The present Thesis, in the form of a collection of three essays, provides a contribution to the literature on the effects of the public support to innovation activities. The first paper aims at providing a review and a critical discussion of the literature dealing with the additionality of innovation policy, that is, the net effects of the public support that would not have occurred in the absence of the policy. In particular, the paper focuses on the behavioural dimension of the additionality concept, i.e. the strategic and behavioural changes induced by the policy. In the first part, the paper argues that the behavioural dimension, though not yet clearly defined, provides a necessary complement to the input and output dimensions, when assessing innovation policies consistently with the evolutionary theory and the related innovation system perspective. In the second part, the paper organises and reviews the recent empirical works that have tried to measure, with econometric and quantitative methods, the strategic and behavioural changes induced by the policy interventions. In so doing, it presents some main methodological issues that characterise the investigation of the behavioural additionality, as well as the main behavioural changes that public support to innovation activities can induce. Starting from the framework provided in the first paper, the Thesis proposes two empirical applications. The first of these is presented in the second paper. This aims at proposing and applying a new multi-level and multi-dimensional evaluation of the additionality effects of innovation policy. The impacts of national and regional support schemes are jointly investigated (multi-level), by simultaneously analysing their input, output and behavioural additionality effects (multi-dimension). By making use of micro-data on manufacturing firms stemming from the 4th wave of the Community Innovation Survey, an empirical application of this kind of assessment is provided for two EU countries, namely Italy and Spain. To control for the selection bias, the econometric strategy is based upon a set of propensity score matching estimations of the average treatment effect on the treated (ATT). The picture of the results is quite complex. In both countries, only national policies increase R&D investment. On the other hand, their regional and national interventions induce additional innovation performances and innovation behaviours of different nature. The proposed methodology is integrated with an original, although somehow tentative, analysis of the relation between the average additionality effects of the policies and the dispersion of their impacts. With the exception of Italian regional policies, the higher is the average additionality level, the lower is found to be the polarisation of the policy effect. The third paper included in the Thesis, has a more narrow focus. It aims at identifying the extent to which regional innovation policy affects firms’ innovation behaviour. Some research hypotheses are put forward. At first, the policy support is supposed to induce relevant changes in the beneficiaries' behaviour, which can help to solve potential regional system failures. Moreover, an increasing amount of regional subsidy is expected to enhance the geographical range of the cooperation with universities and research institutes, allowing firms to interact with “global best” and more suitable research partners. These hypotheses are tested with respect to a sample of manufacturing firms located in the NUTS-2 Emilia-Romagna region of Italy, by making use of a unique dataset including information on pre-policy characteristics and post-policy behaviours. The econometric strategy is based, at first, on a set of propensity score matching estimations. The recently developed generalised propensity score method, which is suitable for a continuous treatment framework, is also employed. At first, the policy is found to enhance the competencies’ upgrading of the beneficiaries, as well as their interactions with both regional and extra-regional research organisations. Furthermore, the amount of subsidy is found to be important to extend beyond the regional borders the cooperation with research partners: over a minimum efficient scale of public funding, an increase in the subsidy enhances the propensity to cooperate with extra-regional universities and research institutes.
Evaluating the Additionality of Innovation Policy: An Investigation at Different Levels of Analysis / Marzucchi, Alberto. - (2012), pp. 1-129.
Evaluating the Additionality of Innovation Policy: An Investigation at Different Levels of Analysis
Marzucchi, Alberto
2012-01-01
Abstract
The present Thesis, in the form of a collection of three essays, provides a contribution to the literature on the effects of the public support to innovation activities. The first paper aims at providing a review and a critical discussion of the literature dealing with the additionality of innovation policy, that is, the net effects of the public support that would not have occurred in the absence of the policy. In particular, the paper focuses on the behavioural dimension of the additionality concept, i.e. the strategic and behavioural changes induced by the policy. In the first part, the paper argues that the behavioural dimension, though not yet clearly defined, provides a necessary complement to the input and output dimensions, when assessing innovation policies consistently with the evolutionary theory and the related innovation system perspective. In the second part, the paper organises and reviews the recent empirical works that have tried to measure, with econometric and quantitative methods, the strategic and behavioural changes induced by the policy interventions. In so doing, it presents some main methodological issues that characterise the investigation of the behavioural additionality, as well as the main behavioural changes that public support to innovation activities can induce. Starting from the framework provided in the first paper, the Thesis proposes two empirical applications. The first of these is presented in the second paper. This aims at proposing and applying a new multi-level and multi-dimensional evaluation of the additionality effects of innovation policy. The impacts of national and regional support schemes are jointly investigated (multi-level), by simultaneously analysing their input, output and behavioural additionality effects (multi-dimension). By making use of micro-data on manufacturing firms stemming from the 4th wave of the Community Innovation Survey, an empirical application of this kind of assessment is provided for two EU countries, namely Italy and Spain. To control for the selection bias, the econometric strategy is based upon a set of propensity score matching estimations of the average treatment effect on the treated (ATT). The picture of the results is quite complex. In both countries, only national policies increase R&D investment. On the other hand, their regional and national interventions induce additional innovation performances and innovation behaviours of different nature. The proposed methodology is integrated with an original, although somehow tentative, analysis of the relation between the average additionality effects of the policies and the dispersion of their impacts. With the exception of Italian regional policies, the higher is the average additionality level, the lower is found to be the polarisation of the policy effect. The third paper included in the Thesis, has a more narrow focus. It aims at identifying the extent to which regional innovation policy affects firms’ innovation behaviour. Some research hypotheses are put forward. At first, the policy support is supposed to induce relevant changes in the beneficiaries' behaviour, which can help to solve potential regional system failures. Moreover, an increasing amount of regional subsidy is expected to enhance the geographical range of the cooperation with universities and research institutes, allowing firms to interact with “global best” and more suitable research partners. These hypotheses are tested with respect to a sample of manufacturing firms located in the NUTS-2 Emilia-Romagna region of Italy, by making use of a unique dataset including information on pre-policy characteristics and post-policy behaviours. The econometric strategy is based, at first, on a set of propensity score matching estimations. The recently developed generalised propensity score method, which is suitable for a continuous treatment framework, is also employed. At first, the policy is found to enhance the competencies’ upgrading of the beneficiaries, as well as their interactions with both regional and extra-regional research organisations. Furthermore, the amount of subsidy is found to be important to extend beyond the regional borders the cooperation with research partners: over a minimum efficient scale of public funding, an increase in the subsidy enhances the propensity to cooperate with extra-regional universities and research institutes.File | Dimensione | Formato | |
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