000			01057nam a2200193 4500
005			20260113125101.0
008			260113b |||||||| |||| 00| 0 eng d
020			_a9780198918837
037			_cTextual
040			_aRTL _cRTL
084			_qRTL
100			_aGaillac, Christophe _9864165
245			_aMachine learning for econometrics
260			_aNew York _bOxford University Press _c2025
300			_axiv, 338 p. _bIncludes bibliographical reference and index
520			_aMachine Learning for Econometrics is a book for economists seeking to grasp modern machine learning techniques - from their predictive performance to the revolutionary handling of unstructured data - in order to establish causal relationships from data. The volume covers automatic variable selection in various high-dimensional contexts, estimation of treatment effect heterogeneity, natural language processing (NLP) techniques, as well as synthetic control and macroeconomic forecasting.
700			_aL`Hour, Jeremy _eCo-author _9864166
942			_2CC _n0 _cTEXL
999			_c1467584 _d1467584