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Microeconometric Strategies for Dealing with Unobservables and Endogenous Variables in Recreation Demand Models

Author

Listed:
  • Klaus Moeltner

    (Department of Agricultural and Applied Economics, Virginia Tech, Blacksburg, Virginia 24061)

  • Roger von Haefen

    (Department of Agricultural and Resource Economics, North Carolina State University, Raleigh, North Carolina 27695
    National Bureau of Economic Research, Cambridge, Massachusetts 02138)

Abstract

The past decade has witnessed significant advances in the microeconometric analysis of recreation data. In this review, we focus on two areas in which these innovations have been especially prolific: accounting for unobserved preference heterogeneity and controlling for unobserved and possibly endogenous site characteristics, such as congestion. Failure to appropriately address these issues with the nonlinear models typically used in recreation demand analysis can severely bias parameter and welfare estimates. We consider these issues of widespread importance within and beyond recreation demand applications. We also expect these estimation challenges to become more ubiquitous as the field gradually moves toward region-wide, multisite applications in reaction to large-scale environmental changes.

Suggested Citation

  • Klaus Moeltner & Roger von Haefen, 2011. "Microeconometric Strategies for Dealing with Unobservables and Endogenous Variables in Recreation Demand Models," Annual Review of Resource Economics, Annual Reviews, vol. 3(1), pages 375-396, October.
    • Handle: RePEc:anr:reseco:v:3:y:2011:p:375-396
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    File URL: http://www.annualreviews.org/doi/abs/10.1146/annurev.resource.012809.103916
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    Citations

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    Cited by:

    1. Kuwayama, Yusuke & Olmstead, Sheila & Zheng, Jiameng, 2022. "A more comprehensive estimate of the value of water quality," Journal of Public Economics, Elsevier, vol. 207(C).
    2. Richard T. Melstrom & Deshamithra H. W. Jayasekera, 2017. "Two-Stage Estimation to Control for Unobservables in a Recreation Demand Model with Unvisited Sites," Land Economics, University of Wisconsin Press, vol. 93(2), pages 328-341.
    3. English, Eric & von Haefen, Roger H. & Herriges, Joseph & Leggett, Christopher & Lupi, Frank & McConnell, Kenneth & Welsh, Michael & Domanski, Adam & Meade, Norman, 2018. "Estimating the value of lost recreation days from the Deepwater Horizon oil spill," Journal of Environmental Economics and Management, Elsevier, vol. 91(C), pages 26-45.
    4. Juan M. Gonzalez Sepulveda & F. Reed Johnson & Deborah A. Marshall, 2021. "Incomplete information and irrelevant attributes in stated‐preference values for health interventions," Health Economics, John Wiley & Sons, Ltd., vol. 30(11), pages 2637-2648, November.
    5. H. Allen Klaiber & Roger H. von Haefen, 2019. "Do Random Coefficients and Alternative Specific Constants Improve Policy Analysis? An Empirical Investigation of Model Fit and Prediction," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(1), pages 75-91, May.
    6. David A. Keiser & Joseph K. Shapiro, 2018. "Consequences of the Clean Water Act and the Demand for Water Quality," Center for Agricultural and Rural Development (CARD) Publications 17-wp571, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    7. David A. Keiser, 2018. "The Missing Benefits of Clean Water and the Role of Mismeasured Pollution," Center for Agricultural and Rural Development (CARD) Publications 18-wp581, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    8. David A Keiser & Joseph S Shapiro, 2019. "Consequences of the Clean Water Act and the Demand for Water Quality," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(1), pages 349-396.
    9. Keiser, David A., 2018. "The Missing Benefits of Clean Water and the Role of Mismeasured Pollution," ISU General Staff Papers 201806290700001048, Iowa State University, Department of Economics.
    10. Wiktor L. Adamowicz & Klaus Glenk & Jürgen Meyerhoff, 2014. "Choice modelling research in environmental and resource economics," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 27, pages 661-674, Edward Elgar Publishing.
    11. Melstrom, Richard & Lupi, Frank, 2012. "Using a Control Function to Resolve the Travel Cost Endogeneity Problem in Recreation Demand Models," MPRA Paper 48036, University Library of Munich, Germany, revised May 2013.

    More about this item

    Keywords

    preference heterogeneity; random effects; latent class models; endogenous sorting; Bayesian methods; expectation-maximum algorithm;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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