Innovation performance and R&amp;D expenditures in Western European regions: Divergence or convergence?

Bednář, Pavel; Halásková, Martina

doi:10.14254/2071-8330.2018/11-1/16

Cited by 21 publications

(14 citation statements)

References 21 publications

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“…DEA and structural modelling were combined, where the DEA efficiency scores were used in the second step of the structural modelling (which is sometimes criticized in the literature; please refer to [34]). In another study, 178 NUTS-2 regions (for Western Europe) were compared using a mixed spatial autoregressive model and difference in differences (DID) approach (years included were 2007, 2009, and 2011) [35]. The results indicated that an innovation intensity divergence exists between the examined regions.…”

Section: Related Literature Overviewmentioning

confidence: 99%

“…Each row in both matrices represents the DMU j, with x o = (x 1o , x 2o , ..., x mo ) and y o = (y 1o , y 2o , ..., y so ) , and x o ≥ 0, x o 0 and y o ≥ 0, y o 0. The slacks-based measure (SBM) model was developed in [34,35] and is the approach used in this study. The reason for this is the fact that it has advantages when compared to the most used models, namely the Charnes-Cooper-Rhodes (CCR) and Banker-Charnes-Cooper (BCC) models; the SBM is an additive model with unit invariance properties and the possibility of being non-oriented and non-radial.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

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R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

Škrinjarić

2020

Sustainability

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Measuring the efficiency of research and development (R&D) expenditure and innovation policy has gained attention in recent years. This research examines the efficiency of 29 selected European countries for the period ranging from 2007 to 2017 in achieving and obtaining R&D goals. The methodology applied is the data envelopment analysis approach with the inclusion of the missing data approach. The contributions of this research include the following: dynamic analysis is conducted to track changes of (in)efficiencies over time; the decomposition of the efficiency is done by separating the main variables of interest into the private, higher education, and government sectors; and the robustness of the results is evaluated, which is often ignored in the literature. The results of the analysis are discussed with possible directions for inefficient countries. The rankings provided in the empirical part of the study confirm previous findings on disparities between the European countries with respect to innovation and the R&D sector.

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Section: Related Literature Overviewmentioning

confidence: 99%

Section: Data Envelopment Analysismentioning

confidence: 99%

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

Škrinjarić

2020

Sustainability

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“…For focused analyses, see e.g. Bednář and Halásková (2018), Prokop and Karbowski (2018) or Romer (1990).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The dependent variable ( ) exhibits strong positive spatial autocorrelation when tested using the Moran's I statistic (for definition and application examples, see e.g. Bednář and Halásková, 2018). However, the spatio-temporal semivariogram (STSV) as per equation (3) can be used for a convenient description and visualization of both spatial and temporal variability aspects in observed data.…”

Section: Datamentioning

confidence: 99%

GDP per capita in selected EU countries: Economic growth factors and spatio-temporal interactions examined at the NUTS2 level

Formánek¹

2019

Journal of International Studies

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This article evaluates the macroeconomic policy tools at which central authorities may focus in times of economic slowdown and/or to boost economic cohesion. For this purpose, a complex spatio-temporal regression model is provided, which controls for spatial and temporal dependencies in data, as well as individual effects and relevant regional macroeconomic conditions. Empirical findings firmly favors GDP-boosting policy actions oriented towards supporting knowledge-based economic activities: enhancing research and development, improving labor force structure towards specialized professional, scientific and technical activities. In contrast, transportation infrastructure (proxied by motorway density) does not enact statistically significant improvement in GDP growth. In this article, regional macroeconomic growth dynamics and its key constituent factors are analyzed using the sample of 11 EU member states ), observed annually (from 2010 to 2016) at the NUTS2 level. Substantial effort is directed towards verification of model robustness and the corresponding validity of the conclusions drawn.

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“…The problem of ensuring economic security of the country is one of the key aspects in the macroeconomic policy of developed and developing countries of the world (Bednar and Halaskova, 2018;Bhowmik, 2018;Fashina et al, 2018;Lyeonov et al, 2018;Milovic and Jocovic, 2017;Nguedie, 2018;Soylu et al, 2018;Vasylieva et al, 2018). The economic security of the state characterizes the condition of the national economy, which protects national interests, resistance to internal and external threats, the ability to develop and protect the vital interests of people, society, and the state.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of Innovation Activity Funding as the Driver of the State's National Economic Security

Zakharkina¹,

Myroshnychenko²,

Smolennikov³

et al. 2018

Montenegrin Journal of Economics

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Purpose. The article is devoted to an analysis of the impact of innovative enterprises activity on ensuring the indicators of state economic security. The main emphasize was made on the innovative component analysis of the economic security in Ukraine. Place and role of stimulating innovative activity to achieve sustainable socioeconomic development and improve competitiveness of the economy is analyzed in the article. Methodology. In the article economic security of Ukraine analyzed by using two methodological approach: Methodological Recommendations on calculating the level of economic security of Ukraine, approved by the order of the Ministry of Economic Development and Trade of Ukraine and the Global Competitiveness Index. Findings. The authors determined which sectors innovation activity can increase the growth rates of economic security and which state support methods should be used to maximize the growth of innovation activity. The conducted research made it possible to find out that the activation of innovation activity as a factor in the economic security formation of the state, which operates in developed countries, is not used properly in Ukraine. Such trends in innovation development of Ukraine are connected, first of all, with low (least critical) level of science funding by the state (primarily applied character, innovation and technology transfer) and low level of funding by economic entities themselves.

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Innovation performance and R&D expenditures in Western European regions: Divergence or convergence?

Cited by 21 publications

References 21 publications

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

GDP per capita in selected EU countries: Economic growth factors and spatio-temporal interactions examined at the NUTS2 level

Efficiency of Innovation Activity Funding as the Driver of the State's National Economic Security

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