An Extended Single Index Model with Missing Response at Random
SFB 649 Discussion Paper 2014-003
32 Pages Posted: 5 Jan 2017
Date Written: January 2, 2017
Abstract
An extended single-index model is considered when responses are missing at random. A three-step estimation procedure is developed to define an estimator for the single index parameter vector by a joint estimating equation. The proposed estimator is shown to be asymptotically normal. An iterative scheme for computing this estimator is proposed. This algorithm only involves one-dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Some simulation study is conducted to investigate the finite sample performances of the pro- posed estimators.
Keywords: Missing data, Estimating equations, Single-index models, Asymptotic normality
JEL Classification: J99, E20
Suggested Citation: Suggested Citation