Becker Friedman Institute
for Research in Economics
The University of Chicago

Research. Insights. Impact. Advancing the Legacy of Chicago Economics.

O32: Management of Technological Innovation and R&D

Sharing R&D Risk in Healthcare via FDA Hedges

Adam Jørring, Andrew W. Lo, Tomas Philipson, Manita Singh, Richard Thakor

The high cost of capital for firms conducting medical research and development (R&D) has been partly attributed to the government risk facing investors in medical innovation. This risk slows down medical innovation because investors must be compensated for it. We propose new and simple financial instruments, Food and Drug Administration (FDA) hedges, to allow medical R&D investors to better share the pipeline risk associated with FDA approval with broader capital markets.

Optimal Taxation and R&D Policies

Ufuk Akcigit, Douglas Hanley, Stefanie Stantcheva

We study the optimal design of R&D policies and corporate taxation when the outputs of innovation are not appropriable in the absence of intellectual property rights policies and there are non-internalized technology spillovers across firms. Firms are heterogeneous in their research productivity, i.e., in the efficiency with which they convert a given set of R&D inputs into successful innovations. There is asymmetric information about firm productivity and about its stochastic evolution over time that prevents the first best solution to the technology spillover.

Does Management Matter? Evidence from India

Nicholas Bloom, Benn Eifert, Aprajit Mahajan, David McKenzie, John Roberts

A long standing question in social science is whether management matters. Certainly management differs across firms, as does performance. However, perhaps every firm chooses its management practices optimally, so that differences across firms simply reflect differences in their environments. To investigate this we run a field experiment on large Indian textile firms to evaluate the causal impact of modernizing their management practices. We do this by providing free management consulting to a set of randomly chosen treatment plants, and compare their performance to a set of control plants.