IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v16y2009i7p653-656.html
   My bibliography  Save this article

Hotel tax receipts and the 'Midnight in the Garden of Good and Evil': a time series intervention seasonal ARIMA model with time-varying variance

Author

Listed:
  • Michael Toma
  • Richard McGrath
  • James Payne

Abstract

This study examines the influence of the release of a best-selling book and movie, Midnight in the Garden of Good and Evil, set in Savannah, Georgia on local tourism demand. Tourism demand is proxied by revenue collected from an ad valorem hotel room tax in Savannah. The hotel tax revenue series is first modelled as a seasonal ARIMA model with three intervention variables: an index variable to capture the influence of the best-selling book and two dummy variables to represent the impact of the 9/11 terrorist attacks and hurricane Floyd. The presence of time-varying variance in the residuals is captured through an ARCH model. The results indicate that the book index had a positive and significant impact on hotel tax receipts, while the dummy variables for the terrorist attacks of 9/11 and hurricane Floyd were each negative with only the dummy variable for hurricane Floyd marginally significant.

Suggested Citation

  • Michael Toma & Richard McGrath & James Payne, 2009. "Hotel tax receipts and the 'Midnight in the Garden of Good and Evil': a time series intervention seasonal ARIMA model with time-varying variance," Applied Economics Letters, Taylor & Francis Journals, vol. 16(7), pages 653-656.
    • Handle: RePEc:taf:apeclt:v:16:y:2009:i:7:p:653-656
    DOI: 10.1080/13504850701221808
    as

    Download full text from publisher

    File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/13504850701221808&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504850701221808?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Song, Haiyan & Witt, Stephen F. & Jensen, Thomas C., 2003. "Tourism forecasting: accuracy of alternative econometric models," International Journal of Forecasting, Elsevier, vol. 19(1), pages 123-141.
    3. Vinod Agarwal & Gilbert Yochum, 1998. "Tourism and advertising: Evidence from Virginia beach," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 4(4), pages 384-397, November.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    5. Carl Bonham & Byron Gangnes, 1995. "Intervention Analysis with Cointegrated Time Series: The Case of the Hawaii Hotel Room Tax," Working Papers 199505, University of Hawaii at Manoa, Department of Economics.
    6. Scott Blunk & David Clark & James McGibany, 2006. "Evaluating the long-run impacts of the 9/11 terrorist attacks on US domestic airline travel," Applied Economics, Taylor & Francis Journals, vol. 38(4), pages 363-370.
    7. Witt, Stephen F. & Witt, Christine A., 1995. "Forecasting tourism demand: A review of empirical research," International Journal of Forecasting, Elsevier, vol. 11(3), pages 447-475, September.
    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. Michael Earhart & E. Frank Stephenson, 2018. "Same-sex marriage legalization and wedding tourism: evidence from Charleston and Savannah," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(3), pages 566-574, July.
    2. Hanyuan Zhang & Jiangping Lu, 2022. "Forecasting hotel room demand amid COVID-19," Tourism Economics, , vol. 28(1), pages 200-221, February.

    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. Allison Zhou & Carl Bonham & Byron Gangnes, 2007. "Modeling the supply and demand for tourism: a fully identified VECM approach," Working Papers 200717, University of Hawaii at Manoa, Department of Economics.
    2. Balli, Hatice Ozer & Tsui, Wai Hong Kan & Balli, Faruk, 2019. "Modelling the volatility of international visitor arrivals to New Zealand," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 204-214.
    3. Charles, Amelie & Darne, Olivier, 2006. "Large shocks and the September 11th terrorist attacks on international stock markets," Economic Modelling, Elsevier, vol. 23(4), pages 683-698, July.
    4. Corbet, Shaen & Efthymiou, Marina & Lucey, Brian & O'Connell, John F., 2021. "When lightning strikes twice: The tragedy-induced demise and attempted corporate resuscitation of Malaysia airlines," Annals of Tourism Research, Elsevier, vol. 87(C).
    5. Bonham, Carl & Gangnes, Byron & Zhou, Ting, 2009. "Modeling tourism: A fully identified VECM approach," International Journal of Forecasting, Elsevier, vol. 25(3), pages 531-549, July.
    6. Song, Haiyan & Qiu, Richard T.R. & Park, Jinah, 2019. "A review of research on tourism demand forecasting," Annals of Tourism Research, Elsevier, vol. 75(C), pages 338-362.
    7. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    8. Shively, Gerald E., 2001. "Price thresholds, price volatility, and the private costs of investment in a developing country grain market," Economic Modelling, Elsevier, vol. 18(3), pages 399-414, August.
    9. Tomanova, Lucie, 2013. "Exchange Rate Volatility and the Foreign Trade in CEEC," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 267, Ekonomik Yaklasim Association.
    10. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    11. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    12. Taoufik Bouezmarni & Mohamed Doukali & Abderrahim Taamouti, 2023. "Testing Granger Non-Causality in Expectiles," University of East Anglia School of Economics Working Paper Series 2023-02, School of Economics, University of East Anglia, Norwich, UK..
    13. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    14. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    15. Chang, Chia-Lin & Hsu, Hui-Kuang, 2013. "Modelling Volatility Size Effects for Firm Performance: The Impact of Chinese Tourists to Taiwan," MPRA Paper 45691, University Library of Munich, Germany.
    16. Budi Setiawan & Marwa Ben Abdallah & Maria Fekete-Farkas & Robert Jeyakumar Nathan & Zoltan Zeman, 2021. "GARCH (1,1) Models and Analysis of Stock Market Turmoil during COVID-19 Outbreak in an Emerging and Developed Economy," JRFM, MDPI, vol. 14(12), pages 1-19, December.
    17. Chia-Lin Chang & Michael McAleer, 2017. "A Simple Test for Causality in Volatility," Econometrics, MDPI, vol. 5(1), pages 1-5, March.
    18. Athanasia Gavala & Nikolay Gospodinov & Deming Jiang, 2006. "Forecasting volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(6), pages 381-400.
    19. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    20. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    More about this item

    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:taf:apeclt:v:16:y:2009:i:7:p:653-656. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.