The Port of Seattle and the Port of New York and New Jersey (NY/NJ) are key hubs serving international and domestic shipping in the United States. To reduce port emissions, both are investing in electrification, including by installing shore power and setting goals for 100% zero-emission harbor craft and trucks. By combining a series of simple, user-friendly tools, this study estimates how port electrification could reduce emissions and how that would benefit the surrounding regions in terms of air quality and public health. We combined ICCT's global Port Emissions Inventory Tool (goPEIT) with our Systematic Assessment of Vessel Emissions (SAVE) model to estimate the emissions from ocean-going vessels (OGVs), harbor craft, and drayage trucks in 2019. We used the area of each port's jurisdiction as the boundaries and together these were the baseline results. We then modeled the emissions in a "full electrification" scenario that assumed 100% shore power connection for OGVs while at berth in ports and 100% electrification of harbor craft and trucks. The baseline and full electrification scenario results were then put into the Intervention model for Air Pollution (InMAP), an open-source, reduced-complexity model that estimates the air quality and health impacts of emissions on nearby regions. We found that, at both ports, OGVs dominated total emissions and were more than 50% of carbon dioxide (CO 2), particulate matter (PM 2.5), and nitrogen oxides (NO x) emissions from OGVs, harbor craft, and drayage trucks in 2019. With full electrification, we estimated total PM 2.5 emissions reductions of 75% and 69% for Seattle and NY/NJ, respectively. Of all electrification technologies, electrifying harbor craft alone could reduce PM2.5 emissions for Seattle and NY/NJ by over 40% and 25%, respectively. In the full electrification scenario, the annual average PM2.5 concentration near the Port of Seattle would be reduced by 0.3–0.42 μg/m3, a considerable amount in light of Seattle’s annual average PM2.5 concentration of 7.5 μg/m3 in 2019. In addition, the total area affected by emissions from the Port of Seattle would be reduced from 292.1 km2 to 54.5 km2. With full electrification, the area near the Port of NY/NJ would also benefit greatly, with the City of Elizabeth seeing the highest air quality improvement of 0.82 μg/ m3 annual average PM2.5 concentration reduction, and Jersey City achieving a 0.59 μg/m3 annual average PM2.5 concentration reduction. The total area affected by emissions from the Port of NY/NJ would be reduced from 2,172.3 km2 to 504.5 km2. Air quality improvement near the Port of Seattle under the full electrification scenario is estimated to provide monetized health benefits of over $27 million annually. For the Port of NY/NJ, air quality improvement is expected to translate to at least $150 million of health benefits per year. This kind of quantification can help various ports apply for funding to support port electrification under programs like the U.S. Maritime Administration’s Port Infrastructure Development Program and others that have received funding increases under the Bipartisan Infrastructure Law.

For most of the 2020-21 school year, Michigan was among the roughly 70% of states that let local school districts, with guidance from local health authorities, determine how and when students were welcomed back into school buildings. Using instructional modality data collected throughout the 2020-21 school year, this paper uncovers not only how district-provided opportunities for in-person and remote instruction varied across Michigan, but how different student groups actually learned during the first full school year of the pandemic and the extent to which family preferences contributed to these outcomes. Our results suggest that many students continued to choose hybrid or remote options even when provided the opportunity to learn in person. Further, we find that student demographics, urbanicity, and county-level political affiliation were all strong predictors of uptake of in-person versus remote instruction, while the relationships between uptake and county-level COVID-19 infection and death rates were generally not significant.

Arabic has become a much more widely spoken language in the United States in recent decades. The number of people ages 5 and older who speak Arabic at home in the U.S. rose from 215,000 in 1980 to 1.4 million in 2021, making it the nation’s seventh-most common non-English language spoken at home. Arabic speakers represent several nationalities and include both immigrants and those born in the U.S. Here are five facts about Arabic speakers in the U.S., based on a Pew Research Center analysis of Census Bureau data.

