IDEAS home Printed from https://ideas.repec.org/a/bla/ecinqu/v52y2014i3p1153-1172.html

R&D AND CREDIT RATIONING IN SMEs

Author

Listed:
  • Maria Luisa Mancusi
  • Andrea Vezzulli

Abstract

type="main" xml:id="ecin12080-abs-0001"> We study the effects of credit rationing on research and development (R&D) investment using survey and accounting data on a large representative sample of manufacturing small- and medium-sized enterprises (SMEs). Our econometric model accounts for the endogeneity of our credit rationing indicator and employs an innovative theory-based identification strategy. We find that credit rationing has a significantly negative effect on both the probability to set up R&D activities and on the level of R&D spending (conditioned on the R&D decision), but the overall estimated reduction in R&D spending is largely to be associated with the first effect. ( JEL G21, D82, O32, C35)

Suggested Citation

  • Maria Luisa Mancusi & Andrea Vezzulli, 2014. "R&D AND CREDIT RATIONING IN SMEs," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 1153-1172, July.
  • Handle: RePEc:bla:ecinqu:v:52:y:2014:i:3:p:1153-1172
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/ecin.2014.52.issue-3
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or

    for a different version of it.

    Other versions of this item:

    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ecinqu:v:52:y:2014:i:3:p:1153-1172. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/weaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.