A latent segmentation approach to a Kuhn-Tucker model: An application to recreation demand

Koichi Kuriyama, W. Michael Hanemann, James R. Hilger

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


In this paper, we extend the latent segmentation approach to the Kuhn-Tucker (KT) model. The proposed approach models heterogeneity in preferences for recreational behavior, using a utility theoretical framework to simultaneously model participation and site selection decisions. Estimation of the latent segmentation KT model with standard maximum likelihood techniques is numerically difficult because of the large number of parameters in the segment membership functions and the utility function for each latent segment. To address this problem, we propose the expectation-maximization (EM) algorithm to estimate the model. In the empirical section, we implement the EM latent segmentation KT approach to analyze a Southern California beach recreation data set. Our empirical analysis suggests that three groups exist in the sample. Using the model to analyze two hypothetical beach management policy scenarios illustrates different welfare impacts across groups.

Original languageEnglish (US)
Pages (from-to)209-220
Number of pages12
JournalJournal of Environmental Economics and Management
Issue number3
StatePublished - Nov 2010
Externally publishedYes


  • Beach recreation
  • Demand system
  • EM algorithms
  • Welfare analysis

ASJC Scopus subject areas

  • Economics and Econometrics
  • Management, Monitoring, Policy and Law


Dive into the research topics of 'A latent segmentation approach to a Kuhn-Tucker model: An application to recreation demand'. Together they form a unique fingerprint.

Cite this