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Cited by 358

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Examining the Evidence on Environmental Regulations and Industry Location

Brunnermeier, Smita B., Levinson, Arik·2004·The Journal of Environment & Development

Abstract

This article offers a review and critique of the large literature on the pollution havens hypothesis. This hypothesis refers to the notion that certain jurisdictions can become pollution havens as dirty industries relocate or expand in response to differences in regulatory stringency. The early literature, based on cross-sectional analyses, typically concludes that environmental regulations have an insignificant effect on firm location decisions. However, recent studies that use panel data to control for unobserved heterogeneity, or instruments to control for endogeneity, find statistically significant pollution haven effects of reasonable magnitude. Furthermore, this distinction appears regardless of whether the studies look across countries, states, counties, or industries, or whether they examine plant locations, investment, or international trade patterns.

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Crossref · 10.1177/1070496503256500

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Metadata

Authors
Brunnermeier, S. B., & Levinson, A.
Venue
The Journal of Environment & Development
Published
2004-03
Volume
13
Issue
1
Pages
6-41
ISSN
  • 1070-4965 (ISSN-L)
  • 1552-5465
OpenAlex
W2112171626
Cited by
358
References
2
FWCI
23.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Examining the Evidence on Environmental Regulations and Industry Location. https://app.cochat.ai/papers/10.1177/1070496503256500
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Brunnermeier, S. B., & Levinson, A. (2004). Examining the Evidence on Environmental Regulations and Industry Location. The Journal of Environment & Development. https://doi.org/10.1177/1070496503256500

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.