Exposure or Income? The Unequal Effects of Pollution on Daily Labor Supply
Bridget Hoffmann and
Juan Pablo Rud
Additional contact information
Bridget Hoffmann: Inter-American Development Bank
Juan Pablo Rud: (Royal Holloway, University of London/IFS
No 109, Working Papers from Red Nacional de Investigadores en Economía (RedNIE)
We use high-frequency data on fine particulate matter air pollution (PM 2.5) at the locality level to study the effects of high pollution on labor supply decisions and hospitalizations for respiratory disease in the metropolitan area of Mexico City. We document a negative, non-linear relationship between PM 2.5 and same-day labor supply, with strong effects on days with extremely high pollution levels. On these days, the average worker experiences a reduction of around 7.5% of working hours. Workers partially compensate for lost hours by increasing their labor supply on days that follow high-pollution days. Informal workers reduce their labor supply less than formal workers on high-pollution days and also compensate less on the following days. This suggests that informal workers may experience greater exposure to high pollution and greater reductions in labor supply and income. We provide evidence that reductions in labor supply due to high pollution are consistent with avoidance behavior and that income constraints may play an important role in workers’ labor supply decisions.
Pages: 60 pages
New Economics Papers: this item is included in nep-ene, nep-env, nep-hea and nep-iue
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aoz:wpaper:109
Access Statistics for this paper
More papers in Working Papers from Red Nacional de Investigadores en Economía (RedNIE) Contact information at EDIRC.
Bibliographic data for series maintained by Laura Inés D Amato ().