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Abstract
Brandsma A. and Kancs d’A. RHOMOLO: a dynamic general equilibrium modelling approach to the evaluation of the European Union's R&D policies, Regional Studies. European integration changes the prospects of regional economies within the member states of the European Union in many ways. Cohesion Policy is the European Union's instrument to influence and complement the efforts made at the national level to ensure that the gains of economic integration reach everyone, and there are no regions left behind. This paper presents and applies a spatial general equilibrium model RHOMOLO to assess the impact of regional policy in the European Union. The presented simulation results highlight strengths of the approach taken in RHOMOLO in handling investments in research and development (R&D), infrastructure and spillovers of investments in the innovation capacity of the regions, both of which cannot be captured by models in which the spatial structure is not present.
Brandsma A. and Kancs d’A. RHOMOLO：一个评估欧盟研发政策的动态一般均衡模型，区域研究。欧盟整合，以诸多方式改变欧盟成员国内的区域经济前景。凝聚政策，是欧盟影响、并补充在国家层级上力图确保每人皆能分享经济整合的果实、且没有任何区域被遗落的政策工具。本文呈现、并应用空间一般均衡模型 RHOMOLO ，对欧盟区域政策的影响进行评估。本文所呈献的模拟结果，强调 RHOMOLO 所採取的方法，在处理研发（R&D）与基础投资，以及区域创新能力投资的外溢方面的优势，而上述两者皆无法以不具备空间结构的模型捕捉之。
Brandsma A. et Kancs d’A. L’évaluation des politiques de l'Union européenne en matière de R et D: la méthode de modélisation en équilibre général dynamique RHOMOLO, Regional Studies. L'intégration européenne modifie de manières différentes les perspectives d'avenir des économies régionales des pays-membres de l'Union européenne. La politique de cohésion constitue l'outil de l'Union européenne qui a pour objet d'influencer et de compléter les efforts faits au niveau national afin d'assurer que les gains de l'intégration économique s'avèrent avantageux pour tout le monde, et que personne n'a du retard. Ce présent article cherche à présenter et à appliquer le modèle d’équilibre général spatial RHOMOLO pour évaluer l'impact de la politique régionale dans l'Union européenne. Les résultats de simulation presentés ici mettent en relief les atouts de la méthode employée par RHOMOLO pour traiter les investissements dans la recherche et le développement (R et D), l'infrastructure et les retombées des investissements dans la capacité d'innovation des régions. Les modèles au sein desquels il manque une structure spatiale ne peuvent capter ni l'un, ni l'autre.
Brandsma A. und Kancs d’A. RHOMOLO: ein Ansatz für ein dynamisches allgemeines Gleichgewichtsmodell zur Bewertung der F&E-Politik der Europäischen Union, Regional Studies. Durch die europäische Integration ändern sich die Aussichten der regionalen Ökonomien innerhalb der Mitgliedstaaten der Europäischen Union auf vielerlei Weise. Die Kohäsionspolitik ist das Instrument der Europäischen Union zur Beeinflussung und Ergänzung der Bemühungen auf nationaler Ebene, um sicherzustellen, dass der Nutzen der wirtschaftlichen Integration jeden erreicht und keine Regionen zurückbleiben. In diesem Beitrag wird das räumliche allgemeine Gleichgewichtsmodell RHOMOLO zur Untersuchung der Auswirkung der Regionalpolitik in der Europäischen Union vorgestellt und angewandt. Die vorgestellten Ergebnisse der Simulation verdeutlichen die Stärken des von RHOMOLO verfolgten Ansatzes beim Umgang mit Investitionen in Forschung und Entwicklung (F&E) und in die Infrastruktur sowie mit den Übertragungseffekten der Investitionen in die Innovationskapazität der Regionen, welche sich beide nicht mit Modellen erfassen lassen, in denen die räumliche Struktur nicht vorhanden ist.
Brandsma A. y Kancs d’A. RHOMOLO: un planteamiento de modelo dinámico de equilibrio general para la evaluación de las políticas de I+D de la Unión Europea, Regional Studies. A través de la integración europea se cambian de muchas maneras las perspectivas de las economías regionales en los Estados miembros de la Unión Europea. La política de cohesión es el instrumento de la Unión Europea que orienta y amplía los esfuerzos realizados en el ámbito nacional con el objetivo de garantizar que las ventajas de la integración económica lleguen a todos y ninguna región quede rezagada. En este artículo presentamos y aplicamos el modelo espacial de equilibrio general RHOMOLO para evaluar el efecto de la política regional en la Unión Europea. Los resultados presentados de la simulación ponen de relieve las ventajas del planteamiento de RHOMOLO en lo que respecta a la gestión de las inversiones en investigación y desarrollo (I+D) y en la infraestructura, así como de los efectos indirectos de las inversiones en la capacidad de innovación de las regiones, los cuales no pueden ser captados por modelos en los que no esté presente la estructura espacial.