The federal tax code is progressive — taxpayers with higher incomes pay a greater share of their income in taxes than taxpayers with lower income. The federal tax system also provides many benefits that favor those with high incomes over those with low incomes. Women, and especially women of color, tend to have lower incomes, and as such, these provisions widen income inequality between men and women, most dramatically women of color. This article argues that refundable tax credits, which deliver benefits to low-income families, have a substantial, positive impact on women and their families, and that recent expansions improved the economic security of women, especially women of color, promoting gender and racial equity.

Your doctor probably came from someplace else. In any state, typically just a quarter of doctors were born there. And local doctors do not constitute a majority in any state - though Nebraska, at 45 percent local doctors, comes the closest.

Studies have failed to show a positive effect of unemployment on incarceration despite reasons to expect such a relationship. We note that prior estimates have been muddied by the absence of substate data, a focus on prisons rather than on jails, limited measures of unemployment, and the fact that the health of the labor market is endogenous to incarceration. We instrument for local exposure to the rise of Chinese exports (“the China Shock”) to estimate the effect of job loss on American incarceration. Marshaling a new data set of prisoners and jail inmates by race at the commuting zone level, we show that negative shocks to local labor markets led to significant increases in total incarceration rates for both Blacks and Whites. The effect seems to be driven by increased prison rather than jail populations. This estimate is invisible to ordinary least squares, which may help explain null results reported by past work. Counterfactual exercises suggest that the effect of job loss was punitively consequential. Had employment gains from the 1990s been preserved into the 2000s, the U.S. incarceration rate would have grown significantly less than it did.

Family planning measures for unmarried women are based on contraceptive demand and use among sexually active women. Sexual activity status is commonly defined based on comparing reported time-since-last-sex to a cutoff time, with women defined to be sexually active if their most recent sex was within the last four weeks. While easy to understand and compute, this approach to constructing family planning measures results in a limited understanding of family planning and exposure to unintended pregnancy because it cannot comprehensively capture the frequency of sex at the population level. We propose a new statistical approach to quantify sexual activity, using reported time-since-last-sex data. Based on estimated frequencies of sex among users and nonusers in need of family planning, we propose new family planning measures, including the ratio of protected exposure over all women's exposure to risk of unintended pregnancy.

Background Older workers experience higher rates of fatal occupational injury than younger workers worldwide. In North Carolina, the population of older workers more than doubled between 2000 and 2017. In 2008, the Great Recession changed occupational patterns among all age groups. We examined annual rates and distribution of fatal occupational injuries experienced by older workers, comparing the pre-recession period (2000–2007) to the post-recession period (2009–2017). Methods Detailed information on all fatal occupational injuries during the period between 1 January 2000 and 31 December 2017 were abstracted from the records of the North Carolina Office of the Chief Medical Examiner and the office of vital records. The decennial Census and American Community Survey were used to estimate the population at risk and derive annual rates of fatal occupational injury. Results During the study period, 537 occupational fatalities occurred among workers 55+ years of age. The rate of fatal occupational injury among older workers declined 2.8% per year, with a 7.7% yearly decline in the pre-recession period compared with a 1.4% increase per year in the post-recession period. Workers 65+ years of age experienced rate increases in both periods. The highest rates of unintentional fatal occupational injury (injuries that were not purposefully inflicted) were observed in forestry, fishing hunting and trapping, and wood building manufacturing. Intentional fatal occupational injury rates (homicide, suicide) were highest in transportation, gas/service stations and grocery/food stores. Conclusions Older workers have persistently high rates of fatal occupational injury in North Carolina before and after the Great Recession.

