Private equity critics claim that leveraged buyouts bring huge job losses and few gains in operating performance. To evaluate these claims, we construct and analyze a new dataset that covers US buyouts from 1980 to 2005. We track 3,200 target firms and their 150,000 establishments before and after acquisition, comparing to controls defined by industry, size, age, and prior growth. Buyouts lead to modest net job losses but large increases in gross job creation and destruction. Buyouts also bring TFP gains at target firms, mainly through accelerated exit of less productive establishments and greater entry of highly productive ones.

An optimal pace of business dynamics—encompassing the processes of entry, exit, expansion, and contraction—would balance the benefits of productivity and economic growth against the costs to firms and workers associated with reallocation of productive resources. It is difficult to prescribe what the optimal pace should be, but evidence accumulating from multiple datasets and methodologies suggests that the rate of business startups and the pace of employment dynamism in the US economy has fallen over recent decades and that this downward trend accelerated after 2000. A critical factor in accounting for the decline in business dynamics is a lower rate of business startups and the related decreasing role of dynamic young businesses in the economy. For example, the share of US employment accounted for by young firms has declined by almost 30 percent over the last 30 years. These trends suggest that incentives for entrepreneurs to start new firms in the United States have diminished over time. We do not identify all the factors underlying these trends in this paper but offer some clues based on the empirical patterns for specific sectors and geographic regions.

There remains considerable debate in the theoretical and empirical literature about the differences in the cyclical dynamics of firms by firm size. This paper contributes to the debate in two ways. First, the key distinction between firm size and firm age is introduced. The evidence presented in this paper shows that young businesses (that are typically small) exhibit very different cyclical dynamics than small/older businesses. The second contribution is to present evidence and explore explanations for the finding that young/small businesses were hit especially hard in the Great Recession. The collapse in housing prices accounts for a significant part of the large decline of young/small businesses in the Great Recession.

The view that small businesses create the most jobs remains appealing to policymakers and small business advocates. Using data from the Census Bureau's Business Dynamics Statistics and Longitudinal Business Database, we explore the many issues at the core of this ongoing debate. We find that the relationship between firm size and employment growth is sensitive to these issues. However, our main finding is that once we control for firm age, there is no systematic relationship between firm size and growth. Our findings highlight the important role of business start-ups and young businesses in U.S. job creation.

In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments’ confidentiality. One approach with the potential for overcoming these risks is to release synthetic data; that is, the released establishment data are simulated from statistical models designed to mimic the distributions of the underlying real microdata. In this article, we describe an application of this strategy to create a public use file for the Longitudinal Business Database, an annual economic census of establishments in the United States comprising more than 20 million records dating back to 1976. The U.S. Bureau of the Census and the Internal Revenue Service recently approved the release of these synthetic microdata for public use, making the synthetic Longitudinal Business Database the first-ever business microdata set publicly released in the United States. We describe how we created the synthetic data, evaluated analytical validity, and assessed disclosure risk.

Small and young businesses are essential for job creation, innovation, and economic growth. Even most of the superstar firms start their business life small and then grow over time. Small firms have less internal resources, which makes them more fragile and sensitive to macroeconomic conditions. This suggests the need for frequent and real-time monitoring of the small business sector’s health. Previously this was difficult due to a lack of appropriate data. This paper fills this important gap by developing a new Intuit QuickBooks Small Business Index that focuses on the smallest of small businesses with at most 9 workers in the US and the UK and at most 19 workers in Canada. The Index aggregates a sample of anonymous Quick- Books Online Payroll subscriber data (QBO Payroll sample) from 333,000 businesses in the US, 66,000 in Canada, and 25,000 in the UK. After comparing the QBO Payroll sample data to the official statistics, we remove the seasonal components and use a Flexible Least Squares method to calibrate the QBO Payroll sample data against official statistics. Finally, we use the estimated model and the QBO Payroll sample data to generate a near real-time index of economic activity. We show that the estimated model performs well both in-sample and out-of-sample. Additionally, we use this analysis for different regions and industries. Keywords:

We link USPTO patent data to U.S. Census Bureau administrative records on individuals and firms. The combined dataset provides us with a directory of patenting household inventors as well as a time-series directory of self-employed businesses tied to household innovations. We describe the characteristics of household inventors by race, age, gender and U.S. origin, as well as the types of patented innovations pursued by these inventors. Business data allows us to highlight how patents shape the early life-cycle dynamics of nonemployer businesses. We find household innovators are disproportionately U.S. born, white and their age distribution has thicker tails relative to business innovators. Data shows there is a deficit of female and black inventors. Household inventors tend to work in consumer product areas compared to traditional business patents. While patented household innovations do not have the same impact of business innovations their uniqueness and impact remains surprisingly high. Back of the envelope calculations suggest patented household innovations granted between 2000 and 2011 might generate $5.0B in revenue (2000 dollars). 

The U.S. Census Bureau in partnership with a team of external researchers developed a series of questions on the use of robotics in U.S. manufacturing establishments. The questions include: (1) capital expenditures for new and used industrial robotic equipment in 2018, (2) number of industrial robots in operation in 2018, and (3) number of industrial robots purchased in 2018. These questions are to be included in the 2018 Annual Survey of Manufactures. This paper documents the background and cognitive testing process used for the development of these questions.

This paper reports on the development and analysis of a newly constructed dataset on the early stages of business formation. The data are based on applications for Employer Identification Numbers (EINs) submitted in the United States, known as IRS Form SS-4 filings. The goal of the research is to develop high-frequency indicators of business formation at the national, state, and local levels. The analysis indicates that EIN applications provide forward-looking and very timely information on business formation. The signal of business formation provided by counts of applications is improved by using the characteristics of the applications to model the likelihood that applicants become employer businesses. The results also suggest that EIN applications are related to economic activity at the local level. For example, application activity is higher in counties that experienced higher employment growth since the end of the Great Recession, and application counts grew more rapidly in counties engaged in shale oil and gas extraction. Finally, the paper provides a description of new public-use dataset, the “Business Formation Statistics (BFS),” that contains new data series on business applications and formation. The initial release of the BFS shows that the number of business applications in the 3rd quarter of 2017 that have relatively high likelihood of becoming job creators is still far below pre-Great Recession levels.