The COVID-19 pandemic constitutes one of the largest threats in recent decades to the health and economic welfare of populations globally. In this paper, we analyze different types of policy measures designed to fight the spread of the virus and minimize economic losses. Our analysis builds on a...

The COVID-19 pandemic constitutes one of the largest threats in recent decades to the health and economic welfare of populations globally. In this paper, we analyze different types of policy measures designed to fight the spread of the virus and minimize economic losses. Our analysis builds on a...

Due to the increasing availability of high-dimensional empirical applications in many research disciplines, valid simultaneous inference becomes more and more important. For instance, high-dimensional settings might arise in economic studies due to very rich data sets with many potential...

Big Data stellt Unternehmen vor die Herausforderung, Daten zur Weiterentwicklung des Geschäftsmodells zu verwenden und dabei auf modernste ökonomische und statistische Methoden zu setzen. Damit Unternehmensentscheidungen langfristig zum Geschäftserfolg beitragen, kommt der Kausalität eine...

Heterogeneous effects are prevalent in many economic settings. As the functional form between outcomes and regressors is generally unknown a priori, a semiparametric negative binomial count data model is proposed which is based on the local likelihood approach and generalized product kernels....

Heterogeneous effects are prevalent in many economic settings. As the functional form between outcomes and regressors is generally unknown a priori, a semiparametric negative binomial count data model is proposed which is based on the local likelihood approach and generalized product kernels....

Here we present an expository, general analysis of valid post-selection or post-regularization inference about a low-dimensional target parameter in the presence of a very high-dimensional nuisance parameter which is estimated using selection or regularization methods. Our analysis provides a...

In this article the package High-dimensional Metrics (hdm) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for...