It is well known that the number of non-English speakers is on the rise in the United States. What is less well known is that the largest proportion of this population is children under the age of 5. These young English language learners (ELLs) often demonstrate achievement gaps in basic math and reading skills when they start school. How best to educate this important and growing preschool population is a pressing concern for policymakers and practitioners. The chapters in this important book provide up-to-date syntheses of the research base for young ELLs on critical topics such as demographics, development of bilingualism, cognitive and neurological benefits of bilingualism, and family relationships, as well as classroom, assessment, and teacher-preparation practices. Each chapter reviews the research and answers the following questions: (1) What does the research clearly indicate for policy and practice?; (2) How solid is this database and what findings are emerging?; and (3) What should the research agenda be for young ELLs?

Income concentration in the U.S. rose sharply since the 1970s. But the share of wealth held by the top 1 percent increased less. This can be partially accounted for by a quantitative model of occupational choice, in which rich individuals choose to become entrepreneurs or managers. Collateral constraints induce entrepreneurs to hold more wealth, while managers earn higher wages as a result of competitive assignments to firms. Declining tax progressivity from 1970 to 2000 replaces top entrepreneurs with top managers, which can account for 65% and 30% of the increase in the share of wages and income earned by the top 1 percent, respectively. At the same time, the share of wealth held by the top 1 percent remains stable, as entrepreneurs decumulate but managers accumulate wealth.

T he American Dream promises that individual talent will be rewarded, regardless of where one comes from or who one’s parents are. Based on this ideal of equal opportunity, it’s tempting to believe that education and career outcomes reflect a natural sorting according to merit. But this presumption risks suggesting that those who do not thrive in school or the workforce lack talent— when, in fact, they more often lack sufficient systemic support on the journey to reach their full potential. In the United States, there is a broadly held presumption that the journey along the pipeline from kindergarten to early career success gradually reveals each child’s innate abilities.1 This presumption is widespread not only in the general public, but among students themselves, who self-identify and identify each other as either academically gifted or generally undistinguished. All too often, these beliefs about one’s talents and the talents of one’s peers become selffulfilling prophesies. The notion that talent . . .

In an article published in the Review (Antman and Duncan, 2015), we document how racial identity responds to state affirmative action policy. A coding error was recently brought to our attention that resulted in 0.55% of our sample being misclassified in terms of their African ancestry.1 We regret and apologize for this error. Although the error only affected a tiny percent of the overall sample, the correction changes the conclusion of how individuals with multiracial African ancestry respond to state affirmative action bans, from a negative and statically significant effect to a positive and statistically significant effect. The corrected Table 3 shows the updated results. The coefficients for college aged individuals with African ancestry reported in Table 5 are also now positive, but are no longer statistically significant at conventional levels. Correcting the error does not change the conclusions for individuals with only African ancestry or no African ancestry. None of the Asian ancestry classifications, and thus none of the results for individuals with Asian ancestry (Table 4 and the last two columns of Table 5) were affected by the coding error. There are no meaningful changes to the summary statistics in Table 2 except in the column for those with multiracial black ancestry. The most notable change is the fraction of individuals with multiracial black ancestry who self-identify as black: 49.37% in the original table and 90.86% in the updated table.2 For a further explanation and a complete set of updated results, see Antman and Duncan (2019). We continue to find that racial identity responds to state affirmative action policy, albeit with a different conclusion for multiracial blacks, and are now able to distinguish stronger effects for multiracial individuals with more distant connections to their minority group.

Research consistently reports a veteran mortality disadvantage relative to nonveterans, but has not considered the contribution of service-connected disability to this differential. We use data from the 1986 and 1989 National Health Interview Survey-2011 Linked Mortality Files ( N = 124,122) to estimate multivariate Cox regression models of the association between veteran status and mortality, taking service-connected disability status into account. Bivariate analyses demonstrate higher mortality risk, lower socioeconomic status, and poorer health and functioning among veterans with a service-connected disability than among nonveterans and veterans without a service-connected disability. Multivariate models confirm a mortality disadvantage for all veteran service-connected disability subgroups, which is reduced by the inclusion of exogenous sociodemographic variables and substantially mediated by the health/functional limitation status measures. Results indicate that service-connected disability status accounts for some variation in, and may have a cumulative effect on, the veteran mortality disadvantage. When possible, future research should account for service-connected disability status when studying veteran–nonveteran mortality differentials.

