Contact Information

[email protected]

Personal Webpage

Available for interviews at

European Job Market for Economists (EEA)

Allied Social Science Associations (ASSA)

CV                         Job Market Paper

 

Research interests

Applied Microeconomics. Environmental Economics. Behavioural Economics. Public Economics.

Placement Officer

Libertad González
[email protected]

References

Jose Apesteguia (Advisor)
[email protected]
Ruben Durante
[email protected]
Hunt Allcott
[email protected]
Ernst Fehr
[email protected]

Research

"The Marginal Impact of Emission Reductions: Estimates, Beliefs and Behaviour" (Job Market Paper)
An important driver for climate change inaction is the belief that individuals cannot have any tangible impact on climate change through their own actions. Currently available statistics are not suited to systematically assess this belief. In this paper, I derive the marginal impact of emission reductions – the effect of reducing emissions by 1 tonne of CO2 (tCO2 ) – on physical climate change outcomes, document important misperceptions and show how they affect behaviour. Using climate models, I find that impact of reducing emissions by 1 tCO2 is 4.000 litres less glacier ice melting, 6 additional hours of aggregate life expectancy and 5 m² less vegetation undergoing ecosystem change. Subjects underestimate these figures by 5 orders of magnitude on average. Moreover, their mental models are inconsistent with climate models. First, they assume that the marginal impact increases when others reduce their emissions (strategic complementarity). Second, they think emission reductions are a threshold public goods game. Providing subjects with the climate scientific findings causally increases perceived self-efficacy, intentions to reduce emissions and real donations to mitigate them. The findings are consistent with a model of threshold thinking, which predicts positive overall emission reductions of information provision in equilibrium.

Publications

"Specification Analysis for Technology Use and Teenager Well-Being: Statistical Validity and a Bayesian Proposal" (with D. Rossell)
A key issue in science is assessing robustness to data analysis choices, while avoiding selective reporting and providing valid inference. Specification Curve Analysis is a tool intended to prevent selective reporting. Alas, when used for inference it can create severe biases and false positives, due to wrongly adjusting for covariates, and mask important treatment effect heterogeneity. As our motivating application, it led an influential study to conclude there is no relevant association between technology use and teenager mental well-being. We discuss these issues and propose a strategy for valid inference. Bayesian Specification Curve Analysis (BSCA) uses Bayesian Model Averaging to incorporate covariates and heterogeneous effects across treatments, outcomes and subpopulations. BSCA gives significantly different insights into teenager well-being, revealing that the association with technology differs by device, gender and who assesses well-being (teenagers or their parents).

Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 71, Issue 5, November 2022, Pages 1330–1355.

Research in Progress

"Do Consumers Reward Green Campaigns? Evidence from a Nationwide True Cost Experiment" (with H. Allcott, T. Gaugler, A. Michalke and L. Stein)

"The not-so-marginal impact of marginal emission reductions on climate change outcomes" (with B. Marzeion, T. Carleton, K. Frieler, G. Krinner, M. Kummu, S. Lange, M. Meinshausen, M. Mengel, D. Notz, A. Slangen, P. Thornton, L. Warszawski, K. Zantout and the FishMIP Team)

"Vegetarian*ism: Evidence from 200 Million Home Deliveries" (with R. Durante and M. Quentel)

"No Ethical Consumption in General Equilibrium? Evidence from the U.S. meat market" (with T. Woolley)