Modelling credit risk for innovative firms: the role of innovation measures
AbstractFinancial constraints are particularly severe for R&D projects of SMEs, which cannot generally rely on equity markets and, in the EU, on a sufficiently developed VC industry. If innovative SMEs have to depend on banks to finance their R&D projects, it is particularly important to develop models able to estimate their probability of default (PD) in consideration of their peculiar features. Based on the signaling value of some innovative assets, the purpose of this paper is to show the importance to include them into models which have proved to be successful for SMEs. To this end, we take a logit model and test it on a unique dataset of innovative SMEs (based on PATSTAT database, EPO BULLETIN and AMADEUS) to estimate a two-year PD with default years 2006-2008. In the regression analysis the innovation-related variables are two in order to account for R&D productivity at the level of the firm and to consider the value of the inventive output. Our analyses first address measurement issues concerning innovation-related variable and then show that, while the accounting variables and the patent value are always significant with the expected sign, the patent number per se reduces the PD only in the presence of an appropriate equity level.
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Bibliographic InfoPaper provided by Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi" in its series Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) with number 11031.
Length: pages 27
Date of creation: Mar 2011
Date of revision:
innovative SMEs; default probability; patent value;
Find related papers by JEL classification:
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- O31 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
- O34 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Intellectual Property Rights
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-03-26 (All new papers)
- NEP-CSE-2011-03-26 (Economics of Strategic Management)
- NEP-ENT-2011-03-26 (Entrepreneurship)
- NEP-INO-2011-03-26 (Innovation)
- NEP-KNM-2011-03-26 (Knowledge Management & Knowledge Economy)
- NEP-PPM-2011-03-26 (Project, Program & Portfolio Management)
- NEP-RMG-2011-03-26 (Risk Management)
- NEP-SBM-2011-03-26 (Small Business Management)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ashish Arora & Andrea Fosfuri & Alfonso Gambardella, 2004. "Markets for Technology: The Economics of Innovation and Corporate Strategy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262511819, June.
- Chiara Pederzoli & Costanza Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: New evidence across the financial crisis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 13091, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
- Silvia Angilella & Sebastiano Mazz\`u, 2013. "The Financing of Innovative SMEs: a multicriteria credit rating model," Papers 1308.0889, arXiv.org.
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