About

Gustavo Manso is a Professor of Finance at the Haas School of Business at the University of California, Berkeley, where he holds the Marie-France and Rene Kern Chancellor’s Chair in Entrepreneurship. His research focuses on identifying incentives for promoting innovation within organizations, examining how managerial compensation influences a firm’s innovation activity, and analyzing how the structure of scientific research funding impacts breakthrough studies. Manso has made significant contributions to understanding the dynamics of innovation and financial decision-making, and his work has been published in leading academic journals. He has been recognized for his teaching excellence, receiving the Earl F. Cheit Award for Excellence in Teaching after just one semester at Berkeley Haas. Manso is also a co-founder and past board member of the Finance Theory Group, an initiative that fosters collaboration among young finance researchers and hosts bi-annual meetings at top business schools. His academic career includes positions at MIT Sloan School of Management and Stanford Graduate School of Business, and he has been actively involved in external service as a referee for numerous prestigious economic and finance journals. His expertise spans corporate finance, entrepreneurship, financial institutions, and financial markets.

Research topics

• Economics
• Industrial organization
• Finance
• Business
• Accounting
• Market economy
• Microeconomics
• Monetary economics
• Financial economics
• Macroeconomics

Selected publications

• Household debt overhang and human capital investment

  Journal of Financial Economics · 2025-07-28 · 3 citations

  article1st author
  PublisherDOI

• The Streetlight Effect in Data-Driven Exploration

  SSRN Electronic Journal · 2024-01-01

  articleOpen access
  PublisherDOI

• The Impact of Connectivity on the Production and Diffusion of Knowledge

  SSRN Electronic Journal · 2024-01-01 · 1 citations

  preprintOpen access1st authorCorresponding
  PublisherDOI

• The Streetlight Effect in Data-Driven Exploration

  National Bureau of Economic Research · 2024-05-01 · 19 citations

  reportOpen access

  We study exploration under uncertainty and show how access to data on past attempts can paradoxically hinder breakthrough discovery. We develop a model of the “streetlight effect” demonstrating that when data highlights attractive but ultimately suboptimal projects, it can narrow exploration and suppress innovation. In a laboratory experiment, we find that revealing the value of an enticing project lowers payoffs and reduces breakthrough discoveries. This drop stems from increased free-riding behavior, which crowds out the generation of new data. We validate our theory in the context of scientific research into the genetic origins of human diseases. To identify the causal impact of past data, we use an instrumental variable that leverages exogenous genetic overlaps between humans and laboratory mice, which reduces research costs for specific genes and leads to prioritized data collection about them. We find that diseases with early evidence of promising genetic targets are 16 percentage points less likely to yield breakthroughs than those where early efforts failed. While competition attenuates the streetlight effect, it does not eliminate it. Our paper provides the first systematic analysis of this phenomenon, outlining the conditions under which data leads agents to look under the lamppost rather than engage in socially beneficial exploration.

  PublisherDOI

• Biased Auctioneers

  The Journal of Finance · 2023-01-18 · 34 citations

  articleOpen access

  ABSTRACT We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and nonvisual object characteristics. We find that higher automated valuations relative to auction house presale estimates are associated with substantially higher price‐to‐estimate ratios and lower buy‐in rates, pointing to estimates' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers' prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.

  PublisherOA PDFDOI

• Household Debt Overhang and Human Capital Investment

  SSRN Electronic Journal · 2022-01-01 · 2 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

• Recommendations with Feedback

  Review of Financial Studies · 2022-04-14 · 4 citations

  articleSenior authorCorresponding

  Abstract We investigate the strategic role of a recommender who cares about accuracy and whose recommendations influence product quality. In the presence of such feedback effects, recommendations have a self-fulling property: the recommendation agent can select any firm that will end up being the firm with the best quality. This produces important inefficiencies that include (a) a lack of incentive to acquire valuable information, (b) a status quo bias, and (c) the avoidance of risky innovations. Monetary payments from firms may work in mitigating these inefficiencies, while competition between recommenders and monetary payments from consumers are ineffective.

  PublisherDOI

• Organizational Learning and Search Track: Scientific and Technical Knowledge: Search, Diffusion, and Impact

  Academy of Management Proceedings · 2022-07-06

  article

  Both innovation and entrepreneurship crucially rely on scientific and technical knowledge. Scientific and engineering principles can be applied to processes of creative search to resolve technical problems, increase useful innovation, and create new business opportunities. Yet, recent years have seen dramatic changes in how knowledge is generated and diffused, with still limited evidence on how these changes are impacting innovation. The emergence of big data and computational capabilities might provide “automated” ways to generate knowledge in the form of predictive statements. What are their effects on the innovation search process and on the rate and the direction of technical change? Furthermore, these trends are magnified by the diffusion of the internet and digital modes of exchanging information. How important is the human component for the diffusion of knowledge? Is the diffusion and impact of knowledge still dependent on localized interactions, despite the widespread availability of ICT and the internet? This panel symposium will assemble four papers on the topics of search, diffusion, and impact of technical knowledge. It will discuss 1) the role of data in the search for innovation, 2) the directional consequences of data availability on the accumulation and diffusion of technical knowledge, and 3) the localization of knowledge and how physical proximity of scientists and inventors influence knowledge flows and company creation. These questions are important to craft strategy processes for managers and the allocation of resources for policymakers.

  PublisherDOI

• The Impact of Connectivity on the Production and Diffusion of Knowledge

  arXiv (Cornell University) · 2022-02-01

  preprintOpen access1st authorCorresponding

  We study a social bandit problem featuring production and diffusion of knowledge. While higher connectivity enhances knowledge diffusion, it may reduce knowledge production as agents shy away from experimentation with new ideas and free ride on the observation of other agents. As a result, under some conditions, greater connectivity can lead to homogeneity and lower social welfare.

  PublisherOA PDFDOI

• Heterogeneous Innovation over the Business Cycle

  The Review of Economics and Statistics · 2021 · 45 citations

  1st authorCorresponding
  • Economics
  • Monetary economics
  • Industrial organization

  Abstract Schumpeter (1939) claims that recessions are periods of “creative destruction,” concentrating innovation that is useful for the long-term growth of the economy. However previous research finds that standard measures of firms’ innovation, such as R&D expenditures or raw patent counts, concentrate in booms. We argue that these measures do not capture shifts in firms’ innovative search strategies. We contemplate firms’ choice between exploration versus exploitation over the business cycle and find evidence with more nuanced measures of patent characteristics that firms shift toward exploration during contractions and exploitation during expansions, with a stronger effect for firms in more cyclical industries.

  PublisherOA PDFDOI

Frequent coauthors

• Bruce Carlin

  54 shared

• Semyon Malamud

  Swiss Finance Institute

  28 shared

• Darrell Duffie

  National Bureau of Economic Research

  18 shared

• Simon Gervais

  13 shared

• Florian Ederer

  Centre for Economic Policy Research

  8 shared

• Joshua Graff Zivin

  National Bureau of Economic Research

  7 shared

• Pierre Azoulay

  7 shared

• Christophe Spaenjers

  7 shared

Education

• Ph.D., Business Administration

  University of California, Berkeley

  2001

• Other, Business Administration

  University of California, Berkeley

  1997

• B.A., Economics

  University of California, Berkeley

  1993

Awards & honors

• Earl F. Cheit Award for Excellence in Teaching (2012)
• NBER IPE Grant, “Incentives and Creativity” (2007–2008)
• Swiss Finance Institute Outstanding Paper Award (2009)
• Review of Financial Studies Young Researcher Award (2009)
• First Prize, Lehman Brothers Fellowship for Research Excelle…