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Papers Containing Keywords(s): 'payroll'

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Bureau of Labor Statistics - 70

Longitudinal Employer Household Dynamics - 61

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Review of Economics and Statistics - 3

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Viewing papers 1 through 10 of 127


  • Working Paper

    LODES Design and Methodology Report: Methodology Version 7

    August 2025

    Working Paper Number:

    CES-25-52

    The purpose of this report is to document the important features of Version 7 of the LEHD Origin-Destination Employment Statistics (LODES) processing system. This includes data sources, data processing methodology, confidentiality protection methodology, some quality measures, and a high-level description of the published data. The intended audience for this document includes LODES data users, Local Employment Dynamics (LED) Partnership members, U.S. Census Bureau management, program quality auditors, and current and future research and development staff members.
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  • Working Paper

    The Effect of the Minimum Wage on Childcare Establishments

    August 2025

    Working Paper Number:

    CES-25-53

    Childcare is essential for working families, yet it remains increasingly unaffordable and inaccessible for parents and offers poverty-level wages to many employees. While research suggests minimum wage policies may improve the welfare of low-wage workers, there is also evidence they may increase firm exits, especially among smaller, low-profit firms, which could reduce access and harm consumer well-being. This study is the first to examine these trade-offs in the childcare industry, a labor-intensive, highly regulated sector where capital-labor substitution is limited, and to provide evidence on how minimum wage policies affect a dual-sector labor market in the U.S., where self-employed and waged providers serve overlapping markets. Using variation from state-level minimum wage increases between 1995 and 2019 and unique microdata, I implement a cross-state county border discontinuity design to estimate impacts on the stocks, flows, and composition of childcare establishments. I find that while county-level aggregate establishment stocks and employment remained stable, establishment-level turnover increased, and employment decreased. I reconcile these findings by showing that minimum wage increases prompted reallocation, with larger establishments in the waged-sector more likely to enter and less likely to exit, making this one of the first studies to link null aggregate effects to shifts in establishment composition. Finally, I show that minimum wage increases may negatively affect the self-employed sector, resulting in fewer owners with advanced degrees and more with only high school education. These findings suggest that minimum wage policies reshape who provides care in ways that could affect both quality and access.
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  • Working Paper

    Tapping 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.
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  • Working Paper

    The 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.
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  • Working Paper

    Work 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.
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  • Working Paper

    Workers' Job Prospects and Young Firm Dynamics

    January 2025

    Authors: Seula Kim

    Working Paper Number:

    CES-25-09

    This paper investigates how worker beliefs and job prospects impact the wages and growth of young firms, as well as the aggregate economy. Building a heterogeneous-firm directed search model where workers gradually learn about firm types, I find that learning generates endogenous wage differentials for young firms. High-performing young firms must pay higher wages than equally high-performing old firms, while low-performing young firms offer lower wages than equally low-performing old firms. Reduced uncertainty or labor market frictions lower the wage differentials, thereby enhancing young firm dynamics and aggregate productivity. The results are consistent with U.S. administrative employee-employer matched data.
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  • Working Paper

    Exploring the Hiring, Pay, and Trading Patterns of U.S. Firms: The Dominance of Multinationals Engaged in Related-Party Trade

    December 2024

    Working Paper Number:

    CES-24-77

    We link U.S. job records with both firm-level business register and customs records to construct a novel set of summary statistics and descriptive regressions that highlight the central role played by the small set of multinational firms (denoted RP XM firms) who engage in both importing and exporting with related parties in translating international trade shocks to shifts in labor demand. We find that RP XM firms 1) dominate trade volumes; 2) account for very disproportionate shares of national employment and payroll; 3) employ greater shares of workers in higher pay deciles; 4) disproportionately poach other firms' high paid workers; 5) offer higher raises to their existing workers. These hiring and pay patterns generally exist even among new RP XM firms, but strengthen with RP XM tenure, and continue to hold, albeit at smaller magnitudes, after conditioning on standard proxies for firm and worker productivity. Taken together, these findings reveal that RP XM status is a reliable proxy for the kind of firm that drives the initial labor market impacts of trade shocks, and that high paid workers are likely to be most directly exposed to such shocks.
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  • Working Paper

    Tip of the Iceberg: Tip Reporting at U.S. Restaurants, 2005-2018

    November 2024

    Working Paper Number:

    CES-24-68

    Tipping is a significant form of compensation for many restaurant jobs, but it is poorly measured and therefore not well understood. We combine several large administrative and survey datasets and document patterns in tip reporting that are consistent with systematic under-reporting of tip income. Our analysis indicates that although the vast majority of tipped workers do report earning some tips, the dollar value of tips is under-reported and is sensitive to reporting incentives. In total, we estimate that about eight billion in tips paid at full-service, single-location, restaurants were not captured in tax data annually over the period 2005-2018. Due to changes in payment methods and reporting incentives, tip reporting has increased over time. Our findings have implications for downstream measures dependent on accurate measures of compensation including poverty measurement among tipped restaurant workers.
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  • Working Paper

    Driving the Gig Economy

    August 2024

    Working Paper Number:

    CES-24-42

    Using rich administrative tax data, we explore the effects of the introduction of online ridesharing platforms on entry, employment and earnings in the Taxi and Limousine Services industry. Ridesharing dramatically increased the pace of entry of workers into the industry. New entrants were more likely to be young, female, White and U.S. born, and to combine earnings from ridesharing with wage and salary earnings. Displaced workers have found ridesharing to be a substantially more attractive fallback option than driving a taxi. Ridesharing also affected the incumbent taxi driver workforce. The exit rates of low-earning taxi drivers increased following the introduction of ridesharing in their city; exit rates of high-earning taxi drivers were little affected. In cities without regulations limiting the size of the taxi fleet, both groups of drivers experienced earnings losses following the introduction of ridesharing. These losses were ameliorated or absent in more heavily regulated markets.
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  • Working Paper

    Expanding the Frontier of Economic Statistics Using Big Data: A Case Study of Regional Employment

    July 2024

    Working Paper Number:

    CES-24-37

    Big data offers potentially enormous benefits for improving economic measurement, but it also presents challenges (e.g., lack of representativeness and instability), implying that their value is not always clear. We propose a framework for quantifying the usefulness of these data sources for specific applications, relative to existing official sources. We specifically weigh the potential benefits of additional granularity and timeliness, while examining the accuracy associated with any new or improved estimates, relative to comparable accuracy produced in existing official statistics. We apply the methodology to employment estimates using data from a payroll processor, considering both the improvement of existing state-level estimates, but also the production of new, more timely, county-level estimates. We find that incorporating payroll data can improve existing state-level estimates by 11% based on out-of-sample mean absolute error, although the improvement is considerably higher for smaller state-industry cells. We also produce new county-level estimates that could provide more timely granular estimates than previously available. We develop a novel test to determine if these new county-level estimates have errors consistent with official series. Given the level of granularity, we cannot reject the hypothesis that the new county estimates have an accuracy in line with official measures, implying an expansion of the existing frontier. We demonstrate the practical importance of these experimental estimates by investigating a hypothetical application during the COVID-19 pandemic, a period in which more timely and granular information could have assisted in implementing effective policies. Relative to existing estimates, we find that the alternative payroll data series could help identify areas of the country where employment was lagging. Moreover, we also demonstrate the value of a more timely series.
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