1 citations · 1 across the 11 of their papers we have counts for
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GARP-EFM: Improving Foundation Models with Revealed Preference Structure
Victor H. Aguiar, Nail Kashaev
Modern pretrained time-series foundation models can forecast without task-specific training, but they do not fully incorporate economic behavior. We show that teaching them basic e…
Discrete Choice with Endogenous Peer Selection
Nail Kashaev, Natalia Lazzati
We develop a continuous time discrete choice model of peer effects. The distinctive feature of the model is that agents might not consider all peers at the moment of making a decis…
Discerning Solution Concepts
Nail Kashaev, Bruno Salcedo
The empirical analysis of discrete complete-information games has relied on behavioral restrictions in the form of solution concepts, such as Nash equilibrium. Choosing the right s…
Identification and Estimation of Discrete Choice Models with Unobserved Choice Sets
Victor H. Aguiar, Nail Kashaev
We propose a framework for nonparametric identification and estimation of discrete choice models with unobserved choice sets. We recover the joint distribution of choice sets and p…
Peer Effects in Random Consideration Sets
Nail Kashaev, Natalia Lazzati
We develop a dynamic model of discrete choice that incorporates peer effects into random consideration sets. We characterize the equilibrium behavior and study the empirical conten…
Identification and estimation of multinomial choice models with latent special covariates
Nail Kashaev
Identification of multinomial choice models is often established by using special covariates that have full support. This paper shows how these identification results can be extend…
Stochastic Revealed Preferences with Measurement Error
Victor H. Aguiar, Nail Kashaev
A long-standing question about consumer behavior is whether individuals' observed purchase decisions satisfy the revealed preference (RP) axioms of the utility maximization theory…
Prices, Profits, Proxies, and Production
Victor H. Aguiar, Nail Kashaev, Roy Allen
This paper studies nonparametric identification and counterfactual bounds for heterogeneous firms that can be ranked in terms of productivity. Our approach works when quantities an…