Differential privacy algorithm is an effective technology to protect data privacy, and there are many pieces of research about differential privacy and some practical applications from the Internet companies, such as Apple and Google, etc. By differential privacy technology, the data organizations can allow external data scientists to explore their sensitive datasets, and the data owners can be ensured provable privacy guarantees meanwhile. It is inevitable that the query results that will cause the error, as a consequence that the differential privacy algorithm would disturb the data, and some differential privacy algorithms are aimed to reduce the introduced noise. However, those algorithms just adopt to the simple or relative uniform data, when the data distribution is complex, some algorithms will lose efficiency. In this paper, we propose a new simple ε-differential privacy algorithm. Our approach includes two key points: Firstly, we used Laplace-based noise to disturb answer to reduce the error of the linear computation queries under intensive data items by workload-aware noise; Secondly, we propose an optimized workload division method. We divide the queries recursively to reduce the added noise, which can reduce computation error when there exists query hot spot in the workload. We conduct extensive evaluation over six real-world datasets to examine the performance of our approach. The experimental results show that our approach can reduce nearly 40% computation error for linear computation when compared with MWEM, DAWA, and Identity. Meanwhile, our approach can achieve better response time to answer the query cases compared with the start-of-the-art algorithms.

This study used a spatial approach to explore metropolitan and nonmetropolitan variation of college enrollment at the interplay of place and race within the state of Texas. Analyzing Integrated Public Use Microdata Series (IPUMS-USA) data and using population proportions as well as regression methods, we pay particular attention to the racial/ethnic diversity in non-metro (i.e., rural) areas and its relationship with college enrollment. We find geography is a mediating factor in the college enrollment racial/ethnic gaps for rural Texans, but there are considerable regional disparities. These disparities show diverse trends among rural regions where large proportions of Latinxs reside. This indicates a need for more research to explore geographic post-secondary opportunity and college access practices and policy with the racial/ethnic diversity of place in mind, especially regarding rural communities of Color.

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

This paper uses data on broadband connections and the production and sales of agricultural products to empirically estimate the impact of improved connectivity on U.S. farming outcomes. The Federal Communications Commission has detailed data on broadband subscriptions from its semi-annual Form 477 collection. The USDA's National Agricultural Statistics Service (NASS) releases a complete census of agriculture every five years to measure agricultural activity. By pairing periodic releases of the Form 477 data collection with information on farm production expenses and crop yields from corresponding releases of the Census of Agriculture, the analysis directly evaluates the benefit of rural broadband development on the U.S. farming industry. Overall, I find evidence of crop yield improvements from increased Internet penetration rates at thresholds of 25 Megabits-per-second download and 3 Megabits-per-second upload speeds. Among the findings, a 1% increase in the number of 25+/3+ connections per 1,000 households is associated with a 3.6% increase in corn yields, as measured in bushels per acre. I also find some evidence of cost savings at thresholds of 10 Megabits-per-second download and 0.768 Megabits-per-second upload speeds. A 1% increase in the number of 10+/0.768+ connections per 1,000 households is associated with a 2.4% decrease in operating expenses per farm operation. The paper also provides an introductory look at changes in the composition and speed thresholds of connectivity available for selected field crops over time.

Background: Despite being one of the wealthiest nations, disparities in adverse birth outcomes persist across racial and ethnic lines in the United States. We studied the association between historical redlining and preterm birth, low birth weight (LBW), small-for-gestational age (SGA), and perinatal mortality over a ten-year period (2006–2015) in Los Angeles, Oakland, and San Francisco, California. Methods: We used birth outcomes data from the California Office of Statewide Health Planning and Development between January 1, 2006 and December 31, 2015. Home Owners’ Loan Corporation (HOLC) Security Maps developed in the 1930s assigned neighborhoods one of four grades that pertained to perceived investment risk of borrowers from that neighborhood: green (grade A) were considered “Best”, blue (grade B) “Still Desirable”, yellow (grade C) “Definitely Declining”, and red (grade D, hence the term “redlining”) “Hazardous”. Geocoded residential addresses at the time of birth were superimposed on HOLC Security Maps to assign each birth a HOLC grade. We adjusted for potential confounders present at the time of Security Map creation by assigning HOLC polygons areal-weighted 1940s Census measures. We then employed propensity score matching methods to estimate the association of historical HOLC grades on current birth outcomes. Because tracts graded A had almost no propensity of receiving grade C or D and because grade B tracts had low propensity of receiving grade D, we examined birth outcomes in the three following comparisons: B vs. A, C vs. B, and D vs. C. Results: The prevalence of preterm birth, SGA and mortality tended to be higher in worse HOLC grades, while the prevalence of LBW varied across grades. Overall odds of mortality and preterm birth increased as HOLC grade worsened. Propensity score matching balanced 1940s census measures across contrasting groups. Logistic regression models revealed significantly elevated odds of preterm birth (odds ratio (OR): 1.02, 95% confidence interval (CI): 1.00–1.05), and SGA (OR: 1.03, 95% CI: 1.00–1.05) in the C vs. B comparison and significantly reduced odds of preterm birth (OR: 0.93, 95% CI: 0.91–0.95), LBW (OR: 0.94–95% CI: 0.92–0.97), and SGA (OR: 0.94, 95% CI: 0.92–0.96) in the D vs. C comparison. Results differed by metropolitan area and maternal race. Conclusion: Similar to prior studies on redlining, we found that worsening HOLC grade was associated with adverse birth outcomes, although this relationship was less clear after propensity score matching and stratifying by metropolitan area. Higher odds of preterm birth and SGA in grade C versus grade B neighborhoods may be caused by higher-stress environments, racial segregation, and lack of access to resources, while lower odds of preterm birth, SGA, and LBW in grade D versus grade C neighborhoods may due to population shifts in those neighborhoods related to gentrification.