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location‐based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health‐specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision‐making and policy, ultimately aimed at reducing the burden of cancer.

Purpose: Approximately 16% of U.S. births to women aged 15e19 years are repeat (second or higher order) births. Repeat teen mothers are at elevated risk for poor perinatal outcomes. Geographic clustering and correlates of repeat teen birth are unknown. Methods: Data from birth certificates on N ¼ 629,939 teen births in N ¼ 3,108 U.S. counties in 2015 e2017 were merged with data on county-level demographic, socioeconomic, and health provider characteristics. We identified contiguous clusters of counties with significantly elevated rates of first teen births only, repeat teen births, both, or neither between 2015 and 2017 and compared demographic, socioeconomic, and medical provider characteristics of counties between 2010 and 2016 in each cluster type. Results: A total of 193 counties (6.21%) had high rates of repeat births only; 504 (16.22%) had high rates of first teen birth only; 991 (31.89%) had high rates of both repeat and first teen births; and 1,420 (45.69%) had neither. Counties with high repeat (vs. first only) birth rates had higher rates of poverty and unemployment, higher levels of income inequality, lower high school graduation rates, a higher share of racial and ethnic minority residents, fewer publicly funded family planning clinics per capita, and more women receiving contraceptive services at publicly funded clinics. Conclusions: First and repeat teen births cluster in differentially resourced geographic areas. Counties with high repeat teen birth rates have lower socioeconomic conditions than counties with high rates of first teen births only. These counties are more reliant on publicly funded family planning clinics but have fewer of them per capita.

An income inequality index number cannot summarize the complete information in the distribution. We propose a family of inequality index curves, which includes curves generated by popular inequality index numbers (e.g. the top income shares, the Gini coefficient and the Palma ratio). The family has two advantages: (1) The family has an axiomatic foundation. (2) Each curve in the family contains the full information of the distribution. We use the family and micro level data to show that the bottom and middle income people in the U.S. became more equally relatively poor (not just relatively poorer) from 1990 to 2010.

The shifting of risk from institutions to individuals in the new economy and increasing occupational polarization has led to greater prevalence and heightened consequences of economic insecurity for U.S. workers in the absence of universal social safety nets. Using data from the new midlife follow-up of the High School and Beyond study, I investigate the link between individuals’ academic preparation in high school and their risk of economic insecurity at midlife in the context of a stratified and changing economy. I focus on how individuals’ pre-labor market skills influence their long-term economic outcomes, with particular attention to how gendered opportunity structures shape men’s and women’s experiences of economic vulnerability. I examine three dimensions of economic insecurity: exposure to bad jobs, labor force attachment, and subjective economic insecurity. Taking a longer view of the link between education and economic outcomes, my findings reveal how high school prepares students for resilience across the life course. My research can increase our understanding of how the interaction between workers’ pre-labor market characteristics and a stratified labor market contribute to significant economic inequalities among middle-aged workers.

Research and policy efforts to increase the racial diversity of STEM fields have focused on how to prime the educational pipeline through interventions in schools and universities. This thesis focuses on recent college graduates who have successfully cleared a key hurdle and graduated with a bachelor’s degree in computer science. I use original survey data from three public universities across Texas to determine whether there are differences in first job outcomes between Hispanic and non-Hispanic computer scientists on the elite tech labor market. I find that university attended is the most consistent predictor of labor market success. Differences between Hispanics and non-Hispanics in job outcomes are mostly attributable to the concentration of Hispanic computer science degree holders in a non-elite, geographically peripheral university. Controlling for university attended, Hispanics are as likely to work in a prestige tech hub and in a core software job as their white and Asian peers; however, they earn lower wages. In addition, results suggest a positive association between geographic mobility, higher earnings, and the likelihood of working in desirable, degree-related jobs. Results suggest that a closer inspection of segregational mechanisms at the post-secondary level is needed to fully understand its effects on elite job opportunities. Although a degree in computer science can provide a ticket to one of the most lucrative occupational fields in Texas, racial stratification within this field occurs early in the career and likely translates into long-lasting socioeconomic inequalities.

