Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

Nonparametric instrumental variable (NPIV) estimation is a cutting‐edge methodological framework employed to uncover causal relationships in the presence of endogenous regressors, without imposing ...

Two forms of CoVaR have recently been introduced in the literature for measuring systemic risk, differing on whether or not the conditioning is on a set of measure zero. We focus on the former, and ...

The covariance matrix of asset returns is the key input for many problems in finance and economics. This paper introduces a Bayesian nonparametric method to estimate the ex post covariance matrix from ...

We study a nonparametric deconvolution density estimation problem. The estimator is obtained by an EM algorithm for a smoothed maximum likelihood estimation problem, which has a unique continuous ...

A brief description of the methods used by the SYSLIN procedure follows. For more information on these methods, see the references at the end of this chapter. There are two fundamental methods of ...