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Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China

Bangzhu Zhu (), Runzhi Pang, Julien Chevallier, Yi-Ming Wei () and Dinh-Tri Vo
Additional contact information
Bangzhu Zhu: Nanjing University of Information Science and Technology
Runzhi Pang: Jinan University
Dinh-Tri Vo: IPAG Lab

The European Journal of Health Economics, 2019, vol. 20, issue 4, 501-511

Abstract: Abstract The concentrations of particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) and 10 µm (PM10) is a widespread concern and has been demonstrated for 103 countries. During the past few years, the exposure–response function (ERf) has been widely used to estimate the health effects of air pollution. However, past studies are either based on the cost-of-illness or the willingness-to-pay approach, and therefore, either do not cover intangible costs or costs due to the absence of work. To address this limitation, a hybrid health effect and economic loss model is developed in this study. This novel approach is applied to a sample of environmental and cost data in China. First, the ERf is used to link PM2.5 concentrations to health endpoints of chronic mortality, acute mortality, respiratory hospital admission, cardiovascular hospital admission, outpatient visits—internal medicine, outpatient visits—pediatrics, asthma attack, acute bronchitis, and chronic bronchitis. Second, the health effect of PM2.5 is monetized into the economic loss. The mean economic loss due to PM2.5 was much heavier in the North than the South of China. Furthermore, the empirical results from 76 cities in China show that the health effects and economic losses were over 4.98 million cases and 382.30 billion-yuan in 2014 and decreased dramatically compared with those in 2013.

Keywords: PM2.5; Exposure–response function; Cost-of-illness method; Willingness-to-pay method; Health effects; Economic losses (search for similar items in EconPapers)
JEL-codes: Q5 (search for similar items in EconPapers)
Date: 2019
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