Papers Containing Tag(s): 'Employer Identification Number'
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Authors
John Haltiwanger - 23
Javier Miranda - 13
Ron Jarmin - 11
Martha Stinson - 10
Kevin L. McKinney - 10
Viewing papers 1 through 10 of 167
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Working PaperTip 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.View Full Paper PDF
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Working PaperGarage Entrepreneurs or just Self-Employed? An Investigation into Nonemployer Entrepreneurship
October 2024
Working Paper Number:
CES-24-61
Nonemployers, businesses without employees, account for most businesses in the U.S. yet are poorly understood. We use restricted administrative and survey data to describe nonemployer dynamics, overall performance, and performance by demographic group. We find that eventual outcome ' migration to employer status, continuing as a nonemployer, or exit ' is closely related to receipt growth. We provide estimates of employment creation by firms that began as nonemployers and become employers (migrants), estimating that relative to all firms born in 1996, nonemployer migrants accounted for 3-17% of all net jobs in the seventh year after startup. Moreover, we find that migrants' employment creation declined by 54% for the cohorts born between 1996 to 2014. Our results are consistent with increased adjustment frictions in recent periods, and suggest accessibility to transformative entrepreneurship for everyday Americans has declined.View Full Paper PDF
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Working PaperNonresponse and Coverage Bias in the Household Pulse Survey: Evidence from Administrative Data
October 2024
Working Paper Number:
CES-24-60
The Household Pulse Survey (HPS) conducted by the U.S. Census Bureau is a unique survey that provided timely data on the effects of the COVID-19 Pandemic on American households and continues to provide data on other emergent social and economic issues. Because the survey has a response rate in the single digits and only has an online response mode, there are concerns about nonresponse and coverage bias. In this paper, we match administrative data from government agencies and third-party data to HPS respondents to examine how representative they are of the U.S. population. For comparison, we create a benchmark of American Community Survey (ACS) respondents and nonrespondents and include the ACS respondents as another point of reference. Overall, we find that the HPS is less representative of the U.S. population than the ACS. However, performance varies across administrative variables, and the existing weighting adjustments appear to greatly improve the representativeness of the HPS. Additionally, we look at household characteristics by their email domain to examine the effects on coverage from limiting email messages in 2023 to addresses from the contact frame with at least 90% deliverability rates, finding no clear change in the representativeness of the HPS afterwards.View Full Paper PDF
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Working PaperIncorporating Administrative Data in Survey Weights for the 2018-2022 Survey of Income and Program Participation
October 2024
Working Paper Number:
CES-24-58
Response rates to the Survey of Income and Program Participation (SIPP) have declined over time, raising the potential for nonresponse bias in survey estimates. A potential solution is to leverage administrative data from government agencies and third-party data providers when constructing survey weights. In this paper, we modify various parts of the SIPP weighting algorithm to incorporate such data. We create these new weights for the 2018 through 2022 SIPP panels and examine how the new weights affect survey estimates. Our results show that before weighting adjustments, SIPP respondents in these panels have higher socioeconomic status than the general population. Existing weighting procedures reduce many of these differences. Comparing SIPP estimates between the production weights and the administrative data-based weights yields changes that are not uniform across the joint income and program participation distribution. Unlike other Census Bureau household surveys, there is no large increase in nonresponse bias in SIPP due to the COVID-19 Pandemic. In summary, the magnitude and sign of nonresponse bias in SIPP is complicated, and the existing weighting procedures may change the sign of nonresponse bias for households with certain incomes and program benefit statuses.View Full Paper PDF
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Working PaperSeparate but Not Equal: The Uneven Cost of Residential Segregation for Network-Based Hiring
October 2024
Working Paper Number:
CES-24-56
This paper studies how residential segregation by race and by education affects job search via neighbor networks. Using confidential microdata from the US Census Bureau, I measure segregation for each characteristic at both the individual level and the neighborhood level. My findings are manifold. At the individual level, future coworkership with new neighbors on the same block is less likely among segregated individuals than among integrated workers, irrespective of races and levels of schooling. The impacts are most adverse for the most socioeconomically disadvantaged demographics: Blacks and those without a high school education. At the block level, however, higher segregation along either dimension raises the likelihood of any future coworkership on the block for all racial or educational groups. My identification strategy, capitalizing on data granularity, allows a causal interpretation of these results. Together, they point to the coexistence of homophily and in-group competition for job opportunities in linking residential segregation to neighbor-based informal hiring. My subtle findings have important implications for policy-making.View Full Paper PDF