Local differential privacy (LDP) has emerged as a privacy standard for collecting distributed data. In multi-dimensional data collection, separately perturbing each dimension is one canonical solution to protect privacy. Yet, it commonly falls short in statistical utility due to excessive noise injection caused by the privacy budget split linearly related to data dimensions. To tackle this problem, we propose a multi-dimensional data collection scheme under LDP, called PPMC, achieving privacy-utility tradeoff through Haar transform-based dimension reduction. Specifically, we apply Haar transform to convert multi-dimensional data into two parts: the average value and eigenvector, so as to lay a foundation for reducing the dimension. We design a probability density-based perturbation mechanism for the average value, which can decrease the noise injection by optimizing the probability distribution. For the eigenvector, a dimension reduction model is presented that promises low utility loss by error-balanced strategy. Further, we develop a global perturbation mechanism for the reduced dimension eigenvector, which can better maintain statistical utility while ensuring privacy via a private sampling strategy. Finally, the noisy multi-dimensional data is generated by utilizing the inverse Haar transform in a locally differential private manner. Theoretical analysis and experiment results confirm the effectiveness of our solution

We provide new insights on the decline of the gender pay gap from the 1970s until today, using data from multiple high-income countries. We find support for a cohort-driven interpretation of the shrinking pay gap: newer worker cohorts with smaller gender gaps gradually replaced older cohorts with larger gaps. We show that the cross-cohort decline in the gender gap in entry wages among younger workers accounts for the overall reduction in the gender gap at most until 2000. After 2000, the exit of older cohorts with larger gaps becomes the prominent driver of cross-cohort convergence. Next, we further examine the progressive reduction in the entry-pay gender gap among younger workers that stopped in 2000. Rather than stemming from younger women's improved outcomes, it mainly originates from younger men's absolute and relative (to women) earning losses. Finally, we show that changes across cohorts in initial allocations to firms help explain the decline in the overall gap, but this is not true of initial sector allocations. Overall, we conclude that the convergence achieved over the last two decades is mostly the slow-moving consequence of equality gains achieved decades ago, a realization that provides a pessimistic outlook for the future trajectory of the gender gap.

The Census Tree is the largest-ever database of record links among the historical U.S. censuses, with over 700 million links for people living in the United States between 1850 and 1940. These links allow researchers to construct a longitudinal dataset that is highly representative of the population, and that includes women, Black Americans, and other under-represented populations at unprecedented rates. In this paper, we describe our process for creating the Census Tree, beginning with a collection of over 317 million links contributed by the users of a free online genealogy platform. We then use these links as training data for a machine learning algorithm to make tens of millions of new matches. Finally, we incorporate other recent efforts to link the historical U.S. censuses and introduce a procedure for filtering the links and adjudicating disagreements. Our complete Census Tree achieves match rates between adjacent censuses that are between 69 and 86% for men, and between 58 and 79% for women, with over 41.5 million links for Black Americans.

Background: The lifetime cost for one HIV infection is $326,500, and the medical cost saved from one averted infection is $229,800. Plans for ending the epidemic in the U.S involves the use of antiretroviral drugs as preexposure prophylaxis (PrEP), a major prevention strategy for reducing HIV infections. However, PrEP use has not been proportional to the need. Despite comparable HIV risk as men, women account for only 5% of PrEP users annually. Research suggests that PrEP ue is highest in states that expanded Medicaid. The gender disparity in PrEP use, however, suggests that other factors specific to women may be negatively impacting their PrEP uptake. The goal of this study was to therefore determine the factors influencing the PrEP use for women across the U.S. using data dating back to 2012, when PrEP was first approved. Methods: This quasi-experimental study used a difference-in-differences regression model to examine the effect of access to healthcare on PrEP use for men and women across the U.S. We hypothesized that states with expanded Medicaid, with greater availability of mental health and substance use disorder treatment, and with greater concentration of family planning clinics are associated with higher PrEP use in women. Results: The results showed that average PrEP use was higher in states that expanded Medicaid, but men had consistently higher PrEP use than women across states. The difference-in-differences model showed a larger percentage increase in both PrEP rate (18.9% v 8.1%) and PNR (42.9% v 17.6%) for men compared with women. Conversely, the availability of healthcare services did not have the expected effect on PrEP use. Conclusions: We identified a need for more tailored interventions to better reach women, by scaling up prevention efforts that are targeted at identifying and engaging women in PrEP care. This study provided a basis for further implementation research and policy changes that prioritizes equity for all.

