Publication:
A Bayesian nonparametric modelling to estimate student response to ICT investment

Thumbnail Image
Identifiers
URI: https://hdl.handle.net/10016/19916
ISSN: 2387-0303
UXXI: DT/0000001317
Files
ws143020.pdf (689.09 KB)
Publication date
2014-12
Defense date
Authors
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Impact
Google Scholar
Export
Research Projects
Organizational Units
Journal Issue
Abstract
This paper estimates the causal impact of investment in information andcommunication technologies (ICT) on student performances in mathematics asmeasured in the Program for International Student Assessment (PISA) 2012 for Spain.To do this we apply a new methodology in this context known as Bayesian AdditiveRegression Trees (BART) that has important advantages over more standardparametric specifications. Results indicate that ICT has a moderate positive effect onmath scores. In addition, we analyze how this effect interacts with variables related toschool features and student socioeconomic status, finding that ICT investment isespecially beneficial for students from a low socioeconomic background.
Description
Keywords
Regression trees, Causality, ICT, Bayesian Statistics, BART
Bibliographic citation
Collections
DES - Working Papers. Statistics and Econometrics. WS