A double machine learning approach to estimate the effects of musical practice on student's skills.

Autor/in	Knaus, Michael C.
Institution	Forschungsinstitut zur Zukunft der Arbeit
Titel	A double machine learning approach to estimate the effects of musical practice on student's skills.
Quelle	Bonn: Forschungsinstitut zur Zukunft der Arbeit (2018), 71 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Reihe	IZA Discussion paper. 11547
Beigaben	Literaturangaben
Sprache	englisch
Dokumenttyp	online; Monographie
Schlagwörter	Kompetenz; Kognitive Kompetenz; Jugend; Schulnote; Lernen; Außerschulisches Lernen; Musik; Musizieren; Computerunterstütztes Verfahren; Entwicklung; Jugendlicher; NEPS (National Educational Panel Study)
Abstract	This study investigates the dose-response effects of making music on youth development. Identification is based on the conditional independence assumption and estimation is implemented using a recent double machine learning estimator. The study proposes solutions to two highly practically relevant questions that arise for these new methods: (i) How to investigate sensitivity of estimates to tuning parameter choices in the machine learning part? (ii) How to assess covariate balancing in high-dimensional settings? The results show that improvements in objectively measured cognitive skills require at least medium intensity, while improvements in school grades are already observed for low intensity of practice. (Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2021/2