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Papers Containing Keywords(s): 'employ'

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Longitudinal Employer Household Dynamics - 131

Bureau of Labor Statistics - 99

Longitudinal Business Database - 90

North American Industry Classification System - 89

Current Population Survey - 85

Center for Economic Studies - 77

Internal Revenue Service - 71

National Science Foundation - 66

Standard Industrial Classification - 65

Ordinary Least Squares - 65

American Community Survey - 64

Employer Identification Numbers - 61

Census Bureau Disclosure Review Board - 61

Alfred P Sloan Foundation - 56

Social Security Administration - 49

Decennial Census - 47

Quarterly Census of Employment and Wages - 46

Quarterly Workforce Indicators - 44

Federal Statistical Research Data Center - 40

National Bureau of Economic Research - 38

Metropolitan Statistical Area - 34

Census of Manufactures - 33

Annual Survey of Manufactures - 33

Business Register - 33

Disclosure Review Board - 32

Social Security - 32

Unemployment Insurance - 31

Protected Identification Key - 30

Federal Reserve Bank - 29

Chicago Census Research Data Center - 29

Bureau of Economic Analysis - 28

Survey of Income and Program Participation - 27

International Trade Research Report - 26

Department of Labor - 25

Cornell University - 25

Social Security Number - 25

Economic Census - 22

Census Bureau Business Register - 22

Longitudinal Research Database - 22

Standard Statistical Establishment List - 22

Individual Characteristics File - 21

Total Factor Productivity - 21

LEHD Program - 21

County Business Patterns - 20

Census Bureau Longitudinal Business Database - 20

Special Sworn Status - 19

Local Employment Dynamics - 19

University of Chicago - 19

AKM - 18

W-2 - 18

Research Data Center - 18

Business Dynamics Statistics - 17

National Institute on Aging - 17

PSID - 17

Federal Reserve System - 16

Employment History File - 15

Census of Manufacturing Firms - 15

Employer Characteristics File - 14

2010 Census - 13

Employer-Household Dynamics - 13

Occupational Employment Statistics - 13

National Longitudinal Survey of Youth - 13

University of Maryland - 13

Herfindahl Hirschman Index - 12

Cornell Institute for Social and Economic Research - 12

Financial, Insurance and Real Estate Industries - 12

American Economic Review - 12

Core Based Statistical Area - 11

Retail Trade - 11

Business Register Bridge - 11

Wholesale Trade - 10

Standard Occupational Classification - 10

Technical Services - 10

Department of Homeland Security - 10

Office of Personnel Management - 10

Successor Predecessor File - 10

Organization for Economic Cooperation and Development - 10

Journal of Labor Economics - 10

Journal of Economic Literature - 10

Master Address File - 9

National Employer Survey - 9

NBER Summer Institute - 9

Census Numident - 9

Business Employment Dynamics - 9

Russell Sage Foundation - 9

Board of Governors - 9

Council of Economic Advisers - 8

Accommodation and Food Services - 8

Agriculture, Forestry - 8

Integrated Longitudinal Business Database - 8

Department of Economics - 8

National Center for Health Statistics - 8

Sloan Foundation - 8

Person Validation System - 8

Columbia University - 8

American Economic Association - 8

Kauffman Foundation - 8

Department of Defense - 8

Sample Edited Detail File - 8

Small Business Administration - 7

Survey of Business Owners - 7

Integrated Public Use Microdata Series - 7

Composite Person Record - 7

Department of Health and Human Services - 7

University of Michigan - 7

Nonemployer Statistics - 7

Michigan Institute for Teaching and Research in Economics - 7

Office of Management and Budget - 7

Business Services - 7

Labor Turnover Survey - 7

JOLTS - 7

National Income and Product Accounts - 7

Service Annual Survey - 7

North American Industry Classi - 7

Census Bureau Business Dynamics Statistics - 7

Journal of Political Economy - 7

1940 Census - 7

Annual Business Survey - 6

Educational Services - 6

Arts, Entertainment - 6

Oil and Gas Extraction - 6

World Trade Organization - 6

