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The impact of commuting time over educational achievement: A machine learning approach

Dante Contreras (), Daniel Hojman, Manuel Matas, Patricio Rodríguez and Nicolás Suárez

Working Papers from University of Chile, Department of Economics

Abstract: Taking advantage of georeferenced data from Chilean students, we estimate the impact of commuting time over academic achievement. As the commuting time is an endogenous variable, we use instrumental variables and fixed effects at school level to overcome this problem. Also, as we don’t know which mode of transport the students use, we complement our analysis using machine learning methods to predictthe transportation mode. Our findings suggest that the commuting time has a negative effect over academic performance, but this effect is not always significant.

New Economics Papers: this item is included in nep-big, nep-cmp, nep-tre and nep-ure
Date: 2018-11
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