Entrepreneurship Working Group Fall 2019

Why is high-growth entrepreneurship scarce in developing countries? Does this scarcity reflect optimal allocations, or constraints? Gonzalez-Uribe and Reyes explore these questions using as laboratory an accelerator in Colombia that selects participants using scores from randomly assigned judges and offers them training, customized advice, and visibility, but no cash. Exploiting exogenous differences in judges' scoring generosity, the researchers show that alleviating constraints to firm capabilities increases average high-growth by unlocking innovative-entrepreneurs' potential, rather than by transforming low-quality ideas. Results demonstrate that some high-potential entrepreneurs in developing economies face firm capabilities constraints, and that accelerators can help identify these entrepreneurs and boost their growth.

Bellon, Cookson, Gilje, and Heimer examine the effect of wealth windfalls on self-employment decisions using a novel data set on unexpected payments to individuals from the fracking revolution in Texas. Individuals who receive large wealth shocks (greater than $50,000) have 59% greater self-employment rates relative to individuals who receive small wealth shocks or no wealth shock. The researchers evaluate several economic channels that could drive these results and find that wealth shocks do not alleviate entrepreneurial financial constraints or reduce risk aversion, but drive self-employment through non-pecuniary channels, such as leisure or job autonomy. Their results indicate that heterogeneity in self-employment types is important when assessing the impact of entrepreneurship on the broader economy.

Evaluating the attractiveness of startup employment requires an understanding of both what startups pay and the implications of these jobs for earnings trajectories. Analyzing Danish registry data, Sorenson, Dahl, Canales, and Burton find that employees hired by startups earn roughly 17% less over the next ten years than those hired by large, established firms. About half of this earnings differential stems from sorting -- from the fact that startup employees have less human capital. Long-run earnings also vary depending on when individuals are hired. While the earliest employees of startups suffer an earnings penalty, those hired by already-successful startups earn a small premium. Two factors appear to account for the earnings penalties for the first employees: Startups fail at high rates, creating costly spells of unemployment for their (former) employees. Job mobility patterns also diverge: After being employed by a small startup, individuals rarely return to the large firms that pay more.

Using matched employer-employee data from France, Hombert and Matray uncover an ICT boomcohort discount on the long-term wage of the large cohort of skilled workers entering in the Information and Communication Technology (ICT) sector during the late 1990s technology boom. Despite starting with 5% higher wages, these workers experience lower wage growth and end up with 6% lower wages fifteen years out, relative to similar workers who started outside the ICT sector. Other moments of the wage distribution are inconsistent with selection effects. These workers accumulate human capital early in their career that rapidly depreciates, implying that labor reallocation during technology booms can have long-lasting effects.

Hellmann and Vulkan use equity crowdfunding data to ask how fundraising amounts can be explained by what entrepreneurs ask for, versus what investors want to invest. The analysis exploits unique features of crowdfunding where entrepreneurs not only set investment goals, but also chose when to close their campaigns. More experienced and more educated founder teams ask for more. Their campaigns succeed more often, and they raise more money. Female teams ask for less, are equally successful, yet raise significantly less. They also wait longer before closing campaigns, suggesting they want to raise more than what they originally asked for.

Kleiner and Hacamo demonstrate entrepreneurial overconfidence is not a fixed trait, but instead shaped by social interactions. In the researchers' setting, randomized connections to peers with high entrepreneurial confidence increase the likelihood young managers also become entrepreneurs, especially women with lower confidence prior to treatment. By surveying treated individuals, they confirm managers gain interest in entrepreneurship through increased confidence. The researchers reject alternative explanations including access to entrepreneurial knowledge and decreased risk aversion. The results also suggest shocks to confidence may increase participation in entrepreneurial training programs. Overall, the researchers offer the first experimental evidence that peers increase entrepreneurship and relate these variables through (over)confidence.