Skip to main navigation Skip to search Skip to main content

Data Selection and Environmental Kuznets Curve Models - Environmental Kuznets Curve Models, Data Choice, Data Sources, Missing Data, Balanced and Unbalanced Panels

  • Avik Sinha
  • , Muhammad Shahbaz
  • , Daniel Balsalobre
  • Goa Institute of Management
  • Montpellier Business School
  • COMSATS University Islamabad
  • University of Castilla-La Mancha

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

68 Citations (Scopus)

Abstract

The literature of environmental Kuznets curve has seen numerous evidences of EKCs for various pollutants across a wide array of contexts. While carrying out these exercises, a number of practical issues are being faced by the researchers. Although Stern (2004) has identified some of those issues, they still remained uncovered. In this study, we have put forth the issues on (a) model selection, (b) model validation, (c) data standardization, (d) variable selection and creation, and (e) proxy for environmental degradation. While discussing these issues in brief, we have also provided basic solutions to these problems. These solutions are demonstrated both logically and empirically, while analyzing the exact data used by the authors in their published studies.

Original languageEnglish
Title of host publicationEnvironmental Kuznets Curve (EKC)
Subtitle of host publicationA Manual
PublisherElsevier
Pages65-83
Number of pages19
ISBN (Electronic)9780128167977
ISBN (Print)9780128167960
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes

Keywords

  • Data
  • Environmental Kuznets curve
  • Falsification
  • Validation
  • Variable

Fingerprint

Dive into the research topics of 'Data Selection and Environmental Kuznets Curve Models - Environmental Kuznets Curve Models, Data Choice, Data Sources, Missing Data, Balanced and Unbalanced Panels'. Together they form a unique fingerprint.

Cite this