We show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are 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.
We thank two anonymous referees and seminar participants at the 2017 “Econometrics of Complex Survey Data: Theory and Applications” workshop organized by the Bank of Canada, Ottawa, Canada, for helpful comments. The simulation experiments reported in this paper were carried out using the HPC facilities of the University of Luxembourg (Varrette et al., 2014, http://hpc.uni.lu).
Cosma, A., Kostyrka, A.V. and Tripathi, G. (2019), "Inference in Conditional Moment Restriction Models When there is Selection Due to Stratification", The Econometrics of Complex Survey Data (Advances in Econometrics, Vol. 39), Emerald Publishing Limited, pp. 137-171. https://doi.org/10.1108/S0731-905320190000039010Download as .RIS
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