Affiliations 

  • 1 School of Commerce, University of Southern Queensland, Toowoomba, Australia
  • 2 School of Commerce, University of Southern Queensland, West St, Toowoomba, QLD, 4350, Australia. gowj@usq.edu.au
Environ Sci Pollut Res Int, 2019 May;26(13):13159-13172.
PMID: 30903468 DOI: 10.1007/s11356-019-04791-1

Abstract

The relationship between national income growth and the environment of 14 Asian economies over a 50 year period is examined using the Environmental Kuznets Curve (EKC) hypothesis. Ecological Footprint (EF) measures environmental impacts and gross domestic product (GDP) measures economic growth. It is hypothesised that increased rates of economic growth come at a cost to the natural environment. The EKC hypothesis has been mainly tested in the literature by cross-sectional or panel data methods. In this study, it is tested using time series analysis through initially examining the relationship between EF and GDP using linear, quadratic and cubic estimating OLS regression functions. In the second stage, the long-run relationship between EF and GDP is investigated using an augmented error correction trend model. There is a statistically significant cointegrated long-run relationship between the variables in most of the countries. The EKC hypothesis is supported in the case of India, Nepal, Malaysia and Pakistan with the other countries exhibiting a positive linear relationship between the two variables. Almost all error correction terms are correct in sign and significance that implies that some percentage of disequilibria in EF in the previous year adjusts back to the long-run equilibrium in the current year. Based on the long-run relationship, it is apparent that rapid economic growth has had an impact on the environment and the ecosystems of these countries over the last 50 years. Despite that, until now, not many of them have taken sufficient steps to reduce their EF or to improve their bioproductive capacity.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.