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Innovation

Paper Session

Sunday, Jan. 3, 2021 12:15 PM - 2:15 PM (EST)

Hosted By: American Economic Association & Committee on the Status of Women in the Economics Profession
  • Chair: Petra Moser, New York University

The Life Cycle of Employers and their Occupational Mix

Sara Moreira
,
Northwestern University
Elizabeth Weber Handwerker
,
U.S. Bureau of Labor Statistics
David Piccone
,
U.S. Bureau of Labor Statistics

Abstract

Does the workforce composition of businesses vary systematically between startups and older businesses? Is the survival and growth of businesses systematically associated with the occupational mix of businesses? Despite the importance of young businesses and the emphasis of policymakers on promoting entrepreneurship, little is known about the characteristics of jobs and employees in startups, and their contribution to their employers' success. Existing research has established that business tend to start small and grow as they become older (e.g. Haltiwanger, Jarmin, and Miranda, 2013). Atkeson and Kehoe (2005) suggest that this life cycle is driven by the accumulation of business-specific organization capital. These studies suggest that businesses experience substantial changes in their occupational mix and such changes have an important role in shaping their growth and survival.
In this paper, we provide large scale empirical evidence on the occupational mix of young businesses in the U.S. for the period 2002-2018. We assemble a micro-level data set that combines the BLS Occupational Employment Statistics and the BLS Quarterly Census of Employment and Wages. By combining these data sets, we are able to measure the occupational mix of individual businesses and their respective performance (e.g., growth, survival) and to follow different cohorts of establishments over their entire life cycle (in three year periods). We use the data set to examine how the workforce composition varies with employer birth cohort and age, and to evaluate the correlation between firm performance (growth, survival) and the occupational composition of their workforce.

The Effects of Prize Structures on Innovative Performance

Elizabeth Lyons
,
University of California-San Diego
Joshua Graff Zivin
,
University of California-San Diego

Abstract

Successful innovation is essential for the survival and growth of organizations but how best to incentivize innovation is poorly understood. We compare how two common incentive schemes affect innovative performance in a fi eld experiment run in partnership with a large life sciences company. We fi nd that a winner-takes-all compensation scheme generates signifi cantly more novel innovation relative to a compensation scheme that offers the same total compensation, but shared across the ten best innovations.
Moreover, the winner-takes-all scheme does not reduce innovative output on average, and among teams of innovators, generates more output than the less risky prize structure.

The Education-Innovation Gap

Barbara Biasi
,
Yale University
Song Ma
,
Yale University

Abstract

Higher education plays a crucial role in the production of human capital and skills by providing individuals with ``up-to-date'' knowledge. To what extent is this type of knowledge provided in colleges and universities? We answer this question with a novel measure: the education-innovation gap, i.e., the distance between the content of college and university courses and frontier ``technologies,'' such as academic research and patents. We construct this measure using the text of three million US college and university syllabi, the abstract of 20 million academic publications, and the text of more than six million patents as data. With this new measure we document three new facts. First, differences among instructors (as opposed to fields or schools) explain the largest proportion of the overall variation in the gap. Second, we show that access to frontier knowledge is unevenly distributed across institutions serving students with different backgrounds. Third, we find that the gap is correlated with students' outcomes.

Technology Adoption and Productivity Growth: Evidence from Industrialization in France

Reka Juhacz
,
Columbia University
Mara P. Squicciarini
,
Bocconi University
Nico Voigtländer
,
University of California-Los Angeles

Abstract

We construct a novel plant-level dataset to examine the process of technology adoption during a period of rapid technological change: The diffusion of mechanized cotton spinning during the Industrial Revolution in France. We document new stylized facts that can help explain why major technological breakthroughs tend to be adopted slowly and -- even after being adopted
-- take time to be reflected in aggregate productivity statistics. Before mechanization, cotton spinning was performed in households, while production in plants only emerged with the new technology around 1800. This allows us to isolate the plant productivity distribution of new technology adopters in mechanized cotton spinning. We find that this distribution was initially highly dispersed. Over the subsequent decades, mechanized spinning experienced dramatic productivity growth that was almost entirely driven by a disappearance of plants in the lower tail. In contrast, innovations in other sectors (with gradual technological progress) shifted the whole productivity distribution. We document rich historical and empirical evidence suggesting that the pattern in cotton spinning was driven by the need to re-organize production under the new technology. This process of `trial and error' led to widely dispersed initial productivity draws, low initial average productivity, and -- in the subsequent decades -- to high productivity growth as new entrants adopted improved methods of operating the mechanized technology.
Discussant(s)
John C. Haltiwanger
,
University of Maryland
Daniel P. Gross
,
Duke University
Kevin Stange
,
University of Michigan
Walker Hanlon
,
New York University-Stern
JEL Classifications
  • O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights
  • J2 - Demand and Supply of Labor