Papers Containing Keywords(s): 'business startups'
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Authors
Emin Dinlersoz - 4
John Haltiwanger - 3
Viewing papers 1 through 10 of 12
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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
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Working PaperThe Local Origins of Business Formation
July 2023
Working Paper Number:
CES-23-34
What locations generate more business ideas, and where are ideas more likely to turn into businesses? Using comprehensive administrative data on business applications, we analyze the spatial disparity in the creation of business ideas and the formation of new employer startups from these ideas. Startups per capita exhibit enormous variation across granular units of geography. We decompose this variation into variation in ideas per capita and in their rate of transition to startups, and find that both components matter. Observable local demographic, economic, financial, and business conditions accounts for a significant fraction of the variation in startups per capita, and more so for the variation in ideas per capita than in transition rate. Income, education, age, and foreign-born share are generally strong positive correlates of both idea generation and transition. Overall, the relationship of local conditions with ideas differs from that with transition rate in magnitude, and sometimes, in sign: certain conditions (notably, the African-American share of the population) are positively associated with ideas, but negatively with transition rates. We also find a close correspondence between the actual rank of locations in terms of startups per capita and the predicted rank based only on observable local conditions ' a result useful for characterizing locations with high startup activity.View Full Paper PDF
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Working PaperThe Transformation of Self Employment
February 2022
Working Paper Number:
CES-22-03
Over the past half-century, while self-employment has consistently accounted for around one in ten of the United States workforce, its composition has changed. Since 1970, industries with high startup capital requirements have declined from 53% of self-employment to 23%. This same time period also witnessed declines in 'hometown' local entrepreneurship and the probability of the self-employed being among top earners. Using 2016 data, we show that high startup capital requirements are linked with lower profitability at small scales. The transition away from high startup capital industries appears most closely linked to changes in small business production functions and less due to advantageous reallocation to other opportunities, growth in returns-to-scale among large businesses, or a worsening of financing conditions and debt levels.View Full Paper PDF
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Working PaperHigh Frequency Business Dynamics in the United States During the COVID-19 Pandemic
March 2021
Working Paper Number:
CES-21-06
Existing small businesses experienced very sharp declines in activity, business sentiment, and expectations early in the pandemic. While there has been some recovery since the early days of the pandemic, small businesses continued to exhibit indicators of negative growth, business sentiment, and expectations through the first week of January 2021. These findings are from a unique high frequency, real time survey of small employer businesses, the Census Bureau's Small Business Pulse Survey (SBPS). Findings from the SBPS show substantial variation across sectors in the outcomes for small businesses. Small businesses in Accommodation and Food Services have been hit especially hard relative to those Finance and Insurance. However, even in Finance and Insurance small businesses exhibit indicators of negative growth, business sentiment, and expectations for all weeks from late April 2020 through the first week of 2021. While existing small businesses have fared poorly, after an initial decline, there has been a surge in new business applications based on the high frequency, real time Business Formation Statistics (BFS). Most of these applications are for likely nonemployers that are out of scope for the SBPS. However, there has also been a surge in new applications for likely employers. The surge in applications has been especially apparent in Retail Trade (and especially Non-store Retailers). We compare and contrast the patterns from these two new high frequency data products that provide novel insights into the distinct patterns of dynamics for existing small businesses relative to new business formations.View Full Paper PDF
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Working PaperEarly-Stage Business Formation: An Analysis of Applications for Employer Identification Numbers
December 2018
Working Paper Number:
CES-18-52
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.View Full Paper PDF
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Working PaperThe Annual Survey of Entrepreneurs: An Update
January 2017
Working Paper Number:
CES-17-46
We provide an update on the Annual Survey of Entrepreneurs (ASE), which is a relatively new Census Bureau business survey. About 290,000 employer firms in the private, non-agricultural U.S. economy are in the ASE sample. Its content is relatively constant over collections, allowing for comparability over time; however, each year there are approximately ten new questions in a changing topical module. Earlier topical modules covered innovation (2014) and management practices (2015). The topical module for reference year 2016 covers business advice and planning, finance, and regulations. The ASE is collected through a partnership of the Census Bureau with the Kauffman Foundation and the Minority Business Development Agency. Qualified researchers on approved projects may request access to the ASE micro data through the Federal Statistical Research Data Center (FSRDC) network.View Full Paper PDF
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Working PaperFirm Dynamics, Persistent Effects of Entry Conditions, and Business Cycles
January 2017
Working Paper Number:
CES-17-29
This paper examines how the state of the economy when businesses begin operations affects their size and performance over the lifecycle. Using micro-level data that covers the entire universe of businesses operating in the U.S. since the late 1970s, I provide new evidence that businesses born in downturns start on a smaller scale and remain smaller over their entire lifecycle. In fact, I find no evidence that these differences attenuate even long after entry. Using new data on the productivity and composition of startup businesses, I show that this persistence is related to selection at entry and demand-side channels.View Full Paper PDF
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Working PaperTaking 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.View Full Paper PDF
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Working PaperThe Promise and Potential of Linked Employer-Employee Data for Entrepreneurship Research
September 2015
Working Paper Number:
CES-15-29
In this paper, we highlight the potential for linked employer-employee data to be used in entrepreneurship research, describing new data on business start-ups, their founders and early employees, and providing examples of how they can be used in entrepreneurship research. Linked employer-employee data provides a unique perspective on new business creation by combining information on the business, workforce, and individual. By combining data on both workers and firms, linked data can investigate many questions that owner-level or firm-level data cannot easily answer alone - such as composition of the workforce at start-ups and their role in explaining business dynamics, the flow of workers across new and established firms, and the employment paths of the business owners themselves.View Full Paper PDF
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Working PaperPast Experience and Future Success: New Evidence on Owner Characteristics and Firm Performance
September 2010
Working Paper Number:
CES-10-24
Because the ability of entrepreneurs to start their own businesses is key to the success of the U.S. economy and to the economic mobility of many disadvantaged demographic groups, understanding why entrepreneurship activity varies across groups and geography is an increasingly important issue. As a step in this direction we employ a novel set of metrics of business success to the growing literature and find great variation across groups and metrics. For example, we find that black-owned firms grow slower than white or Asian-owned firms. However, once we condition on firm survival, the differences disappear. Interestingly, we also find differences across groups in their start-up histories. For example, Asian-owned firms are less likely than white-owned firms to have started-out as nonemployers but firms owned by all other minority groups, as well as women-owned firms, are more likely to start-out without employees.View Full Paper PDF
