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Economic growth and environmental degradation: a conditional nonparametric frontier analysis

  • George E. Halkos
  • Christina Bampatsou
Research Article
  • 22 Downloads

Abstract

This paper examines the effect of economic growth and the association of environmental degradation on economies’ technological change and technological catch-up. Using a conditional nonparametric frontier analysis to a sample of 73 economies over the time period 1980–2014, empirical evidence of the examined relationship is provided both under full and partial frontiers in the constant and variable returns to scale (VRS) models. Specifically, the newly proposed time-dependent conditional nonparametric frontier estimators have been applied. In our case the time-dependent conditional efficiency estimators allow us to model directly the effects of growth and time on economies’ estimated performance without requiring any specification of the production functional form and without assuming the separability condition between time, economic growth and the support of inputs and outputs. The overall results reveal that the efficiency results of full and partial frontiers tend to lead to the same results, except in the cases of full VRS models where energy use and carbon dioxide emissions are incorporated as an additional input and output, respectively. The results demonstrate that countries with a higher environmental efficiency are those that have signed the first agreement between nations (Kyoto Protocol) to mandate country-by-country reductions in greenhouse-gas emissions, while countries that have not signed are relatively inefficient. Ultimately, the empirical findings also suggest that the effect of economic growth is determined by economies’ development stage and geographical region.

Keywords

Economic growth Technological change Technological catch-up Environmental degradation Conditional nonparametric frontier Data envelopment analysis 

JEL Classification

C14 C61 O30 O47 Q53 Q55 Q56 

Notes

Acknowledgements

We would like to thank the anonymous reviewers for helpful and constructive comments that improved the quality of the paper. Any remaining errors are solely the authors’ responsibility.

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Copyright information

© Society for Environmental Economics and Policy Studies and Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory of Operations Research, Department of EconomicsUniversity of ThessalyVólosGreece
  2. 2.Faculty of Economic SciencesIonian UniversityLefkadaGreece

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