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Welfare Estimation Using Aggregate and Individual-Observations Models: A Comparison Using Monte Carlo Techniques

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  • Hellerstein, Daniel

Abstract

Due to the weak behavioral foundations of aggregate demand models, zonal travel cost models have been largely abandoned in favor of models based on individual observations. However, sample selection difficulties in individual-observation models often require the use of distribution-sensitive limited-dependent variables estimators. In this paper I use Monte-Carlo simulations to investigate whether the bias from aggregation is worse than possible bias from these narrowly specified estimators. Somewhat surprisingly, the results indicate that zonal models often outperform the individual-observation models, especially when using an aggregate model that incorporates intrazonal variance of the explanatory variables.

Suggested Citation

  • Hellerstein, Daniel, 1995. "Welfare Estimation Using Aggregate and Individual-Observations Models: A Comparison Using Monte Carlo Techniques," MPRA Paper 25267, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:25267
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    1. Shaw, Daigee, 1988. "On-site samples' regression : Problems of non-negative integers, truncation, and endogenous stratification," Journal of Econometrics, Elsevier, vol. 37(2), pages 211-223, February.
    2. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
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    Cited by:

    1. Shumway, C. Richard & Davis, George C., 2001. "Does consistent aggregation really matter?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(2), pages 1-34.
    2. Scrogin, David, 2005. "Lottery-rationed public access under alternative tariff arrangements: changes in quality, quantity, and expected utility," Journal of Environmental Economics and Management, Elsevier, vol. 50(1), pages 189-211, July.
    3. de Frutos, Pablo & Rodríguez-Prado, Beatriz & Latorre, Joaquín & Martínez-Peña, Fernando, 2019. "Environmental valuation and management of wild edible mushroom picking in Spain," Forest Policy and Economics, Elsevier, vol. 100(C), pages 177-187.
    4. Eva Vicente & Pablo de Frutos, 2011. "Application of the travel cost method to estimate the economic value of cultural goods: Blockbuster art exhibitions," Hacienda Pública Española / Review of Public Economics, IEF, vol. 196(1), pages 37-63, january.
    5. Phaneuf, Daniel James, 1997. "Generalized corner solution models in recreation demand," ISU General Staff Papers 1997010108000013022, Iowa State University, Department of Economics.
    6. Mooney, Sian & Antle, John M. & Capalbo, Susan Marie & Paustian, Keith H., 2003. "Incorporating Uncertainty In Integrated Assessment Modeling," 2003 Annual meeting, July 27-30, Montreal, Canada 22225, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. K. Willis & J. Snowball & C. Wymer & José Grisolía, 2012. "A count data travel cost model of theatre demand using aggregate theatre booking data," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 36(2), pages 91-112, May.
    8. Malte Grossmann, 2011. "Impacts of boating trip limitations on the recreational value of the Spreewald wetland: a pooled revealed/contingent behaviour application of the travel cost method," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 54(2), pages 211-226.
    9. Marini Govigli, Valentino & Górriz-Mifsud, Elena & Varela, Elsa, 2019. "Zonal travel cost approaches to assess recreational wild mushroom picking value: Trade-offs between online and onsite data collection strategies," Forest Policy and Economics, Elsevier, vol. 102(C), pages 51-65.
    10. Yoder, Jonathan K. & Ohler, Adrienne M. & Chouinard, Hayley H., 2014. "What floats your boat? Preference revelation from lotteries over complex goods," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 412-430.
    11. Moeltner, Klaus, 2003. "Addressing aggregation bias in zonal recreation models," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 128-144, January.
    12. Qinghua Liu & C. Richard Shumway, 2004. "Testing aggregation consistency across geography and commodities," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(3), pages 463-486, September.
    13. Akbar Marvasti, 2010. "A welfare estimation of beach recreation with aggregate data," Applied Economics, Taylor & Francis Journals, vol. 42(3), pages 291-296.
    14. Kenneth A. Baerenklau, 2010. "A Latent Class Approach to Modeling Endogenous Spatial Sorting in Zonal Recreation Demand Models," Land Economics, University of Wisconsin Press, vol. 86(4), pages 800-816.
    15. P. Poor & Jamie Smith, 2004. "Travel Cost Analysis of a Cultural Heritage Site: The Case of Historic St. Mary's City of Maryland," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 28(3), pages 217-229, August.
    16. Mayer, Marius & Woltering, Manuel, 2018. "Assessing and valuing the recreational ecosystem services of Germany’s national parks using travel cost models," Ecosystem Services, Elsevier, vol. 31(PC), pages 371-386.
    17. Sandström, Mikael, 1996. "Recreational Benefits from Improved Water Quality: A Random Utility Model of Swedish Seaside Recreation," SSE/EFI Working Paper Series in Economics and Finance 121, Stockholm School of Economics.
    18. Baerenklau, Kenneth A. & González-Cabán, Armando & Paez, Catrina & Chavez, Edgar, 2010. "Spatial allocation of forest recreation value," Journal of Forest Economics, Elsevier, vol. 16(2), pages 113-126, April.

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    More about this item

    Keywords

    aggregation bias; individual-observation models; zonal models.;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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