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

Sophia Ding and Peter Egger

A chapter in The Econometrics of Networks, 2020, vol. 42, pp 205-234 from Emerald Group Publishing Limited

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.

Keywords: Sample selection models; spatial econometrics; network econometrics; Bayesian econometrics; cross-section models; full information estimators; C11; C31; C34 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320200000042013

DOI: 10.1108/S0731-905320200000042013

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