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Cited by 404

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

IMPACT OF FINANCIAL CONSTRAINTS ON INNOVATION: WHAT CAN BE LEARNED FROM A DIRECT MEASURE?

Open access
Savignac, Frédérique·2008·Economics of Innovation and New Technology

Abstract

This paper examines the impact of financial constraints on innovation for established firms. We make use of a direct measure of the existence of financial constraints obtained thanks to a specific survey addressed to French established firms. This is a distinctive feature of this paper as most of previous studies had to rely on proxies (like the cash-flow sensitivity), which may be subject to interpretation problems. The probability to have innovative activities and the probability to face financial constraints are simultaneously estimated by a recursive bivariate probit model. Accounting for the endogeneity of the financial constraint variable, we find that financial constraints significantly reduce the likelihood that firms have innovative activities. The probability to encounter financial constraints is explained by firms’ ex ante financing structure and economic performances.

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Metadata

Authors
Savignac, F.
Venue
Economics of Innovation and New Technology
Published
2008-09
Volume
17
Issue
6
Pages
553-569
ISSN
  • 1043-8599 (ISSN-L)
  • 1476-8364
OpenAlex
W3124068838
Cited by
404
References
24
FWCI
28.52
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: IMPACT OF FINANCIAL CONSTRAINTS ON INNOVATION: WHAT CAN BE LEARNED FROM A DIRECT MEASURE? https://app.cochat.ai/papers/10.1080/10438590701538432
The paper
Savignac, F. (2008). IMPACT OF FINANCIAL CONSTRAINTS ON INNOVATION: WHAT CAN BE LEARNED FROM A DIRECT MEASURE? Economics of Innovation and New Technology. https://doi.org/10.1080/10438590701538432

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.