The impact of commuting time over educational achievement: A machine learning approach
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Contreras Guajardo, Dante
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The impact of commuting time over educational achievement: A machine learning approach
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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 predict
the transportation mode. Our findings suggest that the commuting time has a negative effect over
academic performance, but this effect is not always significant.
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We thank professors Alejandra Mizala, Valentina Paredes, Jaime Ruiz-Tagle, Sergio Urzúa and the assistants to the
internal seminars of the Department of Economics for their valuable comments. Nicolás Suárez thanks professors Dante
Contreras and Daniel Hojman for their guidance in his thesis project, and he acknowledges the financial support provided by
the National Commission of Research in Science and Technology (CONICYT). National Master’s Scholarship 2017-22171231.
†Department of Economics, Faculty of Economics and Business, Universidad de Chile.
‡Center for Advanced Research in Education (CIAE), Universidad de Chile
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URI: https://repositorio.uchile.cl/handle/2250/153416
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Series Documentos de Trabajo No. 472, pp. 1 - 39, Noviembre, 2018
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