A New Estimator for Multivariate Binary Data

Shengfei Fu and J Shonkwiler

No 204963, 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California from Agricultural and Applied Economics Association

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.

Keywords: Agricultural and Food Policy; Consumer/Household Economics; Environmental Economics and Policy; Institutional and Behavioral Economics; Marketing; Research Methods/ Statistical Methods (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-dcm and nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea15:204963

DOI: 10.22004/ag.econ.204963

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