Do wages react to regional unemployment, as proposed by the theory behind the regional wage curve, if regional price differences are taken into account? This paper applies regional price indexes to assess the wage curve, whereas in the literature only nominal wages are used for wage curve regressions. In order to test the impact of regional prices on the wage curve we apply a variety of methodological approaches. With individual data from the US Census and the Polish Labor Force Survey we find a wage curve. However, in both countries, the local unemployment elasticity and spatial spillovers decrease significantly once regional price deflators are applied.

Introduction: Prescription costs are rising, and many patients with chronic illnesses have difficulty paying for prescriptions. Missing or delaying medication because of financial concerns is common; however, the effects of cost-related nonadherence (CRN) on patient outcomes have not been described. Our objective was to de determine if CRN is associated with higher all-cause and diseasespecific mortality among patients living with diabetes and cardiovascular disease in a representative sample of US adults. Methods: We ascertained CRN, vital status, and cause of death for 39,571 patients with diabetes, 61,968 patients with cardiovascular disease, and 124,899 patients with hypertension in the 2000 through 2014 releases of the National Health Interview Survey. We used adjusted Cox proportional hazards models to estimate associations between CRN and all-cause mortality and CRN and diseasespecific mortality. Results: On average, 15% of the sample reported CRN in the year before interview. After adjusting for confounders, CRN was associated with 15% to 22% higher all-cause mortality rates for all conditions (diabetes hazard ratio [HR] = 1.18; 95% CI, 1.1–1.3; cardiovascular disease [CVD] HR = 1.15; 95% CI, 1.1–1.2; hypertension HR = 1.22; 95% CI, 1.2–1.3). Relative to no CRN, CRN was associated with 8% to 18% higher disease-specific mortality rates (diabetes HR = 1.18; 95% CI, 1.0–1.4; CVD HR = 1.09; 95% CI, 1.0–1.2; hypertension HR = 1.08; 95% CI, 0.9–1.3). Conclusion: Relative to full adherence, CRN is associated with higher mortality rates for patients with diabetes, cardiovascular disease, and hypertension, although associations may have weakened since 2011. Policies that increase prescription affordability may decrease mortality for patients experiencing CRN.

The coronavirus pandemic sweeping through the United States has highlighted critical pockets of vulnerability in our system of healthcare coverage. Essential frontline workers in particular face ongoing risk of infection and of infecting their families and others. For these workers, health insurance is critical. Healthcare workers, of course, face great risk of infection in this time, but another group of workers is also particularly vulnerable: service workers outside of healthcare settings, in industries that are deemed essential. In this brief, we analyze rates of insurance among essential frontline healthcare and nonhealthcare workers across New England. In spite of relatively high rates of insurance in New England, there are roughly 50,000 uninsured essential workers across the region. These workers are at increased risk both of infection and of high out-of-pocket medical expenses if they seek care. Such economic risks may preclude them from accessing necessary care in a timely manner, with negative implications for their health. Essential healthcare workers are more likely to be insured than are non-healthcare workers. Within both groups of essential workers, Hispanics and non-Hispanic blacks are clustered in lower-wage jobs with lower rates of insurance. This brief points to the importance of comprehensive and affordable health coverage for treatment of COVID-19 for essential workers and their families, who are putting their lives on the line every day in order to keep our economy running.

