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

Saptorshee Kanto Chakraborty () and Massimiliano Mazzanti ()
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Saptorshee Kanto Chakraborty: University of Ferrara, Italy

No 719, SEEDS Working Papers from SEEDS, Sustainability Environmental Economics and Dynamics Studies

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

Keywords: Green Innovation; Human Capital Spillover; Gross Research and Development; OECD; C-Lasso (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cse, nep-eff, nep-env, nep-knm and nep-tid
Date: 2019-08, Revised 2019-08
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http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0719.pdf First version, 2019 (application/pdf)
http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0719.pdf Revised version, 2019 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:srt:wpaper:0719

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