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The impact of economic crisis on R&D convergence in Romania

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  • Zizi Goschin
  • Steliana Sandu
  • Georgiana Gloria Goschin

Abstract

Research and development (R&D) is an important driver of productivity, competitiveness and economic growth, both nationally and regionally. In Romania all national development strategies acknowledged R&D as a priority sector, but the territorial component of the national innovation system is still underdeveloped. Moreover, research and development activity might be among the factors accountable for the increasing regional economic disparities, as the territorial distribution of its potential and performance is extremely unbalanced, the capital region (Bucharest-Ilfov) concentrating over half of R&D endowment. Romania is still lacking a strong regional R&D policy to address such disparities and the recent economic crisis brought about new hardships on the Romanian innovation system. Following a significant rise in research and development funding prior to the crisis, R&D intensity declined from 0.58 % in 2008 la 0.38 % in 2014, placing Romania at the bottom of European Union hierarchy. The convergence of the regional R&D and innovation system is as an essential component of successful regional development because, on the one hand, it provides a key asset to improve local economic competitiveness and, on the other hand, facilitates cohesion in the social sector. In this context our paper explored the convergence patterns of R&D in Romania over 1995-2014 and several subperiods, with a focus on the recent economic crisis, applying the 'sigma' and "beta" convergence methods, as introduced by Barro and Sala-i-Martin (1995). We used county level (NUTS3) data provided by the National Institute of Statistics. The diagnostics for spatial dependence have been performed, but Moran's I test for errors could not reject spatial randomness (on all time spans considered), therefore classic OLS model has been applied as the best fit for our data. We found a discontinuous sigma convergence trend, with some temporary periods of divergence that disrupted the convergence process, and conditional beta convergence over 1995-2014. When exploring the relevant subperiods of this time span, the results indicated absolute (unconditional) beta convergence until 2008, but no evidence of either convergence or divergence afterwards. The annual average speed of convergence declined from 6.97% over 1995-2000 to 2.65% over 2000-2008. Sigma convergence has been also reversed during the crisis, but seems to have resumed in the last couple of years. Our findings clearly show the disruptive impact of the economic crisis on the convergence path, from the perspective of both sigma and beta technique. The persistence of high R&D regional inequalities and low convergence calls for adequate policies, able to stimulate the regional innovation potential and underpin faster development of the Romanian regional research and innovation system.

Suggested Citation

  • Zizi Goschin & Steliana Sandu & Georgiana Gloria Goschin, 2016. "The impact of economic crisis on R&D convergence in Romania," ERSA conference papers ersa16p499, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa16p499
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa16/Paper499_ERSA2016.pdf
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    References listed on IDEAS

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    Cited by:

    1. Babucea Ana-Gabriela & Răbonțu Cecilia-Irina, 2017. "The Regional R&D Activity in Romania – A Perspective Post-EU Accession," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 66-72, December.

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    More about this item

    Keywords

    research and development; sigma and beta convergence; Romania;
    All these keywords.

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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