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What can we learn about correlations from multinomial probit estimates?

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  • C. Monfardini
  • J.M.C. Santos Silva

Abstract

It is well known that, in a multinomial probit, only the covariance matrix of the location and scale normalized utilities are identified. In this study, we explore the relation between these identifiable parameters and the original elements of the covariance matrix, to find out what can be learnt about the correlations between the stochastic components of the non-normalized utilities. We show that, in certain circumstances, it is possible to obtain information on these behavioural parameters and define appropriate tools for inference. We illustrate the usefulness of our results in applied settings using an example.

Suggested Citation

  • C. Monfardini & J.M.C. Santos Silva, 2006. "What can we learn about correlations from multinomial probit estimates?," Working Papers 558, Dipartimento Scienze Economiche, Universita' di Bologna.
    • Handle: RePEc:bol:bodewp:558
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    References listed on IDEAS

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    1. Peter Hansen, 2003. "Asymptotic Tests of Composite Hypotheses," Working Papers 2003-09, Brown University, Department of Economics.
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