A computational analysis of R&D support programs

Dagoberto Garza, Yahel Giat, Steven T. Hackman, Dan Peled

Research output: Contribution to journalArticlepeer-review

Abstract

We compare two common government R&D support programs, R&D tax credits and direct R&D grants. To study their effectiveness and the extent to which their design matters, we analyze these programs within a dynamic equilibrium model of imperfectly competitive industries. Adopting comprehensive welfare measures that take into account government, producer and consumer surpluses, we find that both schemes exhibit positive social returns. Mid-range R&D-intensive sectors exhibit higher social returns than either high or low R&D-intensive sectors. Both incentive schemes generate positive measures of R&D input additionality of magnitudes consistent with empirical R&D research. However, R&D grants that require firms to allocate subsidy funds to R&D spur less R&D than a more flexible R&D tax credit. Subsidy schemes can even induce competing firms to over-spend on R&D, generating negative producer surplus and possibly negative social returns.

Original languageEnglish
Pages (from-to)682-709
Number of pages28
JournalEconomics of Innovation and New Technology
Volume24
Issue number7
DOIs
StatePublished - 3 Oct 2015

Bibliographical note

Funding Information:
This research was partially funded by the Science Technology and the Economy (STE) Program at the Samuel Neaman Institute and Technion-Israel Institute of Technology.

Publisher Copyright:
© 2014 Taylor & Francis.

Keywords

  • competition
  • process and product R&D
  • R&D additionality
  • R&D price elasticity
  • R&D subsidies
  • social welfare
  • tax credits

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (all)
  • Management of Technology and Innovation

Fingerprint

Dive into the research topics of 'A computational analysis of R&D support programs'. Together they form a unique fingerprint.

Cite this