Title: Identification in multivariate partial observability probit

Authors: Dale J. Poirier

Addresses: Department of Economics, University of California, 3151 SSPA, Irvine, CA 9697-5100, USA

Abstract: Poirier (1980) considered a bivariate probit model in which the binary dependent variables y1 and y2 of a bivariate probit model were not observed individually, but the product z = y1 • y2 was observed. This paper expands this notion of partial observability to multivariate settings.

Keywords: multivariate settings; partial observability probit; Bayesian; latent; pairwise; trivariate.

DOI: 10.1504/IJMMNO.2014.059945

International Journal of Mathematical Modelling and Numerical Optimisation, 2014 Vol.5 No.1/2, pp.45 - 63

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 20 Mar 2014 *

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