A Bayesian nonparametric modelling to estimate student response to ICT investment

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dc.contributor.author Cabras, Stefano
dc.contributor.author Tena Horrillo, Juan de Dios
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2015-01-21T18:44:33Z
dc.date.available 2015-01-21T18:44:33Z
dc.date.issued 2014-12
dc.identifier.issn 2387-0303
dc.identifier.uri http://hdl.handle.net/10016/19916
dc.description.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.
dc.description.sponsorship Juan de Dios Tena acknowledges financial support from the Spanish Ministry of Education and Science, research project ECO2012-32401
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 14-20
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Regression trees
dc.subject.other Causality
dc.subject.other ICT
dc.subject.other Bayesian Statistics
dc.subject.other BART
dc.title A Bayesian nonparametric modelling to estimate student response to ICT investment
dc.type workingPaper
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. ECO2012-32401
dc.type.version submitedVersion
dc.identifier.uxxi DT/0000001317
dc.identifier.repec ws143020
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