The New EU 2020 Innovation Indicator: A Step Forward in Measuring Innovation Output?

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The New EU 2020 Innovation Indicator: A Step Forward in Measuring Innovation Output? Jürgen Janger, with Petra Andries, Machteld Hoskens, Christian Rammer and Torben Schubert Contact e-mail: juergen.janger@wifo.ac.at

Motivation Longstanding empirical difficulties in appropriately measuring innovation output EC 2013: New EU output indicator to complement EU 2020 headline input target (R&D intensity): on its own, input indicator to measure EU standing as most competitive knowledge-intensive economy may put focus on unproductive R&D spending Use for policy advice: Does the EU 2020 indicator measure innovation output adequately and in an unbiased way?

Public return on innovation Innovation Measurement Input Innovative activities Output (Degree of novelty of different types of innovation) Commercial sucess Impact (of innovation on society&economy) Diffusion Outcome (Economic effect of innovation on firms)

Output Measurement Different types of innovations (product, process, marketing, organisational) - to which degree do they change the existing radical vs. incremental Object and subject-based indicators: Improved technical characteristics at the level of individual innovations: Technometric indicators are ill-suited for national comparisons; service sector innovation not covered Survey-based (CIS) measures at firm level ( new to market ) no objective benchmark In practice, output measurement mostly relates to capability of creating new codified technology/knowledge patents as a proxy of output (pre-output) But many problems with patent indicators - output measurement in terms of novelty/quality remains dissatisfactory

Outcome Measurement Economic effects of innovation: increased productivity through higher output in wake of higher quality or new product/ cost savings more value added/higher market share; or merely staying abreast with competition Not clear that radical vs incremental innovations makes a difference for economic benefits (Saviotti and Metcalfe, 1984, Kline and Rosenberg, 1986) e.g. CIS indicator sales share of products new to the market/world We suggest looking at outcomes at sectoral level: Dosi (1988) notes that industrial structure is endogenous to innnovative activity Economic developments at firm level may lead either to structural change or to structural upgrading: growing share of industries with high innovative/knowledge intensity vs. shortening distance to frontier within industry, moving to more innovation-intensive industry segments

Innovation outcomes at the industry level Innovation outcomes at the firm level 1. Improving existing product/process or 2. Introducing new product in comparison with competitors, leads to: Costs unchanged or decreased Market share Value added Quality unchanged or increased Market share Value added Increased value added Structural change towards higher innovation-intensity industries (Share of innovation-intensive industries in total value added increases) Structural upgrading within industries moving to higher innovationintensity segments within industries Climbing the quality ladder Moving closer to the frontier

Change vs. upgrading: is it relevant? Structural upgrading certainly very relevant: A main competitive strategy vs low-cost competitors (Bloom et al., 2011) Reflects increased path dependency of technological change (Jones, 2009, Dosi and Nelson 2010) Or offsetting maturation in older industries (Ghosal and Nair-Reichert, 2009) See concept of quality ladder in trade literature (Grossman-Helpman, 1991) and empirical work Innovation outcome measurement should try to reflect both channels change and upgrading

The EU output indicator Composite indicator, four components Patent indicator (PCT): number of EPO-PCT patent applications per billion GDP Employment share of knowledge-intensive sectors (KIA) Employment share of fast-growing firms in innovative, knowledge-intensive sectors (DYN) Average of i) contribution of high-tech and medium-high-tech products to the trade balance (GOOD) and ii) share of knowledge-intensive services exports (SERV)

EU output indicator cont d Capability indicator: focuses on international markets Three others: innovation, knowledge-intensity of sectors/exports result of international averaging no country specific values: high innovation output = high share of certain sectors International fragmentation of value chains distorts change indicators in particular in manufacturing (Shrolec, 2007) Financial services count as knowledge-intensive No indicators on upgrading if country performs well in less innovation intensive sector mostly ignored

Indicators for upgrading Share of exports in top quality segment of an industry Based on (actual, product-specific) unit values; several methodologies exist (E.g. Vandenbussche 2014, Janger et al., 2011) Manufacturing only; problem with small countries (e.g. Luxemburg, Malta) Business sector R&D intensity corrected for industrial structure, relative to a group of benchmark countries (Reinstaller Unterlass, 2012) Positive values for above-average R&D intensity Not an outcome indicator strictly speaking, but weighting indicator for change indicators Position on value chain in terms of knowledge-intensity

Luxembourg Hungary Czech Republic Poland Slovakia Romania Germany United Kingdom Estonia Malta Slovenia Spain Netherlands Ireland Denmark France Sweden Croatia Greece Austria Belgium Finland Italy Cyprus Bulgaria Lithuania Portugal Latvia Luxembourg Romania Poland Slovakia Hungary Czech Republic Germany Croatia United Kingdom Austria Netherlands Malta Lithuania Ireland Estonia Denmark Slovenia Portugal France Spain Bulgaria Italy Greece Belgium Sweden Finland Latvia Cyprus -15-10 -5 0 5 10 15 20 25-5 -3-1 1 3 5

Tentative empirical results Countries which do well in both change and upgrading do even better Countries which don t do well in either do even worse Countries good in change, bad in upgrading systematically favoured by EU output indicator Countries good in upgrading, bad in change systematically underrated Further research necessary alternative indicators

Conclusions Measuring outputs and outcomes is important (austerity ): the EU indicator is a welcome proposal However, fails to capture relevant dimensions of outcomes: favours structural change towards a specific set of sectors Clash with smart specialisation initiatives and may lead to impression that increased spending on innovation has no outcome Differentiate innovation strategies by change/upgrading (e.g., Portugal vs. Hungary) Further research necessary

References Bloom, N., Draca, M., Reenen, J.V., 2011. Trade Induced Technical Change? The Impact of Chinese Imports on Innovation, IT and Productivity. National Bureau of Economic Research Working Paper Series No. 16717Dosi, G., 1988. Sources, Procedures, and Microeconomic Effects of Innovation. Journal of Economic Literature 26, 1120 1171 European Commission, 2013. Communication from the Commission to the European Parliament, the council, the European Economic and Social Committee and the Committee of the Regions. Measuring innovation output in Europe: towards a new indicator. SWD(2013) 325 final. Ghosal, V., Nair-Reichert, U., 2009. Investments in modernization, innovation and gains in productivity: Evidence from firms in the global paper industry. Research Policy 38, 536 547 Grossman, G.M., Helpman, E., 1991. Quality ladders in the theory of growth. The Review of Economic Studies 58, 43 61 Janger, J., Hölzl, W., Kaniovski, S., Kutsam, J., Peneder, M., Reinstaller, A., Sieber, S., Stadler, I., Unterlass, F., 2011. Structural Change and the Competitiveness of EU Member States. WIFO, Vienna. Jones, Benjamin F. The burden of knowledge and the death of the Renaissance man : is innovation getting harder? The Review of Economic Studies 76, Nr. 1 (2009): 283 317. Kline, S.J., Rosenberg, N., 1986. An overview of innovation. The positive sum strategy: Harnessing technology for economic growth 275, 305. Reinstaller, A., Unterlass, F., 2012. Comparing business R&D across countries over time: a decomposition exercise using data for the EU 27. Appl. Econ. Lett. 19, 1143 1148. doi:10.1080/13504851.2011.615724 Srholec, M., 2007. High-tech exports from developing countries: A symptom of technology spurts or statistical illusion? Rev. World Econ. 143, 227 255. Vandenbussche, H., 2014. Quality in Exports. Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission