Calendrier du 11 septembre 2023
Roy Seminar (ADRES)
Du 11/09/2023 de 17:00 à 18:15
Salle R1-09, Campus Jourdan, 75014 Paris
LANZANI Giacomo (UC Berkeley)
*Selective Memory Equilibrium, with Drew Fudenberg and Philipp Strack
We study agents who are more likely to remember some experiences than others but update beliefs as if the experiences they remember are the only ones that occurred. We show that if the agent’s behavior converges, their limit strategy is a selective memory equilibrium. We illustrate how this new equilibrium concept can be used to understand the long-run effects of several well-documented memory biases. We then extend our analysis to cases where the expected number of recalled experiences is bounded. Here we characterize the long-run action frequencies that can arise.
Econometrics Seminar
Du 11/09/2023 de 16:15 à 17:30
PSE, Campus Jourdan, R1-14
TETENOV Aleksey (University of Geneva)
Constrained Classification and Policy Learning
écrit avec Co-authors: Toru Kitagawa and Shosei Sakaguchi
Modern machine learning approaches to classification, including AdaBoost, support vector machines, and deep neural networks, utilize surrogate loss techniques to circumvent the computational complexity of minimizing empirical classification risk. These techniques are also useful for causal policy learning problems, since estimation of individualized treatment rules can be cast as a weighted (cost-sensitive) classification problem. Consistency of the surrogate loss approaches studied in Zhang (2004) and Bartlett et al. (2006) relies on the assumption of correct specification, which means that the specified set of classifiers is rich enough to contain a first-best classifier. This assumption is, however, less credible when the set of classifiers is constrained by interpretability or fairness, leaving the applicability of surrogate loss-based algorithms unknown in such second-best scenarios. This paper studies consistency of surrogate loss procedures under a constrained set of classifiers without assuming correct specification. We show that in settings where the constraint restricts the classifier’s prediction set only, hinge losses (i.e., l1-support vector machines) are the only surrogate losses that preserve consistency in second-best scenarios. If the constraint additionally restricts the functional form of the classifier, consistency of a surrogate loss approach is not guaranteed, even with hinge loss. We therefore characterize conditions on the constrained set of classifiers that can guarantee consistency of hinge risk minimizing classifiers. Exploiting our theoretical results, we develop robust and computationally attractive hinge loss-based procedures for a monotone classification problem.
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Régulation et Environnement
Du 11/09/2023 de 12:00 à 13:30
R1-09
WENZ Leonie (PIK)
The economic commitment of climate change
Global projections of macroeconomic climate-change damages typically consider impacts from average annual and national temperatures over long-time horizons. Here, we utilize recent empirical findings from more than 1600 regions worldwide over the past 40 years to project sub-national damages from temperature and precipitation including daily variability and extremes. Using an empirical approach which provides a robust lower-bound on the persistence of impacts on economic growth, we find that the world economy is committed to an income reduction of 19% within the next 26 years due to historical carbon emissions and socioeconomic inertia (relative to a baseline without climate impacts, likely range of 11-29% accounting for physical climate and empirical uncertainty). These damages already outweigh the mitigation costs required to limit global warming to two degrees by sixfold over this near-term timeframe, and thereafter diverge strongly dependent on emission choices. Committed damages arise predominantly through changes in average temperature, but accounting for further climatic components raises estimates by approximately fifty percent and leads to stronger regional heterogeneity. Committed losses are projected for all regions except those at very high latitudes, where reductions in temperature variability bring benefits. The largest losses are committed at lower latitudes in regions with lower cumulative historical emissions and lower present-day income.