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dc.rights.licenseopenen_US
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
dc.contributor.authorFOTSO, Ruben
dc.date.accessioned2021-11-19T10:44:34Z
dc.date.available2021-11-19T10:44:34Z
dc.date.issued2021
dc.identifier.issn0892-9912en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/123872
dc.description.abstractEnWhen it comes to evaluating the causal effect of public policies on corporate performance, most studies tend to focus exclusively on targeted firms, as if these firms have no relationship to the rest of the economy. Yet, public policies are highly likely to influence non-targeted firms indirectly due to the relationships they have with targeted firms. This paper aims to fill this gap by evaluating the indirect causal effect of a new French cluster-innovation policy on the financial and employment outcomes of non-targeted companies. To do so, it focuses on French Technological Research Institutes, which are science-industry collaborations based on technology platforms that bring together SMEs, large companies, universities, and public research bodies with the goal of accelerating the transfer of knowledge towards firms and generating spillovers (indirect effects) inside and outside the scheme. Based on the literature on spillover effects and agglomeration economies, it can be assumed that industry-specific spillovers tend to be spatially concentrated. By comparing a non-targeted firm located in the NUTS-3 regions within which the policy was implemented (referred to as "treated regions"), to a non-targeted firm outside of these "treated regions", using a difference-in-differences method with fixed effects applied to panel data (2008–2016) combined with a double matching at the NUTS-3 region and firm level, we find that non-targeted firms located in the "treated regions" significantly improve their financial performance (turnover, financial autonomy) compared to control firms located in the NUTS-3 control regions. The dynamics of employment outcomes are ambiguous. A negative significant effect is observed on the proportion of managers at the beginning of the policy and a positive significant effect is noted later, at the end of the period of observation. An analysis of the dynamics of the effects indicates that performance does not improve immediately after the policy, but later in time. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
dc.language.isoENen_US
dc.subject.enCorporate Performance
dc.subject.enDifference-In-Differences
dc.subject.enFinance
dc.subject.enFinancial Performance
dc.subject.enIndustrial Economics
dc.subject.enIndustry Collaboration
dc.subject.enInnovation Policies
dc.subject.enKnowledge Management
dc.subject.enNuts (Fasteners)
dc.subject.enPublic Policy
dc.subject.enTechnological Researches
dc.subject.enTechnology Platforms
dc.subject.enTransfer Of Knowledge
dc.title.enEvaluating the indirect effects of cluster-based innovation policies: the case of the Technological Research Institutes in France
dc.typeArticle de revueen_US
dc.identifier.doi10.1007/s10961-021-09865-2en_US
dc.subject.halÉconomie et finance quantitative [q-fin]en_US
bordeaux.journalJournal of Technology Transferen_US
bordeaux.hal.laboratoriesGroupe de Recherche en Economie Théorique et Appliquée (GREThA) - UMR 5113en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.exportfalse
dc.rights.ccPas de Licence CCen_US
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