Nonparametric regression methods provide an alternative approach to parametric
estimation that requires only weak identification assumptions and thus minimizes the risk of …

CoVaR is a measure for systemic risk of the networked financial system conditional on
institutions being under distress. The analysis of systemic risk is the focus of recent …

We develop a practical and novel method for inference on intersection bounds, namely
bounds defined by either the infimum or supremum of a parametric or nonparametric …

The EFM approach for single-index models Page 1 The Annals of Statistics 2011, Vol. 39,
No. 3, 1658–1688 DOI: 10.1214/10-AOS871 © Institute of Mathematical Statistics, 2011 THE …

Quantile regression (QR) is a principal regression method for analyzing the impact of
covariates on outcomes. The impact is described by the conditional quantile function and its …

We analyze the statistical properties of nonparametric regression estimators using
covariates which are not directly observable, but have be estimated from data in a …

Models with single-index structures are among the many existing popular semiparametric
approaches for either the conditional mean or the conditional variance. This paper focuses …

This paper presents estimation methods and asymptotic theory for the analysis of a
nonparametrically specified conditional quantile process. Two estimators based on local …

This paper investigates the bias and the weak Bahadur representation of a local polynomial
estimator of the conditional quantile function and its derivatives. The bias and Bahadur …

An estimator of a finite-dimensional parameter is said to be doubly robust (DR) if it imposes
parametric specifications on two unknown nuisance functions, but only requires that one of …