The study of affirmative action bans suffers from focusing on the ivory tower as the site for the impacts of affirmative action bans. Prior literature on affirmative action bans has missed the bigger picture, failing to see that less glamorous schools have also been impacted by the bans. This article fully fleshes out the impacts of affirmative action on postsecondary education by their level of selectivity (Barron’s Admissions Competitiveness Index) and sector (private, public, and for profit) from a merged data set (Integrated Postsecondary Education Data System and the Current Population Survey) spanning 1991 to 2016. The results of a differences-in-differences analysis find that a small group of for-profit institutions with very large enrollments became a destination for underrepresented minority students in the wake of affirmative action bans.

How do ethnic and racial minorities go from underrepresented to proportionately – or perhaps even over – represented in local politics? This paper addresses this question by examining the ongoing incorporation of Latinxs and politicians in the strategic research site (SRS) of Central Falls, Rhode Island against the backdrop of the earlier incorporation of immigrants from Southern and Eastern Europe, as well as French Canada, who arrived in the “Ellis Island Era”. It employs mixed methods to demonstrate: first, that European-Americans entered politics as representatives of spatially segregated ethnic enclaves in the early 20th century; second, that in the absence of spatial segregation, Latinx politicians with distinct national origins had to await and ultimately foster the emergence of a coherent, panethnic community of voters before they could reach office; third, that the emergence of a panethnic political community was a nonlinear function of the Latinx share of the municipal population; and, fourth, that Latinx identity was in large part forged in and through public institutions, especially the public school system. In doing so, the paper helps overcome the "micro- macro divide” that has traditionally bedeviled political sociology and not only identifies but begins to address a major lacuna in the study of Latinx politics: while the literature assumes and addresses their historical underrepresentation in US politics, immigrants from Latin American and their offspring didn’t identify as members of a coherent panethnic group until recently – leaving the boundaries, and perhaps even the existence, of their underrepresentation open to question.

In this paper, we identify two different sets of problems. The first covers the problems that the iterative proportional fitting (IPF) algorithm was developed to solve. These concern completing a population table by using a sample. The other set concerns constructing a counterfactual population table with the purpose of comparing two populations. The IPF is commonly applied by social scientists to solve problems not only in the first set, but also in the second one. We show that while it is legitimate to use the IPF for the first set of problems, it is not the right tool to address the problems of the second kind. We promote an alternative of the IPF, the NM-method, for solving problems in the second set. We provide both theoretical and empirical comparisons of these methods.

We show that past inflation experiences strongly predict homeownership within and across countries. First, we collect novel survey data, which reveals inflation protection to be a key motivation for homeownership, especially after personal experiences of high inflation. Second, using household data from 22 European countries, we find that higher personal exposure to historical inflation predicts higher homeownership rates. We estimate similar associations among immigrants to the US who experienced different past inflation in their home countries but face the same US housing market. As predicted by the experience-effects model, the relationship is strongest in countries with predominantly fixed-rate mortgages.

