Taming the SO2 and NOx emissions: evidence from a SUR model for the US

Michael Polemis () and Thanasis Stengos

Letters in Spatial and Resource Sciences, 2018, vol. 11, issue 2, No 1, 95-104

Abstract: Abstract We construct a Seemingly Unrelated Regression (SUR) model to investigate the link between local environmental pollution (sulfur dioxide-SO2 and nitrogen oxides-NOx emissions) and economic growth on a panel data set framework for the US over the period 1990–2012. The presence of different polynomials of GDP for each equation of SO2 and NOx respectively allows us to utilize a SUR model to estimate jointly the two equations in order to examine the total effect of environmental degradation. While we find evidence of a quartic relationship between SO2 emissions and economic development in a single equation framework this outcome does not seem to hold when we utilize a SUR model controlling for cross section dependence.

Keywords: Environmental Kuznets curve; SUR; Cross section dependence; Local pollutants (search for similar items in EconPapers)
JEL-codes: C33 Q43 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://link.springer.com/10.1007/s12076-018-0203-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lsprsc:v:11:y:2018:i:2:d:10.1007_s12076-018-0203-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/12076

DOI: 10.1007/s12076-018-0203-8

Access Statistics for this article

Letters in Spatial and Resource Sciences is currently edited by Henk Folmer and Amitrajeet A. Batabyal

More articles in Letters in Spatial and Resource Sciences from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().