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Title: Essays on growth and technological change induced by small, young innovators.
Other Titles: Essays on growth and technological change induced by small, young innovators.
Authors: Delanote, Julie
Issue Date: 30-Sep-2014
Abstract: This doctoral dissertation elaborated upon the understanding of the growth potential of small young innovators and looked into an important policy tool, selective R&amp;D subsidies that are often used to trigger innovation activities of firms. A focus on small young innovators is not only relevant in terms of evaluating the current policy stipulations of the European Commission (EC), but also adds to the academic literature that in general increasingly emphasizes the importance of these firms in terms of technological performance and economic growth. As measuring policy impacts remains challenging, the importance of evaluation methods was also considered by dedicating a separate chapter to an alternative methodology to analyze subsidy effects. In line with the increased focus on specific subsets of innovators, a first chapter of this dissertation looked into the growth opportunities of small young innovators, and more specifically of the ”Young Innovative Companies”, the so-called YICs, as fostered by the EC. This analysis shows evidence that these firms, being small, young and intensively engaged in innovation activities grow more than other firms, both in terms of employment and in terms of sales. In addition, the study presented in this chapter confirms the complementarity of the factors size, age and R&amp;D intensity as incorporated in the YIC definition as the latter grow more than other subsets of firms that have less strict innovation criteria. In general, these results confirm the expectations on growth of YICs. The additional findings on complementarity point to the importance of carefully defining subsets of firms. In addition, as a main goal of policies is to foster growth, this study also seems to support the reinforcement of state aid programs toward YICs.Although the growth figures are all supportive for YICs, one might wonder how YICs perform over the growth distribution. Analyzing this by means of quantile regressions shows that YICs grow especially faster than other, already fast growing firms. This result is fully in line with expectations on these firms. However, expectations are also that these firms would, on the other end of the tail, perform much worse than the other slow growers in the economy due to the presumed heterogeneity within this class of firms. Nevertheless, this study showed that, although YIC growth is variable over different quantiles, YICs do not seem to perform significantly worse than other firms at any point of the distribution of firm growth. This suggests that they are on the one hand high performers and on the other hand, do not ’fall harder’ than other players in the economy.Following upon this, a next chapter assessed to what extent the recent orientation of R&amp;D subsidies towards small young, stand-alone high-tech firms is warranted by assessing both input and output additionality effects of subsidies on these firms. This chapter not only analyzed these effects for the independent small young innovators but compared the effects on these firms to the effect on other small young innovators by defining some additional firm categories: small young independent low-tech firms and their group, i.e. non-independent, counterparts. Matching results revealed that full crowding-out with regard to public funding can be rejected for all firm types studied, suggesting that public funding seems to attain its goals in terms of innovation input. However, comparing the treatment effects of the different firm types in a regression framework suggested that treatment effects of NTBFs are actually highest. The latter finding is in line with stipulations of policy makers. Nevertheless, this also suggests that previous estimations of innovation policy impacts might have been partly misleading as in general, no distinction between preferential firm profiles in policy schemes have been made. Next to an assessment of the additional input in R&amp;D triggered by subsidies, this study looked into the ability of subsidized firms to generate additional output. The analysis showed that for nearly all firm categories, both private R&amp;D and subsidy induced R&amp;D lead to new patent applications. In addition, comparing the effects of publicly induced R&amp;D and private R&amp;D does not point to a lower or higher productivity of subsidy induced R&amp;D as compared to private R&amp;D. These findings further suggest that, at least from the viewpoint of the subsidized firm itself, subsidies are not inefficiently spent.Building upon these subsidy evaluation studies, the last chapter presented an entirely new extension to both the CDM (Crépon, Duguet, Mairesse) model and the subsidy evaluation literature by incorporating subsidy evaluation in the CDM framework. The integration of input and output additionality in one framework acknowledges the inextricable nature of this process and thereby provides a new method to assess output additionality and to estimate whether subsidies entail a premium over private R&amp;D or a discount in terms of innovative output. In addition, in contrast to the majority of subsidy evaluation studies using propensity score matching, this set-up allows to make use of more detailed subsidy data allowing to take a step back from the commonly used dichotomous indicator of public subsidies. By adding to existing models in several ways, this chapter mainly draws attention to both the possibilities but also the further need to follow up upon different existing frameworks as these might be highly instrumental in follow-up research tackling new research questions.Results of this chapter indicate that, in line with the prevailing literature, subsidies trigger private R&amp;D investment and crowding-out can thus in general be rejected. In a next step, output additionality was assessed. Findings suggest that, in general, both purely private R&amp;D investment and subsidy induced R&amp;D, the latter encompassing both the subsidy received and the additional R&amp;D investment triggered by the subsidy, contribute to innovation performance at the firm level. Furthermore, the publicly induced R&amp;D does not entail a significant discount or premium relative to privateR&amp;D investmentsin terms of innovative performance. An equal productivity of publicly induced and purely private R&amp;D can thus not be rejected.In sum, the different chapters presented in this dissertation add