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Does green policy pay dividends?

Abstract

While there is a near global consensus about the need to address climate change, most countries are hesitant to employ sufficiently stringent policies in fear of sacrificing economic growth. The objective of this research is to examine the impact of environmental policy on economic growth, using the OECD’s Environmental Policy Stringency (EPS) index across 21 OECD countries from 1990 to 2014. An augmented Solow Model with the inclusion of variables to represent human capital, trade openness and the EPS index is used to assess whether policy stringency affects growth with empirical analysis comprised of a pooled mean group estimator, dynamic OLS, fixed effects and pooled OLS to estimate the short and long run effects. The results reveal that policy stringency negatively affects economic growth in the short run but pays dividends of positive growth in the long run. There appears to be a threshold level of the EPS, beyond which the dividend is realized in the long run. The results are expected to be of interest to policy makers who strive to address climate change without trading off economic growth.

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Notes

  1. 1.

    British Columbia (BC), Canada implemented the first comprehensive revenue-neutral tax on carbon in North America in 2008.

  2. 2.

    Saskatchewan is one of Canada’s ten provinces.

  3. 3.

    Martínez-Zarzoso et al. (2019) used the EPS index to test the Porter Hypothesise described in 2.1.

  4. 4.

    The Solow Model assumes that both technology and labour grow at a constant rate. This formulation of technology is referred to as labour-augmenting. In essence, technology is making labour more effective. Solow’s economic growth model can be written as follows (see Zhao 2019):

    $$Y_{t} = K_{t}^{\alpha } \left( {A_{t} L_{t} } \right)^{{1 - \alpha }}$$

    Further, we assume that technology does not only make labour more efficient, it can also contribute to the productivity of capital. So, ‘A’ in our theoretical discussion is a separate long-run variable.

  5. 5.

    See Martínez-Zarzoso et al. (2019) for a concise explanation of the components of the EPS index.

  6. 6.

    See Brunel and Levinson (2016) for more discussion on the challenges of developing a useful and accurate measure of environmental policy stringency.

  7. 7.

    Five proxies for environmental policy stringency include: CLIMI (European Bank of Reconstruction and Development), World Economic Forum’s Executive Opinion Survey, Energy Prices (Sato et al. 2015), Environmental Patents (share) and Landfilled waste (share, Sauvage 2014; OECD 2016).

  8. 8.

    Given that the dependent variable is in log form and EPS is not in log form, we need to subtract 1 from the exponent of the coefficient and then multiply the value by 100 to determine the effect of EPS on the growth of per capita GDP.

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Acknowledgements

We thank Dr. Peter Tsigaris, who inspired this research with preliminary work and discussion about a potential relationship between carbon addiction and economic growth across countries. We also thank the editors and anonymous reviewers whose suggestions led to a more robust and overall better quality paper.

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Correspondence to Laura Lamb.

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Appendices

Appendix 1

See Table 9.

Table 9 Variable definitions and data sources

Appendix 2

See Fig. 1.

Fig. 1
figure1

Sample countries which signed onto the Kyoto Protocol: CO2 emissions before and after 2000

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Aziz, N., Hossain, B. & Lamb, L. Does green policy pay dividends?. Environ Econ Policy Stud (2021). https://doi.org/10.1007/s10018-021-00317-7

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Keywords

  • Environmental policy
  • Economic growth
  • Pooled mean group estimation
  • Porter hypothesis