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Portuguese Tourism Demand: A Dynamic Panel Data Analysis

Author

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  • Nuno Carlos Leit o

    (Polytechnic Institute of Santar m, ESGTS, Complexo Andaluz, Apt 295-2001-904- Santar m, and CEFAGE-UE, vora University, Portugal)

Abstract

This article considers the determinants of Portuguese tourism demand for the period 2004-2013. The econometric methodology uses a panel unit root test and the dynamic panel data (GMM-system estimator). The different techniques of panel unit root (Levin, Lin and Chu; Im, Pesaran and Shin W-stat and augmented Dickey-Fuller - Fisher Chi-square) show that the variables used in this panel are stationary. The dynamic model proves that tourism demand is a dynamic process. The variables relative prices, income per capita, human capital and government spending encourage international tourism demand for Portugal.

Suggested Citation

  • Nuno Carlos Leit o, 2015. "Portuguese Tourism Demand: A Dynamic Panel Data Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 5(3), pages 673-677.
    • Handle: RePEc:eco:journ1:2015-03-06
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    References listed on IDEAS

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    1. Rodríguez, Xosé A. & Martínez-Roget, Fidel & Pawlowska, Ewa, 2012. "Academic tourism demand in Galicia, Spain," Tourism Management, Elsevier, vol. 33(6), pages 1583-1590.
    2. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    3. Nuno Carlos LEITÃO, 2010. "Does Trade Help to Explain Tourism Demand? The Case of Portugal," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 3(3(544)), pages 63-74, March.
    4. repec:kap:iaecre:v:13:y:2007:i:3:p:313-333 is not listed on IDEAS
    5. Seetaram, Neelu, 2012. "Immigration and international inbound tourism: Empirical evidence from Australia," Tourism Management, Elsevier, vol. 33(6), pages 1535-1543.
    6. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    7. Yair Eilat & Liran Einav, 2004. "Determinants of international tourism: a three-dimensional panel data analysis," Applied Economics, Taylor & Francis Journals, vol. 36(12), pages 1315-1327.
    8. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
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    Citations

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    Cited by:

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    2. Muhammad Shahbaz & Miroslav Mateev & Salah Abosedra & Muhammad Ali Nasir & Zhilun Jiao, 2021. "Determinants of FDI in France: Role of transport infrastructure, education, financial development and energy consumption," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1351-1374, January.
    3. Abdulkarim K. Alhowaish, 2016. "Is Tourism Development a Sustainable Economic Growth Strategy in the Long Run? Evidence from GCC Countries," Sustainability, MDPI, vol. 8(7), pages 1-10, June.
    4. Jean Max Tavares & Nuno Carlos Leitão, 2017. "The determinants of international tourism demand for Brazil," Tourism Economics, , vol. 23(4), pages 834-845, June.
    5. Tanaka, Kiyoyasu, 2016. "Determinants of inbound tourists in Cambodia : a dynamic panel data approach," IDE Discussion Papers 600, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    6. Eugenia LUCAŞENCO & Constantin-Marius APOSTOAIE & Alexandru MAXIM, 2017. "The emergence of environmental factors as catalysts for tourism demand: a case study on Romania," CES Working Papers, Centre for European Studies, Alexandru Ioan Cuza University, vol. 9(4), pages 597-612, December.
    7. Karma Emiljan, 2023. "Patriotic Tourism Demand in Albania: A System GMM Model Approach," South East European Journal of Economics and Business, Sciendo, vol. 18(2), pages 186-196, December.

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    Keywords

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • F10 - International Economics - - Trade - - - General
    • H62 - Public Economics - - National Budget, Deficit, and Debt - - - Deficit; Surplus

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