Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146974 | Journal of Multivariate Analysis | 2009 | 20 Pages |
Abstract
This paper shows how the generalised empirical likelihood method can be used to obtain valid asymptotic inference for the finite dimensional component of semiparametric models defined by a set of moment conditions. The results of the paper are illustrated using three well-known semiparametric regression models: partially linear single index, linear transformation with random censoring, and quantile regression with random censoring. Monte Carlo simulations suggest that some of the proposed test statistics have competitive finite sample properties. The results of the paper are applied to test for functional misspecification in a hedonic price model of a housing market.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Francesco Bravo,