Modelling commuting time in the US: Bootstrapping techniques to avoid overfitting

Gimenez-Nadal, José Ignacio (Universidad de Zaragoza) ; Molina, José Alberto (Universidad de Zaragoza) ; Velilla, Jorge (Universidad de Zaragoza)

Resumen: The research on commuting has emerged in recent decades, but the issue of whether the empirical techniques used are appropriate has not been analysed. Thus, results from prior research could be based on non-accurate models, leading to misleading conclusions. We apply an algorithmic approach based on bootstrapping, variable selection, and mean absolute prediction errors, which is designed to avoid overfitting. Using the American Time Use Survey, we find that models with a reduced set of explanatory variables have similar accuracy to standard econometric models. Our results shed light on the importance of determining whether models can be overfitted.

Idioma: Inglés

DOI: 10.1111/pirs.12424

Año: 2019

Publicado en: Papers in Regional Science 98, 4 (2019), 1667-1684
ISSN: 1056-8190

Factor impacto JCR: 2.22 (2019)

Categ. JCR: GEOGRAPHY rank: 37 / 84 = 0.44 (2019) - Q2 - T2
Categ. JCR: ECONOMICS rank: 96 / 371 = 0.259 (2019) - Q2 - T1
Categ. JCR: REGIONAL & URBAN PLANNING rank: 23 / 39 = 0.59 (2019) - Q3 - T2
Categ. JCR: ENVIRONMENTAL STUDIES rank: 68 / 123 = 0.553 (2019) - Q3 - T2

Factor impacto SCIMAGO: 0.91 - Geography, Planning and Development (Q1) - Environmental Science (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/S32-17R

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Fund. Análisis Económico (Dpto. Análisis Económico)