We present a brief summary of the BK model. All variables are in the model are defined in logs and in relative terms. For example, wi,t is the log relative wage rate in location i at time t: If Wi,t denotes the nominal wage and Wt denotes the national average wage, then wi,t = log (Wi,t/Wt). Labor supply (e S i,t) and demand (e D i,t) in location i at time t are given by where γS > 0 and γD > 0 are (short run) labor supply and demand elasticities. Labor demand and supply may shift as follows.

Using 391 high-skilled firm entries in the U.S. from 1990–2010, we estimate the effects of the firm entry on incumbent residents’ consumption, finances, and mobility. We compare outcomes for residents living close to the entry location with those living far away while controlling for their proximity to potential high-skilled firm entry sites. We find high-skilled incumbents, especially homeowners, benefit. Low-skilled incumbents on average benefit less. For a representative firm entry with 1000 new employees entering a metropolitan area with a population of 1.1 million, the aggregate welfare benefit across all incumbents is an annual equivalent of $25 million. Lowskilled renters living within 10 minutes from the entry bear the largest costs.

Time for 'rest and leisure' is one of the human rights established by the Universal Declaration of Human Rights and the International Covenant on Economic, Social and Cultural Rights (ICESR). Countries which ratify the ICESR are expected to account for their performance in achieving the human rights set out in the covenant in periodic reports to the United Nations. This should include statistical indicators as appropriate. Country reports have, to date, tended to ignore the right to leisure time. This paper seeks to remedy this situation by offering a methodology for assessing national levels of performance, taking account of national resources in the form of Gross Domestic Product per capita. A worked example of the application of the methodology is offered for 23 countries for which leisure time information is available.

Using data covering the universe of injury claims from the nation’s largest worker’s compensation system (2001-2018), we explore the relationship between temperature and workplace safety and its implications for labor market inequality. Hotter temperature increases workplace injuries significantly, causing approximately 20,000 injuries per year. The effects persist in both outdoor and indoor settings (e.g. manufacturing, warehousing), and for injury types ostensibly unrelated to temperature (e.g. falling from heights), consistent with cognitive or cost-related channels. The risks are substantially larger for men versus women; for younger versus older workers; and for workers at the lower end of the income distribution, suggesting that accounting for workplace heat exposure may exacerbate total compensation inequality. We document a decline in the heat-sensitivity of injuries over the study period, suggesting significant scope for adaptation using existing technologies.

I examine why the harmful tradition of female genital mutilation persists in certain countries while in others it has been eradicated. People are more willing to abandon their traditions if they are confident that the government is durable enough to set up long-term replacements for them. Using a country-ethnicity panel dataset spanning 23 countries from 1970 to 2013 and artificial partition of African ethnic groups by national borders, I show that a one-standard-deviation larger increase in political regime durability leads to a 0.1-standard-deviation larger decline in the share of newly-circumcised women, conditional on the presence of an anti-FGM government policy.

Building trust in our research infrastructure is important for the future of the academy. Trust in research data repositories is critical as they provide the evidence for past discoveries as well as the input for future discoveries. Archives and repositories are examining their options for trustworthy review, audit, and certification as a means to build trust within their content creator and user communities. One option these institutions have is to increase and demonstrate their trustworthiness is to apply for the CoreTrustSeal. Applicants for the CoreTrustSeal are becoming more numerous and diverse, ranging general purpose repositories, preservation infrastructure providers, and domain repositories. This demand for certification and the subjective nature of decisions around levels of CORETrustSeal compliance drives this dissertation. It is a study of the review process and its veracity and consistency in determining the trustworthiness of applicant repositories. Several assumptions underlie this work. First, audits and reviews must be based on evidence supplied by the repository under scrutiny; second, and not all reviewers will approach a piece of evidence in the same fashion or give it the same weight. Third, the value and veracity of required evidence may be subject to reviewers’ diverse perspectives and diverse repository community norms. This research used a thematic qualitative analysis approach to identify similarities and differences in CoreTrustSeal reviewers’ responses during semi-structured interviews in order to better understand potential subjective differences among respondents. The participants’ non-probabilistic sample represented a balance in perspectives across three anticipated categories: administrator, archivist, and technologist. Themes converged around several key concepts. Nearly all participants felt they were performing a peer review process and working to help the repository community and the research enterprise. Reviewers were questioned about the various CoreTrustSeal application requirements and which ones they felt were the most important. No clear evidence emerged to indicate that variations in perspectives affected the subjective review of application evidence. The same categories of evidence were often selected and identified as being critical across all three categories (i.e., administrator, archivist, and technologist). Many valuable suggestions from participants were recorded and can be implemented to ensure the consistency and sustainability of this trusted repository review process. These suggestions and concepts were also very evenly distributed across the three perspectives. The balance in perspectives is potentially due to participants’ experience levels and their years of experience in various positions, holding many responsibilities, within the organizations they represented.