Acknowledgements
The authors acknowledge the helpful comments from and valuable contributions made by Stefan Boeters, Steven Brakman, Johannes Broecker, Leen Hordijk, Artem Korzhenevych, Hans Lofgren, Philippe Monfort, Mark Thissen, Charles van Marrewijk, Renger Herman van Nieuwkoop, Damiaan Persyn, Attila Varga; the participants at the European Economic Association and Econometric Society conferences in Glasgow, Oslo, Malaga and Gothenburg; as well as the participants at the seminars and workshops of the European Commission. The authors would like to thank two anonymous reviewers as well as editor of the special issue for their suggestions and comments. The authors are solely responsible for the content of the paper. The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. The same applies to Croatia, which joined in 2013.
2. RHOMOLO = Regional HOlistic MOdeLO.
3. See Brandsma et al. (Citation2015) for a formal description of the latest version of the RHOMOLO model.
4. Labour mobility is introduced through a labour market module which extends this core version of the model with a more sophisticated specification of the labour market. This is described by Brandsma et al. (Citation2014).
5. In the model the regional unemployment rates also enter the migration problem of workers.
6. The authors refer to the 2013 version of RHOMOLO, which was used for simulations presented in this paper. In the next updates of the base year RHOMOLO will be extended to include also Croatia.
7. Currently undergoing extension of the innovation module in RHOMOLO with additional features beyond R&D includes two elements. First, European Commission-based regional patent statistics and citations offer valuable information on technological proximity across regions in Europe. Second, the inclusion of the micro-estimated data from the Community Innovation Survey is used to identify a broader set of regional innovation features – closely related to the policy domains identified in the current taxonomy of Cohesion Policy investments.
8. This is true for all five broad categories, but in particular for interventions categorized under RTDI. Some of the 123 expenditure lines can be associated with improving the public research infrastructure; some others with augmenting the regional knowledge stock as such or with creating incentives for private firms to invest more in R&D. A more precise delineation within the RTDI category would not be of much help either, because the stages of research, development, diffusion and use are known to be highly interdependent.
9. The split between the support to RTDI and human capital development is not very clear-cut. There are also overlaps with aid to the private sector provided under Cohesion Policy, a residual category which is as large as the RTDI part itself, and with the separate category of technical assistance.
10. This simplification means that the link between publicly funded research and the productivity effects of Cohesion Policy interventions is not fully explored in the simulations. In particular, the contribution of the structural and investment funds to increasing the absorption and innovation capacity at the regional level would deserve greater attention in future evaluations of Cohesion Policy.
11. See, for example, Di Comite and Kancs (Citation2015) for a discussion of alternative approaches for implementing and modelling R&D policies.
12. Firm-level studies have estimated the size of productivity elasticity associated with R&D investment ranging from 0.01 to 0.32, and the rate of return to R&D investment between 8.0% and 170.0% (see Mairesse and Sassenou, Citation1991; Griliches, Citation2000; and Mairesse and Mohnen, Citation2001, for surveys).
13. For further details and assumptions of the RTDI scenario construction, see Di Comite and Kancs (Citation2015).
14. For the purpose of simulations presented in the paper, all infrastructure expenditures are aggregated into one category and consequently modelled uniformly as transport infrastructure improvements. In reality, not all ECP expenditures are designed and implemented to improve transport infrastructure, but the dividing lines are difficult to maintain when looking at the actual expenditures across NUTS-2 regions. By far the largest part of the ECP infrastructure expenditures overall, however, is allocated to transport infrastructure (78.1%) (European Commission, Citation2014).
15. For further details and assumptions of transport infrastructure scenario construction, see Kancs (Citation2013).
16. All simulation results reported in this paper were produced using the 2013 version of the RHOMOLO model. See Brandsma et al. (Citation2015) for a formal description of the latest version of the RHOMOLO model.
17. Absorptive capacity is not modelled explicitly in RHOMOLO, however there is a maximum of policy support that can be absorbed per year (0.5% of GDP). In addition, market imperfections, e.g. in labour and capital mobility, may lead to decreasing returns to public investment in the short run.
18. Due to dimensionality issues, this effect is not shown graphically.