IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/218721.html
   My bibliography  Save this article

Generating reliable tourist accommodation statistics: Bootstrapping regression model for overdispersed long-tailed data

Author

Listed:
  • Van Truong, Nguyen
  • Shimizu, Tetsuo
  • Choi, Sunkyung

Abstract

Purpose: Few studies have applied count data analysis to tourist accommodation data. This study was undertaken to investigate the characteristics and to seek for the most fitting models for population total estimation in relation to tourist accommodation data. Methods: Based on the data of 10,503 hotels, obtained from by a nationwide Japanese survey, the bootstrap resampling method was applied for re-randomisation of the data. Training and test sets were derived by randomly splitting each of the bootstrap samples. Six count models were fitted to the training set and validated with the test set. Bootstrap distributions for parameters of significance were used for model evaluation. Results: The outcome variable (number of guests), was found to be heterogenous, over dispersed and long-tailed, with excessive zero counts. The hurdle negative binomial and zero-inflated negative binomial models outperformed the other models. The accuracy (se) of the estimation of total guests with training sets that ranged from 5% to 85%, was from 3.7 to 0.4 respectively. Results appear rather overestimated. Implications: Findings indicated that the integration of the bootstrap resampling method and count regression provide a statistical tool for generating reliable tourist accommodation statistics. The use of bootstrap would help to detect and correct the bias of the estimation.

Suggested Citation

  • Van Truong, Nguyen & Shimizu, Tetsuo & Choi, Sunkyung, 2020. "Generating reliable tourist accommodation statistics: Bootstrapping regression model for overdispersed long-tailed data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 6(2), pages 30-37.
    • Handle: RePEc:zbw:espost:218721
    DOI: 10.5281/zenodo.3835847
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/218721/1/6-2-4.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5281/zenodo.3835847?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
    ---><---

    References listed on IDEAS

    as
    1. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    2. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    3. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    4. Gergaud, Olivier & Livat, Florine & Song, Haiyan, 2018. "Terrorism and Wine Tourism: The Case of Museum Attendance," Journal of Wine Economics, Cambridge University Press, vol. 13(4), pages 375-383, November.
    5. Duarte, R. & Escario, J.J., 2006. "Alcohol abuse and truancy among Spanish adolescents: A count-data approach," Economics of Education Review, Elsevier, vol. 25(2), pages 179-187, April.
    6. Shrestha, Ram K. & Seidl, Andrew F. & Moraes, Andre S., 2002. "Value of recreational fishing in the Brazilian Pantanal: a travel cost analysis using count data models," Ecological Economics, Elsevier, vol. 42(1-2), pages 289-299, August.
    7. A. Georges Assaf & Frank W. Agbola, 2011. "Modelling the Performance of Australian Hotels: A DEA Double Bootstrap Approach," Tourism Economics, , vol. 17(1), pages 73-89, February.
    8. Chou, Ming Che, 2013. "Does tourism development promote economic growth in transition countries? A panel data analysis," Economic Modelling, Elsevier, vol. 33(C), pages 226-232.
    9. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    10. Chen, Rong & Fomby, Thomas B, 1999. "Forecasting with Stable Seasonal Pattern Models with an Application to Hawaiian Tourism Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 497-504, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Del Chiappa, Giacomo & Bregoli, Ilenia & Fotiadis, Anestis K., 2021. "The impact of COVID-19 on Italian accommodation: A supply-perspective," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 7(1), pages 13-22.
    2. Diunugala, Hemantha Premakumara & Mombeuil, Claudel, 2020. "Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods," MPRA Paper 103779, University Library of Munich, Germany.

