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Pierre Azoulay

Pierre Azoulay

· International Programs Professor of Management

Massachusetts Institute of Technology · Technological Innovation Entrepreneurship and Strategic Mgmt

Active 1974–2026

h-index45
Citations7.6k
Papers15935 last 5y
Funding$9.7M

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Pierre Azoulay is the International Programs Professor of Management at the Sloan School of Management, MIT. He is also a Research Associate at the National Bureau of Economic Research and a non-resident Senior Fellow at the Institute for Progress. His research focuses on the organization of the "ideas sector" of the economy and investigates how different institutional arrangements impact innovation. Specifically, he studies how institutional design influences not only the quantity of knowledge produced but also its direction and character, including which questions are asked, who is able to ask them, and the level of risk scientists are willing to undertake. His current research projects include examining management practices and culture in a large sample of biomedical research laboratories and exploring project choice in structural biology. At MIT Sloan, Pierre Azoulay teaches courses in competitive strategy, technology strategy, platform strategy, and a PhD seminar on the economics of ideas and innovation. Alongside Danielle Li, he coordinates the PhD program in Technological Innovation, Entrepreneurship, and Strategy (TIES). He holds a PhD from the Massachusetts Institute of Technology, an MA from Michigan State University, and a Diplôme d’Études Supérieures de Gestion from Institut Mines-Télécom Business School.

Research topics

  • Economics
  • Social Science
  • Sociology
  • Business
  • Economic growth
  • Epistemology
  • Neoclassical economics
  • Marketing
  • Positive economics
  • Demographic economics

Selected publications

  • Age and High-Growth Entrepreneurship

    American Economic Review Insights · 2020 · 404 citations

    1st authorCorresponding

    Many observers, and many investors, believe that young people are especially likely to produce the most successful new firms. Integrating administrative data on firms, workers, and owners, we study start-ups systematically in the United States and find that successful entrepreneurs are middle-aged, not young. The mean age at founding for the 1-in-1,000 fastest growing new ventures is 45.0. The findings are similar when considering high-technology sectors, entrepreneurial hubs, and successful fir…

  • Inside Job or Deep Impact? Extramural Citations and the Influence of Economic Scholarship

    Journal of Economic Literature · 2020 · 112 citations

    Does academic economic research produce material of general scientific value, or do academic economists write only for peers? Is economics scholarship uniquely insular? We address these questions by quantifying interactions between economics and other disciplines. Changes in the influence of economic scholarship are measured here by the frequency with which other disciplines cite papers in economics journals. We document a clear rise in the extramural influence of economic research, while also s…

  • Immigration and Entrepreneurship in the United States

    National Bureau of Economic Research · 2020-09-01 · 84 citations

    report1st authorCorresponding

    Immigration can expand labor supply and create greater competition for native-born workers. But immigrants may also start new firms, expanding labor demand. This paper uses U.S. administrative data and other data resources to study the role of immigrants in entrepreneurship. We ask how often immigrants start companies, how many jobs these firms create, and how these firms compare with those founded by U.S.-born individuals. A simple model provides a measurement framework for addressing the dual…

  • Long-term effects from early exposure to research: Evidence from the NIH “Yellow Berets”

    Research Policy · 2021-08-03 · 24 citations

    articleOpen access1st authorCorresponding
  • Old Moats for New Models: Openness, Control, and Competition in Generative Ai

    SSRN Electronic Journal · 2024-01-01 · 15 citations

    articleOpen access1st authorCorresponding

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