This dissertation has three chapters that discuss issues regarding the U.S. labor market. The first chapter investigates how establishments adjust their production on various mar- gins when wage rates rise. Exploiting state-by-year variation in minimum wage laws, I analyze U.S. manufacturing plants responses over a 23-year period using restricted-access Census Microdata. A one-percent increase in production workers hourly wages reduces total production worker hours by 0.7 percent and increases capital investment on machines by 2.7 percent. Manufacturing plants reduce average hours per production worker more than number of production workers. The elasticity of substitution between capital and labor is 0.85. In addition, when wage rates increase, manufacturing plants are also more likely to exit. Finally, suggestive evidence shows that when minimum wage laws increase wages paid by some of the establishments in a firm, the firm also increases the wages paid at its other establishments.

Objectives: The study aimed to estimate the prevalence of depression and antidepressant use among older adults with different types of disability. Methods: The study sample consisted of 32,193 adults 50 years and older who participated in the Adult Functioning and Disability supplement of the National Health Interview Survey from 2010–2014. Logistic regression was used to estimate depressive symptoms and self-reported antidepressant use by disability type. Results: One in ten participants reported feeling depressed daily or weekly, and less than half of them reported using antidepressants. Adults with a disability in cognition (odds ratio [OR] = 5.55), mobility (OR = 1.92), vision (OR = 1.91), hearing (OR = 1.88), and self-care (OR = 1.66) were more likely to often feel depressed. Antidepressant use was higher among those with cognition and self-care disability compared with no disabilities. A dose-response association existed between the number of disabilities and depression (AOR = 2.3) and antidepressant use (AOR = 1.39). Conclusions: Various forms of disability are strongly associated with depression in older adults. Antidepressants may be underutilized among older adults with certain impairments, including vision, hearing, and mobility. Future research needs should elucidate the mechanisms linking different disabilities to depression and aim to develop treatments tailored to the needs of older adults with disabilities.

While research on immigrant women’s labor market incorporation has increased in recent years, systematic comparisons of employment trajectories by national origin and over time remain rare, and the literature remains dominated by the male experience. Especially lacking are studies that take both individual factors and larger migration dynamics into account, limiting our understanding of women’s contributions to the economic well-being of immigrant families, and of the process of incorporation more broadly. Using U.S. Census and ACS data from 1990 to 2016, we construct synthetic cohorts by national origin, period, and age at arrival to track their labor force participation over time. We construct a typology of national origin trajectories and then model them adjusting for individual characteristics and gendered dynamics of migration flows, namely the sex ratio, share of women arriving single, and share of men arriving with a college education. Results indicate that immigrant women tend to gradually join the workforce over time, though with significant variation in starting levels and growth rates. Cohorts from Mexico, Central America, and South America exhibited a delayed pattern of incorporation (though Mexican women start at lower levels than others), while women from India, Korea and other Asian countries followed an accelerated incorporation trajectory from very low starting rates. Those from Europe, Africa, China, Vietnam, and Canada showed gradual incorporation while Filipinas and Caribbeans exhibited continuous, intensive employment. We show that historically produced gendered dynamics of migration flows explain a substantial share of national origin variation in workforce incorporation.

Models of creative destruction posit that recessions are periods of reallocation and disruption, generating new ideas that catapult new firms to the frontier. However, empirical evidence suggests that research and development (R&D) expenditures and patenting is procyclical, not counter-cyclical. Using panel data on the quantity and quality of patents for nearly two decades, we provide a resolution to the tension by documenting that the quality of innovation is counter-cyclical: innovations produced during busts have a larger effect on the path of future research than those developed during booms. These results are a function of financial constraints that affect private sector firms most heavily, shifting the concentration of resources and time among R&D workers towards longer-term and basic science research in the public sector during busts. Our results suggest that the ongoing coronavirus pandemic could lead to large innovations in the future.

Current literature suggests that urban heat-islands and their consequences are intensifying under climate change and urbanization. Here we explore the relatively unexplored hypothesis that emerging urban corridors (UCs) spawn megaregions of intense heat which are evident from observations. A delineation of the eleven United States UCs relative to their underlying climatological regions (non-UCs) suggest a surprisingly mixed trend. Medians and trends of winter temperatures over the last 60-years are generally higher in the UCs but no such general trends are observed in the summer. Heat wave metrics related to public health, energy demand and relative intensity do not exhibit significantly higher overall trends. Temperature and heat wave indices in the UCs exhibit high correlations with each other including across seasons. Spatiotemporal patterns in population, along with urbanization, agriculture and elevation, exhibit high (positive or negative) rank correlations with warming and heatwave intensification. The findings can inform climate adaptation in megalopolises.

