01979    a2200181   4500003000400000005001700004008004100021020001800062100002200080245003900102260003800141300001100179440006100190520146400251650003601715650002101751700002501772OSt20260324171647.0230703b           ||||| |||| 00| 0 eng d  a9783031151484  aChan, Felix 4ed.  aEconometrics with machine learning  aSwitzerland: bSpringer, c2022.   a371p.   aAdvanced Studies in Theoretical and Applied Econometrics  aThis book helps and promotes the use of machine learning tools and techniques in econometrics and explains how machine learning can enhance and expand the econometrics toolbox in theory and in practice. 
Throughout the volume, the authors raise and answer six questions: 1) What are the similarities between existing econometric and machine learning techniques? 2) To what extent can machine learning techniques assist econometric investigation? Specifically, how robust or stable is the prediction from machine learning algorithms given the ever-changing nature of human behavior? 3) Can machine learning techniques assist in testing statistical hypotheses and identifying causal relationships in ‘big data? 4) How can existing econometric techniques be extended by incorporating machine learning concepts? 5) How can new econometric tools and approaches be elaborated on based on machine learning techniques? 6) Is it possible to develop machine learning techniques further and make them even more readily applicable in econometrics?
As the data structures in economic and financial data become more complex and models become more sophisticated, the book takes a multidisciplinary approach in developing both disciplines of machine learning and econometrics in conjunction, rather than in isolation. This volume is a must-read for scholars, researchers, students, policy-makers, and practitioners, who are using econometrics in theory or in practice.  aEconometrics -- Data processing  aMachine learning  aMatyas, Laszlo 4ed.