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Does Economic Endogeneity of Site Facilities in Recreation Demand Models Lead to Statistical Endogeneity?

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  • Chen, Min
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    Abstract

    Random Utility Models of recreation demand are widely used to relate demand and value to the characteristics of recreation sites. Although some kinds of endogeneity problems have been studied in previous literature, no study has addressed the potential problem with site characteristics that are endogenously supplied. Some site characteristics, like facilities, could be endogenous in an economic sense due to the interplay of supply and demand. That is, more popular recreation sites tend to have better site characteristics since managers with limited budgets would be more willing to invest in them. If recreation site improvements are more likely to occur at the more popular sites, then this economic endogeneity might cause problems for econometric models linking site demand to facilities. In this paper, we use Monte Carlo simulations to investigate under what situations this economic endogeneity will lead to statistical endogeneity.

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    Paper provided by Michigan State University, Department of Agricultural, Food, and Resource Economics in its series Graduate Research Masters Degree Plan B Papers with number 55808.

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    Date of creation: 2009
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    Handle: RePEc:ags:midagr:55808

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    Keywords: Random Utility Maximization models; Facilities; Endogeneity; Monte Carlo simulations; Environmental Economics and Policy; Q51;

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    1. Timothy C. Haab & Robert L. Hicks, . "Accounting for Choice Set Endogeneity in Random Utility Models of Recreation Demand," Working Papers 9710, East Carolina University, Department of Economics.
    2. Chia-Yu Yeh & Timothy Haab & Brent Sohngen, 2006. "Modeling Multiple-Objective Recreation Trips with Choices Over Trip Duration and Alternative Sites," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 34(2), pages 189-209, 06.
    3. W. Bowman Cutter & Linwood Pendleton & J. R. DeShazo, 2007. "Activities in Models of Recreational Demand," Land Economics, University of Wisconsin Press, vol. 83(3), pages 370-381.
    4. von Haefen, Roger H. & Phaneuf, Daniel J., 2008. "Identifying demand parameters in the presence of unobservables: A combined revealed and stated preference approach," Journal of Environmental Economics and Management, Elsevier, vol. 56(1), pages 19-32, July.
    5. P. Geoffrey Allen & Thomas H. Stevens & Scott A. Barrett, 1981. "The Effects of Variable Omission in the Travel Cost Technique," Land Economics, University of Wisconsin Press, vol. 57(2), pages 173-180.
    6. Wetzel, James N., 1977. "Estimating the benefits of recreation under conditions of congestion," Journal of Environmental Economics and Management, Elsevier, vol. 4(3), pages 239-246, September.
    7. Murdock, Jennifer, 2006. "Handling unobserved site characteristics in random utility models of recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 51(1), pages 1-25, January.
    8. Kling, Catherine L., 1988. "Comparing Welfare Estimates of Environmental Quality Changes from Recreation Demand Models," Staff General Research Papers 1584, Iowa State University, Department of Economics.
    9. McConnell, K. E. & Duff, Virginia A., 1976. "Estimating net benefits of recreation under conditions of excess demand," Journal of Environmental Economics and Management, Elsevier, vol. 2(3), pages 224-230, February.
    10. Timmins, Christopher & Murdock, Jennifer, 2007. "A revealed preference approach to the measurement of congestion in travel cost models," Journal of Environmental Economics and Management, Elsevier, vol. 53(2), pages 230-249, March.
    11. Lew, Daniel K. & Larson, Douglas M., 2005. "Accounting for stochastic shadow values of time in discrete-choice recreation demand models," Journal of Environmental Economics and Management, Elsevier, vol. 50(2), pages 341-361, September.
    12. Roger H. von Haefen & D. Matthew Massey & Wiktor L. Adamowicz, 2005. "Serial Nonparticipation in Repeated Discrete Choice Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1061-1076.
    13. Brian W. Gould, 2003. "An Empirical Assessment of Endogeneity Issues in Demand Analysis for Differentiated Products," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(3), pages 605-617.
    14. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
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