The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks
Open accessAbstract
Individuals take preventive measures to avoid costly air pollution exposure. This paper provides new empirical evidence of pollution avoidance that Chinese urban residents purchase particulate-filtering facemasks to protect against ambient air pollution. The analysis is conducted with detailed and comprehensive data available on daily facemask purchases and air quality that became available only very recently. We find that this transitory air pollution avoidance behavior exhibits dynamics and nonlinearities, with significant increases of facemask purchases during extreme pollution episodes. The daily model shows that a 100-point increase in Air Quality Index (AQI) increases the consumption of all masks by 54.5 percent and anti-PM2.5 masks by 70.6 percent. The estimates from the aggregated model with flexible pollution levels are used to simulate the benefit of air quality improvement. If 10 percent of heavy pollution days (AQI ≥201) were eliminated, the total savings on facemasks alone would be approximately 187 million USD in China. This result suggests that reducing the occurrence of “airpocalypse” events represents a signifi1cant opportunity to improve social welfare. Nevertheless, our estimates are likely only a small part of the benefit of clean air because facemasks can only partially reduce the negative health effects of air pollution and the costs of other avoidance behaviors are not included.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
Regression Analysis of Count Data
Cameron, A. C., & Trivedi, P. K. (2013) · doi:10.1017/cbo9781139013567 · Cited by 6,640
Health Effects of Fine Particulate Air Pollution: Lines that Connect
Pope, C. A., & Dockery, D. W. (2006) · Journal of the Air & Waste Management Association · doi:10.1080/10473289.2006.10464485 · Cited by 6,583
Automobile Prices in Market Equilibrium
Berry, S., Levinsohn, J., & Pakes, A. (1995) · Econometrica · doi:10.2307/2171802 · Cited by 4,883
Brunekreef, B., & Holgate, S. T. (2002) · The Lancet · doi:10.1016/s0140-6736(02)11274-8 · Cited by 4,638
Regression Analysis of Count Data
Cameron, A. C., & Trivedi, P. K. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511814365 · Cited by 3,147
Rapid health transition in China, 1990–2010: findings from the Global Burden of Disease Study 2010
Yang, G., Wang, Y., Zeng, Y., Gao, G. F., Liang, X., Zhou, M., Wan, X., Yu, S., Jiang, Y., Naghavi, M., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)61097-1 · Cited by 1,982
Chen, Y., Ebenstein, A., Greenstone, M., & Li, H. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1300018110 · Cited by 1,818
Climate change, mortality, and adaptation: Evidence from annual fluctuations in weather in the US
Deschênes, O., & Greenstone, M. (2011) · American Economic Journal: Applied Economics · doi:10.1257/app.3.4.152 · Cited by 1,064
Findings from the Global Burden of Disease Study 2021
Murray, C. J. L. (2024) · The Lancet · doi:10.1016/s0140-6736(24)00769-4 · Cited by 1,057
Cited by
The Mortality and Medical Costs of Air Pollution: Evidence from Changes in Wind Direction
Deryugina, T., Heutel, G., Miller, N. H., Molitor, D., & Reif, J. (2019) · American Economic Review · doi:10.1257/aer.20180279 · Cited by 771
Air pollution lowers Chinese urbanites’ expressed happiness on social media
Zheng, S., Wang, J., Sun, C., Zhang, X., & Kahn, M. E. (2019) · Nature Human Behaviour · doi:10.1038/s41562-018-0521-2 · Cited by 485
The effect of air pollution on migration: Evidence from China
Chen, S., Oliva, P., & Zhang, P. (2022) · Journal of Development Economics · doi:10.1016/j.jdeveco.2022.102833 · Cited by 428
Metadata
- Authors
- Zhang, J., & Mu, Q.
- Venue
- Journal of Environmental Economics and Management
- Publisher
- Elsevier BV
- Published
- 2018-11
- Volume
- 92
- Pages
- 517-536
- ISSN
- 0095-0696 (ISSN-L)
- OpenAlex
- W3125201815
- Cited by
- 401
- References
- 36
- FWCI
- 3.48
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks. https://app.cochat.ai/papers/10.1016/j.jeem.2017.07.006
- The paper
- Zhang, J., & Mu, Q. (2018). Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks. Journal of Environmental Economics and Management. https://doi.org/10.1016/j.jeem.2017.07.006
Data sources
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.