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Abstract

This paper studies the effects of air pollution on labour supply by gender in Mexico City. We differentiate between the health, income and policy effect. We use a regression discontinuity design to identify the policy effect of the ``Environmental Contingency Program’’ and labour supply decisions in pre- and post-contingency periods. Further, we supplement this evidence with information on pollution from measurement stations across the city linked to a city-representative labour force survey. We find evidence that contemporaneous pollution exposure at moderate levels reduce labour supply, whilst there are dramatic reductions at high levels of pollution with heterogeneous effects by formality status. Moreover, pollution seems to decrease working hours even in non-emergency times with differential effects by gender. For male workers the income effect dominates, and thus labour supply increases at high levels of pollution. Moreover, at the extensive margins, informal male workers appear to be the least able to drop-out of employment in high-pollution days. The story is though different at the intensive margins. Where most female and formal workers are able to reduce their hours of work, informal female workers may have no alternatives. Female informal workers have the highest increase in minutes of work during the peak pollution days. in high pollution days: formal women work more. Why is this? cultural norms related to working formal women (they need to work harder). There is a mediation related by children under 12 presence.

Figure 3c: The Effect of Pollution alerts on labour supply intensive margin (Females by formality)

Citation

Rufrancos et al. 2023. “The unequal effect of pollution exposure on labour supply across gender” University of Stirling, Mimeo.

@unpublished{rufrancospollutionlswip,
author = {Hector Rufrancos and Cecilia Poggi and Eva-Maria Egger and Antonia Schwarz and Mirko Moro},
institution = {University of Stirling},
type={mimeo},
title = {The unequal effect of pollution exposure on labour supplyacross gender},
year = {2023}}