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Modelling the Green Knowledge Production Function with Latent Group Structures for OECD countries

Author

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  • Saptorshee Kanto Chakraborty

    (University of Ferrara, Italy)

  • Massimiliano Mazzanti

    (University of Ferrara; SEEDS, Italy)

Abstract

We explore the green knowledge production function and human capital spillovers in the OECD region using a latent group structure. The number of groups and the group membership are both unknown, we determine these unknowns using a penalized regression technique in the presence of cross-sectional dependence in error terms and nonstationarity. We find substantial heterogenous groups classified under three distinctive groups and their efficient estimates. We try to model the green knowledge production function with Latent-Group Structures using PPC- base method with one unobserved global non-stationary factor, we find heterogeneous behaviour in green technologies using a Cup-Lasso estimate. Human capital and expenditure in Research and Development plays an important part in our findings

Suggested Citation

  • Saptorshee Kanto Chakraborty & Massimiliano Mazzanti, 2019. "Modelling the Green Knowledge Production Function with Latent Group Structures for OECD countries," SEEDS Working Papers 0719, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Aug 2019.
  • Handle: RePEc:srt:wpaper:0719
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    File URL: http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0719.pdf
    File Function: Revised version, 2019
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    Cited by:

    1. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2021. "Renewable electricity and economic growth relationship in the long run: Panel data econometric evidence from the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 330-341.

    More about this item

    Keywords

    Green Innovation; Human Capital Spillover; Gross Research and Development; OECD; C-Lasso;
    All these keywords.

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