We propose a Bayesian nonparametric instrumental variable approach that allows us to correct for endogeneity bias in regression models where the covariate effects enter with unknown functional form. Bias correction relies on a simultaneous equations speci cation with flexible modeling of the...

Recently, the World Bank re-estimated the international poverty line used for global poverty measurement and the first Millennium Development Goal based on an updated country sample of national poverty lines and new results for PPP exchange rates. This generated the new international poverty...

This article proposes a simple and fast approach to build simultaneous confi dence bands and perform specification tests for smooth curves in additive models. The method allows for handling of spatially heterogeneous functions and its derivatives as well as heteroscedasticity in the data. It is...

This paper investigates the finite sample performance of a comprehensive set of semi- and nonparametric estimators for treatment and policy evaluation. In contrast to previous simulation studies which mostly considered semiparametric approaches relying on parametric propensity score estimation,...

In this paper, we critically review conceptual and empirical issues surrounding the derivation of the international poverty line, expressed in PPP-adjusted dollars and linked to various rounds of the International Comparison of Prices (ICP). We find that there are some limitations in the current...

Response functions that link regression predictors to properties of the response distribution are fundamental components in many statistical models. However, the choice of these functions is typically based on the domain of the modeled quantities and is usually not further scrutinized. For...

The ongoing digital transformation has raised hopes for ICT-based climate protection within manufacturing industries, such as dematerialized products and energy efficiency gains. However, ICT also consume energy as well as resources, and detrimental effects on the environment are increasingly...

Gaussian Structured Additive Regression provides a flexible framework for additive decomposition of the expected value with nonlinear covariate effects and time trends, unit- or cluster-specific heterogeneity, spatial heterogeneity, and complex interactions between covariates of different types....