Obtaining analytic derivatives for a popular discrete-choice dynamic programming model

We show how to recursively calculate analytic first and second derivatives of the likelihood for a popular discrete-choice, dynamic programming model. These allow for decreased computing time, and are useful for de-bugging complicated program code and accurately estimating standard errors.

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Year of publication:	2008
Authors:	Eberwein, Curtis ; Ham, John C.
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 101.2008, 3, p. 168-171
Publisher:	Elsevier
Keywords:	Derivatives Dynamic programming Structural estimation Computation Standard errors

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005296818