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Abstract
This study proposes a new estimator for multivariate binary response data. This study
considers binary responses as being generated from a truncated multivariate discrete distribution.
Specifically the discrete normal probability mass function, which has support on all
integers, is extended to a multivariate form. Truncating this point probability mass function
below zero and above one results the multivariate binary discrete normal distribution. This
distribution has a number of attractive properties. Monte Carlo simulation and empirical
applications are performed to show the properties of this new estimator; comparisons are made to the
traditional multivariate probit model.