Papers Containing Tag(s): 'Employer Identification Numbers'
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Viewing papers 81 through 90 of 183
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Working PaperHiring through Startup Acquisitions: Preference Mismatch and Employee Departures
September 2018
Working Paper Number:
CES-18-41
This paper investigates the effectiveness of startup acquisitions as a hiring strategy. Unlike conventional hires who choose to join a new firm on their own volition, most acquired employees do not have a voice in the decision to be acquired, much less by whom to be acquired. The lack of worker agency may result in a preference mismatch between the acquired employees and the acquiring firm, leading to elevated rates of turnover. Using comprehensive employee-employer matched data from the US Census, I document that acquired workers are significantly more likely to leave compared to regular hires. By constructing a novel peer-based proxy for worker preferences, I show that acquired employees who prefer to work for startups ' rather than established firms ' are the most likely to leave after the acquisition, lending support to the preference mismatch theory. Moreover, these departures suggest a deeper strategic cost of competitive spawning: upon leaving, acquired workers are more likely to found their own companies, many of which appear to be competitive threats that impair the acquirer's long-run performance.View Full Paper PDF
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Working PaperLEHD Infrastructure S2014 files in the FSRDC
September 2018
Working Paper Number:
CES-18-27R
The Longitudinal Employer-Household Dynamics (LEHD) Program at the U.S. Census Bureau, with the support of several national research agencies, maintains a set of infrastructure files using administrative data provided by state agencies, enhanced with information from other administrative data sources, demographic and economic (business) surveys and censuses. The LEHD Infrastructure Files provide a detailed and comprehensive picture of workers, employers, and their interaction in the U.S. economy. This document describes the structure and content of the 2014 Snapshot of the LEHD Infrastructure files as they are made available in the Census Bureau's secure and restricted-access Research Data Center network. The document attempts to provide a comprehensive description of all researcher-accessible files, of their creation, and of any modifications made to the files to facilitate researcher access.View Full Paper PDF
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Working PaperLabor Market Concentration, Earnings Inequality, and Earnings Mobility
September 2018
Working Paper Number:
carra-2018-10
Using data from the Longitudinal Business Database and Form W-2, I document trends in local industrial concentration from 1976 through 2015 and estimate the effects of that concentration on earnings outcomes within and across demographic groups. Local industrial concentration has generally been declining throughout its distribution over that period, unlike national industrial concentration, which declined sharply in the early 1980s before increasing steadily to nearly its original level beginning around 1990. Estimates indicate that increased local concentration reduces earnings and increases inequality, but observed changes in concentration have been in the opposite direction, and the magnitude of these effects has been modest relative to broader trends; back-of-the-envelope calculations suggest that the 90/10 earnings ratio was about six percent lower and earnings were about one percent higher in 2015 than they would have been if local concentration were at its 1976 level. Within demographic subgroups, most experience mean earnings reductions and all experience increases in inequality. Estimates of the effects of concentration on earnings mobility are sensitive to specification.View Full Paper PDF
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Working PaperOccupational Classifications: A Machine Learning Approach
August 2018
Working Paper Number:
CES-18-37
Characterizing the work that people do on their jobs is a longstanding and core issue in labor economics. Traditionally, classification has been done manually. If it were possible to combine new computational tools and administrative wage records to generate an automated crosswalk between job titles and occupations, millions of dollars could be saved in labor costs, data processing could be sped up, data could become more consistent, and it might be possible to generate, without a lag, current information about the changing occupational composition of the labor market. This paper examines the potential to assign occupations to job titles contained in administrative data using automated, machine-learning approaches. We use a new extraordinarily rich and detailed set of data on transactional HR records of large firms (universities) in a relatively narrowly defined industry (public institutions of higher education) to identify the potential for machine-learning approaches to classify occupations.View Full Paper PDF
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Working PaperFirm Leverage, Labor Market Size, and Employee Pay
August 2018
Working Paper Number:
CES-18-36
We provide new estimates of the wage costs of firms' debt using an empirical approach that exploits within-firm geographical variation in workers' expected unemployment costs due to variation in local labor market in a large sample of public firms. We find that, following an increase in firm leverage, workers with higher unemployment costs experience higher wage growth relative to workers at the same firm with lower unemployment costs. Overall, our estimates suggest wage costs are an important component in the overall cost of debt, but are not as large as implied by estimates based on ex post employee wage losses due to bankruptcy; we estimate that a 10 percentage point increase in firm leverage increases wage compensation for the median worker by 1.9% and total firm wage costs by 17 basis points of firm value.View Full Paper PDF
