Measuring the Business Dynamics of Firms that Received Pandemic Relief Funding: Findings from a New Experimental BDS Data Product
January 2025
Working Paper Number:
CES-25-05
Abstract
This paper describes a new experimental data product from the U.S. Census Bureau's Center for Economic Studies: the Business Dynamics Statistics (BDS) of firms that received Small Business Administration (SBA) pandemic funding. This new product, BDS-SBA COVID, expands the set of currently published BDS tables by linking loan-level program participation data from SBA to internal business microdata at the U.S. Census Bureau. The linked programs include the Paycheck Protection Program (PPP), COVID Economic Injury Disaster Loans (COVID-EIDL), the Restaurant Revitalization Fund (RRF), and Shuttered Venue Operators Grants (SVOG). Using these linked data, we tabulate annual firm and establishment counts, measures of job creation and destruction, and establishment entry and exit for recipients and non-recipients of program funds in 2020-2021. We further stratify the tables by timing of loan receipt and loan size, and business characteristics including geography, industry sector, firm size, and firm age. We find that for the youngest firms that received PPP, the timing of receipt mattered. Receiving an early loan correlated with a lower job destruction rate compared to non-recipients and businesses that received a later loan. For the smallest firms, simply participating in PPP was associated with lower employment loss. The timing of PPP receipt was also related to establishment exit rates. For businesses of nearly all ages, those that received an early loan exited at a lower rate in 2022 than later loan recipients.
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
enterprise,
quarterly,
company,
organizational,
proprietorship,
finance,
sector,
establishment,
incorporated,
borrower,
loan,
bank,
lender,
revenue,
funding,
fund,
irs,
banking,
mortgage
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Internal Revenue Service,
Small Business Administration,
Center for Economic Studies,
Longitudinal Business Database,
Retail Trade,
Decennial Census,
Employer Identification Numbers,
Wholesale Trade,
North American Industry Classification System,
Paycheck Protection Program,
Technical Services,
Census Bureau Business Register,
Business Register,
Protected Identification Key,
Census Bureau Disclosure Review Board,
Disclosure Review Board,
Business Dynamics Statistics,
Arts, Entertainment,
Accommodation and Food Services,
Agriculture, Forestry,
COVID-19
Similar Working Papers
Similarity between working papers are determined by an unsupervised neural
network model
know as Doc2Vec.
Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the
capture of semantic meaning in a way that relates to the context of words within the document. The model learns to
associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
document vectors are compared using cosine similarity/distance to determine the most similar working papers.
Papers identified with 🔥 are in the top 20% of similarity.
The 10 most similar working papers to the working paper 'Measuring the Business Dynamics of Firms that Received Pandemic Relief Funding: Findings from a New Experimental BDS Data Product' are listed below in order of similarity.
-
Working PaperBusiness Dynamics Statistics for Single-Unit Firms🔥
December 2022
Working Paper Number:
CES-22-57
The Business Dynamics Statistics of Single Unit Firms (BDS-SU) is an experimental data product that provides information on employment and payroll dynamics for each quarter of the year at businesses that operate in one physical location. This paper describes the creation of the data tables and the value they add to the existing Business Dynamics Statistics (BDS) product. We then present some analysis of the published statistics to provide context for the numbers and demonstrate how they can be used to understand both national and local business conditions, with a particular focus on 2020 and the recession induced by the COVID-19 pandemic. We next examine how firms fared in this recession compared to the Great Recession that began in the fourth quarter of 2007. We also consider the heterogenous impact of the pandemic on various industries and areas of the country, showing which types of businesses in which locations were particularly hard hit. We examine business exit rates in some detail and consider why different metro areas experienced the pandemic in different ways. We also consider entry rates and look for evidence of a surge in new businesses as seen in other data sources. We finish by providing a preview of on-going research to match the BDS to worker demographics and show statistics on the relationship between the characteristics of the firm's workers and outcomes such as firm exit and net job creation.View Full Paper PDF
-
Working PaperBusiness Dynamics Statistics of Coastal Counties: A Description of Differences in Coastal Areas Over Time
