Special Issue "Sustainability and the Environmental Kuznets Curve Conjecture"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editor

Prof. Dr. Bertrand Hamaide
E-Mail Website
Guest Editor
Department of Economics, Université Saint-Louis – Bruxelles, 43 boulevard Botanique, 1000 Brussels, Belgium
Interests: nature reserve selection and design, climate change, biodiversity, ecosystem services, growth and environment

Special Issue Information

Dear Colleagues,

The Environmental Kuznets Curve (EKC) hypothesis implies the existence of an inverted U-shaped relation between environmental damage (generally represented by emission or concentration of various pollutants) and economic development (generally represented by per capita income).  If true, this would imply that higher levels of economic growth might lead to environmental improvement and enhance sustainability. However, such a relation between environment and development remains a conjecture, and the virtuous path of sustainable growth is far from being proved.

This Special Issue will help to nourish the debate around sustainability and the EKC by concentrating on (albeit not limited to those) various issues. 

First, knowing that environmental regulations in developed countries might further encourage displacement of polluting activities toward developing countries, is that Pollution Haven Hypothesis (PHH) visible in specific countries? Additionally, what is the sustainability impact of trade, economic policies or environmental policies?

Second, EKC analyses with country comparisons for specific pollutants or EKC analyses comparing various pollutants for the same country, or concentrating on one pollutant and a specific methodology, or examining the turning point and its level of income may help to enlighten knowledge about the sustainability of public policies.

Empirical papers (original research) in those (non-exclusive) areas are welcome, and so are reviews and opinions.

Prof. Dr. Bertrand Hamaide
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Environmental Kuznets Curve
  • Pollution Haven Hypothesis
  • growth and environment
  • developing countries and environmental pressure
  • developed countries and environmental regulation

Published Papers

This special issue is now open for submission, see below for planned papers.

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Planed paper 1:

Type :article
Title:Estimating Long-run Relationship Between Renewable Energy Use and CO2 Emissions: A Radial Basis Function Neural Network (RBFNN) Approach

Submission date: 7 August

Pradyot Ranjan Jena1, Japan Majhi2, Shunsuke Managi3

 1    Babita1 School of Management, National Institute of Technology Karnataka, India, Surathkal. Email – [email protected]

2    Dept. of CSIT, Guru Ghasidas Vishwavidyalaya, Central University, Bilaspur, India (email:[email protected])

3    Urban Institute, Kyushu University, Japan

 

Abstract: The contributions of existing seminal works to the literature of EKC hypotheses are significant. However, time series and panel data estimations of EKC in general follow the same estimated parameters within whole sample period. Although some prominent works consider the structural breaks in cross-section dependence tests of panel data, they reveal eventually constant estimates in observing the effect of GDP (GDI) on environmental degradation for the whole predicted time period. Few articles aim at detecting the relevant estimates of coefficients with one or two structural breaks in a dynamic structure. The dynamic structure of an EKC model can be evaluated through either the effects of leads and lags of independent variable (GDI) on dependent variable (environmental degradation or CO2 emissions), or, through possible changes in estimated parameters in one or more potential structural breaks. Furthermore, dynamic structure of an EKC model can be examined through all possible shifts in estimated values at all possible different time periods and at all relevant time frequencies. Such analyses, thereby, observe numerous structural breaks within different time cycles (frequencies) and, hence, might result in more efficient, consistent, and unbiased estimators. Considering that there might be nonlinear relationship between the indicators of economic growth and the environmental quality we develop a multilayer artificial neural network (ANN) model. A multilayer artificial neural network model is more efficient in capturing the nonlinearity present in the time series data and provides higher accuracy in forecasting the CO2 emissions based on the past values of the emissions and the economic indicators such as GDP, population density, and urbanization. We have considered two types of countries – first, countries that emit 2% or more share of global CO2 emissions and countries that emit less than 2% share. Using the multilayer ANN model, we forecast the CO2 emissions for both types of countries for 2025 and 2030. This model trains 80% of the data to optimize the weights and tests the remaining 20% of the data. Forecasting error of less than 2% has been achieved by the model during the testing procedure. Such forecasts for the near future will provide insights for regulations on pollution control.

Planed paper 2
Type :article
Title:Asymmetric Impact of Institutional Quality and Human Capi-2 tal on Environmental Degradation: Evidence of The Environ-3 mental Kuznets Curve

Submission date: Pending

Author: Farrah Dina Abd Razak 1, Norlin Khalid 2, *, Mohd Helmi Ali 2 and Law Siong Hook 3

1 Faculty of Business and Management, Universiti Teknologi MARA, Perak, Malaysia;
2 Faculty of Economics and Management, Universiti Kebangsaan Malaysia, Malaysia;
3 Faculty of Economics and Management, Universiti Putra Malaysia, Malaysia;

Abstract: The objective of this paper is to explore the presence of asymmetry impacts between institutional quality and environmental degradation by featuring human capital and financial development covering the Malaysia economy during the period from 1989 until 2019. This paper employs  a nonlinear auto regressive distributed lag (NARDL) model approach to identify the asymmetric  cointegration between the variables. Additionally, an asymmetric causality test is adopted to examine the causal association between selected variables. The implication of this finding provides new guidelines for authorities to consider the asymmetries in formulating environmental related policies to maintain environmental quality and achieving sustainable development goals.
Keywords: institutional quality; environmental degradation; human capital

Back to TopTop