This paper examines whether the institutional quality of immigrants’ origin countries matters when testing the relationship between immigration and the US states’ economic freedom scores. Our results show that, in the short run, the relationship between economic freedom and immigrants from countries ranked in the second quartile of the Fraser Institute’s Economic Freedom of the World report is negative and statistically significant, but it is not economically significant. In the long run, the relationship between economic freedom and immigrants from countries ranked in the bottom quartile of the EFW report is positive and statistically significant, but it is not economically significant. For other immigrant groups coming from countries that rank higher in terms of economic freedom, the relationship is negative but is not statistically significant or is weakly significant. Our results are robust to various specifications.

We document the falling socioeconomic status of American households without private vehicles and the continuing financial burden that cars present for low-income households that own them. We tie both these trends to the auto-orientation of America’s built environment, which forces people to either spend heavily on cars or risk being locked out of the economy. We first show that vehicle access remains difficult for low-income households and vehicle operating costs remain high and volatile. Using data from the Panel Study of Income Dynamics, Survey of Consumer Finances, and Census Public Use Microdata, we then show that in the last fifty years households without vehicles have lost income, both in absolute terms and relative to households with vehicles. We link these trends to the built environment by examining the fortunes of carless households in New York City, and particularly in Manhattan. Most of New York’s built environment did not change to accommodate cars, and in New York the fortunes of the carless did not fall. Our results suggest that planners should see vehicles, in most of the United States, as essential infrastructure, and work to close gaps in vehicle access.

This study presents a new approach to evaluating energy efficiency potential that provides a more accurate, granular, and flexible estimate of the cost-effective energy efficiency potential in households of various income ranges. Results from this work estimate that in U.S. single-family households with income less than 200% of the federal poverty level, energy efficiency packages tailored to maximize net present value could result in an estimated $13 billion per year in energy cost savings, or $670 per year for an average household, corresponding to about 1 EJ (0.9 quads) of annual primary energy savings. These types of metrics can be estimated for other geographies (regions, states, and counties) and for other ranges of household income. These results can be used by policymakers and program designers to improve the cost-effectiveness of income-qualified programs and to improve the equity of non-income-qualified programs. The results can also be used to understand how energy efficiency opportunities differ between urban and rural areas, as well as how energy efficiency can spur economic development in areas that have had high poverty rates for decades.

This paper studies the origins and function of customs aimed at restricting women’s sexuality, such as a particularly invasive form of female genital cutting, restrictions on women’s freedom of mobility, and norms about their sexual behavior. The analysis tests the anthropological theory that a particular form of pre-industrial subsistence – pastoralism – favored the adoption of such customs. Pastoralism was characterized by heightened paternity uncertainty due to frequent and often extended periods of male absence from the settlement, implying larger payoffs to imposing restrictions on women’s sexuality. Using within-country variation across 500,000 women in 34 countries, the paper shows that women from historically more pastoral societies (i) are significantly more likely to have undergone infibulation, the most invasive form of female genital cutting; (ii) adhere to more restrictive norms about women’s promiscuity; (iii) are more restricted in their freedom of mobility. Instrumental variable estimations that make use of the ecological determinants of pastoralism support a causal interpretation of the results. The paper further shows that the mechanism behind these patterns is indeed male absence, rather than male dominance per se, or historical economic development.

This chapter assesses several factors that have contributed to New York City's post- I 980 family income and earnings trends based on race and ethnicity. These include: the outmigration of Whites in the l980s and 1990s; the increased number and share of immigrants; economic transformations affecting the relative growth of specific sectors and occupations; the relative economic position of New York City in that changing landscape, and; the broader national dynamic fueling the continued income polarization since the late I970s.

