Extreme weather events and pro-environmental behavior: evidence from a climate change vulnerable country

ABSTRACT

Experiencing an extreme weather event and its consequences might make the risks associated with climate change more tangible, easier to evaluate, and more salient. Consequently, those experiences might translate into the adoption of pro-environmental behaviours. Understanding this relationship is fundamental for the successful design of policies aimed towards promoting the adoption of climate change adaptation and mitigation measures. This work contributes to the literature by showing that there is in fact a positive relation between experiencing an extreme weather event and willingness to take pro-environmental actions. The prevailing available evidence is for developed countries. Our empirical analysis is based on a nationally representative sample of households from Mexico, a developing country that is highly vulnerable to the effects of extreme weather events.

KEYWORDS:

• Extreme weather event
• pro-environmental behaviour
• willingness to adopt
• Mexico
• climate change

JEL CODES:

• Q2
• Q5
• Q54
• D80

Acknowledgments

We thank Danae Hernández-Cortés, Isael Fierros, participants at the 16^th annual meeting of the Environment for Development Initiative, and an anonymous reviewer, for their valuable comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ We use a quasi-maximum likelihood Poisson estimator, which has the advantage of being consistent regardless of the form of the variance (Wooldridge 2010). As a robustness check we estimated binomial models to consider the fact that our count data is conditional on an upper bound. The results of that model are qualitatively the same as those presented here; the marginal effects are almost indistinguishable across the different estimations. Finally, since our data does not show overdispersion, estimating negative binomial models leads to the same results as estimating Poisson models.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.