Modelling the effect of rural electrification on employment via component-wise boosted causal distributional regression

• Guillermo Briseño Sánchez ^[1] ; Andreas Groll
  1. [1] TU Dortmund University
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 25-30
• Idioma: inglés
• Enlaces
  • Texto Completo Libro
• Resumen

  • This work is concerned with addressing the issue of variable selection in high-dimensional distributional regression models employed for causal inference. We regularise a Two-Stage Generalised Additive Model for Location, Scale, and Shape (2SGAMLSS) using component-wise gradient boosting in order to obtain a sparse model to assess the causal effect of rural electrification on female and male employment rates using socio-demographic data from South Africa.