03.1.1. Deriving the Observed Information Matrix in Ordered Probit and Logit Models Using the Complete-Data Likelihood Function

S.K. Sapra

Econometric Theory, 2003, vol. 19, issue 01, pages 225-225

Abstract: Louis (1982) presents a method for computing the observed information matrix and standard errors of maximum likelihood estimates obtained via the EM algorithm based on the complete-data log likelihood function. The problem illustrates the well-known method of Louis (1982) for a widely used qualitative response model in econometrics. The observed-data log likelihood function for the following model can, of course, be easily differentiated to obtain the observed information matrix; our objective is to illustrate the method and not to recommend its use for this model.

Date: 2003

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Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:19:y:2003:i:01:p:225-225_21

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