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Papers Containing Keywords(s): 'earnings'

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Longitudinal Employer Household Dynamics - 83

Current Population Survey - 76

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Longitudinal Business Database - 45

Center for Economic Studies - 44

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National Bureau of Economic Research - 27

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Cornell University - 21

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Longitudinal Research Database - 18

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Detailed Earnings Records - 16

International Trade Research Report - 16

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National Longitudinal Survey of Youth - 9

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UC Berkeley - 9

Employment History File - 9

Master Earnings File - 9

Kauffman Foundation - 9

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Characteristics of Business Owners - 9

Securities and Exchange Commission - 8

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National Institute on Aging - 8

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Russell Sage Foundation - 7

Center for Research in Security Prices - 7

University of Chicago - 7

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Federal Insurance Contribution Act - 7

Office of Management and Budget - 7

Journal of Economic Literature - 7

Employer Characteristics File - 7

Person Identification Validation System - 6

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Standard Occupational Classification - 6

Occupational Employment Statistics - 6

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NBER Summer Institute - 6

Office of Personnel Management - 6

American Economic Review - 6

Federal Reserve Board of Governors - 6

Census Bureau Longitudinal Business Database - 6

Employer-Household Dynamics - 6

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Cornell Institute for Social and Economic Research - 6

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Ohio State University - 5

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Duke University - 5

2010 Census - 4

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Journal of Political Economy - 4

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National Center for Health Statistics - 4

Boston College - 4

Center for Administrative Records Research and Applications - 4

General Accounting Office - 4

Sloan Foundation - 4

Society of Labor Economists - 4

Business Register Bridge - 4

Current Population Survey Annual Social and Economic Supplement - 4

Census Industry Code - 4

Medical Expenditure Panel Survey - 4

Personally Identifiable Information - 4

Wholesale Trade - 4

Department of Economics - 4

Journal of Labor Economics - 4

Federal Government - 4

Labor Turnover Survey - 4

Organization for Economic Cooperation and Development - 4

Stern School of Business - 4

Agriculture, Forestry - 4

Labor Productivity - 4

2SLS - 3

Integrated Longitudinal Business Database - 3

SSA Numident - 3

National Institutes of Health - 3

Department of Homeland Security - 3

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Successor Predecessor File - 3

New York Times - 3

American Immigration Council - 3

Center for Administrative Records Research - 3

Disability Insurance - 3

Master Address File - 3

Review of Economic Studies - 3

Core Based Statistical Area - 3

Temporary Assistance for Needy Families - 3

Indian Health Service - 3

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Cumulative Density Function - 3

