The Role of EU Policy in Supporting Technological Innovation in SMEs - a Bayesian Network Analysis of Firm-Level Data from Poland

Massimo Florio, Aleksandra Parteka and Emanuela Sirtori

Departmental Working Papers from Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano

Abstract: We study the effectiveness of the ‘Technological Credit’ (TC) instrument in supporting innovation in Polish SMEs. Our research question is: to what extent does providing credit to SMEs tied to technological investment affect capital expenditure and how does this change the innovativeness of firms? So far, the evidence on the impact of this policy instrument is unsystematic. To answer the question, we use an approach which is novel in innovation policy studies: we perform a Bayesian Network Analysis of survey data. Our data include a unique sample of 200 Polish firms that received TC support during the 2007-2013 programming period. Our findings confirm short-term positive effects (i.e. a wider range of products/services offered and increased sales and exports) and we also have many interesting results related to behavioural changes in firms (which are not necessarily quantifiable economically). We also find that only more financially solid and more internationalized firms were able to take advantage of the policy. These findings suggest that schemes based on technological credits are not appropriate for promoting innovation in all types of SME and should be designed to shift the technological frontier rather than to sustain a catching up process for firms lagging behind the frontier.

Keywords: technological innovation; innovation policy; ex-post evaluation; Bayesian Network Analysis (search for similar items in EconPapers)
JEL-codes: C11 O31 O33 R11 (search for similar items in EconPapers)
Date: 2016-11-19
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Persistent link: https://EconPapers.repec.org/RePEc:mil:wpdepa:2016-13

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