Many studies have examined the impact of immigration on native wages. Some of these studies have relied upon education-experience groups to define labor markets and identify the wage elasticity with respect to immigrant labor supply. However, evidence suggests that immigrants’ educational attainment is treated differently in the labor market and constructing labor markets based upon this characteristic leads to potentially biased conclusions. We utilize O∗NET occupational characteristics to form a different set of labor markets. Our analysis finds higher partial equilibrium effects on native wages than prior work using education-experience skill groups, as expected. These larger effects, however, are shown to be concentrated on the least skilled natives. Estimates of the total wage effect along the distribution of occupational skills confirm that the negative wage effect is concentrated on native workers in the bottom tail of the distribution. Natives in the upper tail of the distribution experience wage gains as a result of immigration. The distributional impact is likely due to the distribution of skills among recent immigrants.

We present experimental evidence on the effects of four U.S. reemployment programs for youth Unemployment Insurance (UI) recipients during the Great Recession. The three programs that emphasized monitoring and service referrals reduced UI receipt but had minimal effects on employment and earnings; these programs mainly induced the early exit of participants. The fourth program, which combined mandatory job counseling with monitoring, caused the largest reductions in UI receipt and clearly increased employment and earnings. Both early participant exits and effective job counseling underlie these impacts. We conclude that policymakers should require job counseling for youth UI recipients during recessions.

Community Survey data to cover the years 1940 to 2018, we document trends in the proportions of ever-married men and women who are widowed. Then, focusing on women (who experience higher levels of widowhood than men), we examine variation in widowhood across race/ethnicity, education, and age. The proportion of ever-married adults who are widowed reflects not only change in the widowhood rate, but also the changing propensity for widow(er)s to remarry and exit the widowed state. For more information on changes in marital statuses over time, see our profiles on more than century of change in marriage (FP-20-21) and a more than a century of change in divorce (FP-20-22).

Ethnic-racial identity (ERI) formation is an important developmental task. Although families are a primary context for ERI socialization, little is known about siblings’ role. Accordingly, we applied the Actor-Partner Interdependence Model to longitudinal data from 2 siblings to examine the links between siblings’ ERI exploration, resolution, and affirmation. Participants were Mexican-origin mothers, fathers, and 2 siblings (older siblings Mage = 20.65 years; younger siblings Mage = 17.72 years) from 246 families in Arizona who were interviewed on 2 occasions across 2 years. Siblings’ ERI exploration in late adolescence positively predicted young adult ERI, accounting for mothers’ and fathers’ ERIs. For resolution, the sibling (i.e., partner) effect was moderated by sibling gender constellation, such that the sibling effect emerged only for same-sex dyads. For affirmation, the sibling effect emerged for older but not younger siblings. These findings highlight the need to understand siblings’ role in ERI and to expand research on family socialization of ERI beyond parents. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

We study a program that funded 39,000 Jewish households in New York City to leave enclave neighborhoods circa 1910. Compared to their neighbors with the same occupation and income score at baseline, program participants earned 4 percent more ten years after removal, and these gains persisted to the next generation. Men who left enclaves also married spouses with less Jewish names, but they did not choose less Jewish names for their children. Gains were largest for men who spent more years outside of an enclave. Our results suggest that leaving ethnic neighborhoods could facilitate economic advancement and assimilation into the broader society, but might make it more difficult to retain cultural identity.

The 2007–2009 financial crisis has caused economic disruption in many US cities and has drawn considerable academic attention. Despite abundant evidence of immigrants’ economic and social value to urban areas, little research has examined the relationship between immigration and resilience. This article investigates whether immigration enhanced economic resilience to the Great Recession for metropolitan areas in the US. It uses ordinary least squares and instrumental variable regressions to test the immigration effects between 2007 and 2014. The findings indicate that immigration leads to employment and income resilience. On average, metropolitan areas with a larger immigrant population tended to better preserve their growth paths during the Great Recession and to experience greater levels of employment and per capita income growth following the recession.

Technological change is a prominent hypothesis for the recent polarization of the labor market and the related decline for occupations specializing in performing routine tasks. In this paper, I provide a quantitative evaluation of this hypothesis. To do so, I build an extension of the standard growth model which allows for endogenous determination of the demand and supply for occupational labor in response to investment specific technological change. I further evaluate the extent to which this channel of technological change can account for recent declines in aggregate employment and the labor share of income. My analysis finds that technological change is able to account for a large fraction of changes in occupational employment and earnings, as well as the decline in the labor share, through the year 2000, but is unable to reconcile many of these patterns in the subsequent decade. In particular, after 2000, the model significantly overpredicts wages and hours for higher skilled occupations. This is at odds with both the recent measured slowdown in demand for these occupations as well as the hypothesis that slowing technological change can account for this phenomenon