Small Business Administration - 3

Arts, Entertainment - 3

Data Management System - 3

Business Services - 3

North American Free Trade Agreement - 3

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Professional Services - 3

University of California Los Angeles - 3

Information and Communication Technology Survey - 3

Urban Institute - 3

Brookings Institution - 3

IZA - 3

American Economic Association - 3

Pew Research Center - 3

JOLTS - 3

Public Administration - 3

Fabricated Metal Products - 3

Hypothesis 2 - 3

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MIT Press - 3

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bias - 13

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company - 13

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tenure - 13

retirement - 12

labor statistics - 12

employment statistics - 12

earnings employees - 12

hire - 12

employment wages - 12

industrial - 12

employment dynamics - 12

earnings mobility - 11

disclosure - 11

market - 11

earns - 11

census bureau - 11

demand - 11

compensation - 11

layoff - 11

organizational - 11

earnings workers - 11

workplace - 11

earnings growth - 10

earnings age - 10

opportunity - 10

efficiency - 10

welfare - 10

data - 10

minority - 10

average - 10

ssa - 10

wage earnings - 10

venture - 10

woman - 10

longitudinal employer - 10

discrimination - 9

yearly - 9

corporate - 9

wage growth - 9

census employment - 9

corporation - 9

employing - 9

earnings inequality - 9

report - 9

wages productivity - 9

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earnings gap - 8

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wages employment - 6

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employment effects - 6

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rent - 6

income distributions - 6

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measures employment - 6

capital productivity - 6

industry productivity - 6

employee data - 6

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technological - 5

employment estimates - 5

owner - 5

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medicaid - 5

gain - 5

expense - 5

firm data - 5

statistician - 5

economic census - 5

segregation - 4

parents income - 4

matching - 4

loan - 4

borrowing - 4

contract - 4

borrow - 4

institutional - 4

measures productivity - 4

benefit - 4

monopolistic - 4

firms productivity - 4

impact - 4

disadvantaged - 4

bankrupt - 4

ethnic - 4

exogeneity - 4

increase employment - 4

taxation - 4

employment distribution - 4

volatility - 4

assessing - 4

distribution - 4

disparity - 4

unobserved - 4

wage differences - 4

fertility - 4

marriage - 4

couple - 4

spouse - 4

innovation - 4

inventory - 4

regional - 4

trends employment - 4

productivity wage - 4

productivity estimates - 4

employment trends - 4

executive - 4

longitudinal - 4

employment measures - 4

mobility - 4

industry employment - 4

dependent - 4

divorced - 4

productive - 4

wage changes - 4

wage regressions - 4

equilibrium - 4

wage variation - 4

household income - 4

employment flows - 4

insurance coverage - 4

produce - 4

owned businesses - 4

research census - 4

capital - 4

productivity increases - 4

segregated - 3

generation - 3

housing - 3

neighborhood - 3

parent - 3

family income - 3

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advancement - 3

creditor - 3

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state employment - 3

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worker wages - 3

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education - 3

wage effects - 3

industry wages - 3

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premium - 3

federal - 3

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econometrically - 3

estimates production - 3

rural - 3

plant productivity - 3

productivity shocks - 3

provided census - 3

younger firms - 3

employer household - 3

analysis - 3

fiscal - 3

medicare - 3

healthcare - 3

job growth - 3

investment productivity - 3

employment production - 3

recession employment - 3

credit - 3

income households - 3

enrollment - 3

industry concentration - 3

worker demographics - 3

firm dynamics - 3

productivity differences - 3

productivity measures - 3

sector productivity - 3

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manager - 3

assessed - 3

proprietor - 3

record - 3

health insurance - 3

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efficient - 3

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Viewing papers 1 through 10 of 190


  • Working Paper

    How Do Neighborhoods and Firms Affect Intergenerational Mobility?

    March 2026

    Working Paper Number:

    CES-26-18

    We use data from the Longitudinal Employer Household Dynamics linked to the 2000 Census to study intergenerational earnings mobility in the United States. We augment the standard intergenerational transmission model relating children's log earnings to those of their parent with an additional term representing mean log parent earnings in the childhood neighborhood. The between-neighborhood intergenerational relationship is twice as strong as the within-neighborhood relationship, even after adjusting for measurement error in parents' earnings. Moreover, mean earnings of the parents in a neighborhood capture over 80% of the variation in unrestricted neighborhood effects that reflect differences in 'absolute mobility'. Next, we use an AKM framework to decompose parents', children's, and neighboring parents' earnings into person effects and establishment premiums. Children's person effects are mainly influenced by parents' and neighbors' person effects, whereas children's establishment premiums are mainly influenced by parents' and neighbors' establishment premiums. These patterns point to separate channels for human capital and access to jobs in the intergenerational transmission process. Finally, we explore the implications for the Black-white earnings gap. Neighborhoods explain 30% of the Black-white gap in children's earnings conditional on parents' earnings, operating largely through gaps in average person effects. Conditional on neighborhood average earnings, children from neighborhoods with higher Black shares achieve higher adult earnings.
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  • Working Paper

    College Majors and Earnings Growth

    February 2026

    Working Paper Number:

    CES-26-14

    We estimate major-specific earnings profiles using matched American Community Survey (ACS) and Longitudinal Employer-Household Dynamics (LEHD) data. Building on Deming and Noray (2020), we exploit a long earnings panel to overcome key limitations of cross-sectional approaches to lifecycle estimation. We find that engineering and computer science majors experience earnings growth that is comparable to or faster than that of other majors, a category including humanities, education, psychology, and similar fields. In contrast, Deming and Noray (2020) use a crosscohort approach and find that earnings for engineering and computer science majors decline relative to other fields over the lifecycle.
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  • Working Paper

    Establishment-Level Life Cycle and Analysts' Forecasts

    February 2026

    Working Paper Number:

    CES-26-12

    This paper examines how multi-unit firms' life-cycle stages affect analyst forecast accuracy. While prior studies focus on the firm-level life cycle, we utilize the Census data and focus on the establishment level. We find that analyst forecast accuracy is lower for multi-unit firms whose establishments are in different life-cycle stages than those in the same life-cycle stage. This finding suggests that the forecasting difficulty of more diversified firms can be attributed to the different life-cycle stages of each establishment. We also find that for firms whose units are in different stages, analyst forecast accuracy is lower if the establishments in earlier stages are larger (i.e., generate more revenue) than those in later stages. As a comparison, we estimate the life-cycle stages using firms' segment classifications in their 10-K filings. We find that analysts' forecast accuracy is lower when firms report fewer segments than the number of establishments, suggesting that aggregating more establishments for segment reporting could complicate analysts' forecasting. To our knowledge, this is the first study that focuses on the establishment-level life cycle. This study highlights that firm-level life cycles should not be taken without caution, as aggregating multiple units' life cycles may be misleading. In order to provide better forecasts to investors, analysts should have a deeper understanding of firms' subunits, especially when the establishments are in different life-cycle stages.
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  • Working Paper

    Careers of Minimum Wage Workers

    January 2026

    Working Paper Number:

    CES-26-07

    We characterize the careers of minimum wage workers by merging SIPP panels covering 1992-2016 into the LEHD. A long-run analysis shows strong earnings growth for these workers in subsequent decades, becoming indistinguishable from peers earning modestly more initially. Most of this growth is due to the steep earnings trajectories of young workers. Older workers earning minimum wages show a modest dip in earnings at that moment compared to earlier and later periods. Increases in state minimum wages do not significantly alter the future careers of workers who are on the minimum wage when the increases occur.
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  • Working Paper

    Non-Random Assignment of Individual Identifiers and Selection into Linked Data: Implications for Research