In this paper, I explore how property crime can affect static and dynamic general equilibrium behavior of households and firms. I calibrate a model with a representative firm and heterogeneous households where households have the choice to commit property crime. In contrast to previous literature, I treat crime as a transfer rather than home production. This creates a feedback loop wherein negative productivity shocks increase property crime which further depresses legitimate work and capital accumulation. These responses by households are particularly important when thinking about the effect of property crime on the economy. Household and firm losses account for 24% of compensating variation (CV) and 37% of lost production. This suggests that behavioral responses are quite important when calculating the cost of property crime. Finally, on the margin, decreasing property crime by 1% increases social welfare by 0.19%, but the effect is diminishing suggesting that reducing crime entirely may not be optimal from a policymakers perspective.

The determination of death in the United States can have strong financial implications. For example, a declaration of suicide can nullify life insurance benefits. However, the intent of death may be made by an elected official who is not required to have any medical training. Medical examiners and coroners determine cause of death when the death is sudden, violent, or untimely. Consequently, these officials can affect counts of sudden infant death syndrome, homicide, and suicide in a state. This paper uses a difference-in-differences model to estimate the effect of elected coroners versus appointed medical examiners on a state’s suicide rate. Elected coroners need not receive training in 13 states, must receive initial and continuous training in 16 states, and are required to be physicians in 4 states. We exploit state policy changes to the minimum required training elected coroners must complete. Data on the underlying intent of death is collected from the CDC Wonder mortality files from 1968 - 2016.

Post-earthquake fire (PEF) ignition events constitute a secondary consequence of an earthquake and may result in the loss of life and substantial property damage, especially in urban areas where the potential for fire spread and conflagration exists. These secondary hazards can cause severe structural and non-structural damage, potentially more significant damage than the direct damage caused by the initial earthquake, and can lead to catastrophic structural failures, devastating economic losses, and casualties. To manage the impact of PEF in urban areas, it is important to identify the potential ignition sources and quantify the vulnerabilities of these ignition sources as a result of earthquake-induced structural damage. The results of such analyses can be used to offer resiliency improvement investments and mitigation strategies in urban areas located in seismically active regions. Most of the previous PEF studies are data-driven, utilizing ignitions reported following recent earthquakes. However, in areas for which historical PEF data are not available, such as the Midwestern United States, a different methodology for developing a PEF model is needed. This paper describes an analytical model for quantifying the vulnerabilities of residential buildings to PEF by estimating the failure of ignition sources upon a probable seismic event. The underlying concept in developing the method is that (1) ignition sources in residential buildings remain unchanged before and after an earthquake, and (2) the total probability of PEF occurrence can be estimated by adjusting the probabilistic fire occurrence data for normal conditions (everyday operation of ignition sources) to account for the effect of the earthquake. This paper’s contribution to state of the art is in developing a new framework for estimating the probability of PEF for areas in which historical PEF data is unavailable. The developed framework uses the likelihood of ignition occurrence during normal condition as a baseline; this baseline is then adjusted using certain key parameters to capture spatial characteristics, ignitability, and potential seismic intensity of the study area to estimate the probability of PEF as a function of projected earthquake characteristics. The model was tested for St. Louis City as a populated area with potential future earthquake hazard because of its proximity to the New Madrid Fault zone. Using the National Fire Incident Reporting System dataset, the frequency of normal condition ignitions was determined as 1.97E−03 ignition per unit per year. Using the proposed PEF model considering PEFs caused by damage to drift and acceleration sensitive equipment and human actions, the projected frequency of PEF was estimated between 2.79E−06 and 2.81E−06 ignitions per household per year. Using this model, and the average number of households between 2010 to 2015, 175,854 households, it was estimated that in the next 50 years, approximately 25 households would experience fires related to probable earthquake events in St. Louis City.

Rationale As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI). Objectives To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California. Methods We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained. Measurements and main results In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4–16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY. Conclusions Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks.

We develop new aggregate total factor productivity (TFP) growth estimates for the USA between 1899 and 1941, and sectoral estimates at the most disaggregated level so far, 38 industries. We include hard-to-measure services, and a refined measure of sectoral labour quality growth. The resulting data set supersedes Kendrick (1961), showing TFP growth lower than previously thought, broadly based across industries, and strongly variant intertemporally. The four ‘great inventions’ that Gordon (2016) highlighted were important but less dominant in TFP growth than their predecessors in the British industrial revolution. The findings also make it unlikely the 1930s had the twentieth century's highest TFP growth.