Figure 1
Theoretical model of the impact of public financial support on different activities of treated enterprise.
Source: Own elaboration.
Table 1
Initial sample description
| Country | Sample | Sample split |
|---|---|---|
| BG | 14,255 | 14.4 |
| CY | 1,346 | 1.4 |
| CZ | 5,198 | 5.3 |
| DE | 6,282 | 6.4 |
| EE | 1,760 | 1.8 |
| EL | 2,507 | 2.5 |
| ES | 30,333 | 30.7 |
| HR | 3,265 | 3.3 |
| HU | 6,817 | 6.9 |
| LT | 2,421 | 2.5 |
| LV | 1,501 | 1.5 |
| NO | 5,045 | 5.1 |
| PT | 7,083 | 7.2 |
| RO | 8,206 | 8.3 |
| SK | 2,790 | 2.8 |
| Total | 98,809 | 100.0 |
[i] BG, Bulgaria; CY, Cyprus; CZ, Czech Republic; DE, Germany; EE, Estonia; EL, Greece; ES, Spain; HR, Croatia; HU, Hungary; LT, Lithuania; LV, Latvia; NO, Norway; PT, Portugal; RO, Romania; SK, Slovakia; CIS, Community Innovation Survey.
[ii] Source: Own calculations based on micro-data from CIS 2012–2014.
Table 2
Variable operationalization
| Variable | Description and construction of variables | Abbr. from CIS 2014 |
|---|---|---|
| PubSuppEU | Variable—“Financial support from European Union” | |
| “1” if the firm received public financial support for innovation activity from EU; 0” otherwise. | FUNEU | |
| InnoPerf | Variable—“Innovation performance of supported enterprise” | |
| Log of fraction (from 0 to 100) of turnover from innovative products introduced in 2012–2014 in total turnover in 2014 | TURNMA + TURNIN | |
| KnowAcq | Variable—“Knowledge acquisition as the proxy for R&D budget” | |
| “1” if the firm declared acquisition of machinery, equipment, software and buildings to be used for new or significantly improved products, processes or acquisition of existing knowledge from other enterprises or organizations (existing know-how, copyrighted works, patented and non-patented inventions, etc. from other enterprises or organizations for the development of new or significantly improved products and processes; “0” otherwise | RMAC ROEK | |
| InnoCoopTr | Variable—“Innovation cooperation and personnel training” | |
| “1” if the firm declared cooperation with local suppliers; customers; competitors; consultants; universities, research institutes, or cooperation with EU suppliers; customers; competitors; consultants; universities, research institutes, or cooperation with non-EU (China, India, the United States, other countries) suppliers; customers; competitors; consultants; universities, research institutes, or conducted internal or external training for its personnel for the development and/or introduction of new products and processes; “0” otherwise | Co11-Co75. RTR | |
[i] CIS, Community Innovation Survey; R&D, research and development.
[ii] Source: Own compilation based on questionnaire CIS 2012–2014.
Table 3
Results of path analysis for the whole sample of enterprises from 14 EU member states
| Variable | Impact direction | Variable | H | Estimate | S.E. | P | Standardized |
|---|---|---|---|---|---|---|---|
| KnowAcq | <--- | PublSuppEU | H1 | 0.417 | 0.015 | *** | 0.203 |
| InnoPerf | <--- | PublSuppEU | H2 | 0.066 | 0.012 | *** | 0.046 |
| InnoCoopTr | <--- | PublSuppEU | H3 | 0.107 | 0.011 | *** | 0.063 |
| InnoPerf | <--- | KnowAcq | 0.030 | 0.022 | 0.175 | 0.010 | |
| InnoPerf | <--- | InnoCoopTr | 0.065 | 0.014 | *** | 0.037 | |
| KnowAcq | <--- | InnoCoopTr | 0.357 | 0.005 | *** | 0.430 |
Table 4
Results of path analysis for the whole sample of enterprises from 14 EU member states, total effect, direct effect, and indirect effect
| Variables | Total effects | Direct effects | Indirect effects | ||||||
|---|---|---|---|---|---|---|---|---|---|
| PublSuppEU | KnowAcq | InnoCoopTr | PublSuppEU | KnowAcq | InnoCoopTr | PublSuppEU | KnowAcq | InnoCoopTr | |
| KnowAcq | 0.417 | 0.000 | 0.000 | 0.417 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
| InnoCoopTr | 0.256 | 0.357 | 0.000 | 0.107 | 0.357 | 0.000 | 0.149 | 0.000 | 0.000 |
[i] EU. European Union.
[ii] Source: Own elaboration based on results of path analysis.
Table 5
Taxonomy of EU innovation activity support within surveyed countries results from path models for each country sample and verification of hypotheses
| Additionality type | H | BG | CY | CZ | EE | EL | ES | HR | HU | LT | LV | NO | PO | RO | SK |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Input additionality standardized | H1 | 0.188 | 0.199 | 0.125 | 0.076 | 0.082 | 0.061 | 0.107 | 0.173 | 0.146 | 0.053 | 0.004 | 0.122 | 0.075 | 0.058 |
| Input additionality P value | H1 | *** | *** | *** | 0.244 | ** | *** | ** | *** | *** | 0.538 | 0.866 | *** | 0.501 | 0.252 |
| Input additionality (external R&D) | H1 | + | + | + | No | + | + | + | + | + | No | No | + | No | No |
| Output additionality standardized | H2 | 0.019 | 0.045 | 0.013 | 0.029 | −0.024 | 0.041 | −0.022 | −0.015 | 0.052 | 0.173 | 0.033 | 0.012 | 0.056 | 0.001 |
| Output additionality P value | H2 | .457 | 0.433 | 0.595 | 0.695 | 0.522 | ** | 0.590 | 0.566 | 0.082 | 0.388 | 0.159 | 0.590 | 0.614 | 0.987 |
| Output additionality | H2 | No | No | No | No | No | + | No | No | No | No | No | No | No | No |
| Behavioral additionality standardized | H3 | 0.184 | 0.116 | 0.209 | 0.023 | 0.207 | 0.286 | 0.125 | 0.146 | 0.180 | 0.173 | 0.233 | 0.290 | 0.198 | 0.195 |
| Behavioral additionality P value | H3 | *** | 0.038 | *** | 0.755 | *** | *** | ** | *** | *** | 0.058 | *** | *** | 0.066 | *** |
| Behavioral additionality | H3 | + | + | + | No | + | + | + | + | + | No | + | + | No | + |
| Policy type | B.ID | BI.D | BI.D | NO.AE | BI.D | MULT | BI.D | BI.D | BI.D | NO.AE | MONO.D | BID | NO.AE | MONO.D |
Figure 2
Results of path analysis for selected EU countries—input additionality and behavioral additionality.
Source: Own elaboration based on the results of path analysis of 14 countries under study. EU, European Union.