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

Curtis Eberwein and John Ham

Economics Letters, 2008, vol. 101, issue 3, 168-171

Abstract: 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.

Keywords: Derivatives; Dynamic; programming; Structural; estimation; Computation; Standard; errors (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (3)

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