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Redesigning the Longitudinal Business Database
May 2021
Working Paper Number:
CES-21-08
In this paper we describe the U.S. Census Bureau's redesign and production implementation of the Longitudinal Business Database (LBD) first introduced by Jarmin and Miranda (2002). The LBD is used to create the Business Dynamics Statistics (BDS), tabulations describing the entry, exit, expansion, and contraction of businesses. The new LBD and BDS also incorporate information formerly provided by the Statistics of U.S. Businesses program, which produced similar year-to-year measures of employment and establishment flows. We describe in detail how the LBD is created from curation of the input administrative data, longitudinal matching, retiming of economic census-year births and deaths, creation of vintage consistent industry codes and noise factors, and the creation and cleaning of each year of LBD data. This documentation is intended to facilitate the proper use and understanding of the data by both researchers with approved projects accessing the LBD microdata and those using the BDS tabulations.
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Male Earnings Volatility in LEHD before, during, and after the Great Recession
September 2020
Working Paper Number:
CES-20-31
This paper is part of a coordinated collection of papers on prime-age male earnings volatility. Each paper produces a similar set of statistics for the same reference population using a different primary data source. Our primary data source is the Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) infrastructure files. Using LEHD data from 1998 to 2016, we create a well-defined population frame to facilitate accurate estimation of temporal changes comparable to designed longitudinal samples of people. We show that earnings volatility, excluding increases during recessions, has declined over the analysis period, a finding robust to various sensitivity analyses. Although we find volatility is declining, the effect is not homogeneous, particularly for workers with tenuous labor force attachment for whom volatility is increasing. These 'not stable' workers have earnings volatility approximately 30 times larger than stable workers, but more important for earnings volatility trends we observe a large increase in the share of stable employment from 60% in 1998 to 67% in 2016, which we show to largely be responsible for the decline in overall earnings volatility. To further emphasize the importance of not stable and/or low earning workers we also conduct comparisons with the PSID and show how changes over time in the share of workers at the bottom tail of the cross-sectional earnings distributions can produce either declining or increasing earnings volatility trends.
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Total Error and Variability Measures for the Quarterly Workforce Indicators and LEHD Origin Destination Employment Statistics in OnTheMap
September 2020
Working Paper Number:
CES-20-30
We report results from the first comprehensive total quality evaluation of five major indicators in the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): total flow-employment, beginning-of-quarter employment, full quarter employment, average monthly earnings of full-quarter employees, and total quarterly payroll. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics (LODES) workplace reports as displayed in On-TheMap (OTM), including OnTheMap for Emergency Management. We account for errors due to coverage; record-level non response; edit and imputation of item missing data; and statistical disclosure limitation. The analysis reveals that the five publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs are a transition zone, where cells may be fit for use with caution. Tabulations involving one or two jobs, which are generally suppressed on fitness-for-use criteria in the QWI and synthesized in LODES, have substantial total variability but can still be used to estimate statistics for untabulated aggregates as long as the job count in the aggregate is more than 10.
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Older 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.
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High Growth Young Firms: Contribution to Job, Output and Productivity Growth
February 2017
Working Paper Number:
carra-2017-03
Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don't create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries - in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don't have significantly smaller shares of either employment or output activity accounted for by high growth firms.
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Differences in Self-employment Duration by Year of Entry & Pre-entry
November 2016
Working Paper Number:
carra-2016-09
Self-employment is associated with entrepreneurship and a motivation to pursue an opportunity. Previous research indicates that people also become self-employed because of limited opportunities in the wage sector. Using a unique set of data that links the American Community Survey to Form 1040 and W-2 records, this paper extends the existing literature by examining self-employment duration 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 pre-entry wage labor attachment of entrants. Specifically, we ask whether an association exists between wage labor attachment and the duration of self-employment. We also explore whether the demographic/socio-economic characteristics and self-employment exit behavior of the cohorts are different, and if so, how. We find evidence consistent with the existence of "necessity" vs. "opportunity" self-employment types.
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The New Lifecycle of Women's Employment: Disappearing Humps, Sagging Middle, Expanding Tops
November 2016
Working Paper Number:
carra-2016-07
The new lifecycle of women's employment is initially high and flat, there is a dip in the middle and a phasing out that is more prolonged than for previous cohorts. The hump is gone, the middle is a bit sagging and the top has greatly expanded. We explore the increase in cumulative work experience for women from the 1930s to the 1970s birth cohorts using the SIPP and the HRS. We investigate the changing labor force impact of a birth event across cohorts and by education and also the impact of taking leave or quitting. We find greatly increased labor force experience across cohorts, far less time out after a birth and greater labor force recovery for those who take paid or unpaid leave. More work experience across the lifecycle is related to the increased employment of women in their older ages.
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Playing with Matches: An Assessment of Accuracy in Linked Historical Data
June 2016
Working Paper Number:
carra-2016-05
This paper evaluates linkage quality achieved by various record linkage techniques used in historical demography. I create benchmark, or truth, data by linking the 2005 Current Population Survey Annual Social and Economic Supplement to the Social Security Administration's Numeric Identification System by Social Security Number. By comparing simulated linkages to the benchmark data, I examine the value added (in terms of number and quality of links) from incorporating text-string comparators, adjusting age, and using a probabilistic matching algorithm. I find that text-string comparators and probabilistic approaches are useful for increasing the linkage rate, but use of text-string comparators may decrease accuracy in some cases. Overall, probabilistic matching offers the best balance between linkage rates and accuracy.
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High Growth Young Firms: Contribution to Job, Output and Productivity Growth
January 2016
Working Paper Number:
CES-16-49
Recent research shows that the job creating prowess of small firms in the U.S. is better attributed to startups and young firms that are small. But most startups and young firms either fail or don't create jobs. A small proportion of young firms grow rapidly and they account for the long lasting contribution of startups to job growth. High growth firms are not well understood in terms of either theory or evidence. Although the evidence of their role in job creation is mounting, little is known about their life cycle dynamics, or their contribution to other key outcomes such as real output growth and productivity. In this paper, we enhance the Longitudinal Business Database with gross output (real revenue) measures. We find that the patterns for high output growth firms largely mimic those for high employment growth firms. High growth output firms are disproportionately young and make disproportionate contributions to output and productivity growth. The share of activity accounted for by high growth output and employment firms varies substantially across industries ' in the post 2000 period the share of activity accounted for by high growth firms is significantly higher in the High Tech and Energy related industries. A firm in a small business intensive industry is less likely to be a high output growth firm but small business intensive industries don't have significantly smaller shares of either employment or output activity accounted for by high growth firms.
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Taking the Leap: The Determinants of Entrepreneurs Hiring their First Employee
January 2016
Working Paper Number:
CES-16-48
Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of startups. Longitudinal data from the Integrated Longitudinal Business Database (iLBD), Kauffman Firm Survey (KFS), and the Growing America through Entrepreneurship (GATE) experiment are used to provide some of the first evidence in the literature on the determinants of taking the leap from a non-employer to employer firm among startups. Several interesting patterns emerge regarding the dynamics of non-employer startups hiring their first employee. Hiring rates among the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses such as incorporated and EIN businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. After this point in time relatively few non-employer startups hire an employee. Focusing on more growth- and employment-oriented startups in the KFS, we find that Asian-owned and Hispanic-owned startups have higher rates of hiring their first employee than white-owned startups. Female-owned startups are roughly 10 percentage points less likely to hire their first employee by the first, second and seventh years after startup. The education level of the owner, however, is not found to be associated with the probability of hiring an employee. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from the largest random experiment providing entrepreneurship training in the United States ever conducted, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.
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