Climate change and international tourism: A simulation study

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Abstract

The literature on tourism and climate change lacks an analysis of the global changes in tourism demand. Here, a simulation model of international tourism is presented that fills that gap. The current pattern of international tourist flows is modelled using 1995 data on departures and arrivals for 207 countries. Using this basic model the impact on arrivals and departures through changes in population, per capita income and climate change are analysed. In the medium to long term, tourism will grow, however, the change from climate change is smaller than from population and income changes.

Introduction

Tourism is one of the largest and fastest growing economic sectors. Tourism is obviously related to climate. It is therefore surprising that the tourism literature pays little attention to climate and climatic change (e.g., Witt and Witt, 1995). It is equally surprising that the climate change impact literature pays little attention to tourism (Smith et al., 2001).

The situation is now slowly changing. Three branches of literature have started to grow. Firstly, there are a few studies (e.g., Maddison, 2001) that build statistical models of the behaviour of certain groups of tourists as a function of weather and climate. Secondly, there are a few studies (e.g., Abegg, 1996) that relate the fates of particular tourist destinations to climate. Thirdly, there are studies (e.g., Matzarakis, 2002) that try to define indicators of the attractiveness to tourists of certain weather conditions. These three strands in the literature share a common deficit, namely the lack of a larger, global assessment of push and pull factors of international tourism. This study is an attempt to fill that gap.

If one wants to estimate the implications of climate change for a particular tourist destination, then one would not only want to know how the attractiveness of that place is changing—as is done in the second strand of literature defined above. Rather, one would need to know how climate change affects the attractiveness of that place relative to its competitors. If, for instance, Switzerland loses half of its snow, but other European skiing destinations lose all—then Switzerland's position may well be strengthened as the only place in Europe with natural snow. Similarly, one would need the change in behaviour of all tourists, and not just of those from Germany, the Netherlands and the UK—as the first strand of literature does. This paper combines the first and second strands of literature to overcome these drawbacks. Like the third strand of literature, it uses attractiveness indicators, albeit ones that are based on observed behaviour. In combining these three elements, we obviously had to simplify. The novelty of this paper lies in the interactions of push and pull factors at a global scale, not in the details.

Section 2 reviews the literature on tourism, climate, and climate change. Section 3 presents the model, its calibration and the base results. Section 4 discusses the sensitivity of the model. Section 5 concludes.

Section snippets

Tourism demand

Tourism demand forecasting has been given considerable coverage in the literature. Witt and Witt (1995) review the various methods used in tourism demand forecasting and compare the explanatory variables used in econometric models, gravity models and time series analyses. Using Meta-Analysis, Crouch (1995) examines the results of 80 studies on international tourism demand. Sixty of the 110 studies reviewed by Lim (1995) included qualitative variables in the model specification. The number of

Model structure

We constructed a model of international tourist flows from 207 countries to 207 countries. The purpose of the model is not to understand the current pattern of international tourism; for that, we need more detailed information than was available to us. Rather, the purpose of the model is to analyse how the current pattern may change under not-implausible scenarios of future population growth, economic growth and, particularly, climate change. The inputs to the patterns and their changes are the

Sensitivity analyses

The model and the results presented above depend on a number of parameters, each of which is uncertain. We showed the sensitivity to differences in the scenarios of population growth, economic growth and greenhouse gas emissions. In this section, we report further sensitivity analyses.

The country-specific attractiveness indices are based on distance to the power −1.7×10−4, a number we have kept constant. However, one may argue that travel speed will continue to increase, and travel costs

Discussion and conclusion

We present a simulation model of international tourism, and develop scenarios of changes in international arrivals and departures because of changes in population numbers, per capita income, and climate change. A model like this is for testing sensitivities rather than making predictions. Results are qualitative, not quantitative.

The model shows that the past growth of international tourism may well continue unabated in the medium to long term. The main driver is economic growth, and the growth

Acknowledgements

The CEC DG Research through the DINAS-Coast project (EVK2-2000-22024), the US National Science Foundation through the Center for Integrated Study of the Human Dimensions of Global Change (SBR-9521914) and the Michael Otto Foundation for Environmental Protection provided welcome financial support. All errors and opinions are ours.

References (47)

  • S.F. Witt et al.

    Forecasting tourism demand: a review of empirical research

    International Journal of Forecasting

    (1995)
  • Abegg, B., 1996. Klimaänderung und Tourismus—Klimafolgenforschung am Beispiel des Wintertourismus in den Schweizer...
  • Agnew, M.D., Palutikof, J.P., 2001. Climate impacts on the demand for tourism. In: International Society of...
  • Central Statistical Office Poland, 2002. Tourists. Retrieved from...
  • CIA, 2002. The World Factbook 2002. Central Intelligence Agency, Washington, DC, Retrieved from...
  • S. Cunliffe

    Forecasting risks in the tourism industry using the Delphi Technique

    Tourism

    (2002)
  • C.R. de Freitas

    Recreation climate assessment

    International Journal of Climatology

    (1990)
  • de Freitas, C.R., 2001. Theory, concepts and methods in tourism climate research. In: International Society of...
  • H. Elsasser et al.

    Climate change as a threat to tourism in the Alps

    Climate Research

    (2002)
  • A.M. Freeman

    The Measurement of Environmental and Resource Values: Theory and Methods

    (1993)
  • F.J. Gable

    Climate change impacts on Caribbean coastal areas and tourism

    Journal of Coastal Research

    (1997)
  • Hamilton, J.M., 2003. Climate and the Destination Choice of German Tourists, Research Unit Sustainability and Global...
  • Y. Hu et al.

    Measuring destination attractiveness: a contextual approach

    Journal of Travel Research

    (1993)
  • Cited by (0)

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