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Predictive Validity Under Partial Observability

  • Eduardo Alarcón-BustamanteEmail author
  • Ernesto San Martín
  • Jorge González
Conference paper
  • 113 Downloads
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 322)

Abstract

To assess the predictive capacity of selection tests is a challenge because the response variable is observed only in selected individuals. In this paper we propose to evaluate the predictive capacity of selection tests through marginal effects under a partial identification approach. Identification bounds are defined for the marginal effects under monotonicity assumptions of the response variable. The performance of our method is assessed using a real data set from the university selection test applied in Chile and compared with the marginal effect of the traditional model used in Chile to evaluate the predictive capacity of the selection test.

Keywords

Selection problem Marginal effects Partial identification Identification bounds 

Notes

Acknowledgements

Eduardo Alarcón-Bustamante was funded by CONICYT Doctorado Nacional grant 2018-21181007. Ernesto San Martín was partially funded by the FONDECYT grant 1181261.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Eduardo Alarcón-Bustamante
    • 1
    • 2
    Email author
  • Ernesto San Martín
    • 1
    • 2
    • 3
  • Jorge González
    • 4
  1. 1.Department of Statistics, Faculty of MathematicsPontificia Universidad Católica de ChileSantiagoChile
  2. 2.Interdisciplinary Laboratory of Social StatisticsSantiagoChile
  3. 3.The Economics School of LouvainUniversité Catholique de LouvainOttignies-Louvain-la-NeuveBelgium
  4. 4.Facultad de MatematicasPontificia Universidad Católica de ChileSantiagoChile

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