January 2025
Working Paper Number:
CES-25-08R
The Business Dynamics Statistics of Coastal Counties (BDS-CC) is a new experimental data product extending the set of statistics published by the Business Dynamics Statistics (BDS) program to provide more detail on businesses operating in coastal regions of the United States. The BDS-CC provides annual measures of employment, the number of establishments and firms, job creation, job destruction, openings, and closings for businesses in Coastal Shoreline (CS), Coastal Non-Shoreline (CNS), and Non-Coastal (NC) counties. Counties are grouped into these categories based on definitions from the National Oceanic and Atmospheric Administration (NOAA). This product allows for comparisons across industries and coastal regions of the impact of natural disasters and other events that affect coastal areas. The BDS-CC series provides annual statistics for 1978 to 2022 for each of the coastal categories by firm size and firm age, initial firm size, establishment size and establishment age, initial establishment size, sector, 3-digit NAICS code, 4-digit NAICS code, urban/rural categories, and various coastal regions. Following a description of the data and methodology, we highlight some historical trends and analyses conducted using these data.View Full Paper PDF
-
Working PaperThe Metamorphosis of Women Business Owners: A Focus on Age
November 2024
Working Paper Number:
CES-24-71
Due to their growth, increasing performance, and significant contributions to the United States economy, women-owned businesses have spurred the interest of policymakers, researchers, and advocacy groups. Using various data products from the Census Bureau's Business Demographics Program, this study examines how women business ownership changes over time by age. We find that young owners experienced growth in ownership between 2012 and 2020 and that younger employer businesses were mostly owned by women under the age of 35 in 2021. We show that among women aged 45 to 54 and those aged 55 to 64 ownership rates declined 5.5% and 4.8% between 2012 and 2020, implying an acceleration in the drop out of entrepreneurship for mid to late career age groups. We also show that older owners operate most businesses in capital-intensive industries, had more prior businesses, and higher rates of selling their most recently started businesses. Finally, we find that age groups often characterized as childbearing ages found balancing work and family as key drivers of their decision to start a business.View Full Paper PDF
-
Working PaperBusiness Formation: A Tale of Two Recessions
January 2021
Working Paper Number:
CES-21-01
The trajectory of new business applications and transitions to employer businesses differ markedly during the Great Recession and COVID-19 Recession. Both applications and transitions to employer startups decreased slowly but persistently in the post-Lehman crisis period of the Great Recession. In contrast, during the COVID-19 Recession new applications initially declined but have since sharply rebounded, resulting in a surge in applications during 2020. Projected transitions to employer businesses also rise but this is dampened by a change in the composition of applications in 2020 towards applications that are more likely to be nonemployers.View Full Paper PDF
-
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
-
Working PaperThe Composition of Firm Workforces from 2006'2022: Findings from the Business Dynamics Statistics of Human Capital Experimental Product
April 2025
Working Paper Number:
CES-25-20
We introduce the Business Dynamics Statistics of Human Capital (BDS-HC) tables, a new Census Bureau experimental product that provides public-use statistics on the workforce composition of firms and its relationship to business dynamics. We use administrative W-2 filings to combine population-level worker demographic data with longitudinal business data to estimate the demographic and educational composition of nearly all non-farm employer businesses in the United States between 2006 and 2022. We use this newly constructed data to document the evolution of employment, entry, and exit of employers based on their workforce compositions. We also provide new statistics on the interaction between firm and worker characteristics, including the composition of workers at startup firms. We find substantial changes between 2006 and 2022 in the distribution of employers along several dimensions, primarily driven by changing workforce compositions within continuing firms rather than the reallocation of employment between firms. We also highlight systematic differences in the business dynamics of firms by their workforce compositions, suggesting that different groups of workers face different economic environments due to their employers.View Full Paper PDF
-
Working PaperBusiness Owners and the Self-Employed: 33 Million (and Counting!)
