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Carbon dioxide reducing environmental innovations, sector upstream/downstream integration and policy: evidence from the EU

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Abstract

Eco innovations (EI) that address climate change mitigation require pressures and knowledge from outside the firm’s and sector’s boundaries, due to the radicalness and variety of techno-organisational knowledge the economy needs to curb emissions by 90 % in the long run and 40 % in the medium run, at least according to EU targets. The role of policy as a tool that potentially tackles two externalities—innovation and environmental market failures—has been studied over the past decade. Sector integration, which is increasingly relevant for understanding the economic, environmental and innovation performances of countries, might additionally influence innovations, and it is relatively overlooked. We integrate these two perspectives to provide evidence on the adoption of EI in EU sectors over 2006–2008. Using past CO2 emission intensity as a proxy of policy stringency we find that emission intensive sectors are more likely to adopt CO2-related eco-innovations. The aforementioned results are valid for both the economy as a whole and for industrial sectors specifically. We additionally show that inter sector integration and knowledge sources matter: we do observe that sectors with more emission intensive upstream ‘partners’ eco-innovate more to reduce their CO2 footprints. The positive and significant effect of upstream emission intensity (supplier’s emission intensity) on EI is actually stronger than the effect of ‘direct’ CO2 emission intensity (policy effect).

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Notes

  1. One of the most consolidated definitions of eco-innovation defines it as the production, application or use of a product, service, production process or management system new to the firm adopting or developing it, and which implies a reduction in environmental impact and resource use (including energy) throughout its life-cycle (Kemp 2010).

  2. The literature on EI at the micro level is usually developed at the national level (Cainelli and Mazzanti 2013; Horbach et al. 2012).

  3. Lissoni and Metcalfe (1994) debate innovation diffusion and adoption issues. We note that though patents are a somewhat good proxy of innovation capacity (UCL 2014), only a fraction of inventions become marketed and diffused as innovations (OECD 2011; Johnstone 2007).

  4. The quantitative analyses below make use of the most recent and only available data at the EU level for EI concerning CO2: (1) the Eurostat sector CIS data and the (2) aggregated meso data (aggregation of similar firms into clusters) that are provided by Eurostat in the CIS Cd-ROM. Option (1) is the best given the wide EU coverage, option (2) is interesting since it extends dataset breadth. We rule out analyses on micro data from a methodological perspective. It would nevertheless be impossible to present full EU coverage due to national-based data availability and copyright issues.

  5. We stress that the sector level is the only one feasible in providing EU-wide evidence. A firm-based analysis is constrained by data availability: Innovation CIS data is mostly available to researchers only at a national level. Beyond this, there is no possibility of matching innovation and emission/value added data at the moment: micro data is protected by privacy policies and emissions data is rarely available, excluding niche case studies and specific sectors in specific countries. In addition, even emissions data is often ‘protected’ and not fully available to researchers.

  6. Represented by the CO2/value indicator as is usual in the literature (see Costantini and Crespi 2008).

  7. For direct emissions we refer to the amount of emissions directly generated by firms through their production processes. On the other hand, indirect emissions are related to the amount of emissions generated along the supply chain, mainly due to the production of intermediates needed to generate the output of a specific sector.

  8. Cainelli and Mazzanti (2013) conclude that in the specific manufacturing-services case, EI adoption seems independent upon a sector’s integration, and they stress that further research on the role of the increased integration of manufacturing-services is needed in relation to innovation and environmental performances based on micro and sector data.

  9. On NAMEA innovation and economic related issues, we refer to Costantini et al. (2012). We use 2005 to define a lag with respect to 2006–2008 (mitigating simultaneity and endogeneity) and due to data availability.

  10. A similar approach has been used in Crespi (2013).

  11. Belgium (BE), the Czech Republic (CZ), Germany (DE), Estonia (EE), Finland (FI), France (FR), Hungary (HU), Ireland (IE), Italy (IT), Lithuania (LT), the Netherlands (NL), Poland (PL), Portugal (PT), Romania (RO), Sweden (SE), Slovakia (SK).

  12. Due to missing information on either emissions data or CIS data, our potential sample of 688 observations was reduced to 448.

  13. A one-to-one sector concordance between Nace rev 1.1 and Nace rev 2 is not possible while a much better match is possible for the 4-digit level of aggregation. We build a many-to-many weighted concordance between 2-digit Nace rev 1.1 and 2-digit Nace rev 2 in which we use the number (count) of 4-digit sectors within each 2-digit sector pair as weights.

  14. This approach has many advantages. First, data are readily available and of good quality; second, the data provide a direct and easy way to interpret the measure of stringency; third, data are generally available for long-time series which allow for both within-country and between-country variations. Such measures of policy stringency might, however, be biased if part of the variation of the indicator is due to factors different from the policy itself. If, for instance, variations in the series of energy intensity data depend on an unobserved characteristic which does not relate to the real policy stringency, the result would be either an overestimation or an underestimation of the effect of the policy.

  15. The link between energy intensity and emission intensity is also relevant when considering the role played by energy prices. First, rapidly growing energy prices over the last 15 years induced substantial improvements in terms of energy efficiency, with corresponding improvements in emission efficiency. Second, many environmental policies (e.g. carbon taxes, cap-and-trade schemes) implicitly consist in perceived higher- energy prices.

  16. The currently limited availability of energy and environmental taxation data at the sector level prevents analyses that use specific policy proxies. CO2/VA is a widespread proxy of stringency.

  17. The EU 2020 package sets the target of cutting GHG emissions by 20 percent from the 1990 level by 2020 while the ‘Roadmap for moving to a competitive low-carbon economy’ aims at abating 80 percent of GHG emissions by 2050.

  18. The effect of downstream emission intensity remains weakly significant for industry sectors only when not controlling for process-or-product innovation (column 2 in Table 9).

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Acknowledgments

This paper is based on work carried out in the CECILIA2050 research project, funded by the European Union under the 7th Framework Programme for Research (grant agreement n° 308680, www.cecilia2050.eu). It has benefited considerably from discus-sions with numerous partners in the CECILIA2050 research consortium, including Paul Drummond, Will McDowall and Paolo Agnolucci for specific hints. We thank comments provided by various industry experts in specific interviews and at the Stakeholder’s workshop Meeting related to task 2.6 (WP2) held in Brussels on the 18th of September 2013. We finally thank two anonymous referees for useful suggestions that have substantially improved the paper. Usual disclaimers apply.

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Authors and Affiliations

  1. Department of Economics and Management, University of Ferrara and SEEDS, Ferrara, Italy

    Massimiliano Mazzanti & Susanna Mancinelli

  2. Ceris-CNR, Institute for Economic Research on Firms and Growth, National Research Council of Italy, Milan, Italy

    Giovanni Marin & Francesco Nicolli

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  1. Massimiliano Mazzanti
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Correspondence to Massimiliano Mazzanti.

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Mazzanti, M., Marin, G., Mancinelli, S. et al. Carbon dioxide reducing environmental innovations, sector upstream/downstream integration and policy: evidence from the EU. Empirica 42, 709–735 (2015). https://doi.org/10.1007/s10663-014-9273-z

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