COVID-19 - 6

Professional Services - 6

New York University - 6

IQR - 6

Company Organization Survey - 6

CDF - 6

Cumulative Density Function - 6

Ohio State University - 6

Health Care and Social Assistance - 6

Urban Institute - 6

National Establishment Time Series - 6

Geographic Information Systems - 6

Bureau of Labor - 6

IZA - 6

Society of Labor Economists - 6

Detailed Earnings Records - 6

Quarterly Journal of Economics - 6

Hypothesis 2 - 6

Current Employment Statistics - 6

New York Times - 6

BLS Handbook of Methods - 6

Characteristics of Business Owners - 6

Consolidated Metropolitan Statistical Areas - 6

Permanent Plant Number - 6

WECD - 6

North American Free Trade Agreement - 5

Ewing Marion Kauffman Foundation - 5

LODES - 5

Department of Education - 5

Stanford University - 5

Legal Form of Organization - 5

Census Bureau Center for Economic Studies - 5

Department of Housing and Urban Development - 5

MIT Press - 5

Center for Research in Security Prices - 5

Public Administration - 5

Harvard University - 5

Review of Economics and Statistics - 5

Business Master File - 5

American Housing Survey - 5

Labor Productivity - 5

NICHD - 5

American Statistical Association - 5

Duke University - 5

Postal Service - 5

Generalized Method of Moments - 5

Public Use Micro Sample - 5

Department of Commerce - 5

Form W-2 - 4

VAR - 4

University of Texas - 4

Multiple Worksite Report - 4

University of Toronto - 4

Harmonized System - 4

Social Security Disability Insurance - 4

Federal Emergency Management Agency - 4

Princeton University - 4

Cobb-Douglas - 4

Indian Health Service - 4

National Institutes of Health - 4

Patent and Trademark Office - 4

Retirement History Survey - 4

Medical Expenditure Panel Survey - 4

Federal Tax Information - 4

DOB - 4

Agency for Healthcare Research and Quality - 4

Center for Administrative Records Research - 4

Personally Identifiable Information - 4

Federal Reserve Board of Governors - 4

Pew Research Center - 4

Housing and Urban Development - 4

LEHD Origin-Destination Employment Statistics - 4

ASEC - 4

Census 2000 - 4

Initial Public Offering - 4

University of California Los Angeles - 4

SSA Numident - 4

Journal of Economic Perspectives - 4

Social and Economic Supplement - 4

Department of Agriculture - 4

Journal of Econometrics - 4

Heckscher-Ohlin - 4

Limited Liability Company - 3

Maximum Likelihood Estimation - 3

Department of Energy - 3

MAF-ARF - 3

United States Census Bureau - 3

Federal Trade Commission - 3

Department of Justice - 3

Boston College - 3

Longitudinal Firm Trade Transactions Database - 3

Kauffman Firm Survey - 3

Person Identification Validation System - 3

Research and Development - 3

Securities and Exchange Commission - 3

Probability Density Function - 3

Data Management System - 3

Federal Insurance Contribution Act - 3

Journal of Human Resources - 3

Disability Insurance - 3

2SLS - 3

UC Berkeley - 3

American Immigration Council - 3

Current Population Survey Annual Social and Economic Supplement - 3

HHS - 3

Census Industry Code - 3

Federal Reserve Bank of Chicago - 3

Supreme Court - 3

World Bank - 3

Census of Services - 3

Boston Research Data Center - 3

Cambridge University Press - 3

Survey of Manufacturing Technology - 3

employed - 158

workforce - 142

labor - 141

employee - 108

worker - 75

earnings - 72

payroll - 66

recession - 65

job - 52

hiring - 52

salary - 45

economist - 44

econometric - 42

occupation - 39

unemployed - 36

employment growth - 35

hire - 35

earner - 34

entrepreneurship - 34

workplace - 33

earn - 33

endogeneity - 33

employment dynamics - 33

heterogeneity - 31

quarterly - 30

industrial - 30

employing - 29

estimating - 28

macroeconomic - 28

survey - 28

growth - 28

establishment - 28

tenure - 28

shift - 27

census employment - 26

layoff - 25

employment statistics - 25

entrepreneur - 24

manufacturing - 24

sector - 22

longitudinal - 22

labor statistics - 21

entrepreneurial - 20

metropolitan - 20

labor markets - 18

venture - 18

turnover - 18

incentive - 17

longitudinal employer - 17

discrimination - 16

census bureau - 16

market - 16

employment estimates - 16

production - 16

estimates employment - 15

economically - 15

employment data - 15

employee data - 15

employment wages - 15

unemployment rates - 14

expenditure - 14

gdp - 14

econometrician - 14

immigrant - 14

proprietorship - 14

bias - 14

agency - 13

trend - 13

employment trends - 13

compensation - 13

relocation - 13

enterprise - 13

organizational - 13

ethnicity - 13

trends employment - 12

export - 12

regress - 12

migrant - 12

work census - 12

rent - 12

opportunity - 12

employment count - 12

employer household - 12

minority - 11

proprietor - 11

industry employment - 11

specialization - 11

immigration - 11

statistical - 11

report - 11

spillover - 11

workers earnings - 11

wage growth - 11

retirement - 11

estimation - 11

segregation - 11

mobility - 11

aging - 11

revenue - 10

earnings employees - 10

respondent - 10

research census - 10

recessionary - 10

effect wages - 10

employment earnings - 10

acquisition - 10

hispanic - 10

housing - 10

resident - 10

worker wages - 10

ethnic - 10

manager - 10

wage data - 10

union - 10

earnings workers - 9

exogeneity - 9

unobserved - 9

relocate - 9

employment effects - 9

company - 9

endogenous - 9

demand - 9

industry wages - 9

insurance - 9

residential - 9

residence - 9

state - 9

matching - 9

finance - 9

employment unemployment - 9

employment changes - 9

economic census - 9

disparity - 8

employment declines - 8

profit - 8

socioeconomic - 8

wage earnings - 8

career - 8

impact employment - 8

migration - 8

data census - 8

population - 8

effects employment - 8

worker demographics - 8

employment production - 8

woman - 8

geographically - 8

neighborhood - 8

productivity growth - 8

technological - 8

earnings growth - 8

educated - 8

wage industries - 8

workforce indicators - 8

disadvantaged - 8

wages employment - 8

racial - 7

decline - 7

wage variation - 7

employment firms - 7

employment increases - 7

employment distribution - 7

migrate - 7

employment flows - 7

efficiency - 7

census data - 7

investment - 7

decade - 7

job growth - 7

city - 7

increase employment - 7

innovation - 7

sale - 7

associate - 7

wage changes - 7

accounting - 7

aggregate - 7

employment measures - 7

recession employment - 7

poverty - 7

state employment - 7

wage regressions - 7

rates employment - 7

clerical - 7

labor productivity - 7

declining - 6

irs - 6

regressing - 6

welfare - 6

shock - 6

moving - 6

regional - 6

startup - 6

growth employment - 6

employment entrepreneurship - 6

immigrant workers - 6

prospect - 6

coverage - 6

earnings inequality - 6

pension - 6

microdata - 6

unemployment insurance - 6

wage differences - 6

rural - 6

merger - 6

department - 6

earnings mobility - 6

data - 6

restructuring - 6

discriminatory - 5

analyst - 5

regression - 5

migrating - 5

multinational - 5

paper census - 5

censuses surveys - 5

employed census - 5

startups employees - 5

enrollment - 5

import - 5

exporter - 5

ownership - 5

wealth - 5

home - 5

insured - 5

graduate - 5

refugee - 5

debt - 5

race - 5

federal - 5

productivity wage - 5

medicaid - 5

filing - 5

econometrically - 5

firms grow - 5

firm dynamics - 5

firms employment - 5

native - 5

firms young - 5

measures employment - 5

wages production - 5

employment recession - 5

bankruptcy - 5

heterogeneous - 5

relocating - 5

financial - 5

mexican - 5

factory - 5

white - 5

tax - 4

measures productivity - 4

information census - 4

monopolistic - 4

benefit - 4

autoregressive - 4

international trade - 4

nonemployer businesses - 4

urban - 4

growth productivity - 4

transition - 4

impact - 4

advancement - 4

insurance employer - 4

analysis - 4

statistician - 4

financing - 4

executive - 4

productive - 4

saving - 4

model - 4

coverage employer - 4

disability - 4

wage effects - 4

founder - 4

younger firms - 4

earnings age - 4

gender - 4

record - 4

citizen - 4

startup firms - 4

census research - 4

leverage - 4

wages productivity - 4

discrepancy - 4

inference - 4

sociology - 4

corporate - 4

segregated - 4

