitions. The main point of comparison will be the commonly used Flip walk, which randomly changes the assignment label of a single node at a time. We present evidence that ReCom mixes efficiently, especially in contrast to the slow-mixing Flip, and provide experiments that demonstrate its qualitative behavior. We demonstrate the advantages of ReCom on real-world data and explain both the challenges of the Markov chain approach and the analytical tools that it enables. We close with a short case study involving the Virginia House of Delegates.

We argue that rising supply of experience not only reduces experienced workers’ relative wages but also their relative labor market participation. From a theoretical model we derive predictions which we quasi-experimentally investigate, using variation across U.S. local labor markets (LLMs) over the last decades and instrumenting experience supply by the LLMs’ age structures a decade earlier. We find that aging substantially reduces experienced workers’ relative wages and employment rates, and also their labor market participation rates. Our results imply that the effect of demographic change on labor markets might be more severe than previously recognized, as it reaches beyond wages.

Making use of the Annual Social and Economic (ASEC) supplement to the Current Population Survey (CPS), I study job mobility in the USA in 1975-2017. I document a pronounced increase in job mobility from the 1970s to the 1990s, i.e., the annual share of continuously employed job-to-job movers rises from 5.9 percent of the labor force in 1975-1979 to 8.8 percent in 1995-1999. Job mobility exhibits a downward trend since the turn of the millennium. Furthermore, job mobility has an unconditional correlation of-0.86 with the unemployment rate at business-cycle frequencies, varying by around three percentage points over the business cycle.

The Statistical Atlases published by the Census Bureau in the late 1800s utilized a number of novel methods for displaying data. In this paper, we examine the use of framed spine and mosaic plots used in two plates of the Statistical Atlas of 1870. We use forensic statistics to recreate the data using available census information, and then use that data to create framed charts using modern plotting methods. We then examine the effectiveness of the framed charts compared to other alternatives with a user study. The data and code for this study are available online.

Motivated by the desire to inform climate policy, this dissertation consists of a compilation of three essays devoted to unravelling the significance of weather and climate as drivers of social welfare in two different contexts: the impact of weather fluctuations on labour markets and the importance of heterogeneity in determining individuals’ preferences for climate. Chapter 2 investigates the existence of weather-related changes in earnings and working times in the Mexican labour market. Leveraging quasi-random day-to-day variation in an individual’s exposure to weather, I provide evidence of extreme-rainfall days causing economy-wide meaningful reductions in working times. However, I observe no average heat effects on either earnings or working times, but only a small cold-related drop in minutes worked. Further analysis reveals considerable heterogeneity in temperature and precipitation effects across industries as well as job- and individual-specific characteristics, with non-trivial earnings losses observed for individuals working in unprotected working environments. Applying a residential choice model, Chapter 3 tests for the importance of origin climates in driving climate preferences of Mexican migrants to the United States (U.S.). I find temperature preferences to differ significantly between migrants originating from colder and warmer Mexican municipalities. Building upon the findings from Chapter 3, Chapter 4 further investigates heterogeneity in the amenity value of temperatures and individuals’ willingness to pay (WTP) for mitigation of global warming. The study employs a two-stage random utility sorting model to analyse location choice decisions of Mexican migrants to the U.S. The econometric model captures both observed heterogeneity and unobserved preference heterogeneity in temperatures. Evaluation of the first stage is done following a Bayesian estimation procedure. Examining heterogeneity in individual climate valuations reveals significant differences in the marginal willingness to pay (MWTP) for preferable temperatures across both demographic and clinal characteristics.

Higher education policies, such as student loans and grants, increase the possibilities for low-income students to attend college and earn high incomes later in life. For that reason , education policies are commonly assumed to increase intergenerational mobility. This paper shows that education policies have another effect, working in the opposite direction. Policies increase the overall importance of education for earnings versus other components such as luck. The human capital that education helps build is relatively persistent over generations, so that policies may actually reduce mobility. Which channel dominates is an empirical question. To that end, the paper develops a quantitative theory of the markets for higher education and labor. It features linked generations of heterogeneous agents, as well as heterogeneous colleges. A credible parameterization of the resulting model is possible due to recent empirical results. Counter to common assumptions, higher education policies turn out to decrease intergenerational mobility. Thus, there is a trade-off between welfare and intergenerational mobility. The paper includes two further sets of results. First, even when students are essentially uncon-strained in their extensive margin of college choice (going or not), they may still be constrained in their intensive margin of college choice (which college to go to). Second, the model yields a decomposition of the sources of intergenerational mobility.

