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Determinants of Environmental Innovation – New Evidence from German Panel Data Sources

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  • Jens Horbach

    (University of Applied Sciences Anhalt)

Abstract

In most cases, empirical analyses of environmental innovations based on firm-level data relied on survey data for one point in time. These surveys, especially designed for the analysis of environmental innovations, are useful because they allow for the inclusion of many explanatory variables such as different policy instruments or the influence of stake-holders and pressure groups. On the other hand, it is not possible to address the dynamic character of the environmental innovation process. This paper uses two German panel data bases, the establishment panel of the Institute for Employment Research (IAB) and the Mannheim Innovation Panel (MIP) of the Centre for European Economic Research (ZEW), to explore the determinants of environmental innovations. These data bases were not specifically collected to analyze environmental issues, but they contain questions that allow the identification of environmental innovations. We use discrete choice models for each of the data bases to analyze hypotheses derived from the theoretical (environmental) innovation literature. The econometric estimations show that the improvement of the technological capabilities (“knowledge capital”) by R&D or further education measures triggers environmental innovations – this result is confirmed by both data bases and both methods to measure environmental innovation. The hypothesis that “Innovation breeds innovation” is confirmed by the analysis of the MIP data. General and environmental innovative firms in the past are more likely to innovate in the present. Environmental regulation, environmental management tools and general organizational changes and improvements trigger environmental innovation, a result that has also been postulated by the famous Porter-hypothesis. Environmental management tools especially help to detect cost-savings (specifically material and energy savings). Following our econometric results, cost-savings are an important driving force of environmental innovation.

Suggested Citation

  • Jens Horbach, 2006. "Determinants of Environmental Innovation – New Evidence from German Panel Data Sources," Working Papers 2006.13, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2006.13
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    Cited by:

    1. Massimiliano Mazzanti & Davide Antonioli & Francesco Nicolli & Marianna Gilli, 2013. "Information Technology, Environmental Innovations and Complementarity Strategies," Working Papers 2013132, University of Ferrara, Department of Economics.
    2. Jin, Chenfei & Tsai, Fu-Sheng & Gu, Qiuyang & Wu, Bao, 2022. "Does the porter hypothesis work well in the emission trading schema pilot? Exploring moderating effects of institutional settings," Research in International Business and Finance, Elsevier, vol. 62(C).
    3. Shuai Shao & Zhigao Hu & Jianhua Cao & Lili Yang & Dabo Guan, 2020. "Environmental Regulation and Enterprise Innovation: A Review," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1465-1478, March.
    4. Qi Hu & Fang Wu & Yingna Qu & Ke Guo & Xinyi Du, 2022. "Green Innovation’s Promoting Impact on the Fusion of Industry and Talent: The Case of Pharmaceutical Industry in the Yangtze River Economic Belt of China," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    5. Wen, Jun & Zhao, Xinxin & Fu, Qiang & Chang, Chun-Ping, 2023. "The impact of financial risk on green innovation: Global evidence," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).

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    More about this item

    Keywords

    Environmental innovation; Panel data analysis; Discrete choice models;
    All these keywords.

    JEL classification:

    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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