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Working PaperTransitional Costs and the Decline of Coal: Worker-Level Evidence
September 2024
Working Paper Number:
CES-24-53
We examine the labor market impacts of the U.S. coal industry's decline using comprehensive administrative data on workers from 2005-2021. Coal workers most exposed to the industry's contraction experienced substantial earnings losses, equivalent to 1.6 years of predecline wages. These losses stem from both reduced employment duration (0.37 fewer years employed) and lower annual earnings (17 percent decline) between 2012-2019, relative to similar workers less exposed to coal's decline. Earnings reductions primarly occur when workers remain in local labor markets but are not employed in mining. While coal workers do not exhibit lower geographic mobility, relocation does not significantly mitigate their earnings losses.View Full Paper PDF
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Working PaperU.S. Worker Mobility Across Establishments within Firms: Scope, Prevalence, and Effects on Worker Earnings
May 2024
Working Paper Number:
CES-24-24
Multi-establishment firms account for around 60% of U.S. workers' primary employers, providing ample opportunity for workers to change their work location without changing their employer. Using U.S. matched employer-employee data, this paper analyzes workers' access to and use of such between-establishment job transitions, and estimates the effect on workers' earnings growth of greater access, as measured by proximity of employment at other within-firm establishments. While establishment transitions are not perfectly observed, we estimate that within-firm establishment transitions account for 7.8% percent of all job transitions and 18.2% of transitions originating from the largest firms. Using variation in worker's establishment locations within their firms' establishment network, we show that having a greater share of the firm's jobs in nearby establishments generates meaningful increases in workers' earnings: a worker at the 90th percentile of earnings gains from more proximate within-firm job opportunities can expect to enjoy 2% higher average earnings over the following five years than a worker at the 10th percentile with the same baseline earnings.View Full Paper PDF
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Working PaperAfter the Storm: How Emergency Liquidity Helps Small Businesses Following Natural Disasters
April 2024
Working Paper Number:
CES-24-20
Does emergency credit prevent long-term financial distress? We study the causal effects of government-provided recovery loans to small businesses following natural disasters. The rapid financial injection might enable viable firms to survive and grow or might hobble precarious firms with more risk and interest obligations. We show that the loans reduce exit and bankruptcy, increase employment and revenue, unlock private credit, and reduce delinquency. These effects, especially the crowding-in of private credit, appear to reflect resolving uncertainty about repair. We do not find capital reallocation away from neighboring firms and see some evidence of positive spillovers on local entry.View Full Paper PDF
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Working PaperThe Impact of Immigration on Firms and Workers: Insights from the H-1B Lottery
April 2024
Working Paper Number:
CES-24-19
We study how random variation in the availability of highly educated, foreign-born workers impacts firm performance and recruitment behavior. We combine two rich data sources: 1) administrative employer-employee matched data from the US Census Bureau; and 2) firm level information on the first large-scale H-1B visa lottery in 2007. Using an event-study approach, we find that lottery wins lead to increases in firm hiring of college-educated, immigrant labor along with increases in scale and survival. These effects are stronger for small, skill-intensive, and high-productivity firms that participate in the lottery. We do not find evidence for displacement of native-born, college-educated workers at the firm level, on net. However, this result masks dynamics among more specific subgroups of incumbents that we further elucidate.View Full Paper PDF
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Working PaperStarting Up AI
March 2024
Working Paper Number:
CES-24-09
Using comprehensive administrative data on business applications over the period 2004-2023, we study emerging business ideas for developing AI technologies or producing goods or services that use, integrate, or rely on AI. The annual number of new AI business applications is stable between 2004 and 2012 but begins to rise after 2012, and increases faster from 2016 onward into the pandemic, with a large, discrete jump in 2023. The distribution of AI business applications is highly uneven across states and sectors. AI business applications have a higher likelihood of becoming employer startups and higher expected initial employment compared to other business applications. Moreover, controlling for application characteristics, employer businesses originating from AI business applications exhibit higher employment, revenue, payroll, average pay per employee, and labor share, but have similar labor productivity and lower survival rate, compared to those originating from other business applications. While these early patterns may change as the diffusion of AI progresses, the rapid rise in AI business applications, combined with their generally higher rate of transition to employers and better performance in some post-transition outcomes, suggests a small but growing contribution from these applications to business dynamism.View Full Paper PDF
