RHOMOLO: A Dynamic General Equilibrium Modelling Approach to the Evaluation of the European Union's R&amp;D Policies

Brandsma, Andries; Kancs, d’Artis

doi:10.1080/00343404.2015.1034665

Cited by 26 publications

(15 citation statements)

References 12 publications

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“…In the longer run, investing in the innovation activity encourages knowledge-based economy, drives demand for high-skilled, educated workers and eventually brings a country on the higher growth path. However, a comprehensive assessment of these effects is only possible within general-equilibrium models that capture vertical and horizontal linkages between firms, which is not possible to account for in micro-econometric studies, such as the one presented in this paper (Brandsma and Kancs, 2016). Hence aligning our results with macro results is indeed important for enhancing our understanding of the employment effect of innovation and it sets a promising avenue for the future research.…”

Section: Conclusion Policy Recommendations and Limitationsmentioning

confidence: 91%

Employment effect of innovation

Kancs

Siliverstovs

2019

Empir Econ

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This publication is a Technical report by the Joint Research Centre (JRC), the European Commission's science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication.

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Section: Conclusion Policy Recommendations and Limitationsmentioning

confidence: 91%

Employment effect of innovation

Kancs

Siliverstovs

2019

Empir Econ

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“…Second, in contrast to the system of models approach to R&D as proposed by Varga (2011) for studies at the regional and the EU macroeconomic levels, this paper keeps R&D within one model. Finally in contrast to the RHOMOLO approach (Brandsma and Kancs, 2015) which uses one model for all EU countries, this paper proposes a country specific model for Poland (POLTERM).…”

Section: Fig 1 Randd Intensities In 2011 and Targets For 2020mentioning

confidence: 99%

“…Estimates for the rate of return on R&D stock ( ) in the literature vary from 8.0 to 170.0% (Brandsma and Kancs, 2015: Mairesse and Sassenou M., 1991: Pakes and Schankerman, 1978. Kolasa (2008) investment, whereas GDP movements depend both on changes in the TFP itself and on changes in capital stock and employment, which in turn depend on many factors apart from changes in R&D stock.…”

Section: Modelling Randd In Poltermmentioning

confidence: 99%

R&D in a post centrally-planned economy: The macroeconomic effects in Poland

Zawalińska

Tran

Płoszaj

2018

Journal of Policy Modeling

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Half a century of centrally planned policy in the Central and Eastern European countries resulted in outdated technologies, inefficient allocation of resources and low productivity. Following the end of communism there was a fifteen year process of transition which ended in 2004 with eight post-communist countries joining the European Union (EU) of which Poland was the largest. As part of the EU these countries now face the challenge of the common EU strategy Europe 2020, which has set the target of achieving R&D expenditure to GDP ratio (called the R&D intensity) of 3% by 2020 for the Union as a whole in an effort to increase the competitiveness of the region. Poland, like the other post-communist countries, faces a lower target of R&D intensity, set at 1.7%. Nevertheless, the challenge is immense, since the country is still at only half that level and has little experience in developing policies to help achieve it. In this paper we tested two possible policy options to achieve the target: (1) to increase government expenditures on R&D and; (2) to provide tax relief on R&D to businesses. The method applied to assess the options is a recursive dynamic computable general equilibrium (CGE) model for Poland with an explicit link between productivity and R&D stock. The results show that achieving the R&D intensity target via the use of tax relief is 2.5 times more costly to the government budget, but it has a greater impact on the economy in terms of a higher GDP growth. Tax relief proved efficient in the short run while in the long run the government expenditure policy provides better value for money.

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“…Unfortunately, the effects of the previous programming period regarding the intervention by means of structural funds did not always lead to the expected results [4][5][6]. This demonstrates the need to assess the previous actions and to point out new and more efficient solutions [7,8]. This policy acts in very different local contexts and aims at very heterogenous economic and social regional contexts.…”

Section: Introductionmentioning

confidence: 99%

The Effects of the Cohesion Policy on the Sustainable Development of the Development Regions in Romania

et al. 2018

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The objective of this study was to characterize the development regions in Romania and to measure spatial imbalances, starting from the national and the European Union aspiration to promote more economic and social policies adapted to the different regional particularities. For this purpose, we conducted a multifactorial analysis of the sustainability of the development regions in Romania at NUTS II level by constructing a synthetic index of socio-economic development for the regions that appreciate sustainability and have accepted structural and cohesion funds. The multi-criteria synthetic index was obtained by aggregating several sub-indices (economy, health, education, public utilities, and living standards). We used cluster analysis to identify patterns of regional development in Romania over time. For 1998 and 2006, the same cluster structure was obtained. However, due to economic and social changes that occurred after 2006 (negative impact of the global financial crisis as well as the positive impact of EU funds), in 2016, we recorded another structure of clusters, except in the Bucharest-Ilfov region which continues to present a number of unique features. In addition, we show that the polarized regional development model is increasingly strengthening and the network of urban agglomerations needs to be territorially balanced to boost their ability to “export” wealth.

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RHOMOLO: A Dynamic General Equilibrium Modelling Approach to the Evaluation of the European Union's R&D Policies

Cited by 26 publications

References 12 publications

Employment effect of innovation

Employment effect of innovation

R&D in a post centrally-planned economy: The macroeconomic effects in Poland

The Effects of the Cohesion Policy on the Sustainable Development of the Development Regions in Romania

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