Inference in Conditional Moment Restriction Models When there is Selection Due to Stratification

We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference
in models characterized as conditional moment equalities when data is collected by variable probability sampling.
Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate
the model parameters very well in small to moderately sized stratified samples.