to the innovation literature in different ways, extending upon the specific literature focusing on small young innovators, and adding to the more general subsidy evaluation literature and the papers building upon the framework set up by Crépon, Duguet and Mairesse.In terms of the literature focusing on subsets of innovators, results confirm that a refined focus might be warranted as the specific subset of YICs seems to stimulate growth and job creation, more than other firms. Building upon this, this dissertation also suggests that the reinforcement of state aid programs towards specific subsets of small young innovators might be beneficial and might help these firms to overcome some of the market failures related to innovation activities, which are acknowledged to be especially hindering the innovation activities of these firms. At least, granting R&amp;D subsidies to specific subsets of firms does seem to attain its goal in terms of fostering both innovation input and output. The inclusion of subsets in this context also has implications for policy recommendations; the increasingly postulated view that an entrepreneurial state should be built at least to some extent by specific and more refined intervention of public institutions can thus not be rejected. Next to adding evidence to the literature assessing the importance of small young innovators, this work suggests that the innovation literature, more broadly, should increasingly incorporate firm heterogeneity in its analysis as some general effects found might differ between different firm types. In the context of this dissertation for example, the majority of the subsidy evaluation literature has focused on very broad sets of firms, while only some incorporated different subsets of firms, as done in this work.Next to adding to the literature on small young innovators and the general innovation literature, this dissertation also adds to the methodologies used to evaluate policy instruments. By adding to these existing methodologies, this thesis does not only present possibilities to extend research in this respect, but also points to further opportunities to incorporate existing methods in new settings or elaborate upon new methods in order to validate (or question) existing findings in the innovation literature.<w:latentstyles deflockedstate="false" defunhidewhenused="true"  <w:lsdexception="" locked="false" priority="0" semihidden="false"  <w:lsdexceptionlocked="false"
Table of Contents: List of Tables v
List of Figures vii
1 General Introduction 1
1.1 Firm heterogeneity and economic growth . . . . . . . . . . . . . . . 2
1.2 Fostering innovation-induced growth? . . . . . . . . . . . . . . . . . 5
1.3 Overview of the different thesis chapters . . . . . . . . . . . . . . . 9
1.3.1 Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.3.2 R&D subsidies: firm and method heterogeneity . . . . . . . 10
1.3.3 Only the beginning of a roadmap . . . . . . . . . . . . . . . . 12
2 Young Innovative Companies: the new high-growth firms? 13
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.2 Theoretical background . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.1 The growth of companies . . . . . . . . . . . . . . . . . . . . 15
2.2.2 The growth of Young Innovative Companies . . . . . . . . . 17
2.3 Data and descriptive statistics . . . . . . . . . . . . . . . . . . . . . . 19
2.3.1 Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3.2 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3.3 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . 24
2.4 Empirical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.4.1 The growth of Young Innovative Companies: pooled OLS . 26
2.4.2 Quantile regressions . . . . . . . . . . . . . . . . . . . . . . . 30
2.5 Robustness checks . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.5.1 YIC growth in the short and medium term . . . . . . . . . . 37
2.5.2 Controlling for a potential survival bias . . . . . . . . . . . . 39
2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3 R&D subsidies to small young companies: should the independent and high-tech ones be favored? 45
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2 Subsidy input evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2.1 Literature review . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.2.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3 Subsidy output evaluation: the patent production function . . . . . 57
3.4 Data, variables and descriptive statistics . . . . . . . . . . . . . . . . 59
3.4.1 Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
3.4.2 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.4.3 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . 65
3.5 Estimation and results . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.5.1 Subsidy effect on small young firms . . . . . . . . . . . . . . 67
3.5.2 Further evaluation of the treatment effects . . . . . . . . . . 71
3.5.3 The effect on technological progress . . . . . . . . . . . . . . 76
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4 Incorporating innovation subsidies in the CDM framework: empirical
evidence from Belgium 83
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.2.1 Conceptual background . . . . . . . . . . . . . . . . . . . . . 85
4.2.2 Previous literature . . . . . . . . . . . . . . . . . . . . . . . . 87
4.3 Extending the CDM model: assessing output additionality of subsidies
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.3.1 Econometric implementation . . . . . . . . . . . . . . . . . . 92
4.4 Data, variables and descriptive statistics . . . . . . . . . . . . . . . . 94
4.4.1 Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.4.2 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.4.3 Descriptive statistics . . . . . . . . . . . . . . . . . . . . . . . 99
4.5 Empirical implementation and results . . . . . . . . . . . . . . . . . 100
4.5.1 Innovation inputs . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.5.2 Innovation outputs . . . . . . . . . . . . . . . . . . . . . . . . 103
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5 General Conclusion 109
Appendices 119
Overview of the different firm-types discussed in the dissertation . . . . 121
Appendix to chapter 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Appendix to chapter 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Appendix to chapter 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Bibliography 147
Publication status: published
KU Leuven publication type: TH
Appears in Collections:Department of Managerial Economics, Strategy and Innovation (MSI), Leuven

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