This research explores the life circumstances of older persons (aged 60 years and above), focusing on the sociodemographic and socioeconomic conditions of those who live alone. We situate the living arrangements of older persons within the global context of changing household structures in 76 countries from all regions of the world. Older persons who live alone are among those most likely to need governmental and other forms of social support. The analysis presented here is crucial for supporting policy responses to the needs of older persons, including the special attention they require during the current COVID-19 crisis. It also supports the operationalization of the Madrid International Plan of Action on Ageing (MIPAA)(United Nations, 2002), the realization of United Nations Principles for Older Persons (United Nations, 1991), and the broader framework of the Programme of Action of the International Conference on Population and Development(ICPA-POA).

This paper investigates the relationship between real incomes in Sub-Saharan African countries during 1990–2018 and child wellbeing. A new UNICEF-WHO-World Bank database of child growth and malnutrition and annual measures of child mortality from the World Development Indicators are employed. Changes in real incomes are related to changes in these measures. Real incomes are found to be strongly negatively conditionally associated with stunting, underweight and child mortality. The fraction of each country’s export revenue derived from major nonagricultural export commodities in 1990 is then used to construct a counterfactual value of export revenues. This measure is used to predict real incomes in a country in a year. The impact of incomes on child mortality outcomes is then assessed. Instrumental variables results suggest that improved incomes may have causally reduced neonatal and under-five mortality.

Previous analyses showed an overall pattern of improvement in self-rated health of U.S. older adults in the 1980s and the 1990s, but it was uncertain if the declining shares of elderly persons reporting fair or poor health would continue over the next decades. Using the 2000–2018 pooled data from the National Health Interview Survey, this study examined recent trends in self-rated health of adults aged 45 and older. The results showed important variations in self-rated health trends across age groups. Between 2000 and 2018, the shares of adults aged 60 and above reporting fair or poor health declined significantly while self-rated health trends for middle-aged adults worsened over time. Educational and racial/ethnic differentials in self-rated health persisted over time but there were important group variations. To further improve the health of the elderly population, it is important to consider changing health disparities in later life.

Among the economic demands of the 1963 March on Washington for Jobs and Freedom was a demand for a federal jobs program that would eliminate unemployment for African Americans. From the 1960s to today, Black Americans have been about twice as likely as White Americans to be unemployed. Consequently, Black people never achieve low unemployment. They can be said to be living in a permanent economic recession. This Article presents a suite of policies to end high unemployment in African American communities. The policies include those that work indirectly by increasing the demand for goods and services, and those that directly create jobs. Since anti-Black racial discrimination in the labor market is at the root of the persistently high rate of Black joblessness, a strong affirmative action program to counteract discrimination will also be needed. Some might think that a universal basic income is an acceptable alternative to a jobs program, but a job has economic, psychological, and sociological benefits beyond an income. A society that denies many African Americans the opportunity to work denies them not just an income, but also opportunities for identity, self-esteem, service, and social relationships. Ending the permanent recession in Black America is an important step toward providing equal opportunity in America.

One of the main steps in the data lifecycle is to publish it for data analysts to discover hidden patterns. But, data publishing may lead to unwanted disclosure of personal information and cause privacy problems. Data anonymization techniques preserve privacy models to prevent the disclosure of individuals’ private information in published data. In this paper, a distributed in-memory method is proposed on the Apache Spark framework to preserve the ℓ-diversity privacy model. This method anonymizes large-scale data in a three-phase process, which includes, seed selection, data clustering for $$\ell$$ -diversity, and finalizing phase. In this method, a hierarchical kmeans-based data clustering algorithm has been designed for data anonymization. One of the major challenges of anonymization methods is to establish a better trade-off between data utility and privacy. Therefore, for calculating the distance between records and forming more cohesive ℓdiverse-clusters, the authors have designed two Manhattan-based and Euclidean-based distance functions to satisfy the requirements of the ℓ-diversity model. Given the 100-fold speed of the Spark compared to MapReduce, the proposed method is presented using in-memory RDD programming in Apache Spark, to address the runtime, scalability, and performance in large-scale data anonymization as it exists in the previous MapReduce-based algorithms. Our method provides general knowledge to use parallel in-memory computation of Spark in big data anonymization. In experiments, this method has obtained lower information loss and loses about 1% to 2% accuracy and FMeasure criteria; therefore, it establishes a better trade-off than the state-of-the-art MapReduce-based Mondrian methods

