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Gaussian Quadrature Versus Simulation for the Estimation of Random Parameters

Some Evidence from Stated-Preference Choice Data
  • William S. Breffle
  • Edward Morey
  • Donald Waldman
Chapter
Part of the The Economics of Non-Market Goods and Resources book series (ENGO, volume 6)

Abstract

In environmental economics, numerical simulation using random draws is the method most commonly used to estimate joint probabilities of individual choices in discrete-choice, random-parameters models. This paper compares simulation to another method of estimation, Gaussian quadrature, on the basis of speed and accuracy. The comparison is done using stated preference data consisting of the answers to choice questions for fishing in Green Bay, a large bay on Lake Michigan. Each sampled individual chose between a pair of Green Bay scenarios with different fishing conditions. Quadrature is found to be as accurate as simulation based on random draws, but Gaussian quadrature attains stability in estimated parameters considerably faster.

Keywords

Gaussian Hermite quadrature random parameters discrete-choice model recreational fishing fish consumption advisories 

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Copyright information

© Springer 2005

Authors and Affiliations

  • William S. Breffle
    • 2
  • Edward Morey
    • 1
  • Donald Waldman
    • 1
  1. 1.Department of EconomicsUniversity of ColoradoUSA
  2. 2.Stratus Consulting Inc.BoulderUSA

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