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DEGREE OF STRINGENCY MATTERS: REVISITING THE POLLUTION HAVEN HYPOTHESIS BASED ON HETEROGENEOUS PANELS AND AGGREGATE DATA

Published online by Cambridge University Press:  20 February 2018

Thomas Jobert ,
Fatih Karanfil  and
Anna Tykhonenko
Thomas Jobert
Affiliation:
GREDEG, Nice Sophia Antipolis University
Fatih Karanfil*
Affiliation:
EconomiX, University of Paris Nanterre, King Abdullah Petroleum Studies and Research Center and Galatasaray University Economic Research Center
Anna Tykhonenko
Affiliation:
GREDEG, Nice Sophia Antipolis University
*
Address correspondence to: Fatih Karanfil, King Abdullah Petroleum Studies and Research Center (KAPSARC), P.O. Box 88550, Riyadh 11672, Saudi Arabia; emails: [email protected], [email protected].
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Abstract

Empirical studies on the trade-environment nexus that use panel data face two simultaneous challenges. One is associated with the potential presence of unobserved cross-country heterogeneity, while the other is due to the use of aggregate data. In this paper, we apply both the dynamic fixed effects and iterative empirical Bayes estimators to show first that when country heterogeneity is accurately accounted for in the estimation, it is possible to obtain significant impacts of trade variables on the environment, even though we use aggregate data. Second, using both the empirical Bayes parameter estimates and indicators of stringency of environmental regulations, we show that at low levels of stringency, the probability of having pollution-intensive foreign direct investments (FDIs) increases with a decrease in stringency. However, at high levels of regulatory stringency, more stringent regulations may lead to more pollution-intensive FDIs. This implies that pollution havens may exist only if environmental regulations are very lax or nonexistent.

Keywords

Foreign Direct InvestmentPollution HavenRegulatory StringencyBayesian Shrinkage Estimator
Type
Articles
Information
Macroeconomic Dynamics , Volume 23 , Issue 7 , October 2019 , pp. 2675 - 2697
Copyright
Copyright © Cambridge University Press 2018 

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