Distributional regression models that overcome the traditional focus on relating the
conditional mean of the response to explanatory variables and instead target either the …

The performance of economic producers is often affected by external or environmental
factors that, unlike the inputs and the outputs, are not under the control of the Decision …

We describe the R np package via a series of applications that may be of interest to applied
econometricians. The np package implements a variety of nonparametric and …

The majority of empirical research in economics ignores the potential benefits of
nonparametric methods, while the majority of advances in nonparametric theory ignores the …

We study the problem of learning a real-valued function that satisfies the Demographic
Parity constraint. It demands the distribution of the predicted output to be independent of the …

We extend the linear quantile regression with a neural network structure to enable more
flexibility in every quantile of the bank loan loss given default distribution. This allows us to …

We suggest quantile regression methods for a class of smooth coefficient time series
models. We use both local polynomial and local constant fitting schemes to estimate the …

This review is a primer for those who wish to familiarize themselves with nonparametric
econometrics. Though the underlying theory for many of these methods can be daunting for …

Efficiency estimations which do not account for the operational environment where
production units are operating in may have only a limited value. This article presents a fully …

Empirical growth regressions typically include mean years of schooling as a proxy for
human capital. However, empirical research often finds that the sign and significance of …