Entrepreneurship, Innovation und Produktivitätswachstum
Diese Gruppe befasst sich mit Forschungsthemen, die für unser Verständnis von Innovationsmustern und Produktivitätswachstum von Bedeutung sind, und untersucht die Auswirkungen auf Arbeitnehmer und Unternehmen. Zu den Schwerpunkten gehören der Rückgang der Unternehmensdynamik, die Zunahme der Automatisierung, Entrepreneurship und Innovation sowie Lieferketten.
Forschungscluster
Produktivität und InstitutionenIhr Kontakt
- Abteilung Zentrum für Firmen- und Produktivitätsdynamik
PROJEKTE
06.2024 ‐ 05.2027
High-growth Entrepreneurship, Innovation, and the Transformation of our Economy (Kooperative Exzellenz)
Leibniz-Gemeinschaft
Referierte Publikationen
Declining Dynamism, Allocative Efficiency, and the Productivity Slowdown
in: American Economic Review: Papers and Proceedings, Vol. 107 (5), 2017
Abstract
A large literature documents declining measures of business dynamism including high-growth young firm activity and job reallocation. A distinct literature describes a slowdown in the pace of aggregate labor productivity growth. We relate these patterns by studying changes in productivity growth from the late 1990s to the mid 2000s using firm-level data. We find that diminished allocative efficiency gains can account for the productivity slowdown in a manner that interacts with the within-firm productivity growth distribution. The evidence suggests that the decline in dynamism is reason for concern and sheds light on debates about the causes of slowing productivity growth.
Taking the Leap: The Determinants of Entrepreneurs Hiring Their First Employee
in: Journal of Economics and Management Strategy, Vol. 26 (1), 2017
Abstract
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.
Where Has All the Skewness Gone? The Decline in High-growth (Young) Firms in the U.S.
in: European Economic Review, Vol. 86 (July), 2016
Abstract
The pace of business dynamism and entrepreneurship in the U.S. has declined over recent decades. We show that the character of that decline changed around 2000. Since 2000 the decline in dynamism and entrepreneurship has been accompanied by a decline in high-growth young firms. Prior research has shown that the sustained contribution of business startups to job creation stems from a relatively small fraction of high-growth young firms. The presence of these high-growth young firms contributes to a highly (positively) skewed firm growth rate distribution. In 1999, a firm at the 90th percentile of the employment growth rate distribution grew about 31 percent faster than the median firm. Moreover, the 90−50 differential was 16 percent larger than the 50−10 differential reflecting the positive skewness of the employment growth rate distribution. We show that the shape of the firm employment growth distribution changes substantially in the post-2000 period. By 2007, the 90−50 differential was only 4 percent larger than the 50−10, and it continued to exhibit a trend decline through 2011. The overall decline reflects a sharp drop in the 90th percentile of the growth rate distribution accounted for by the declining share of young firms and the declining propensity for young firms to be high-growth firms.
Declining Business Dynamism: What We Know and the Way Forward
in: American Economic Review: Papers and Proceedings, Vol. 106 (5), 2016
Abstract
A growing body of evidence indicates that the U.S. economy has become less dynamic in recent years. This trend is evident in declining rates of gross job and worker flows as well as declining rates of entrepreneurship and young firm activity, and the trend is pervasive across industries, regions, and firm size classes. We describe the evidence on these changes in the U.S. economy by reviewing existing research. We then describe new empirical facts about the relationship between establishment-level productivity and employment growth, framing our results in terms of canonical models of firm dynamics and suggesting empirically testable potential explanations.
Private Equity, Jobs, and Productivity
in: American Economic Review, Vol. 104 (12), 2014
Abstract
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.
Arbeitspapiere
Measuring the Impact of Household Innovation using Administrative Data
in: NBER Working Paper, Nr. 25259, 2018
Abstract
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).
Development of Survey Questions on Robotics Expenditures and Use in U.S. Manufacturing Establishments
in: Center for Economic Studies (CES) Working Paper Series, Nr. 44, 2018
Abstract
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.
Early-Stage Business Formation: An Analysis of Applications for Employer Identification Numbers
in: NBER Working Paper, Nr. 24364, 2018
Abstract
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.