Papers Containing Tag(s): 'American Community Survey'
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Viewing papers 1 through 10 of 263
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Working PaperTapping Business and Household Surveys to Sharpen Our View of Work from Home
June 2025
Working Paper Number:
CES-25-36
Timely business-level measures of work from home (WFH) are scarce for the U.S. economy. We review prior survey-based efforts to quantify the incidence and character of WFH and describe new questions that we developed and fielded for the Business Trends and Outlook Survey (BTOS). Drawing on more than 150,000 firm-level responses to the BTOS, we obtain four main findings. First, nearly a third of businesses have employees who work from home, with tremendous variation across sectors. The share of businesses with WFH employees is nearly ten times larger in the Information sector than in Accommodation and Food Services. Second, employees work from home about 1 day per week, on average, and businesses expect similar WFH levels in five years. Third, feasibility aside, businesses' largest concern with WFH relates to productivity. Seven percent of businesses find that onsite work is more productive, while two percent find that WFH is more productive. Fourth, there is a low level of tracking and monitoring of WFH activities, with 70% of firms reporting they do not track employee days in the office and 75% reporting they do not monitor employees when they work from home. These lessons serve as a starting point for enhancing WFH-related content in the American Community Survey and other household surveys.View Full Paper PDF
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Working PaperDivorce, Family Arrangements, and Children's Adult Outcomes
May 2025
Working Paper Number:
CES-25-28
Nearly a third of American children experience parental divorce before adulthood. To understand its consequences, we use linked tax and Census records for over 5 million children to examine how divorce affects family arrangements and children's long-term outcomes. Following divorce, parents move apart, household income falls, parents work longer hours, families move more frequently, and households relocate to poorer neighborhoods with less economic opportunity. This bundle of changes in family circumstances suggests multiple channels through which divorce may affect children's development and outcomes. In the years following divorce, we observe sharp increases in teen births and child mortality. To examine long-run effects on children, we compare siblings with different lengths of exposure to the same divorce. We find that parental divorce reduces children's adult earnings and college residence while increasing incarceration, mortality, and teen births. Changes in household income, neighborhood quality, and parent proximity account for 25 to 60 percent of these divorce effects.View Full Paper PDF
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Working PaperThe Impact of Childcare Costs on Mothers' Labor Force Participation
April 2025
Working Paper Number:
CES-25-25
The rising costs of childcare pose challenges for families, leading to difficult choices including those impacting mothers' labor force participation. This paper investigates the relationship between childcare costs and maternal employment. Using data from the National Database of Childcare Prices, the American Community Survey, and the Longitudinal Employer Household Dynamics, we estimate the impact of childcare costs on mothers' labor force participation through two empirical strategies. A fixed-effects approach controls for geographic and temporal heterogeneity in costs as well as mothers' idiosyncratic preferences for work and childcare, while an instrumental variables approach addresses the endogeneity of mothers' preferences for work and childcare by leveraging exogenous geographic and temporal variation in childcare licensing requirements. Our findings across both research designs indicate that higher childcare costs reduce labor force participation among mothers, with lower-income mothers exhibiting greater responsiveness to changes in childcare costs.View Full Paper PDF
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Working PaperPlace Based Economic Development and Tribal Casinos
April 2025
Working Paper Number:
CES-25-24
Tribal lands in the U.S. have historically experienced some of the worst economic conditions in the nation. We review some existing research on the effect of American Indian tribal casinos on various measures of local economic development. This is an industry that began in the early 1990s and currently generates more than $40 billion annually. We also review the state of the literature on the effects of casino operations on communities in or adjacent to tribal areas. Using a new dataset linking individual and enterprise-level data longitudinally, this study examines the industry- and location-specific impacts of tribal casino operations. We focus in particular on the employment of American Indians. We document positive flows from unemployment and non-casino geographies to work in sectors related to casino operations. Tribal casinos differ from other standard place-based economic development projects in that they are focused on a single industry; we discuss these differences and note that some of the positive spillover effects may be similar to other, more standard place-based policies. Finally, we discuss additional and open-ended questions for future research on this topic.View Full Paper PDF
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Working PaperRe-assessing the Spatial Mismatch Hypothesis
April 2025
Working Paper Number:
CES-25-23
We use detailed location information from the Longitudinal Employer-Household Dynamics (LEHD) database to develop new evidence on the effects of spatial mismatch on the relative earnings of Black workers in large US cities. We classify workplaces by the size of the pay premiums they offer in a two-way fixed effects model, providing a simple metric for defining 'good' jobs. We show that: (a) Black workers earn nearly the same average wage premiums as whites; (b) in most cities Black workers live closer to jobs, and closer to good jobs, than do whites; (c) Black workers typically commute shorter distances than whites; and (d) people who commute further earn higher average pay premiums, but the elasticity with respect to distance traveled is slightly lower for Black workers. We conclude that geographic proximity to good jobs is unlikely to be a major source of the racial earnings gaps in major U.S. cities today.View Full Paper PDF
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Working PaperSize Matters: Matching Externalities and the Advantages of Large Labor Markets
April 2025
Working Paper Number:
CES-25-22