black - 4

technology - 4

census business - 3

2010 census - 3

midwest - 3

forecast - 3

applicant - 3

immigrant entrepreneurs - 3

assimilation - 3

percentile - 3

assessed - 3

preschool - 3

wage gap - 3

earnings gap - 3

takeover - 3

wholesale - 3

employees startups - 3

subsidy - 3

industry heterogeneity - 3

exporting - 3

exporters multinationals - 3

warehousing - 3

outsourced - 3

renter - 3

town - 3

suburb - 3

commute - 3

researcher - 3

funding - 3

firms census - 3

industry concentration - 3

medicare - 3

healthcare - 3

health insurance - 3

insurance premiums - 3

estimator - 3

earns - 3

women earnings - 3

managerial - 3

industry variation - 3

ssa - 3

area - 3

volatility - 3

imputation - 3

gain - 3

profitability - 3

trends labor - 3

census file - 3

geographic - 3

household surveys - 3

use census - 3

fiscal - 3

trade models - 3

firms plants - 3

capital - 3

network - 3

matched - 3

immigrant population - 3

produce - 3

plant employment - 3

firm growth - 3

characteristics businesses - 3

owned businesses - 3

tech - 3

owner - 3

plants industry - 3

factor productivity - 3

Viewing papers 71 through 80 of 253


  • Working Paper

    Earnings Growth, Job Flows and Churn

    April 2020

    Working Paper Number:

    CES-20-15

    How much do workers making job-to-job transitions benefit from moving away from a shrinking and towards a growing firm? We show that earnings growth in the transition increases with net employment growth at the destination firm and, to a lesser extent, decreases if the origin firm is shrinking. So, we sum the effect of leaving a shrinking and entering a growing firm and remove the excess turnover-related hires because gross hiring has a much smaller association with earnings growth than net employment growth. We find that job-to-job transitions with the cross-firm job flow have 23% more earnings growth than average.
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  • Working Paper

    Between Firm Changes in Earnings Inequality: The Dominant Role of Industry Effects

    February 2020

    Working Paper Number:

    CES-20-08

    We find that most of the rising between firm earnings inequality that dominates the overall increase in inequality in the U.S. is accounted for by industry effects. These industry effects stem from rising inter-industry earnings differentials and not from changing distribution of employment across industries. We also find the rising inter-industry earnings differentials are almost completely accounted for by occupation effects. These results link together the key findings from separate components of the recent literature: one focuses on firm effects and the other on occupation effects. The link via industry effects challenges conventional wisdom.
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  • Working Paper

    Do Cash Windfalls Affect Wages? Evidence from R&D Grants to Small Firms

    February 2020

    Working Paper Number:

    CES-20-06

    This paper examines how employee earnings at small firms respond to a cash flow shock in the form of a government R&D grant. We use ranking data on applicant firms, which we link to IRS W2 earnings and other U.S. Census Bureau datasets. In a regression discontinuity design, we find that the grant increases average earnings with a rent-sharing elasticity of 0.07 (0.21) at the employee (firm) level. The beneficiaries are incumbent employees who were present at the firm before the award. Among incumbent employees, the effect increases with worker tenure. The grant also leads to higher employment and revenue, but productivity growth cannot fully explain the immediate effect on earnings. Instead, the data and a grantee survey are consistent with a backloaded wage contract channel, in which employees of financially constrained firms initially accept relatively low wages and are paid more when cash is available.
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  • Working Paper

    Nonemployer Statistics by Demographics (NES-D): Exploring Longitudinal Consistency and Sub-national Estimates

    December 2019

    Working Paper Number:

