Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/47696
Title: | Endogeneity and nonlinearity in the environmental kuznets curve: A control function approach | Authors: | Çağlayan Akay, Ebru Kangallı Uyar, Sinem Güler |
Keywords: | CO2 emissions Control function approach Endogeneity Environmental Kuznets curve Nonparametric models |
Publisher: | Savez Ekonomista Vojvodine | Abstract: | Summary: This study investigates the existence and shape of an environmental Kuznets curve (EKC) across 16 developed countries and 58 developing countries during the period 1995-2010. The basic model of the EKC is a polynomial equation of real GDP per capita. The EKC model estimated for CO2 emission per capita was extended by using control variables, such as trade, urban population, fossil fuel consumption, and service sector. Based on the nonparametric test of poolability of Badi H. Baltagi, Javier Hidalgo, and Qi Li (1996), the relationship was found to have structural stability. A nonparametric pooled regression model was constructed, which allowed functional form flexibility and considered the endogeneity problem often emphasized in the EKC literature. The estimation results show the nonexistence of an EKC for both groups. The study also indicates the existence of nonlinearity and heterogeneity in the relationships between CO2 emission and the control variables across both groups. © 2021, Savez Ekonomista Vojvodine. All rights reserved. | URI: | https://doi.org/10.2298/PAN171009012C https://hdl.handle.net/11499/47696 |
ISSN: | 1452-595X |
Appears in Collections: | İktisadi ve İdari Bilimler Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
Files in This Item:
File | Size | Format | |
---|---|---|---|
1452-595X1900012C.pdf | 649.71 kB | Adobe PDF | View/Open |
CORE Recommender
SCOPUSTM
Citations
2
checked on Nov 16, 2024
Page view(s)
112
checked on Aug 24, 2024
Download(s)
64
checked on Aug 24, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.