Full-information Bayesian Estimation of Cross-sectional Sample Selection Models

Abstract

This chapter proposes an approach toward the estimation of cross-sectional sample selection models, where the shocks on the units of observation feature some interdependence through spatial or network autocorrelation. In particular, this chapter improves on prior Bayesian work on this subject by proposing a modified approach toward sampling the multivariate-truncated, cross-sectionally dependent latent variable of the selection equation. This chapter outlines the model and implementation approach and provides simulation results documenting the better performance of the proposed approach relative to existing ones.

Citation

Ding, S. and Egger, P.H. (2020), "Full-information Bayesian Estimation of Cross-sectional Sample Selection Models", de Paula, Á., Tamer, E. and Voia, M.-C. (Ed.) The Econometrics of Networks (Advances in Econometrics, Vol. 42), Emerald Publishing Limited, Leeds, pp. 205-234. https://doi.org/10.1108/S0731-905320200000042013