Estimating the Magnitude of Negative Externalities and Designing a Tax Scheme for Their Internalization: A Case Study of Sarcheshmeh Copper Complex in Rafsanjan

Pourdamghan, Sanaz; Shahnazi, Rouhollah; Sadrai-javaheri, Ahmad; Jafari, Mahboubeh

doi:10.22055/jqe.2026.51455.2747

Estimating the Magnitude of Negative Externalities and Designing a Tax Scheme for Their Internalization: A Case Study of Sarcheshmeh Copper Complex in Rafsanjan

10.22055/jqe.2026.51455.2747

Articles in Press, Accepted Manuscript
Available Online from 28 October 2026

Quarterly Journal of Quantitative Economics (JQE)

Document Type : Article-Based Dissertations

Authors

Sanaz Pourdamghan

rouhollah Shahnazi

Ahmad Sadrai-javaheri

Mahboubeh Jafari

Shiraz university

Abstract

Considering global goals for reducing greenhouse gas emissions and achieving net-zero carbon, controlling industrial pollutant emissions, especially in sectors with negative externalities on health and the environment, is essential. The cathode copper production chain at the Sarcheshmeh Copper Complex represents a major source of CO₂ and local pollutants such as SO₂ and NO₂, significantly affecting air quality and the health of Rafsanjan residents. This study aims to estimate both regional and global negative externalities by evaluating the willingness to pay (WTP) of Rafsanjan citizens for air pollution reduction and assessing the associated carbon damage. Data were collected in 2024–2025 through 386 randomly sampled questionnaires completed by local residents. The average monthly WTP per individual was approximately 645,930 Iranian Rial (IRR), indicating a total monthly damage of around 200 billion IRR for the entire population. Estimates based on the Gross External Damage (GED) index, resulting from the annual emission of approximately 1 million tons of CO₂ from the production of 250,000 tons of cathode copper, indicate a global damage of about 46 trillion IRR. Accordingly, a Pigouvian tax of roughly 180 million IRR per ton of cathode is proposed as a policy tool to internalize social costs and incentivize emission reduction. A two-dimensional double-bounded dichotomous choice (DBDC) logit regression analysis revealed that bid amount, preferred environmental activity, disease history, proximity to the pollution source, and membership in environmental protection groups significantly influence WTP.

Keywords

Willingness to Pay (WTP)

Contingent Valuation (CV)

Bivariate Double-Bounded Logit Regression

Pollution Tax

Environmental Damage

Subjects