    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. Majo, M.C., 2010. "A microeconometric analysis of health care utilization in Europe," Other publications TiSEM 1cf5fd2f-8146-4ef8-8eb5-e, Tilburg University, School of Economics and Management.
    2. João Cotter Salvado, 2008. "The Determinants of Health Care Utilization in Portugal: An Approach with Count Data Models," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(III), pages 437-458, September.
    3. Sergi Jiménez‐Martín & José M. Labeaga & Maite Martínez‐Granado, 2002. "Latent class versus two‐part models in the demand for physician services across the European Union," Health Economics, John Wiley & Sons, Ltd., vol. 11(4), pages 301-321, June.
    4. Óscar Lourenço & Carlota Quintal & Pedro Lopes Ferreira & Pedro Pita Barros, 2007. "A equidade na utilização de cuidados de saúde em Portugal: Uma avaliação baseada em modelos de contagem," Notas Económicas, Faculty of Economics, University of Coimbra, issue 25, pages 6-26, June.
    5. Prayaga, Prabha, 2017. "Estimating the value of beach recreation for locals in the Great Barrier Reef Marine Park, Australia," Economic Analysis and Policy, Elsevier, vol. 53(C), pages 9-18.
    6. Majo, M.C. & van Soest, A.H.O., 2011. "The Fixed-Effects Zero-Inflated Poisson Model with an Application to Health Care Utilization," Other publications TiSEM 68cf0f9b-fc68-4017-97a9-a, Tilburg University, School of Economics and Management.
    7. McLeod, Logan, 2011. "A nonparametric vs. latent class model of general practitioner utilization: Evidence from Canada," Journal of Health Economics, Elsevier, vol. 30(6), pages 1261-1279.
    8. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    9. Daniele Fabbri & Chiara Monfardini, 2016. "Opt Out or Top Up? Voluntary Health Care Insurance and the Public vs. Private Substitution," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(1), pages 75-93, February.
    10. Jie Q. Guo & Pravin K. Trivedi, 2002. "Flexible Parametric Models for Long‐tailed Patent Count Distributions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(1), pages 63-82, February.
    11. Alegre, Joaquín & Mateo, Sara & Pou, Llorenç, 2011. "A latent class approach to tourists’ length of stay," Tourism Management, Elsevier, vol. 32(3), pages 555-563.
    12. Richard Layte & Anne Nolan, 2015. "Eligibility for free GP care and the utilisation of GP services by children in Ireland," International Journal of Health Economics and Management, Springer, vol. 15(1), pages 3-27, March.
    13. Bago d'Uva, Teresa & Jones, Andrew M. & van Doorslaer, Eddy, 2009. "Measurement of horizontal inequity in health care utilisation using European panel data," Journal of Health Economics, Elsevier, vol. 28(2), pages 280-289, March.
    14. Kurt Lavetti & Thomas DeLeire & Nicolas R. Ziebarth, 2023. "How do low‐income enrollees in the Affordable Care Act marketplaces respond to cost‐sharing?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(1), pages 155-183, March.
    15. José Solana-Ibáñez & Manuel Caravaca-Garratón & Lorena Para-González, 2016. "Two-Stage Data Envelopment Analysis of Spanish Regions: Efficiency Determinants and Stability Analysis," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 10(3), September.
    16. Martin Schellhorn & Andreas E. Stuck & Christoph E. Minder & John C. Beck, 2000. "Health services utilization of elderly Swiss: evidence from panel data," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 533-545, September.
    17. José Murteira & Óscar Lourenço, 2011. "Health care utilization and self-assessed health: specification of bivariate models using copulas," Empirical Economics, Springer, vol. 41(2), pages 447-472, October.
    18. Dardanoni, Valentino & Li Donni, Paolo, 2012. "Incentive and selection effects of Medigap insurance on inpatient care," Journal of Health Economics, Elsevier, vol. 31(3), pages 457-470.
    19. Teresa Bago d'Uva, 2006. "Latent class models for utilisation of health care," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 329-343, April.
    20. Claudio Detotto & Manuela Pulina & Juan Brida, 2014. "Assessing the productivity of the Italian hospitality sector: a post-WDEA pooled-truncated and spatial analysis," Journal of Productivity Analysis, Springer, vol. 42(2), pages 103-121, October.

    More about this item

    Keywords

    tourism statistics; bootstrap; econometrics; over dispersed data; zero-inflated data;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • L8 - Industrial Organization - - Industry Studies: Services
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • Z3 - Other Special Topics - - Tourism Economics

    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:zbw:espost:218721. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    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.