A Bayesian nonparametric modelling to estimate student response to ICT investment
Stefano Cabras and
Juan de Dios Tena ()
DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de Estadística
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.
Keywords: ICT; BART; Causality; Bayesian; Statistics; Regression; trees (search for similar items in EconPapers)
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Journal Article: A Bayesian non-parametric modeling to estimate student response to ICT investment (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:ws143020
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