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Effects of budgetary constraints on international tourism expenditures

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  • Wang, Yu Shan

Abstract

This paper implements a logistic transition regression model to examine the relationships between GDP per capita and international tourism expenditures across countries in 2001–2010 by types of savings regimes. While studies have focused on the effect of income on international tourism expenditures, none consider the nonlinear smooth transition status of savings and its impacts on discretionary spending and hence expenditure on tourism. The impact of income on tourism expenditures can vary under different savings regimes. The results show that in a low savings regime the effect of an increase in the GDP per capita on international tourism expenditures is more pronounced. In a high-savings regime, there is strong motivation for precautionary savings and tourism is considered a luxury; therefore such spending is crowded out by an increase in savings as GDP per capita increases. Although international tourism expenditures also increase with GDP per capita, they do so at a slower rate. These findings establish an accurate understanding of the effects of savings on international tourism expenditures.

Suggested Citation

  • Wang, Yu Shan, 2014. "Effects of budgetary constraints on international tourism expenditures," Tourism Management, Elsevier, vol. 41(C), pages 9-18.
    • Handle: RePEc:eee:touman:v:41:y:2014:i:c:p:9-18
    DOI: 10.1016/j.tourman.2013.08.006
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    More about this item

    Keywords

    Budgetary constraint; Tourism participation; Saving; GDP per capita; International tourism expenditure;
    All these keywords.

    JEL classification:

    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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