• Medientyp: Elektronischer Konferenzbericht
  • Titel: The impact of economic crisis on R&D convergence in Romania
  • Beteiligte: Goschin, Zizi [VerfasserIn]; Sandu, Steliana [VerfasserIn]; Goschin, Georgiana Gloria [VerfasserIn]
  • Erschienen: Louvain-la-Neuve: European Regional Science Association (ERSA), 2016
  • Sprache: Englisch
  • Schlagwörter: R11 ; sigma and beta convergence ; research and development ; Romania ; C51
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  • Beschreibung: 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 ...
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