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Startup Dynamics: Transitioning from Nonemployer Firms to Employer Firms, Survival, and Job Creation
April 2025
Working Paper Number:
CES-25-26
Understanding the dynamics of startup businesses' growth, exit, and survival is crucial for fostering entrepreneurship. Among the nearly 30 million registered businesses in the United States, fewer than six million have employees beyond the business owners. This research addresses the gap in understanding which companies transition to employer businesses and the mechanisms behind this process. Job creation remains a critical concern for policymakers, researchers, and advocacy groups. This study aims to illuminate the transition from non-employer businesses to employer businesses and explore job creation by new startups. Leveraging newly available microdata from the U.S. Census Bureau, we seek to gain deeper insights into firm survival, job creation by startups, and the transition from non-employer to employer status.
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Garage Entrepreneurs or just Self-Employed? An Investigation into Nonemployer Entrepreneurship
October 2024
Working Paper Number:
CES-24-61
Nonemployers, businesses without employees, account for most businesses in the U.S. yet are poorly understood. We use restricted administrative and survey data to describe nonemployer dynamics, overall performance, and performance by demographic group. We find that eventual outcome ' migration to employer status, continuing as a nonemployer, or exit ' is closely related to receipt growth. We provide estimates of employment creation by firms that began as nonemployers and become employers (migrants), estimating that relative to all firms born in 1996, nonemployer migrants accounted for 3-17% of all net jobs in the seventh year after startup. Moreover, we find that migrants' employment creation declined by 54% for the cohorts born between 1996 to 2014. Our results are consistent with increased adjustment frictions in recent periods, and suggest accessibility to transformative entrepreneurship for everyday Americans has declined.
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Entrepreneurial Teams: Diversity of Skills and Early-Stage Growth
December 2020
Working Paper Number:
CES-20-45
We use employer-employee linked data to track the employment histories of team members prior to startup formation for a full cohort of new firms in the U.S. Using pre-startup industry experience to measure skillsets, we find that startups that have founding teams with more diverse collective skillsets grow faster than peer firms in the same industries and local economies. A one standard deviation increase in teams' skill diversity is associated with an increase in five-year employment (sales) growth of 16% (10%) from the mean. The effects are stronger among startups in innovative industries and among startups facing greater ex-ante uncertainty. Moreover, the results are robust to a variety of approaches to address the endogeneity of team composition. Overall, our results suggest that teams with more diverse collective skillsets adapt their strategies more successfully in the uncertain environments faced by (innovative) startup firms.
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Hiring 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.
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Going Entrepreneurial? IPOs and New Firm Creation
January 2017
Working Paper Number:
CES-17-18
Using matched employee-employer US Census data, we examine the effect of a successful initial public offering (IPO) on employee departures to startups. Accounting for the endogeneity of a firm's choice to go public, we find strong evidence that going public induces employees to leave for start-ups. Moreover, we document that the increase in turnover following an IPO is driven by employees departing to start-ups; we find no change in the rate of employee departures for established firms. We present evidence that, following an IPO, many employees who received stock grants experience a positive shock to their wealth which allows them to better tolerate the risks associated with joining a startup or to obtain funding. Our results suggest that the recent declines in IPO activity and new firm creation in the US may be causally linked. The recent decline in IPOs means fewer workers may move to startups, decreasing overall new firm creation in the economy.
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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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Entrepreneurial teams' acquisition of talent: a two-sided approach
January 2016
Working Paper Number:
CES-16-45
While it is crucial for startups to hire high human capital employees, little is known about what drives the hiring decisions. Considering the stakes for both startups and their hires (i.e., joiners), we examine the phenomenon using a two-sided matching model that explicitly reveals the preferences of each side. We apply the model to a sample of startups from five technological manufacturing industries while examining a range of variables grounded in prior work on startup human capital. The analysis is based on the Longitudinal Employer Household dynamics from the U.S. Census Bureau. Our findings indicate that, in the context of entrepreneurship, both startups and joiners rely heavily on signals of quality. Further, quality considerations that are important for the match play a minimal role in determining earnings. Our approach refines our understanding of how entrepreneurial human capital evolves.
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The 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.
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