Defined-benefit pensions, which provide guaranteed monthly retirement income based on a worker’s salary and years of service, are a key pillar of public employee compensation. In Sonoma County, K-12 teachers and other educators are covered by the California State Teachers’ Retirement System (CalSTRS), County of Sonoma (i.e., county government) employees and Sonoma Valley Fire District employees are covered by the Sonoma County Employee Retirement Association (SCERA), and most other state and local government employees are covered by the California Public Employee Retirement System (CalPERS). This brief examines pension benefits for public servants in Sonoma County in terms of their role in employee compensation, the evolving financial status of pension systems, the impact of pension reform on costs, and how different pension systems in the county and surrounding Bay Area region stack up against each other in terms of protection from inflation during retirement. Section 1 outlines the size and makeup of public employment and highlights the public sector pay penalty in Sonoma County based on Census data. Section 2 analyzes pension system funded status and cost trends using retirement system actuarial data. Section 3 compares cost-of-living adjustment (COLA) policies among public pensions across the Bay Area and highlights the impact of SCERA’s lack of systematic inflation protection on retiree incomes and pension benefit value. Much of the retirement system analysis in this brief focuses on SCERA. A more detailed analysis of CalPERS and CalSTRS funded status, costs, and accounting and actuarial reforms can be found in Brief #2 of the UC Berkeley Labor Center’s Marin Public Pension Series. 1

How do societies respond to adversity? After a negative shock, separate strands of research have documented either an increase in religiosity or a boost in innovation efforts. In this paper, we show that both reactions can occur simultaneously, driven by different individuals within society. The setting of our study is the Influenza pandemic of 1918-19 in the United States. To measure religiosity, we construct a novel indicator based on naming patterns, and we measure innovation through the universe of granted patents. Exploiting plausibly exogenous variation in exposure to the pandemic, we provide evidence that more affected counties become both more religious and more innovative. Looking within counties, we uncover a heterogeneous response: individuals from more religious backgrounds further embrace religion, while those from less religious ones become more likely to choose a scientific occupation. Facing adversity widens the distance in religiosity between scientific-minded individuals and the rest of the population, and it leads to a polarization of religious beliefs.

This dissertation focuses on research at the intersection of labor, public, and regional economics. Chapter 1 evaluates the effect of Secure Communities (SC), an immigration enforcement program, on the living arrangements of U.S.-born elderly. Using U.S. Census data and exploiting spatial and temporal variation in the implementation of SC, I estimate a difference-in-differences model. I find that SC increased the likelihood of coresidence among the elderly. Furthermore, I provide suggestive evidence that the elderly are more likely to coreside with a person out of the labor force. Empirical tests suggest that the increased price of household services due to the reduction of immigrants’ labor supply is the key mechanism generating these effects. These findings suggest that strict immigration enforcement policies could greatly impact the living arrangements and work decisions of U.S.-born persons. Chapter 2 examines the impact of automation on young workers’ career paths and educational choices. Using NLSY79 data, we document two stylized facts. First, children whose parents were employed in routine-intensive occupations are more likely to be employed in similar occupations by routine content. Second, the gap between children of parents with high- and low-routine jobs persists over age and time. Second, the gap between children of parents in the first (lowest) and last (highest) terciles by routine intensity is persistent over age and career trajectory. With the persistence of intergenerational occupational types, policies promoting education and occupation variety are beneficial for economic growth. Chapter 3 explores the growth effect of human capital in the U.S. Using U.S. census data for 1980-2018, the instrumental variable analysis shows that college graduates, not residents with high school degrees, drive job growth. By exploiting a Community Zone (CZ) growth model, I disentangle the estimated effect into two components related to higher productivity and higher quality of life. In nonmetropolitan areas, the analysis confirms evidence of the causal relationship between human capital and growth in employment, suggesting that the whole effect is explained by the increase in quality of life. In an urban setting, I find that higher productivity contributed to more than 80% of the effect at the CZ level.

Does mass emigration encourage or undermine protests? Emigration, being a personal decision made by households, can potentially aggregate into a collective expression of discontent against the prevailing status quo. In this paper, we focus on whether large-scale emigration influences protest support and participation.Using a survey experiment conducted in Honduras, we assess how emigration’s salience affected public opinion about anti-government demonstrations in 2021.Our findings reveal that respondents primed with information about migration expressed more favorable opinions toward protests, although their participation in demonstrations was unaffected. This study contributes to a better understanding of the link between emigration and public opinion for those who stay in their origin country, and also its limitations to mobilizing for change during periods of political turmoil