Alfred Galichon

This paper derives conditions under which preferences and technology are nonparametrically identified in hedonic equilibrium models, where products are differentiated along more than one dimension and agents are characterized by several dimensions of unobserved heterogeneity.

We propose a notion of conditional vector quantile function and a vector quantile regression.

The authors propose a notion of conditional vector quantile function and a vector quantile regression.

The authors propose new concepts of statistical depth, multivariate quantiles, vector quantiles and ranks, ranks, and signs, based on canonical transportation maps between a distribution of interest on Rd and a reference distribution on the d-dimensional unit ball.

We propose new concepts of statistical depth, multivariate quantiles, ranks and signs, based on canonical transportation maps between a distribution of interest on IRd and a reference distribution on the d-dimensional unit ball.

The authors propose a notion of conditional vector quantile function and a vector quantile regression.

The most common approach to estimating conditional quantile curves is to fit a curve, typically linear, pointwise for each quantile.

This paper applies a regularization procedure called increasing rearrangement to monotonize Edgeworth and Cornish-Fisher expansions and any other related approximations of distribution and quantile functions of sample statistics.

The authors show that these estimates can always be improved with no harm using rearrangement techniques.

A cemmap working paper.

A cemmap working paper.

A cemmap working paper.