Economists have long hypothesized that large and thick labor markets facilitate the matching between workers and firms. We use administrative data from the LEHD to compare the job search outcomes of workers originally in large and small markets who lost their jobs due to a firm closure. We define a labor market as the Commuting Zone'industry pair in the quarter before the closure. To account for the possible sorting of high-quality workers into larger markets, the effect of market size is identified by comparing workers in large and small markets within the same CZ, conditional on workers fixed effects. In the six quarters before their firm's closure, workers in small and large markets have a similar probability of employment and quarterly earnings. Following the closure, workers in larger markets experience significantly shorter non-employment spells and smaller earning losses than workers in smaller markets, indicating that larger markets partially insure workers against idiosyncratic employment shocks. A 1 percent increase in market size results in a 0.015 and 0.023 percentage points increase in the 1-year re-employment probability of high school and college graduates, respectively. Displaced workers in larger markets also experience a significantly lower need for relocation to a different CZ. Conditional on finding a new job, the quality of the new worker-firm match is higher in larger markets, as proxied by a higher probability that the new match lasts more than one year; the new industry is the same as the old one; and the new industry is a 'good fit' for the worker's college major. Consistent with the notion that market size should be particularly consequential for more specialized workers, we find that the effects are larger in industries where human capital is more specialized and less portable. Our findings may help explain the geographical agglomeration of industries'especially those that make intensive use of highly specialized workers'and validate one of the mechanisms that urban economists have proposed for the existence of agglomeration economies.View Full Paper PDF
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Working PaperThe Composition of Firm Workforces from 2006'2022: Findings from the Business Dynamics Statistics of Human Capital Experimental Product
April 2025
Working Paper Number:
CES-25-20
We introduce the Business Dynamics Statistics of Human Capital (BDS-HC) tables, a new Census Bureau experimental product that provides public-use statistics on the workforce composition of firms and its relationship to business dynamics. We use administrative W-2 filings to combine population-level worker demographic data with longitudinal business data to estimate the demographic and educational composition of nearly all non-farm employer businesses in the United States between 2006 and 2022. We use this newly constructed data to document the evolution of employment, entry, and exit of employers based on their workforce compositions. We also provide new statistics on the interaction between firm and worker characteristics, including the composition of workers at startup firms. We find substantial changes between 2006 and 2022 in the distribution of employers along several dimensions, primarily driven by changing workforce compositions within continuing firms rather than the reallocation of employment between firms. We also highlight systematic differences in the business dynamics of firms by their workforce compositions, suggesting that different groups of workers face different economic environments due to their employers.View Full Paper PDF
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Working PaperGeographic Immobility in the United States: Assessing the Prevalence and Characteristics of Those Who Never Migrate Across State Lines Using Linked Federal Tax Microdata
March 2025
Working Paper Number:
CES-25-19
This paper explores the prevalence and characteristics of those who never migrate at the state scale in the U.S. Studying people who never migrate requires regular and frequent observation of their residential location for a lifetime, or at least for many years. A novel U.S. population-sized longitudinal dataset that links individual level Internal Revenue Service (IRS) and Social Security Administration (SSA) administrative records supplies this information annually, along with information on income and socio-demographic characteristics. We use these administrative microdata to follow a cohort aged between 15 and 50 in 2001 from 2001 to 2016, differentiating those who lived in the same state every year during this period (i.e., never made an interstate move) from those who lived in more than one state (i.e., made at least one interstate move). We find those who never made an interstate move comprised 75 percent of the total population of this age cohort. This percentage varies by year of age but never falls below 62 percent even for those who were teenagers or young adults in 2001. There are also variations in these percentages by sex, race, nativity, and income, with the latter having the largest effects. We also find substantial variation in these percentages across states. Our findings suggest a need for more research on geographically immobile populations in U.S.View Full Paper PDF
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Working PaperWork Organization and Cumulative Advantage
March 2025
Working Paper Number:
CES-25-18
Over decades of wage stagnation, researchers have argued that reorganizing work can boost pay for disadvantaged workers. But upgrading jobs could inadvertently shift hiring away from those workers, exacerbating their disadvantage. We theorize how work organization affects cumulative advantage in the labor market, or the extent to which high-paying positions are increasingly allocated to already-advantaged workers. Specifically, raising technical skill demands exacerbates cumulative advantage by shifting hiring towards higher-skilled applicants. In contrast, when employers increase autonomy or skills learned on-the-job, they raise wages to buy worker consent or commitment, rather than pre-existing skill. To test this idea, we match administrative earnings to task descriptions from job posts. We compare earnings for workers hired into the same occupation and firm, but under different task allocations. When employers raise complexity and autonomy, new hires' starting earnings increase and grow faster. However, while the earnings boost from complex, technical tasks shifts employment toward workers with higher prior earnings, worker selection changes less for tasks learned on-the-job and very little for high autonomy tasks. These results demonstrate how reorganizing work can interrupt cumulative advantage.View Full Paper PDF
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Working PaperThe Design of Sampling Strata for the National Household Food Acquisition and Purchase Survey
February 2025
Working Paper Number:
CES-25-13
The National Household Food Acquisition and Purchase Survey (FoodAPS), sponsored by the United States Department of Agriculture's (USDA) Economic Research Service (ERS) and Food and Nutrition Service (FNS), examines the food purchasing behavior of various subgroups of the U.S. population. These subgroups include participants in the Supplemental Nutrition Assistance Program (SNAP) and the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), as well as households who are eligible for but don't participate in these programs. Participants in these social protection programs constitute small proportions of the U.S. population; obtaining an adequate number of such participants in a survey would be challenging absent stratified sampling to target SNAP and WIC participating households. This document describes how the U.S. Census Bureau (which is planning to conduct future versions of the FoodAPS survey on behalf of USDA) created sampling strata to flag the FoodAPS targeted subpopulations using machine learning applications in linked survey and administrative data. We describe the data, modeling techniques, and how well the sampling flags target low-income households and households receiving WIC and SNAP benefits. We additionally situate these efforts in the nascent literature on the use of big data and machine learning for the improvement of survey efficiency.View Full Paper PDF
