IDEAS home Printed from https://ideas.repec.org/a/eee/resene/v84y2025ics0928765525000594.html

Sampling of alternatives in spatial decision contexts with logit and logit mixture models: Simulation and application to freshwater recreation in Germany

Author

Listed:
  • Becker, Oliver
  • Börger, Tobias
  • Meyerhoff, Jürgen

Abstract

Destination choice modeling is challenging as the number of feasible sites is often very large. Sampling of alternatives has been used successfully to make large choice sets manageable and yields consistent estimates under certain conditions. However, the specific structure of destination choice data has rarely been addressed explicitly. Besides large numbers of alternatives, it is characterized by a skewed distribution of travel costs with few low-cost nearby sites and a disproportionate increase in alternatives with distance. In this paper, we investigate how this characteristic travel cost structure affects the quality of destination choice models estimated on samples of alternatives. Comparing uniform and strategic sampling (Lemp and Kockelman, 2012), we find that (i) strategic sampling reduces bias and improves efficiency relative to uniform sampling, (ii) sampling performance generally declines with stronger travel cost sensitivity, and (iii) the gains from strategic sampling increase as travel cost sensitivity becomes stronger. For multinomial logit, strategic sampling yields high levels of accuracy and precision when drawing as few as 10 out of 20,000 alternatives. For mixed logit, bias is higher, while the protocol still offers substantial performance gains. After presenting Monte Carlo evidence, we apply both sampling approaches to a nationwide freshwater recreation dataset and examine their impact on welfare estimates for two policy scenarios, as well as on bias and efficiency.

