Innovation rankings: good, bad or revealing?

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.

Keywords:

• Data Envelopment Analysis
• efficiency indicators
• Global Competitiveness Report

JEL Classification:

• C610
• C140
• O380

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, 2002).

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, 1978; Coelli, 1996).

⁵ For a more detailed discussion of the second-stage set-up and results, see Cai and Hanley (2012).