We study the consequences of measurement error in the dependent variable of random-coefficients models, focusing on the particular case of quantile regression. The popular quantile regression estimator of Koenker and Bassett (1978) is biased if there is an additive error term. Approaching this problem as an errors-in-variables problem where the dependent variable suffers from classical measurement error, we present a sieve maximum likelihood approach that is robust to left-hand-side measurement error. After providing sufficient conditions for identification, we demonstrate that when the number of knots in the quantile grid is chosen to grow at an adequate speed, the sieve-maximum-likelihood estimator is consistent and asymptotically normal, permitting inference via bootstrapping. Monte Carlo evidence verifies our method outperforms quantile regression in mean bias and MSE. Finally, we illustrate our estimator with an application to the returns to education highlighting changes over time in the returns to education that have previously been masked by measurement-error bias.

A better understanding of trends in workforce exit due to disability and how these trends vary across states and subgroups can help federal and state policymakers identify both individual-level and state-level factors associated with increased risk of workforce exit due to disability. Using national survey data and Bayesian multilevel modeling techniques, we produce yearly estimates of trends in the risk of workforce exit due to disability for states and demographic subgroups. These estimates are more stable and have narrower uncertainty intervals than estimates produced using classical statistical methods. We identify Current Population Survey respondents as being "newly at-risk"of exiting the workforce due to disability if they reported being employed in one month and out of the labor force because of a disability in the next month, and we refer to their share of the working-age population as the "at-risk rate."We find that age, education, race, and gender are important factors for the at-risk rate, in decreasing order. Holding demographics constant across states and time reduces the cross-state variation in the at-risk rate but does little to reduce variability over time. State at-risk rates are typically higher than application rates for the Social Security Administration's disability programs, but the relationship between these rates varies considerably by state. Our preliminary exploration of the reasons for cross-state variation in this relationship suggests that differences across states may be due to differences in their industrial composition, job opportunities, and safety net structure.

The sections that follow sketch the broad contours of some of the most needed reforms in the legal immigration system, with a particular focus on adjustments to employment-based and family-sponsored immigration. It is a road map for ongoing work by the Migration Policy Institute (MPI) laying out more detailed proposals for reshaping the various legal immigration streams (see Box 1).

This paper examines the effect of the female-to-male wage ratio, "relative wage," on women's spouse quality, marriage, and labor supply over three decades. Exploiting task-based demand shifts as a shock to relative pay, I find that a higher relative wage (a) increases the quality of women's mates, as measured by higher spousal education; (b) reduces marriage without substitution to cohabitation; and (c) raises women's hours of work. These effects are consistent with a model in which a higher relative wage increases the minimum nonpecuniary benefits ("quality") women require from a spouse and therefore reduce marriage among low-quality husbands.

The Southwest region of the United States has had a Hispanic presence for more than 400 years. Historical accounts reveal a long history of Hispanic settlement in the region that began with the establishment of the Spanish colonial territory of New Spain in 1521.1 For 300 years, the Southwest, including what is present-day Nevada, was controlled by Spain, until Mexico established its independence from Spain on August 24, 1821. For more than twenty years, Mexico would retain control of the territory that now comprises the states of Texas, California, New Mexico, Utah, Arizona, Nevada, and areas of Colorado and Wyoming.2 Mexico would eventually lose control of this territory to the United States after its defeat in the Mexican-American War of 1848.3 And two years later, in 1850, with the first US Census that provided detailed household information, we began to have data confirming the enduring and impactful presence of Hispanics and Latinos in the Southwest, and specifically in the territory that would later become the state of Nevada.

Spatial differences in labor market performance are large and highly persistent. Using data from the United States, Germany, and the United Kingdom, we document striking similarities in spatial differences in unemployment, vacancies, job finding, and job filling within each country. This robust set of facts guides and disciplines the development of a theory of local labor market performance. We find that a spatial version of a Diamond-Mortensen-Pissarides model with endogenous separations and on-the-job search quantitatively accounts for all the documented empirical regularities. The model also quantitatively rationalizes why differences in job-separation rates have primary importance in inducing differences in unemployment across space while changes in the job-finding rate are the main driver in unemployment fluctuations over the business cycle.

