IDEAS home Printed from https://ideas.repec.org/a/aag/wpaper/v24y2020i3p110-141.html
   My bibliography  Save this article

Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis

Author

Listed:
  • Adrian Mendieta-Aragon

    (National University of Distance Education (UNED), Madrid, Spain)

  • Teresa Garin-Munoz

    (National University of Distance Education (UNED), Madrid, Spain)

Abstract

This paper studies the main determinants of the inbound international tourism in Andalusia and quantify its incidence. Based on the classical theoretical framework for tourism demand, we incorporate dynamics into the model by adding the lagged dependent variable as an explanatory variable, along with the per capita income of the tourist's country of origin, the relative prices between the origin and destination countries and the cost of travel. The empirical model is applied to a panel data set consisting of 21 countries of origin of the tourists for the period 2008–2018. Data were collected from the Hotel Occupancy Survey (HOS), published by the National Statistics Institute of Spain (INE). The results have been obtained using the GMM DIFF estimator of Arellano and Bond. The parameters estimated reflect a high level of consumer loyalty and the importance of the word-of-mouth effect. Moreover, the income elasticity indicates that the demand for tourism in Andalusia may be considered as a luxury good. Prices have a negative relationship with tourism demand. The cost of travel, which has a negative effect, is statistically significant to explain the number of tourists' arrivals and, however, it is not significant for the overnight stays model.

Suggested Citation

  • Adrian Mendieta-Aragon & Teresa Garin-Munoz, 2020. "Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(3), pages 110-141, September.
  • Handle: RePEc:aag:wpaper:v:24:y:2020:i:3:p:110-141
    as

    Download full text from publisher

    File URL: https://iads.site/Foreign-Tourism-in-Andalusia-A-Dynamic-Panel-Data-Analysis
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nikeel Kumar & Ronald Ravinesh Kumar & Arvind Patel & Syed Jawad Hussain Shahzad & Peter Josef Stauvermann, 2020. "Modelling inbound international tourism demand in small Pacific Island countries," Applied Economics, Taylor & Francis Journals, vol. 52(10), pages 1031-1047, February.
    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. Kumar, Nikeel Nishkar & Patel, Arvind, 2023. "Nonlinear effect of air travel tourism demand on economic growth in Fiji," Journal of Air Transport Management, Elsevier, vol. 109(C).
    2. Adrian Mendieta-Aragon & Teresa Garin-Munoz, 2020. "Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(3), pages 110-141, September.
    3. Alessandro Severino & Larysa Martseniuk & Salvatore Curto & Larysa Neduzha, 2021. "Routes Planning Models for Railway Transport Systems in Relation to Passengers’ Demand," Sustainability, MDPI, vol. 13(16), pages 1-27, August.
    4. Amitrajeet A. Batabyal & Seung Jick Yoo, 2020. "A theoretical analysis of preference matching by tourists and destination choice," Asia-Pacific Journal of Regional Science, Springer, vol. 4(3), pages 809-820, October.
    5. Nikeel Nishkar Kumar & Arvind Patel & Sean Kimpton & Antony Andrews, 2022. "Asymmetric reactions in the tourism‐led growth hypothesis," Australian Economic Papers, Wiley Blackwell, vol. 61(4), pages 661-677, December.
    6. Yoichi Matsubayashi & Yoshihisa Inada, 2023. "Individual tourist expenditures in Japan during the inbound tourism boom period (2015–2017): Empirical evidence from micro survey data," Asian Economic Journal, East Asian Economic Association, vol. 37(4), pages 492-518, December.
    7. Nikeel N Kumar & Arvind Patel & Rup Singh, 2022. "Modelling tourism competitiveness in small Pacific island countries," Tourism Economics, , vol. 28(3), pages 692-713, May.

    More about this item

    Keywords

    Dynamic model; Panel data; Tourism demand elasticities; Consumer loyalty; Habit persistence;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

    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:aag:wpaper:v:24:y:2020:i:3:p:110-141. 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: Vincent Pan (email available below). General contact details of provider: https://edirc.repec.org/data/dfasitw.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.