Forschungsthema
Title of Project: Successive sample selection and its relevance for management decisions
Keywords: Bayesian estimation, Targeting, Cross sectional analysis, Scoring,
Causal reasoning
We investigate models for data generated by successive selection or filtering, and implied decisions. Such data are ubiquitous in marketing. For example, a data base may contain prospective customers that were targeted through direct mail, prospective customers that have responded favorably to the direct mail, asking for additional information, customers that already purchased, and customers that already purchased repeatedly. We developed a model that handles correlated unobservables across multiple stages of successive sample selection.