Residential mobility rates in the United States have fallen considerably over the past three decades. The cause of the long-term decline remains largely unexplained. In this paper we investigate the relative importance of alternative drivers of residential mobility, including job opportunities, neighborhood and housing amenities, social networks, and housing and moving costs, using data from two waves of the New York Fed's Survey of Consumer Expectations. Our hypothetical choice methodology elicits choice probabilities from which we recover the distribution of preferences for location and mobility attributes without concerns about omitted variables and selection biases that hamper analyses based on observed mobility choices alone. We estimate substantial heterogeneity in the willingness to pay (WTP) for location and housing amenities across different demographic groups, with income considerations, proximity to friends and family, neighbors' shared norms and social values, and monetary and psychological costs of moving being key drivers of migration and residential location choices. The estimates point to potentially important amplifying roles played by family, friends, and shared norms and values in the decline of residential mobility rates.

This paper studies how corporate research and development investment (R&D) affects labor reallocation around the firm boundary, using employer-employee matched U.S. Census panel data. We document that R&D increases employee departures to entrepreneurship, but not to other incumbent firms or exit from employment. The ideas or skills that spill into startups seem to benefit from focused, high-powered incentives. For example, R&D-induced startups are much more likely to receive venture capital. The effect also seems to reflect ideas or skills that are poor complements to the firm's assets.

We examine whether shocks to a city’s average level of human capital are associated with persistent or permanent changes in human capital. The Mariel boatlift of 1980 represents an exogenous negative shock to Miami’s average human capital because it attracted a particularly low-skilled mix of immigrants. To assess whether the boatlift affected Miami’s future human capital accumulation, we construct a synthetic control group to analyze the effect of this shock. The results suggest that the Miami metropolitan area experienced slower increases in average human capital than its synthetic control city after the boatlift. This result is robust to alternative estimation strategies, data sets, and alternative hypotheses. The result implies that a decreased level of average skills tends to subsequently attract unskilled skilled workers more strongly than skilled workers, at least in the context of immigration shocks. We discuss plausible mechanisms for this finding and place the findings into the context of the spatial equilibrium model.

The formation and stability of social hierarchies is a question of general relevance. Here, we propose a simple generalized theoretical model for establishing social hierarchy via pairwise interactions between individuals and investigate its stability. In each interaction or fight, the probability of “winning” depends solely on the relative societal status of the participants, and the winner has a gain of status whereas there is an equal loss to the loser. The interactions are characterized by two parameters. The first parameter represents how much can be lost, and the second parameter represents the degree to which even a small difference of status can guarantee a win for the higher-status individual. Depending on the parameters, the resulting status distributions reach either a continuous unimodal form or lead to a totalitarian end state with one high-status individual and all other individuals having status approaching zero. However, we find that in the latter case long-lived intermediary distributions often exist, which can give the illusion of a stable society. As we show, our model allows us to make predictions consistent with animal interaction data and their evolution over a number of years. Moreover, by implementing a simple, but realistic rule that restricts interactions to sufficiently similar-status individuals, the stable or long-lived distributions acquire high-status structure corresponding to a distinct high-status class. Using household income as a proxy for societal status in human societies, we find agreement over their entire range from the low-to-middle-status parts to the characteristic high-status “tail”. We discuss how the model provides a conceptual framework for understanding the origin of social hierarchy and the factors which lead to the preservation or deterioration of the societal structure.

Las explicaciones de las migraciones calificadas han seguido un cause propio, relativamente distanciado de las explicaciones téoricas de las migraciones en general sin haber establecido un diálogo cercano, reproduciendo y no discutiendo lo suficiente categorías, conceptos y supuestos que replican estereotipos de género. Con base en la revisión de elementos empíricos evidenciados en la migración de personas calificadas en la región de norteamérica, en particular entre México y Estados Unidos, el artículo propone recoger aquellos elementos que abonan a la premisa planteada.

