A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student’s Skills
Journal
Journal of the Royal Statistical Society Series A (Statistics in Society)
Type
journal article
Date Issued
2021-01
Author(s)
Abstract (De)
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.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SEPS - Quantitative Economic Methods
Refereed
Yes
Volume
184
Number
1
Start page
282
End page
300
Subject(s)
Division(s)
Eprints ID
260954