    January 2026

    Working Paper Number:

    CES-26-06

    The U.S. Census Bureau's Person Identification Validation System facilitates anonymous linkages between survey and administrative records by assigning Protected Identification Keys (PIKs) to person records. While PIK assignment is generally accurate, some person records are not successfully assigned a PIK, which can lead to sample selection bias in analyses of linked data. Using the American Community Survey (ACS) and the Current Population Survey Annual Social and Economic Supplement (CPS ASEC) between 2005 and 2022, we corroborate and extend existing findings on the drivers of PIK assignment, showing that the rate of PIK assignment varies widely across socio-demographic subgroups. Using earnings as a test case, we then show that limiting a survey sample of wage earners to person records with PIKs or successful linkages to W-2 wage records tends to overestimate self-reported wage earnings, on average, indicative of linkage-induced selection bias. In a validation exercise, we demonstrate that reweighting methods, such as inverse probability weighting or entropy balancing, can mitigate this bias.
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  • Working Paper

    Borrowing Constraints, Markups, and Misallocation

    December 2025

    Working Paper Number:

    CES-25-75

    We document new facts that link firms' markups to borrowing constraints: (1) less constrained firms within an industry have higher markups, especially in industries where assets are difficult to borrow against and firms rely more on earnings to borrow; (2) markup dispersion is also higher in industries where firms rely more on earnings to borrow. We explain these relationships using a standard Kimball demand model augmented with borrowing against assets and earnings. The key mechanism is a two-way feedback between markups and borrowing constraints. First, less constrained firms charge higher markups, as looser constraints allow them to attain larger market shares. Second, higher markups relax borrowing constraints when firms rely on earnings to borrow, as those with higher markups have higher earnings. This two-way feedback lowers TFP losses from markup dispersion, particularly when firms rely on earnings to borrow.
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  • Working Paper

    Double-Pane Glass Ceiling: Commercial Engagement and the Female-Male Earnings Gap for Faculty

    September 2025

    Authors: Joseph Staudt

    Working Paper Number:

    CES-25-68

    I use administrative data from universities (UMETRICS) linked to the universe of confidential W-2 and 1040-C tax records to measure faculty commercial engagement and its role in female-male earnings gaps. Female faculty are 20 percentage points less likely to engage commercially, with the entire gap driven by self-employment. The raw earnings gap is $63,000 on a base of $162,000 and non-university earnings account for $18,000 (29 percent) of this total. Thus, while university pay explains most of the gap, commercial engagement substantially amplifies it. Earnings gaps appear in all components of non-university pay ' self-employment, and work for incumbent, young/startup, high-tech, and non-high-tech firms ' and remain large, though attenuated, after controlling publications, patents, field, university, scientific resources, age, marital status, childbearing, and demographics. Gaps widen as faculty move up the earnings distribution, and commercial engagement becomes a larger contributor. Men and women engage with similar industries, but men earn more in all shared industries.
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  • Working Paper

    Job Tasks, Worker Skills, and Productivity

    September 2025

    Working Paper Number:

    CES-25-63

    We present new empirical evidence suggesting that we can better understand productivity dispersion across businesses by accounting for differences in how tasks, skills, and occupations are organized. This aligns with growing attention to the task content of production. We link establishment-level data from the Bureau of Labor Statistics Occupational Employment and Wage Statistics survey with productivity data from the Census Bureau's manufacturing surveys. Our analysis reveals strong relationships between establishment productivity and task, skill, and occupation inputs. These relationships are highly nonlinear and vary by industry. When we account for these patterns, we can explain a substantial share of productivity dispersion across establishments.
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  • Working Paper

    Estimating the Graduate Coverage of Post-Secondary Employment Outcomes

    September 2025

    Authors: Cody Orr

    Working Paper Number:

    CES-25-61

    This paper proposes a new methodology for estimating the coverage rate of the Post-Secondary Employment Outcomes data product (PSEO), both as a share of new graduates and as a share of total working-age degree holders in the United States. This paper also assesses how representative PSEO is of the broader population of college graduates across an array of institutional and individual characteristics.
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  • Working Paper

    Unemployment Insurance, Wage Pass-Through, and Endogenous Take-Up

    September 2025

    Working Paper Number:

    CES-25-59

    This paper studies how unemployment insurance (UI) generosity affects reservation wages, re-employment wages, and benefit take-up. Using Benefit Accuracy Measurement (BAM) data, we estimate a cross-sectional elasticity of reservation wages with respect to weekly UI benefits of 0.014. Exploiting state variation in Pandemic Unemployment Assistance (PUA) intensity and the timing of federal supplements, we find that expanded benefits during COVID-19 increased reservation wages by 8'12 percent. Using CPS rotation data, we also document a 9 percent rise in re-employment wages for UI-eligible workers relative to ineligible workers. Over the same period, the UI take-up rate rose from roughly 30 to 40 percent; Probit estimates indicate that higher benefit levels, rather than changes in observables, account for this increase. A directed search model with an endogenous filing decision replicates these facts: generosity primarily operates through the extensive margin of take-up, which mutes the pass-through from benefits to wages.
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