This dissertation frames affirmative action bans as the policy manifestation of colorblind, laissez faire racism; a term describing the hidden and often unintentional nature of racism. I explore several outcomes of affirmative action bans using difference in differences methodologies to test hypotheses that the racialized control of education ultimately leads to racial inequality in educational outcomes and later life. Chapter 2, “The Affirmative Action Ban Cascade: Where Students Enroll After Affirmative Action Bans,” finds that affirmative action bans have not only displaced underrepresented minority students from the most selective institutions, but they have also created a complex ‘cascade’ effect wherein underrepresented minority students have increasingly enrolled at for-profit colleges. Chapter 3, “The Machinations of Laissez Faire Racism in Action: Differences in Underrepresented Student STEM and non-STEM Degree Attainment in the Wake of Affirmative Action Bans,” finds that underrepresented minority student completion of undergraduate degrees in STEM was impacted more by affirmative action bans than their completion of undergraduate degrees in non-STEM majors. Because a degree in a STEM field is more prestigious and competitive than one in a non-STEM field, this result is consistent with the hypothesis that competition for coveted resources leads to reduced opportunities for underrepresented minority students. Chapter 4, “The Unintended Consequences of Affirmative Action: How Affirmative Action Bans Have Shaped Interracial Marriage,” finds that affirmative action bans have decreased interracial marriage; largely as a result of a decrease in White and Asian intermarriage. Together the chapters of this dissertation examine how laissez faire racism operates through affirmative action bans to produce racial inequality.

This study examines the historical establishment and shifting residential access to city parks over time. It begins by engaging and extending a theory of urbanization as socioenvironmental succession. It then assembles and analyzes longitudinal data on city park creation and neighborhood change in Houston from 1947 to 2015. Results reveal how socially privileged residents have long enjoyed unequal access to city parks as well as strong influence over where new ones are established. At the same time, growing minority populations have managed to gain more equitable access not by having new parks come to them so much as by moving into neighborhoods where Whites once lived. These dynamics obscure past processes and patterns of inequality while allowing newer, unexpected ones to emerge. We conclude with a discussion of what these findings imply for understanding not just unequal access to city parks but broader processes of urbanization.

Citizenship can accelerate immigrant integration and result in benefits for both local communities and the foreign-born themselves. Yet the majority of naturalization eligible immigrants in the United States do not apply for citizenship and we lack systematic evidence on specific policies to encourage uptake. In this study we analyze the impact of a policy change by the United States Citizenship and Immigration Service (USCIS), the standardization of the fee waiver process in 2010. This reform allowed low-income immigrants eligible for citizenship to use a standardized form to have their application fee waived. We employ a difference-in-differences methodology, comparing naturalization behavior among eligible and ineligible foreign-born before and after the policy change. We find that the fee waiver reform increased the citizenship rate by 1.5 percentage points. This amounts to about 73,000 immigrants per year gaining citizenship who would not have applied otherwise. In contrast to previous research on the take-up of federal benefits programs, we find that the positive effect of the fee waiver reform was concentrated among the subgroups of immigrants with lower incomes, language skills, and education levels, who typically face the steepest barriers to naturalization. Further evidence suggests that this pattern is driven by immigration service providers, who help mostly poorer immigrants file the fee waiver request.

In this paper, I address the U-shaped dynamics (a decrease followed by an increase) in the age at first marriage during the twentieth century. First, I show that the U-shaped dynamics have been steeper in Western that in other countries. Second, I find that these dynamics in Western Europe are strongly related to the post-WWII economic development. By contrast, in the nineteenth and the first half of the twentieth centuries age of marriage was much less correlated across Western countries. I propose a simple model where age of marriage is a function of search frictions and a structural change of the economy. Both factors put together generate U-shaped dynamics as a result of an industrial boom that mimics the post-WWII economic development, especially in Western countries.

Objectives Although emerging research suggests neighborhood characteristics can support and restrict social participation in older adults, further research regarding a wider range of neighborhood characteristics and interactions between individual and neighborhood characteristics is needed. This study explored associations between neighborhood characteristics and frequency of participation in three social activities among older adults and interactions between neighborhood characteristics and mobility limitation as they relate to participation. Method Data from the 2008 wave of the Health and Retirement Study linked with American Community Survey data were used. Participants included community-dwelling adults aged 65 years or older. Analysis involved multivariate logistic regression. Results High proportion of neighborhood residents aged 65 and older was associated with increased odds of more frequent participation in all three activities. High population density was associated with increased odds of club attendance. High neighborhood social cohesion was associated with increased odds of attending nonreligious meetings. Interactions between walking limitation and population . . .

Why are prices in some sectors increasing dramatically even as economy-wide technology and productivity improves? Education and healthcare are notable examples of sectors seemingly stricken by constantly rising prices. Educational expenditures doubled between 1980 and 2005, even as math scores remained flat during that period. Physician and nurse salaries have almost tripled since 1960. At the same time, home appliances and telecommunications have become much cheaper. Why? Is there a common factor that unites sectors. . .