Abstract
The standard indicators used to compare cross-country innovation are in the Global Competitiveness Report (GCR). But there are problems with aggregation and response bias with these largely self-reported measures (Hollanders and van Cruysen, 2008).
We propose a theory-based metric using Data Envelopment Analysis which corrects for sample bias and considers returns to scale. The derived ranking compares well to components of the GCR. Moreover, in second-stage estimations, our corrected efficiency score correlates well with standard Growth Theory indicators.
Acknowledgement
This article is partly granted by Innovation Program of the Chinese Academy of Social Sciences (CASS) under the project ‘Strategy and Policy analysis of Science and Technology’.
Notes
1 Qatar, Singapore and the UAE top the ‘Government procurement of high-tech equipment’ list but Switzerland, Japan and Finland top the ‘Private R&D spending’ list.
2 Differences in the competitiveness of the BRICS are highlighted in the 2013 GCR (2012–2013) where of all the BRICS countries, only China is viewed as competitive (see ‘heat-map’ p. 12).
3 Where the DEA considers returns to scale and bootstraps estimates (see Simar and Wilson, Citation2002).
4 The flexibility of our method (‘output-oriented’) allows for the inclusion of other inputs. Both ‘output-oriented’ and ‘input-oriented’ versions give comparable measures for technical efficiency and eventual ranking scores when CRS exist (Färe and Knox Lovell, Citation1978; Coelli, Citation1996).
5 For a more detailed discussion of the second-stage set-up and results, see Cai and Hanley (Citation2012).