    CES-19-34

    Until recently, the quinquennial Survey of Business Owners (SBO) was the only source of information for U.S. employer and nonemployer businesses by owner demographic characteristics such as race, ethnicity, sex and veteran status. Now, however, the Nonemployer Statistics by Demographics series (NES-D) will replace the SBO's nonemployer component with reliable, and more frequent (annual) business demographic estimates with no additional respondent burden, and at lower imputation rates and costs. NES-D is not a survey; rather, it exploits existing administrative and census records to assign demographic characteristics to the universe of approximately 25 million (as of 2016) nonemployer businesses. Although only in the second year of its research phase, NES-D is rapidly moving towards production, with a planned prototype or experimental version release of 2017 nonemployer data in 2020, followed by annual releases of the series. After the first year of research, we released a working paper (Luque et al., 2019) that assessed the viability of estimating nonemployer demographics exclusively with administrative records (AR) and census data. That paper used one year of data (2015) to produce preliminary tabulations of business counts at the national level. This year we expand that research in multiple ways by: i) examining the longitudinal consistency of administrative and census records coverage, and of our AR-based demographics estimates, ii) evaluating further coverage from additional data sources, iii) exploring estimates at the sub-national level, iv) exploring estimates by industrial sector, v) examining demographics estimates of business receipts as well as of counts, and vi) implementing imputation of missing demographic values. Our current results are consistent with the main findings in Luque et al. (2019), and show that high coverage and demographic assignment rates are not the exception, but the norm. Specifically, we find that AR coverage rates are high and stable over time for each of the three years we examine, 2014-2016. We are able to identify owners for approximately 99 percent of nonemployer businesses (excluding C-corporations), 92 to 93 percent of identified nonemployer owners have no missing demographics, and only about 1 percent are missing three or more demographic characteristics in each of the three years. We also find that our demographics estimates are stable over time, with expected small annual changes that are consistent with underlying population trends in the U.S.. Due to data limitations, these results do not include C-corporations, which represent only 2 percent of nonemployer businesses and 4 percent of receipts. Without added respondent burden and at lower imputation rates and costs, NES-D will provide high-quality business demographics estimates at a higher frequency (annual vs. every 5 years) than the SBO.
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  • Working Paper

    What Do Establishments Do When Wages Increase? Evidence from Minimum Wages in the United States

    November 2019

    Authors: Yuci Chen

    Working Paper Number:

    CES-19-31

    I investigate how establishments adjust their production plans on various margins when wage rates increase. Exploiting state-by-year variation in minimum wage, I analyze U.S. manufacturing plants' responses over a 23-year period. Using instrumental variable method and Census Microdata, I find that when the hourly wage of production workers increases by one percent, manufacturing plants reduce the total hours worked by production workers by 0.7 percent and increase capital expenditures on machinery and equipment by 2.7 percent. The reduction in total hours worked by production workers is driven by intensive-margin changes. The estimated elasticity of substitution between capital and labor is 0.85. Following the wage increases, no statistically significant changes emerge in revenue, materials or total factor productivity. Additionally, I nd that when wage rates increase, establishments are more likely to exit the market. Finally, I provide evidence that when the minimum wage increases the wages of some of the establishments in a firm, the firm also increases the wages for its other establishments.
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  • Working Paper

    A Task-based Approach to Constructing Occupational Categories with Implications for Empirical Research in Labor Economics

    September 2019

    Working Paper Number:

    CES-19-27

    Most applied research in labor economics that examines returns to worker skills or differences in earnings across subgroups of workers typically accounts for the role of occupations by controlling for occupational categories. Researchers often aggregate detailed occupations into categories based on the Standard Occupation Classification (SOC) coding scheme, which is based largely on narratives or qualitative measures of workers' tasks. Alternatively, we propose two quantitative task-based approaches to constructing occupational categories by using factor analysis with O*NET job descriptors that provide a rich set of continuous measures of job tasks across all occupations. We find that our task-based approach outperforms the SOC-based approach in terms of lower occupation distance measures. We show that our task-based approach provides an intuitive, nuanced interpretation for grouping occupations and permits quantitative assessments of similarities in task compositions across occupations. We also replicate a recent analysis and find that our task-based occupational categories explain more of the gender wage gap than the SOC-based approaches explain. Our study enhances the Federal Statistical System's understanding of the SOC codes, investigates ways to use third-party data to construct useful research variables that can potentially be added to Census Bureau data products to improve their quality and versatility, and sheds light on how the use of alternative occupational categories in economics research may lead to different empirical results and deeper understanding in the analysis of labor market outcomes.
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  • Working Paper

