We propose a way to compute the hedging Delta using the Malliavin weight method. Our approach, which we name the l-method, generally outperforms the standard Monte Carlo finite difference method, especially for discontinuous payoffs. Furthermore, our approach is nonparametric, as we only assume...

We propose an optimal-transport-based matching method to nonparametrically estimate linear models with independent latent variables. The method consists in generating pseudo-observations from the latent variables, so that the Euclidean distance between the model's predictions and their matched...

The standard regression discontinuity (RD) design deals with a binary treatment. Manyempirical applications of RD designs involve continuous treatments. This paper establishesidentification and robust bias-corrected inference for such RD design. Causal identificationis achieved by utilizing any...

I propose a nonparametric structural estimator for the distribution of liquidity needs in a version of the Diamond and Dybvig (1983) model when only the aggregate level of withdrawals is observed. The model is an extension of Peck and Shell (2003) with a continuum of depositors. I show how the...

We revisit the classical problem of price elasticity estimation from a causal perspective. When the price is perceived as a continuous but endogenous treatment, the flexible estimation of price elasticity can be turned into the estimation of heterogeneous treatment effects. To this end, we...

This paper studies a dynamic discrete choice model including an unobservable state, which evolves by a hidden action of agents. First, this paper shows new nonparametric identification results for observable and unobservable conditional choice probabilities (CCPs) and an initial type probability...