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

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

Abstract

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.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Environmental Economics and Management.

Volume (Year): 60 (2010)
Issue (Month): 3 (November)
Pages: 209-220

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Handle: RePEc:eee:jeeman:v:60:y:2010:i:3:p:209-220

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Web page: http://www.elsevier.com/locate/inca/622870

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Keywords: Welfare analysis Demand system EM algorithms Beach recreation;

References

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  1. Herriges, Joseph A. & Kling, Catherine L. & Phaneuf, Daniel J., 2004. "What's the Use? Welfare Estimates from Revealed Preference Models when Weak Complementarity Does Not Hold," Staff General Research Papers, Iowa State University, Department of Economics 1905, Iowa State University, Department of Economics.
  2. Paul A. Ruud., 1988. "Extensions of Estimation Methods Using the EM Algorithm.," Economics Working Papers, University of California at Berkeley 8899, University of California at Berkeley.
  3. von Haefen, Roger H., 2007. "Empirical strategies for incorporating weak complementarity into consumer demand models," Journal of Environmental Economics and Management, Elsevier, Elsevier, vol. 54(1), pages 15-31, July.
  4. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 39(8), pages 679-707, September.
  5. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 35(7), pages 677-693, August.
  6. Herriges, Joseph A. & Kling, Catherine L. & Phaneuf, Daniel J., 1999. "Corner Solution Models of Recreation Demand: A Comparison of Competing Frameworks," Staff General Research Papers, Iowa State University, Department of Economics 1513, Iowa State University, Department of Economics.
  7. Stephen Hynes & Nick Hanley & Riccardo Scarpa, 2008. "Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 90(4), pages 1011-1027.
  8. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521747387.
  9. Bill Provencher & Kenneth A. Baerenklau & Richard C. Bishop, 2002. "A Finite Mixture Logit Model of Recreational Angling with Serially Correlated Random Utility," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, Agricultural and Applied Economics Association, vol. 84(4), pages 1066-1075.
  10. Daniel J. Phaneuf & Catherine L. Kling & Joseph A. Herriges, 2000. "Estimation and Welfare Calculations in a Generalized Corner Solution Model with an Application to Recreation Demand," The Review of Economics and Statistics, MIT Press, MIT Press, vol. 82(1), pages 83-92, February.
  11. von Haefen, Roger H. & Phaneuf, Daniel J., 2003. "Estimating preferences for outdoor recreation:: a comparison of continuous and count data demand system frameworks," Journal of Environmental Economics and Management, Elsevier, Elsevier, vol. 45(3), pages 612-630, May.
  12. von Haefen, Roger H., 2000. "Incorporating Observed Choice In The Construction Of Welfare Measures From Random Utility Models," 2000 Annual meeting, July 30-August 2, Tampa, FL, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) 21836, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  13. von Haefen R.H. & Phaneuf D.J. & Parsons G.R., 2004. "Estimation and Welfare Analysis With Large Demand Systems," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 22, pages 194-205, April.
  14. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, European Association of Environmental and Resource Economists, European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
  15. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, Elsevier, vol. 21(3), pages 263-285, April.
  16. Phaneuf, Daniel J. & Smith, V. Kerry, 2006. "Recreation Demand Models," Handbook of Environmental Economics, Elsevier, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 15, pages 671-761 Elsevier.
  17. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, MIT Press, vol. 68(4), pages 715-19, November.
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Citations

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Cited by:
  1. Sobhani, Anae & Eluru, Naveen & Faghih-Imani, Ahmadreza, 2013. "A latent segmentation based multiple discrete continuous extreme value model," Transportation Research Part B: Methodological, Elsevier, Elsevier, vol. 58(C), pages 154-169.
  2. Koichi Kuriyama & James Hilger & Michael Hanemann, 2013. "A Random Parameter Model with Onsite Sampling for Recreation Site Choice: An Application to Southern California Shoreline Sportfishing," Environmental & Resource Economics, European Association of Environmental and Resource Economists, European Association of Environmental and Resource Economists, vol. 56(4), pages 481-497, December.
  3. Taro Ohdoko & Kentaro Yoshida, 2012. "Public preferences for forest ecosystem management in Japan with emphasis on species diversity," Environmental Economics and Policy Studies, Society for Environmental Economics and Policy Studies - SEEPS, Society for Environmental Economics and Policy Studies - SEEPS, vol. 14(2), pages 147-169, April.

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