    Did Timing Matter? Life Cycle Differences in Effects of Exposure to the Great Recession

    September 2019

    Authors: Kevin Rinz

    Working Paper Number:

    CES-19-25

    Exposure to a recession can have persistent, negative consequences, but does the severity of those consequences depend on when in the life cycle a person is exposed? I estimate the effects of exposure to the Great Recession on employment and earnings outcomes for groups defined by year of birth over the ten years following the beginning of the recession. With the exception of the oldest workers, all groups experience reductions in earnings and employment due to local unemployment rate shocks during the recession. Younger workers experience the largest earnings losses in percent terms (up to 13 percent), in part because recession exposure makes them persistently less likely to work for high-paying employers even as their overall employment recovers more quickly than older workers'. Younger workers also experience reductions in earnings and employment due to changes in local labor market structure associated with the recession. These effects are substantially smaller in magnitude but more persistent than the effects of unemployment rate increases.
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  • Working Paper

    Gender Differences in Self-employment Duration: the Case of Opportunity and Necessity Entrepreneurs

    September 2019

    Working Paper Number:

    CES-19-24

    A strand of the self-employment literature suggests that those 'pushed' into self-employment out of necessity may perform differently from those 'pulled' into self-employment to pursue a business opportunity. While findings on self-employment outcomes by self-employed type are not unanimous, there is mounting evidence that performance outcomes differ between these two self-employed types. Another strand of the literature has found important gender differences in self-employment entry rates, motivations for entry, and outcomes. Using a unique set of data that links the American Community Survey to administrative data from Form 1040 and W-2 records, we bring together these two strands of the literature. We explore whether there are gender differences in self-employment duration of self-employed types. In particular, we examine the likelihood of self-employment exit towards unemployment versus the wage sector for five consecutive entry cohorts, including two cohorts who entered self-employment during the Great Recession. Severely limited labor-market opportunities may have driven many in the recession cohorts to enter self-employment, while those entering self-employment during the boom may have been pursuing opportunities under favorable market conditions. To more explicitly test the concept of 'necessity' versus 'opportunity' self-employment, we also examine the wage labor attachment (or weeks worked in the wage sector) in the year prior to becoming self-employed. We find that, within the cohorts we examine, there are gender differences in the rate at which men and women depart self-employment for either wage work or non-participation, but that the patterns are dependent on pre self-employment wage-sector attachment and cohort effects.
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  • Working Paper

    Pay, Employment, and Dynamics of Young Firms

    July 2019

    Working Paper Number:

    CES-19-23

    Why do young firms pay less? Using confidential microdata from the US Census Bureau, we find lower earnings among workers at young firms. However, we argue that such measurement is likely subject to worker and firm selection. Exploiting the two-sided panel nature of the data to control for relevant dimensions of worker and firm heterogeneity, we uncover a positive and significant young-firm pay premium. Furthermore, we show that worker selection at firm birth is related to future firm dynamics, including survival and growth. We tie our empirical findings to a simple model of pay, employment, and dynamics of young firms.
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  • Working Paper

    Demographic Origins of the Startup Deficit

    July 2019

    Working Paper Number:

    CES-19-21

    We propose a simple explanation for the long-run decline in the startup rate. It was caused by a slowdown in labor supply growth since the late 1970s, largely pre-determined by demographics. This channel explains roughly two-thirds of the decline and why incumbent firm survival and average growth over the lifecycle have been little changed. We show these results in a standard model of firm dynamics and test the mechanism using shocks to labor supply growth across states. Finally, we show that a longer startup rate series imputed using historical establishment tabulations rises over the 1960-70s period of accelerating labor force growth.
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