… of econometrics to the machine learning community, our aim here was to present
concepts and tools developed over time by that very community and which may be of use to …

… We present a way of thinking about machine learning that gives it its own place in the
econometric toolbox. Machine learning not only provides new tools, it solves a different problem. …

… editing this volume of contributions to econometrics and machine learning. This is a remarkably
… The holy grail of quantitative economics/econometrics research in the last 100 years has …

… than traditional econometric models. In this paper, several machine learning methods that
are … This paper further investigates the various Supervised machine learning techniques that …

… of the recent machine learning (ML) literature for economics and econometrics. First we …
between the ML literature and the traditional econometrics and statistics literatures. Then we …

… in combining econometrics with machine learning in research… by saying “when economics
meets machine learning”. We will … by saying “combining econometrics into machine learning”. …

… and contrasting ML with traditional econometrics tools for causal … in econometrics and statistics
combining machine learning … both ML and statistics/ econometrics. Finally, I step back and …

… contrast machine learning (ML) and structural econometrics (… on dynamic structural
econometrics at the University of … of Structural Dynamic Models and Machine Learning'. ML offers …

… This article provided a detailed overview of the architecture of econometric and machine
learning models. We discussed the various investment applications of each type of framework, …

… 5For machine learning to offer meaningful results in science, … of guarantees that comes with
machine learning results: the … debate on the role of machine learning for (social) science, this …