ETD

• climate change
• EU
• inflation
• quantile local projection
• tail risks

Climate change is increasingly shaping the global economy, with consequences that extend far beyond environmental damage. Extreme weather events and gradual warming disrupt production, strain supply chains, and undermine economic stability across countries. While the effects of temperature shocks on economic activity, e.g. GDP, have been largely investigated, the inflation response to climate and weather change is considerably less understood, even though food and energy markets stand out as potentially vulnerable. This thesis examines how temperature shocks affect inflation across European Union countries (EU28) between 2000 and 2019. To move beyond average effects and capture risks across the full distribution, it applies the quantile local projection estimator developed by Machado and Silva (2019). Results reveal that the impacts of
climate shocks are highly asymmetric and concentrated in the right tail of the distribution. Food inflation responds with sharp but short-lived spikes, while energy inflation exhibits more persistent upward pressures. At the aggregate level, headline inflation appears relatively muted under linear models, but once non-linearities are considered, pronounced
upper-tail risks emerge. Taken together, these findings show that climate change does not simply shift expected inflation, but reshapes its entire distribution, increasing the probability of extreme outcomes. By amplifying vulnerabilities in food and energy markets and
propagating to aggregate inflation under nonlinear dynamics, climate shocks create challenges for monetary policy that traditional, mean-based approaches are ill-suited to address.