by Robert W. Fairlie and Javier Miranda

Job creation is one of the most important aspects of entrepreneurship, but we know relatively little about the hiring patterns and decisions of start-ups. 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 nonemployer to employer firm among start-ups. Several interesting patterns emerge regarding the dynamics of nonemployer start-ups hiring their first employee. Hiring rates among the universe of nonemployer start-ups are very low, but increase when the population of nonemployers is focused on more growth-oriented businesses such as incorporated and employer identification number businesses. If nonemployer start-ups hire, the bulk of hiring occurs in the first few years of existence. After this point in time, relatively few nonemployer start-ups hire an employee. Focusing on more growth- and employment-oriented start-ups in the KFS, we find that Asian-owned and Hispanic-owned start-ups have higher rates of hiring their first employee than white-owned start-ups. Female-owned start-ups are roughly 10 percentage points less likely to hire their first employee by the first, second, and seventh years after start-up. 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 nonemployers hire their first employee.

1. Please briefly describe the main results of your paper.

Using data from three sources, we 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 in the universe of non-employer startups are very low, but increase when the population of non-employers is focused on more growth-oriented businesses. If non-employer startups hire, the bulk of hiring occurs in the first few years of existence. Focusing on more growth- and employment-oriented startups, 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. Among business characteristics, we find evidence that business assets and intellectual property are associated with hiring the first employee. Using data from a large random experiment, we do not find evidence that entrepreneurship training increases the likelihood that non-employers hire their first employee.

2. What databases does this paper draw upon and why are they especially apt for examining the decisions made by nonemployers hiring their first employee?

In this paper, we use data from three sources: 1) the U.S. Census Bureau’s Integrated Longitudinal Business Database (iLBD) which provides panel data on the universe of non-employers matched to employers over time, 2) the Kauffman Firm Survey (KFS) which provides panel data on detailed owner and business characteristics and follows growth-oriented startups over the first several years of existence, and 3) the Growing America through Entrepreneurship (GATE) experiment which is the largest random experiment on the effects of entrepreneurship training ever conducted. Using these data, this paper provides one of the first detailed longitudinal studies of the owner, business, and training determinants of non-employers hiring their first employee.

3. What policy implications might arise from this work? 

We do not focus on evaluating specific policies in the article, but policies that could encourage job creation among minority- and female-owned startups could be important for economic growth. There appears to be a lot of unmet potential in business success for these population groups.

4. What directions might you suggest for further research?

Job creation among startups is an understudied topic in the literature. More research is clearly needed. One of the main arguments for encouraging entrepreneurship is the potential for job creation. We need to better understand how this potential is achieved.