Conference Agenda

Whether personal experience with extreme weather translates into climate action

remains unclear. This paper estimates the short- and long-run effects of local

temperature anomalies on climate beliefs and carbon-related behaviour, by leveraging

the UK Household Longitudinal Study merged with high-resolution temperature

anomalies. Using quasi-random interview timing around these shocks, I find that

extreme heat increases climate concern in the short run (by about 3% of the mean in

beliefs), but the effect fades within 2-3 months. Exploiting variation in cumulative

anomaly exposure over multiple years, I then show that sustained exposure works in

the opposite direction: while pro-environmental beliefs trend upward over the sample

period, the most exposed individuals gain about 2 points less on a 0-100 belief scale

than comparable unexposed households, with the attenuation concentrated among

those with higher baseline concern and greater material stakes. Behavioural responses

show a persistent belief-action gap and only small long-run adjustment. Overall, the

results suggest that experience with extreme temperatures is an unreliable driver of

climate action.

We study how confidence bias affects investment in learning via experimentation, a mechanism critical for climate change adaptation. We hypothesize that bias direction and strength predict how willingness to experiment diverges from unbiased agents. We measure revealed and stated demand for experimenting with drought-resistant crop varieties of 1,957 farmers in West Africa, a climate change hotspot. Consistent with our hypothesis, confidence bias strongly predicts willingness to experiment. The effect, however, is driven exclusively by underconfident agents, among whom females are overrepresented. In deteriorating environments, this behavioral friction undercuts effective technology diffusion and risks trapping individuals in maladapted production environments.

I propose a novel framework to study climate change adaptation strategies via buffer saving under uncertainty, where constrained agents dispose of assets as a self-insurance mechanism in order to protect themselves from increasingly erratic income shocks and smooth consumption. I frame the problem as a mixed classical-impulse stochastic control problem, where consumption and labor supply are continuous and asset transactions happen at discrete times. I prove optimality of the solution for the general problem in both finite and infinite time, and present a closed form solution for specific functional forms. I study the probabilistic properties of asset transactions as hitting times and show that buffer stock saving emerges as the combination of wealth and precautionary effects. I further show how market imperfections can generate Pareto tails in transaction timing. I apply this novel framework to study how farmers in West Africa adapt to climate shocks by using livestock as a buffer stock. Using a novel spatially explicit climate and household dataset for Burkina Faso, I show reduced form evidence of the model predictions and quantify the welfare loss that stems from the absence of crop insurance markets. This framework is general and can be used to explain a wide variety of climate change adaptation strategies throughout the developing world.

With the large number of empirical estimates of climate change damage, particularly heat stress shocks, and ad hoc recommendations of trade as an adaptation tool in combating climate change, evidence of trade’s mitigative effect is relatively scarce. In investigating its role, we find muted trade responses to heat stress shocks, with only one medium-term response to temperature shocks consistent with hedging against future shocks in global agricultural markets. We propose a theoretical optimization framework that highlights risk minimization in import decisions, which suggests that optimal selection of partners and trade shares, reduces supply growth volatility. Empirically however, we find increasing export suppliers is associated with a reduction in price volatilities at the expense of increased supply volatility, while increased external dependence is associated with increased supply volatility and no significant impact on price volatility. Subsequent data calibration and counterfactual analysis points to a higher preference for supply growth maximization as a potential reason for the higher supply volatility observed.