The majority of federal support for older people needing in-home services and supports comes from the Medicaid program. However, less than 10% of older people are eligible for Medicaid and to receive long-term services, a person must have a severe disability. Many older people with moderate levels of disability or those who are not impoverished are not eligible. In response to these system limitations, some counties across the nation have developed alternative funding strategies, such as property tax levies, to better serve older members of their communities. After identifying 15 states with such initiatives, a survey was distributed to 414 contacts within these states, with a response rate of 55%. Respondents included organizations such as area agencies on aging, councils on aging, and county departments on aging. Local funding varied within and across states, with annual funding ranging from $8,000-$47 million. Most commonly provided services with local funds include home-delivered (81%) and congregate (73%) meals, transportation (61%), and homemaker services (49%). A majority of programs (63%) indicated that local funds are used to provide at least one family or friend caregiver service. This study is the first compilation and description of locally-funded elder service initiatives in the U.S. Locally-funded initiatives can help older people with long-term services needs continue to live in their own homes and communities. On the other hand, some have raised questions about whether this is a good approach to funding aging services, raising concerns that this will lead to further inequities across states and communities.

Collective trauma refers to the emotional and psychological reactions to an event that affects an entire society or community (Hirschberger, 2018). Given the major events occurring in 2020, including the global pandemic and the social upheaval in the United States, it is easy to perceive these events as having both a significant and shared impact on U.S. society. Contending with the loss of hundreds of thousands of lives from the novel coronavirus pandemic (COVID-19), the United States continues to grapple with the pervasive issues of inequalities that are inextricably linked to this epidemic. COVID-19 highlighted longstanding inequities, insecurities, and vulnerabilities within the United States, including racial disparities in socioeconomic classes and the distribution of wealth, lack of affordable health care, widespread food insecurities, access to housing, and a “digital divide” among social classes. Placing even more pressure on our weakened state, the United States once again addressed the pervasive issues of systemic racism, oppression, and stratification within the fabric of the country. Further, as if these events were not enough, the United States experienced one of the most volatile and polarized political climates in its history. While the long-term impacts of 2020 are still unknown, it is clear that the issues of inequity were highlighted over the past year. The United States has awakened to the disparities related to inequities in various arenas. For example, while numerous leaders found themselves in a holding pattern and struggled with the ambiguity surrounding COVID-19, the #MeToo and Black Lives Matter movements have also placed the topic of diversity squarely on the leadership agenda. Underrepresented groups have absorbed a disproportionate percentage of COVID-19 related deaths (Moore et al., 2020). Within the devastating impact of the pandemic on the U.S. economy, we must acknowledge that women and people of color have been disproportionately impacted by resulting furloughs and layoffs. One year following the onset of the pandemic, the U.S. Bureau of Labor Statistics (2021) noted that, of the 1.1 million people who exited the workforce, 80% were women. Further, according to the Institute for Social Research and Data Innovation (2021) IPUMS Current Population Survey, the unemployment rates for people of color were double that of white counterparts. Through the lens of leadership, our aim in the symposium is to examine diversity critically and courageously in various communities of practice. In doing so, we intend to examine both challenges and opportunities afforded to leaders in these identified sectors, as we reconceptualize the meaning of “work” within our workforce. The reality that recent events have thrust upon leaders is that unanticipated changes and unpredictability generate a great sense of apprehension, discomfort, and vulnerability within organizations (Fernandez & Shaw, 2020). Experts have forewarned of the rapid rise of the “new normal,” which creates a fundamental question for all leaders and scholars: Within the “new normal,” how can we continue our attempts to harness the benefits of a diversified workforce?

Although the fairness community has recognized the importance of data, researchers in the area primarily rely on UCI Adult when it comes to tabular data. Derived from a 1994 US Census survey, this dataset has appeared in hundreds of research papers where it served as the basis for the development and comparison of many algorithmic fairness interventions. We reconstruct a superset of the UCI Adult data from available US Census sources and reveal idiosyncrasies of the UCI Adult dataset that limit its external validity. Our primary contribution is a suite of new datasets derived from US Census surveys that extend the existing data ecosystem for research on fair machine learning. We create prediction tasks relating to income, employment, health, transportation, and housing. The data span multiple years and all states of the United States, allowing researchers to study temporal shift and geographic variation. We highlight a broad initial sweep of new empirical insights relating to trade-offs between fairness criteria, performance of algorithmic interventions, and the role of distribution shift based on our new datasets. Our findings inform ongoing debates, challenge some existing narratives, and point to future research directions.