Suggested Citation

  • Becker, Oliver & Börger, Tobias & Meyerhoff, Jürgen, 2025. "Sampling of alternatives in spatial decision contexts with logit and logit mixture models: Simulation and application to freshwater recreation in Germany," Resource and Energy Economics, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:resene:v:84:y:2025:i:c:s0928765525000594
    DOI: 10.1016/j.reseneeco.2025.101535
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0928765525000594
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.reseneeco.2025.101535?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. George R. Parsons & GAndrew J. Plantinga & GKevin J. Boyle, 2000. "Narrow Choice Sets in a Random Utility Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 76(1), pages 86-99.
    2. Agimass, Fitalew & Lundhede, Thomas & Panduro, Toke Emil & Jacobsen, Jette Bredahl, 2018. "The choice of forest site for recreation: A revealed preference analysis using spatial data," Ecosystem Services, Elsevier, vol. 31(PC), pages 445-454.
    3. Robert L. Hicks & Ivar E. Strand, 2000. "The Extent of Information: Its Relevance for Random Utility Models," Land Economics, University of Wisconsin Press, vol. 76(3), pages 374-385.
    4. Klaus Glenk & Robert J. Johnston & Jürgen Meyerhoff & Julian Sagebiel, 2020. "Spatial Dimensions of Stated Preference Valuation in Environmental and Resource Economics: Methods, Trends and Challenges," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(2), pages 215-242, February.
    5. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    6. David Scrogin & Richard Hofler & Kevin Boyle & J. Walter Milon, 2010. "An efficiency approach to choice set formation: theory and application to recreational destination choice," Applied Economics, Taylor & Francis Journals, vol. 42(3), pages 333-350.
    7. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    8. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    9. Tardieu, Léa & Tuffery, Laëtitia, 2019. "From supply to demand factors: What are the determinants of attractiveness for outdoor recreation?," Ecological Economics, Elsevier, vol. 161(C), pages 163-175.
    10. George R. Parsons & A. Brett Hauber, 1998. "Spatial Boundaries and Choice Set Definition in a Random Utility Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 74(1), pages 32-48.
    11. Krinsky, Itzhak & Robb, A Leslie, 1990. "On Approximating the Statistical Properties of Elasticities: A Correction," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 189-190, February.
    12. Andrew Daly & Stephane Hess & Kenneth Train, 2012. "Assuring finite moments for willingness to pay in random coefficient models," Transportation, Springer, vol. 39(1), pages 19-31, January.
    13. Léa Tardieu & Laetitia Tufféry, 2019. "From supply to demand factors : what are the determinants of attractiveness for outdoor recreation?," Post-Print hal-02883545, HAL.
    14. Hicks, Robert L. & Schnier, Kurt E., 2008. "Eco-labeling and dolphin avoidance: A dynamic model of tuna fishing in the Eastern Tropical Pacific," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 103-116, September.
    15. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
    16. Dekker, Thijs & Bansal, Prateek & Huo, Jinghai, 2025. "Revisiting McFadden’s correction factor for sampling of alternatives in multinomial logit and mixed multinomial logit models," Transportation Research Part B: Methodological, Elsevier, vol. 192(C).
    17. Lemp, Jason D. & Kockelman, Kara M., 2012. "Strategic sampling for large choice sets in estimation and application," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 602-613.
    18. Peter M. Feather, 1994. "Sampling and Aggregation Issues in Random Utility Model Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(4), pages 772-780.
    19. Jens Abildtrup & Søren Bøye Olsen & Anne Stenger, 2015. "Combining RP and SP data while accounting for large choice sets and travel mode - an application to forest recreation," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 4(2), pages 177-201, July.
    20. George R. Parsons & Mary Jo Kealy, 1992. "Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation," Land Economics, University of Wisconsin Press, vol. 68(1), pages 93-106.
    21. von Haefen, Roger H. & Domanski, Adam, 2018. "Estimation and welfare analysis from mixed logit models with large choice sets," Journal of Environmental Economics and Management, Elsevier, vol. 90(C), pages 101-118.
    22. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    23. Czajkowski, Mikołaj & Budziński, Wiktor, 2019. "Simulation error in maximum likelihood estimation of discrete choice models," Journal of choice modelling, Elsevier, vol. 31(C), pages 73-85.
    24. Mette Termansen & Colin J McClean & Hans Skov-Petersen, 2004. "Recreational Site Choice Modelling Using High-Resolution Spatial Data," Environment and Planning A, , vol. 36(6), pages 1085-1099, June.
    25. Tsoleridis, Panagiotis & Choudhury, Charisma F. & Hess, Stephane, 2022. "Utilising activity space concepts to sampling of alternatives for mode and destination choice modelling of discretionary activities," Journal of choice modelling, Elsevier, vol. 42(C).
    26. Jooyoung Kim & Seungjae Lee, 2017. "Comparative analysis of traveler destination choice models by method of sampling alternatives," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(4), pages 465-478, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. von Haefen, Roger H. & Domanski, Adam, 2018. "Estimation and welfare analysis from mixed logit models with large choice sets," Journal of Environmental Economics and Management, Elsevier, vol. 90(C), pages 101-118.
    2. Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).
    3. Phaneuf, Daniel J. & Smith, V. Kerry, 2006. "Recreation Demand Models," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 15, pages 671-761, Elsevier.
    4. Agimass, Fitalew & Lundhede, Thomas & Panduro, Toke Emil & Jacobsen, Jette Bredahl, 2018. "The choice of forest site for recreation: A revealed preference analysis using spatial data," Ecosystem Services, Elsevier, vol. 31(PC), pages 445-454.
    5. Hicks, Robert L. & Schnier, Kurt E., 2010. "Spatial regulations and endogenous consideration sets in fisheries," Resource and Energy Economics, Elsevier, vol. 32(2), pages 117-134, April.
    6. Stafford, Tess M., 2018. "Accounting for outside options in discrete choice models: An application to commercial fishing effort," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 159-179.
    7. Backstrom, Jesse D. & Woodward, Richard T., "undated". "Using Qualitative Site Characteristics Data in Marine Recreational Fishing Models: A New Site Aggregation Approach," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258276, Agricultural and Applied Economics Association.
    8. von Haefen, Roger H., 2003. "Incorporating observed choice into the construction of welfare measures from random utility models," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 145-165, March.
    9. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    10. J. DeShazo & Trudy Cameron & Manrique Saenz, 2009. "The Effect of Consumers’ Real-World Choice Sets on Inferences from Stated Preference Surveys," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 319-343, March.
    11. Li, Lianhua & Adamowicz, Wiktor & Swait, Joffre, 2015. "The effect of choice set misspecification on welfare measures in random utility models," Resource and Energy Economics, Elsevier, vol. 42(C), pages 71-92.
    12. de Ayala, Amaia & Hoyos, David & Mariel, Petr, 2015. "Suitability of discrete choice experiments for landscape management under the European Landscape Convention," Journal of Forest Economics, Elsevier, vol. 21(2), pages 79-96.
    13. Waleska Sigüernza & Petr Mariel, 2013. "Valoración económica de los servicios sanitarios en la Comunidad Autónoma del País Vasco," Hacienda Pública Española / Review of Public Economics, IEF, vol. 207(4), pages 71-99, December.
    14. John N. Ng’ombe & B. Wade Brorsen, 2022. "The Effect of Including Irrelevant Alternatives in Discrete Choice Models of Recreation Demand," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 71-97, June.
    15. Hutniczak, Barbara & Münch, Angela, 2018. "Fishermen's location choice under spatio-temporal update of expectations," Journal of choice modelling, Elsevier, vol. 28(C), pages 124-136.
    16. Daziano, Ricardo A. & Achtnicht, Martin, 2014. "Accounting for uncertainty in willingness to pay for environmental benefits," Energy Economics, Elsevier, vol. 44(C), pages 166-177.
    17. Dekker, Thijs & Bansal, Prateek & Huo, Jinghai, 2025. "Revisiting McFadden’s correction factor for sampling of alternatives in multinomial logit and mixed multinomial logit models," Transportation Research Part B: Methodological, Elsevier, vol. 192(C).
    18. Termansen, Mette & McClean, Colin J. & Jensen, Frank Søndergaard, 2013. "Modelling and mapping spatial heterogeneity in forest recreation services," Ecological Economics, Elsevier, vol. 92(C), pages 48-57.
    19. Mariel, Petr & Meyerhoff, Jürgen, 2018. "A More Flexible Model or Simply More Effort? On the Use of Correlated Random Parameters in Applied Choice Studies," Ecological Economics, Elsevier, vol. 154(C), pages 419-429.
    20. Angel Bujosa & Antoni Riera & Robert Hicks, 2010. "Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(4), pages 477-493, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • Q25 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Water
    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:resene:v:84:y:2025:i:c:s0928765525000594. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/505569 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.