A nonparametric procedure for quantile regression, or more generally nonparametric M-estimation, is proposed which is completely data-driven and adapts locally to the regularity of the regression function. This is achieved by considering in each point M-estimators over different local...

We analyze the properties of non- and semiparametric estimation procedures involving nonparametric regression with generated covariates. Such estimators appear in numerous econometric applications, including nonparametric estimation of simultaneous equation models, sample selection models,...

Principal component analysis denotes a popular algorithmic technique to dimension reduction and factor extraction. Spatial variants have been proposed to account for the particularities of spatial data, namely spatial heterogeneity and spatial autocorrelation, and we present a novel approach...

The quality of newly constructed single-family houses is usually homogeneous in and heterogeneous between neighborhoods. Such quality-clustering will be caused by the variation of natural amenities throughout a suburban area. Clustering will be enforced if the quality of neighboring buildings...

In many applications, covariates are not observed but have to be estimated from data. We outline some regression-type models where such a situation occurs and discuss estimation of the regression function in this context.We review theoretical results on how asymptotic properties of nonparametric...

In this paper, we study a general class of semiparametric optimization estimators of a vector-valued parameter. The criterion function depends on two types of innite-dimensional nuisance parameters: a conditional expectation function that has been estimated nonparametrically using generated...

Due to dependency of energy demand on temperature, weather derivatives enable the effective hedging of temperature related fluctuations. However, temperature varies in space and time and therefore the contingent weather derivatives also vary. The spatial derivative price distribution involves a...

We study a general class of semiparametric estimators when the innite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametri- cally using generated covariates. Such estimators are used frequently to e.g. estimate nonlinear models with...

The distribution of treatment eects extends the prevailing focus on average treatment eects to the tails of the outcome variable and quantile treatment eects denote the predominant technique to compute those eects in the presence of a confounding mechanism. The underlying quantile regression is...

The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the...