SME Performance and Public Support for International RJVs^*

* We thank the editor, Professor Massimo Colombo, and three anonymous reviewers for their helpful comments. We are also grateful to the audiences at the CONCORD 2011 (Sevilla), the SAEe 2011 (Vigo), the Eu‐SPRI conference 2012 (Karlsruhe) and the Department of Applied Economics II (Universitat de Valéncia). This study has been financially supported by projects ECO2010‐19847 and ECO2014‐52051‐R.

Abstract

The objective of the present study is to analyze the impact of public support for international research joint ventures on SME performance considering two dimensions: technological and economic results. The research is also intended to examine the time pattern of this effect. For that purpose, we use a panel dataset containing information about Spanish participants in consortia supported by the SME‐specific measures of the sixth Framework Programme. Empirical evidence corroborates a direct and positive impact on technological assets of participants. On the part of the economic indicators, EBITDA per employee and labor productivity are positively influenced by the improvement of technological background. All those effects are effective three years after the end of the project, confirming that SMEs are involved in market‐oriented R&D projects.

* We thank the editor, Professor Massimo Colombo, and three anonymous reviewers for their helpful comments. We are also grateful to the audiences at the CONCORD 2011 (Sevilla), the SAEe 2011 (Vigo), the Eu‐SPRI conference 2012 (Karlsruhe) and the Department of Applied Economics II (Universitat de Valéncia). This study has been financially supported by projects ECO2010‐19847 and ECO2014‐52051‐R.

* We thank the editor, Professor Massimo Colombo, and three anonymous reviewers for their helpful comments. We are also grateful to the audiences at the CONCORD 2011 (Sevilla), the SAEe 2011 (Vigo), the Eu‐SPRI conference 2012 (Karlsruhe) and the Department of Applied Economics II (Universitat de Valéncia). This study has been financially supported by projects ECO2010‐19847 and ECO2014‐52051‐R.

Notes

* We thank the editor, Professor Massimo Colombo, and three anonymous reviewers for their helpful comments. We are also grateful to the audiences at the CONCORD 2011 (Sevilla), the SAEe 2011 (Vigo), the Eu‐SPRI conference 2012 (Karlsruhe) and the Department of Applied Economics II (Universitat de Valéncia). This study has been financially supported by projects ECO2010‐19847 and ECO2014‐52051‐R.

1 These countries can be European Union Member States or Associated Candidate Countries (European Commission, 2002).

2 Although the sixth FP was formally launched in 2002, during that year there was no application registered.

3 Proposals are evaluated by independent experts according to some common criteria. However, such information is absent from our database.

4 Other measures of technological outputs used in previous empirical evidence like product and process innovations or patents are not available in our database.

5 See, for example, Busom (2000), Lach (2002), González et al. (2005), or Czarnitzki et al. (2007).

6 Around 16% of all non‐Spanish partners involved in awarded projects belong to Germany. Italy accounts for 15%, the United Kingdom for 13% and France for 9%. Partners from Greece, Poland, Portugal and the Netherlands are present in around 5% of foreign participations.

7 The information is considered as a pool given that most firms only have one application in this sample.

8 The fixed effect (FE) estimator can also be used. This method allows for unbiased estimates in the presence of correlation between independent variables and unobservable firm‐specific characteristics. However, we prefer to show the results obtained using an RE model for two reasons: first, when we repeat the regressions using an FE estimator, the parameters of interest keep their signs and significance; second, most of the variation in our data is in the cross‐section dimension and the FE estimator eliminates useful inter‐firm variation (see Hu et al., 2005).

9 As usual, to avoid the problem generated by zeros when logs are taken, we use the transformation: log (k+1).

10 Note that, although the average duration of a project is around 24 months, the phase of negotiation with the European Commission before the awarding could also take several months.

11 Kaiser and Kuhn (2012) also investigate the time pattern in the impact of subsidised Danish RJV on technological output measured by the number of patent applications. They obtain evidence of a positive effect that appears both instantaneously and with lags of up to three years.

12 Specifically, we use the predicted value of “intangible fixed assets per employee” from equation (1) as an instrument of the observed ratio in equation (2).

13 We have also performed estimates of the equation without including the intangible assets as an explanatory variable. The results show that, even in this case, treatment variables are insignificant.

14 Empirical evidence shows that RJVs have a clear positive effect on technological capabilities of large firms although there is no general accepted conclusion about the economic impact (Branstetter and Sakakibara, 2002; Scott, 2003).

Additional information

Notes on contributors

Ascensión Barajas

Ascensión Barajas is a member of the Unit of Impact Assessment at CDTI.

Elena Huergo

Elena Huergo is Associate Professor of Economic Analysis at Complutense University of Madrid.

Lourdes Moreno

Lourdes Moreno is Associate Professor of Economic Analysis at Complutense University of Madrid.