The Implications of Climate Change Mitigation Policy and Oil Price Volatility for Tourism Arrivals to the Caribbean

Abstract

Globally, tourism is a non-negligible contributor of greenhouse gas (GHG) emissions, primarily through tourist transport, and in particular rapidly increasing air travel. A number of policy proposals to reduce GHG emissions from domestic and international aviation have been introduced between 2005 and 2009. Oil price volatility, especially since 2008, has forced airlines to make adjustments to flight schedules and even to add fuel surcharges to plane tickets. Tourism destinations dependent on long-haul air travel have expressed concern about the potential impact of change mitigation policies and high oil prices on tourist mobility and arrivals to their countries. A tourist arrivals model was constructed to examine whether aviation sector mitigation policy introduced in the major market regions of the European Union and North America, coupled with a return to recent oil price market volatility might adversely affect tourist arrivals to the Caribbean region. A sensitivity analysis that included 18 scenarios with different combinations of three GHG mitigation policy scenarios for aviation (represented by varied carbon prices), two oil price projections, and three price elasticity estimates, representing the range in the air travel economics literature, was conducted to examine the impact on air travel arrivals from eight outbound market nations to the Caribbean region. Results indicate that under proposed aviation sector mitigation policies and the range of oil price projections currently available, growth in visitor numbers through to 2020 would decrease only slightly (−1.3% to −4.3%) relative to a reference scenario based on recent growth trends. A detailed case study of Jamaica further revealed the different sensitivity of market segments (package vacations) to climate policy and oil price related increases in air travel costs and the economic implications of reduced growth in tourist arrivals. As the international policy framework for managing GHG emissions from bunker fuels (air and marine transport) solidifies, further research will be required to understand the implications for tourist mobility, tour operator routing and the longer-term risks to tourism development in the Caribbean.

Acknowledgements

We would like to acknowledge Stephan Gössling (Lund University, Sweden and Western Norway Research Institute, Norway) and Paul Peeters (Breda University of Applied Sciences, Netherlands) for their comments on the conceptual development of this arrivals model. We also would like to acknowledge the UNWTO Statistics Division for access to the data used in this research. This research would not have been possible without the support of the Government of Canada's Canada Research Chair programme and the Social Sciences and Humanities Research Council.

Notes

Interest in an ETS system from North America can be illustrated by pointing to the American Clean Energy and Security Act of 2009 (Waxman-Markey Bill) which is currently before the US Senate (2009) and by looking to information presented by Ljunggren (2008) on the interest the Canadian government has in working with the US government to develop a North American ETS system.

The reference oil price projection assumes current laws and policies remain unchanged, whereas the high oil price scenario attempts to quantify the uncertainty that exists when projecting long-term oil prices (EIA, 2008).

Due to data limitations, two countries (Montserrat and Saint Kitts & Nevis) were not included in the scenario runs.

This database of tourist arrivals does not distinguish between leisure and business travellers.

While every effort was made to provide authoritative carbon and oil price estimates that represent probabilities in the future, one can never be certain about the price of a commodity, particularly under new regulatory regimes. We therefore acknowledge that the sensitivity analysis may not have covered the full range of plausible prices for carbon emissions and crude oil in the decade ahead.

There are many different emission calculators to choose from but it was believed that using an industry source would give more credibility to the study from an industry perspective. Also, since it was necessary to find an online calculator which matched the EUETS's current criteria of only accounting for CO₂ impacts, ICAO's was chosen as it also does not consider non-CO₂ impacts (Department of Transport, 2007).

Although these two are separate emission prices, the same carbon price was used due to evidence that the two values have historically been nearly equal. For example, in November 2008, the value of a tonne of carbon on the European Climate Exchange (the open market) was €16.33 (European Climate Exchange, 2009) while the same day in the UK's auction for Phase II allowances (closed market), a tonne of carbon sold for €16.15 (Europa, 2009).

The price of an all inclusive vacation was taken from Travelocity.com for the travel dates May 10–17, 2009 for travel from John F. Kennedy International Airport in New York City to Norman Manley International Airport in Kingston, Jamaica and accommodation in a 4-star resort.

The differences between the model used in this analysis and the Gössling et al. (2008) model are also manifest in several other ways: the tonnes of carbon emitted for any given market destination flight were taken, for this analysis, from the ICAO online calculator while Gössling et al. (2008) gathered their emission numbers by performing several detailed calculations; this analysis took annual aviation growth rates (for 2007–2027) from an industry projection for RPK's while Gössling et al. (2008) used the value of >100% in aviation from 2005–2020 which was taken from the Commission of the European Communities; this analysis used a 60% threshold for arrivals to determine the main source markets (done because once beyond the 60% threshold, the number of countries making up the remaining arrivals increased drastically and these tended not to be countries located in North America or Europe so would not be impacted by the proposed ETS regardless) while Gössling et al. (2008) used a 70% threshold; this analysis modelled 18 scenarios (plus two additional for the case study) and the Gössling et al. (2008) modelled four (an air travel only and a total travel cost model under EU ETS and the same two variances under a worldwide serious climate policy); Gössling et al. (2008) multiplied their emission estimates by a factor of two to account for non-CO₂ impacts and they also estimated the percentage of flights which would be re-routed around the EU to avoid the extra costs required from the ETS.

Scenario 16 uses the lowest oil prices, the low price elasticity estimate (–1.04) and the high cost of carbon ($61/tonne). This is compared to the Gössling et al. (2008) scenario of EU ETS air travel which utilized an elasticity estimate of –1, no oil price and a cost of carbon at €46.9 in 2020 (approximately equivalent to US$68.74).

Part of the reason for the differences noted, particularly for Cuba, is that Canada provides a large portion of arrivals and was not taken into consideration by Gössling et al. (2008) in the scenario discussed above.