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Working PaperOlder and Slower: The Startup Deficit's Lasting Effects on Aggregate Productivity Growth
June 2018
Working Paper Number:
CES-18-29
We investigate the link between declining firm entry, aging incumbent firms and sluggish U.S. productivity growth. We provide a dynamic decomposition framework to characterize the contributions to industry productivity growth across the firm age distribution and apply this framework to the newly developed Revenue-enhanced Longitudinal Business Database (ReLBD). Overall, several key findings emerge: (i) the relationship between firm age and productivity growth is downward sloping and convex; (ii) the magnitudes are substantial and significant but fade quickly, with nearly 2/3 of the effect disappearing after five years and nearly the entire effect disappearing after ten; (iii) the higher productivity growth of young firms is driven nearly exclusively by the forces of selection and reallocation. Our results suggest a cumulative drag on aggregate productivity of 3.1% since 1980. Using an instrumental variables strategy we find a consistent pattern across states/MSAs in the U.S. The patterns are broadly consistent with a standard model of firm dynamics with monopolistic competition.View Full Paper PDF
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Working PaperCreditor Rights, Technology Adoption, and Productivity: Plant-Level Evidence
April 2018
Working Paper Number:
CES-18-20
I analyze the impact of stronger creditor rights on productivity using plant-level data from the U.S. Census Bureau. Following the adoption of anti-recharacterization laws that give lenders greater access to the collateral of firms in financial distress, total factor productivity of treated plants increases by 2.6 percent. This effect is mainly observed among plants belonging to financially constrained firms. Furthermore, treated plants invest in capital of younger vintage and newer technology, and become more capital-intensive. My results suggest that stronger creditor rights relax borrowing constraints and help firms adopt more efficient production technologies.View Full Paper PDF
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Working PaperAge and High-Growth Entrepreneurship
April 2018
Working Paper Number:
carra-2018-03
Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. We use administrative data at the U.S. Census Bureau to study the ages of founders of growth-oriented start-ups in the past decade. Our primary finding is that successful entrepreneurs are middle-aged, not young. The mean founder age for the 1 in 1,000 fastest growing new ventures is 45.0. The findings are broadly similar when considering high-technology sectors, entrepreneurial hubs, and successful firm exits. Prior experience in the specific industry predicts much greater rates of entrepreneurial success. These findings strongly reject common hypotheses that emphasize youth as a key trait of successful entrepreneurs.View Full Paper PDF
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Working PaperFathers, Children, and the Intergenerational Transmission of Employers
March 2018
Working Paper Number:
CES-18-12
We document the tendency of fathers in the U.S. to share employers with their sons and daughters. We show that the rate of job sharing is much higher than can be explained by the fact that fathers and sons tend to live near each other. Younger children are much more likely to share their father's employer, as are children of high-earning fathers. We find that sons' earnings at shared jobs tend to be higher than at unshared jobs but see no statistically signi?cant di'erence for daughters. Much of the earnings differential is associated with jobs at shared employers being in higher-paying industries. When we control for employer characteristics, we see a much smaller son earnings premium for working together with his father. We also investigate the impact of sharing an employer on intergenerational mobility and demonstrate that for sons, sharing an employer at some point before age 30 is associated with a higher rank in the earnings distribution as an adult but that this association is independent of the father's rank in the earnings distribution.View Full Paper PDF
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Working PaperSmall and Large Firms Over the Business Cycle
February 2018
Working Paper Number:
CES-18-09
Drawing on a new, con dential Census Bureau dataset of financial statements of a representative sample of 80000 manufacturing firms from 1977 to 2014, we provide new evidence on the link between size, cyclicality, and financial frictions. First, we only find evidence of lower cyclicality among the very largest firms (the top 1% by size). Second, due to high and rising concentration of sales and investment, the lower sensitivity of the top 1% firms dominates the behavior of aggregate fluctuations. Third, we show that this differential sensitivity does not appear to be driven by financial frictions. The higher sensitivity of the bottom 99% does not disappear after controlling for measures of financial strength, is not statistically significant after identified monetary policy shocks, and does not appear in debt financing flows. Evidence from 3-digit industries suggests a non-financial explanation: the largest 1% of firms are less sensitive due to a more diversified customer base.View Full Paper PDF
