This paper consider penalized empirical loss minimization of convex loss functions with unknown non-linear target functions. Using the elastic net penalty we establish a finite sample oracle inequality which bounds the loss of our estimator from above with high probability. If the unknown target...

This paper develops a unified framework for fixed and random effects estimation of higher-order spatial autoregressive panel data models with spatial autoregressive disturbances and heteroskedasticity of unknown form in the idiosyncratic error component. We derive the moment conditions and...

This article aims to analyze the implications of economic integration policies in the convergence or the divergence process among developing countries according to their regional membership. In other words, does or does not regional integration induce the intra- or inter-zone convergence? What...

New empirical models of consumer demand that incorporate social preferences, observational learning, word-of-mouth or network effects have the feature that the adoption of others in the reference group - the Òinstalled-baseÓ - has a causal effect on current adoption behavior. Estimation of...

The moment conditions or estimating equations for instrumental variables quantile regression involves the discontinuous indicator function. We instead use smoothed estimating equations, with bandwidth h. This is known to allow higher-order expansions that justify bootstrap refinements for...

While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models....

An asymptotic theory is developed for nonparametric and semiparametric series estimation under general cross-sectional dependence and heterogeneity. A uniform rate of consistency, asymptotic normality, and sufficient conditions for convergence, are established, and a data-driven studentization...

Dealing with endogenous regressors is a central challenge of applied research. The standard solution is to use instrumental variables that are assumed to be uncorrelated with unobservables. We instead allow the instrumental variable to be correlated with the error term, but we assume the...

In this paper we explore the application of Generalised Additive Models of Location, Scale and Shape for the analysis of conditional income distributions in Germany following the reunification. We find that conditional income distributions can generally be modelled using the three parameter...

Since conventional cross-validation bandwidth selection methods do not work for the case where the data considered are serially dependent, alternative bandwidth selection methods are needed. In recent years, Bayesian based global bandwidth selection methods have been proposed. Our experience...