September 2025
Working Paper Number:
CES-25-60
Entrepreneurs are known to be key drivers of economic growth, and the rise of online platforms and the broader 'gig economy' has led self-employment to surge in recent decades. Yet the young and small businesses associated with this activity are often absent from economic data. In this paper, we explore a novel longitudinal dataset that covers the owners of tens of millions of the smallest businesses: those without employees. We produce three new sets of statistics on the rapidly growing set of nonemployer businesses. First, we measure transitions between self-employment and wage and salary jobs. Second, we describe nonemployer business entry and exit, as well as transitions between legal form (e.g., sole proprietorship to S corporation). Finally, we link owners to their nonemployer businesses and examine the dynamics of business ownership.View Full Paper PDF
-
Working PaperThe Business Dynamics Statistics: Describing the Evolution of the U.S. Economy from 1978-2019
October 2021
Working Paper Number:
CES-21-33
The U.S. Census Bureau's Business Dynamics Statistics (BDS) provide annual measures of how many businesses begin, end, or continue their operations and the associated job creation and destruction. The BDS is a valuable resource for information on the U.S. economy because of its long time series (1978-2019), its complete coverage (all private sector, non-farm U.S. businesses), and its tabulations for both individual establishments and the firms that own and control them. In this paper, we use the publicly available BDS data to describe the dynamics of the economy over the past 40 years. We highlight the increasing concentration of employment at old and large firms and describe net job creation trends in the manufacturing, retail, information, food/accommodations, and healthcare industry sectors. We show how the spatial distribution of employment has changed, first moving away from the largest cities and then back again. Finally, we show long-run trends for a group of industries we classify as high-tech and explore how the share of employment at small and young firms has changed for this part of the economy.View Full Paper PDF
-
Working PaperDon't Quit Your Day Job: Using Wage and Salary Earnings to Support a New Business
September 2013
Working Paper Number:
CES-13-45
This paper makes use of a newly constructed Census Bureau dataset that follows the universe of sole proprietors, employers and non-employers, over 10 years and links their transitions to their activity as employees earning wage and salary income. By combining administrative data on sole proprietors and their businesses with quarterly administrative data on wage and salary jobs held by the same individuals both preceding and concurrent with business startup, we create the unique opportunity to quantify significant workforce dynamics that have up to now remained unobserved. The data allow us to take a first glimpse at these business owners as they initiate business ventures and make the transition from wage and salary work to business ownership and back. We find that the barrier between wage and salary work and self-employment is extremely fluid, with large flows occurring in both directions. We also observe that a large fraction of business owners takeon both roles simultaneously and find that this labor market diversification does have implications for the success of the businesses these owners create. The results for employer transitions to exit and non-employer suggest that there is a 'don't quit your day job' effect that is present for new businesses. Employers are more likely to stay employers if they have a wage and salary job in the year just prior to the transitions that we are tracking. It is especially important to have a stable wage and salary job but there is also evidence that higher earnings from the wage and salary job makes transition less likely. For nonemployers we find roughly similar patterns but there are some key differences. We find that having recent wage and salary income (and having higher earnings from such wage and salary activity) increases the likelihood of survival. Having recent stable wage and salary income decreases the likelihood of a complete exit but increases the likelihood of transiting to be an employer. Having recent wage and salary income in the same industry as the non-employer business has a large and positive impact on the likelihood of transiting to being a non-employer business.View Full Paper PDF
-
Working PaperJust Passing Through: Characterizing U.S. Pass-Through Business Owners
January 2017
Working Paper Number:
CES-17-69
We investigate the use of administrative data on the owners of partnerships and S-corporations to develop new statistics that characterize business owners. Income from these types of entities is "passed through" to owners to be taxed on the owners' tax returns. The information returns associated with such pass-through entities (Form K1 records) make it possible to link individual owners to the businesses they own. These linkages can be leveraged to associate measures of the demographic and human capital characteristics of business owners with the characteristics of the businesses they own. This paper describes measurement issues associated with administrative records on these pass-through entities and their integration with other Census data products. In addition, we document a number of interesting trends in business ownership among pass-through entities. We show a substantial decline in both entry and exit with less churn among both owners and owned businesses. We also show that the owners of pass-through entities are older, more likely to be male, and more likely to be white compared to the working population.View Full Paper PDF
